| 1 |
Author(s):
Matthew Kwon.
Page No : 1-8
|
Harnessing Zero Valent Iron-Derived Hydrogen for Acclimatized Betaproteobacteria-Driven Denitrification in Nitrate-Contaminated Water
Abstract
Nitrate contamination poses environmental and public-health risks, yet conventional removal
technologies (reverse osmosis, ion exchange, nanofiltration) can be costly for small or underserved
systems. We evaluated zero-valent iron (ZVI) granules as an inexpensive, safe electron source that
generates H₂ in situ to support hydrogenotrophic denitrification by mixed Betaproteobacteria. Duplicate
1-L batch systems (Media-1, Media-2) were run for ~2 months at 36 °C with periodic media replacement.
Nitrate was dosed as NaNO₃ (~25–50 mg/L as NO₃–N target) and measured colorimetrically (Hach 353;
reported as NO₃–N). Across 32 measurements, median effluent nitrate was 0 mg/L as N (mode = 0; mean
= 0.044 mg/L as N), with 78.3% average reduction from influent and final concentrations consistently
below the U.S. Environmental Protection Agency (EPA) maximum contaminant level of 10 mg/L as N.
Volatile suspended solids (VSS) increased within each growth period, indicating resilient biomass after
each media reset. Slopes of nitrate vs. time were negative in both reactors (Media-1: −0.00269; Media-2:
−0.00431 mg/L), consistent with acclimation. Improved nitrite reduction supported the conclusion that
repeated ZVI exposure enhanced bacterial nitrate-reducing mechanisms. These results support ZVI
derived H₂ as a scalable, affordable driver for biological denitrification, particularly where chemical
electron donors are impractical. Cost comparisons and long-term stability merit further work.
| 2 |
Author(s):
Apoorva Siragavarapu.
Page No : 9-16
|
Analyzing the Expression and Function of Autism-associated Genes Throughout the Brain
Abstract
Autism Spectrum Disorder (ASD) is one of the most prevalent neurodevelopmental conditions,
affecting approximately 1 in 54 children. Due to the complexity of the disorder, the pathogenesis of ASD
is multifaceted. Pre-existing research has linked many genes to ASD; however, the mechanisms by which
these genes contribute to ASD are not always clear. This study aims to identify similarities between
ASD related genes. By analyzing their similarities in expression in the cerebellum, hippocampus, and
prefrontal cortex, this study identifies a brain region with the highest expression of autism-associated
genes. TSC1, SHANK2, TAOK1, and CHD8 are genes that were chosen to analyze as they are high
confidence ASD genes. Phase 1 includes gathering information from published literature on how the genes
cause ASD. Phase 2 and 3 use RNA sequencing databases to analyze the percent expression of the genes
in the cerebellum, hippocampus, and prefrontal cortex. It was found that cerebellar purkinje neurons
have the highest expression (84.24%) of the selected autism-associated genes. Additional research is
needed to better understand how autism-associated genes affect brain functions, so identifying regions
like this may be promising targets which can lead to the treatment of ASD.
| 3 |
Author(s):
Chloe Jung, Suri Gime.
Page No : 17-27
|
Continental Variation in the Association between Climate Change Indicators and Allergic Diseases
Abstract
Global warming has emerged as a significant environmental threat with potential impacts on
human health. Although the association between climate change and respiratory diseases has been
studied extensively, very little focus has been placed on allergic diseases with the account for
continental variation. The objective of this study is to explore the associations between indicators of
global warming, mean temperature anomaly and greenhouse gas emission, and health outcomes of
asthma and atopic dermatitis. Data were obtained from a worldwide health database during the years
2000 to 2020. The analysis was broken down in five continents (Asia, Africa, Europe, North America,
South America). Average temperature anomaly in April and greenhouse gas emissions were selected
as global warming indicators. Health outcomes included asthma disability-adjusted life years, asthma
incidence, asthma prevalence, atopic dermatitis incidence, and atopic dermatitis prevalence, stratified
by three age groups (10–19 years, ≥55 years, and all ages). Multiple linear regression analysis showed
regional different correlation between global warming indicators and allergic disease outcomes.
Strong correlations were found for prevalence rates of asthma and atopic dermatitis in Asia and in
Africa, whereas Europe and North America showed more diversified associations. The effect of global
warming on allergic disease might be heterogeneous between and among regions and populations.
More evidence is needed to fully understand these associations better and to inform public health
mitigation measures.
| 4 |
Author(s):
Claire Yirea Sim.
Page No : 28-36
|
Exploring Risk Factors of Child Growth Faltering: A Narrative Review and Regional Regression Study in South and Southeast Asia
Abstract
Child growth faltering remains a pressing global health issue, particularly in South and Southeast
Asia, where stunting and undernutrition rates persist despite economic development. This study
combines a narrative review with a quantitative analysis to investigate the most influential risk factors
contributing to impaired growth in early childhood. Drawing from literature published between 2008
and 2023, the review highlights key intervention strategies such as exclusive breastfeeding promotion,
improved sanitation, and community-based education. In parallel, a multiple linear regression analysis
using recent regional health datasets (2020–2021) was conducted to assess the predictive power of six
malnutrition-related variables on child growth rate. Among them, suboptimal breastfeeding emerged as
the most significant negative predictor (β = –0.196, p = 0.003), even when controlling for other factors
such as micronutrient deficiencies, low birthweight, and poor sanitation. The findings underscore the
critical importance of early-life nutrition and maternal practices and suggest that culturally sensitive,
community-level approaches remain essential for effective and sustainable intervention. Strengthening
local health systems to support targeted, education-based strategies may be key to reducing long-term
developmental inequality in the region.
| 5 |
Author(s):
Xinyao Sarah Huang, Maisarah Aminah Dombrowski, Esthyr Stucky.
Page No : 37-46
|
Heat and History: The Influence of Historical Redlining Practices on Heat-Related Illnesses in Modern U.S. Cities
Abstract
Heat illness is becoming one of the most fatal climate-related conditions. Its harmful effects
disproportionately impact historically marginalized groups due to a long history of institutionalized
racism. In the 1930s, the Home Owners’ Loan Corporation (HOLC) assessed neighborhoods based on
their investment risk. These grades discriminated against people of color, enforcing segregation and
disinvestment long after the practice was outlawed. The process is now referred to as redlining, and its
ongoing effects can be observed through various health and socioeconomic impacts. Our study intends
to address the question “How does historical redlining influence the prevalence of heat-related illnesses
in cities throughout the United States?”. We created faceted maps and ran linear regression using data
from the US Census Bureau, the Centers for Disease Control, and Mapping Inequality to investigate
the correlation between the percentage of the Black population and heat illnesses. Our models yielded
mixed results in the strength of correlation between our variables. Chicago had the highest statistical
correlation. Nonetheless, our study forms a link between the perpetuation of racially biased housing
policies and the current prevalence of heat morbidity in Black-dominant neighborhoods.
| 6 |
Author(s):
Pratik Paduri.
Page No : 47-57
|
Economic and Ecological Impacts of Climate Change on Coastal Fisheries: A Global Analysis of Vulnerability and Adaptive Management Strategies
Abstract
Climate Change, which is driven by rising greenhouse gas emissions and increasing global
temperatures, poses a significant threat to sea-based industries globally. Coastal fisheries are the
most at risk because they depend on ocean ecosystems that are especially vulnerable to changes in
the environment. Although the effects of ocean warming and rising sea levels are well documented
already, the issue remains of how these effects can compound with existing anthropogenic effects
like overfishing and habitat degradation. These impacts have important considerations for not only
the biodiversity of these ecosystems, but the economic health of communities who rely on them as a
source of income and food. This is shown in small island developing states like Fiji and the Maldives,
and other developing states where fisheries contribute to a large amount of both the GDP and the food
security of those countries. This study looks at how these environmental changes, combined with
social and economic factors, are putting pressure on coastal fisheries, shipping, coastal real estate,
and renewable marine energy. Using real-world research, it explores ways communities can adapt
such as managing fisheries through clear rights, restoring damaged ecosystems, and creating marine
protected areas led by locals. The results show that we need policies that bring together science and
good governance to help these communities recover. These kinds of approaches are key to keeping
coastal fisheries and related industries healthy and sustainable as our oceans continue to change.
| 7 |
Author(s):
Naomi Felleke.
Page No : 58-66
|
Personalized Hypertension Treatment: Genome-based Prescriptions
Abstract
Genetic polymorphism refers to the simultaneous occurrence of two or more genotypes in a
population. Key genes related to hypertension involved in this phenomenon—such as the angiotensin
converting enzyme insertion (I)/deletion (D) variant ( ACE I/D), β1-adrenergic receptor (ADRB1,
Arg389Gly), cytochrome P450 3A5 (CYP3A5 *1/*3 alleles), and α-adducin (ADD1, Gly460Trp)—
influence responses to antihypertensive medications, including angiotensin II receptor blockers
(ARBs), angiotensin-converting enzyme inhibitors (ACEi), β-adrenergic blockers ( β-blockers),
calcium channel blockers (CCBs), and diuretics. Incorporating genotype-guided prescription planning
using weighted multi-gene panels, healthcare providers can tailor antihypertensive therapy to each
patient’s genetic profile, eliminating the trial-and-error approach to prescribing antihypertensive
medication. This precision medicine strategy can potentially enhance blood pressure control, reduce
the risk of adverse side effects, and enhance overall treatment outcomes in hypertensive patients.
Further research and clinical studies of these multi-gene algorithms could revolutionize hypertension
management by offering personalized treatment.
| 8 |
Author(s):
Milo Linn-Boggs, Teagan Peabody.
Page No : 67-79
|
Defining Academic Success: Socioeconomic Influences on High School Students’ Perceptions
Abstract
The U.S. secondary education system shows persistent achievement gaps, especially along
socioeconomic lines. Prior work has emphasized objective SES metrics and material measures
of success, often overlooking students’ own definitions. This study aimed to: (1) collect baseline
data for thematic analysis of high schoolers’ perspectives across school types (public, private non
denominational, and alternative private non-denominational); (2) develop explanatory grounded
theory; (3) interpret findings and propose causal mechanisms; and (4) translate insights into practice.
Using a realist stance, we combined Straussian grounded theory with thematic analysis and a
phenomenological interview approach while mitigating acquiescence, wording, and habituation
biases. The MacArthur Scale of Subjective Social Status assessed perceived status in two contexts.
Participants were 18 students (ages 15–18; grades 9–11) from nine schools. Semantic and latent themes
were generated inductively through a five-step process; grounded theory used a three-step Straussian
procedure. Two central themes emerged: (1) “success means different things to me” (multiplicity of
definitions) and (2) “where ideas come from” (the social construction of success). The core concept
was “calibrating academic success between external benchmarks and personal growth within the
realities of available support.” Grades and college were the most common definitions (17/18); mastery
and curiosity was second (7/18 interviews). Interviews with multiple definitions (10/18) were associated
with higher subjective social status scores. These findings provide baseline data and theory on how
students’ meanings of success shape their educational experiences and relate to perceived social
position.
| 9 |
Author(s):
Rosemary Spindler.
Page No : 80-92
|
“Excuse Me, I’m Speaking” Do Girls Face a Level Playing Field in Public Forum Debates?
Abstract
High school debate offers the opportunity for students to develop skills critical to leadership and
civic participation, yet there remains a gender gap in both performance and participation. Several
empirical papers have shown that attrition is a significant cause of the gap, but previous research has
focused on national or collegiate vs. regional competition, and more technical events like Lincoln
Douglas or Policy debate. Instead, this paper explores the gender gap in Public Forum high school
debate at the regional level. Specifically, it determines what effect gender has on a team’s success at
the Texas Forensic Association State tournaments over the last two years. This data set was chosen
strategically to analyze judge bias as a possible explanation: Public Forum is often judged by nontechnical judges, leaving results more subject to personal bias; second, by the time competitors get to
TFA, they have already shown persistence, minimizing the attrition explanation; and third, regional
competitions are a more inclusive space. Publicly available data was collected from Tabroom, the
system most commonly used to run tournaments. Using an Ordinary Least Squares regression with
gender and prior experience as explanatory variables, it was found that an all female team was about
7 percent less likely to win a round than an all male team, given the same levels of experience. This
result had high significance, although the relatively low R-squared value suggests there are variables
other than prior experience and gender that are relevant to understanding success to be explored
further.
| 10 |
Author(s):
Anirudh Parthasarathy.
Page No : 93-102
|
Tackling Food Insecurity Through Food Surplus Redistribution
Abstract
Food insecurity remains a global problem despite sufficient food production, posing substantial
human, economic, and environmental consequences. In the United States, an estimated 83% of edible
food is lost at the retail, food service, and consumer sectors. This review examines U.S. surplus
food redistribution initiatives across national networks, technology platforms, and community-based
efforts. Through a qualitative review of academic literature, organizational websites and government
reports, the analysis identifies key challenges such as liability protection, confusing date labeling, and
limited efforts in the household sector along with opportunities in AI-based logistics, crowdsourced
volunteers and standardized federal policies across the nation. Combining technological innovations
with strong policy frameworks and community-based initiatives offer a clear path toward reducing
waste and improving food access.
| 11 |
Author(s):
Nikita Mirghasemi, Nicole C. Guilz.
Page No : 103-111
|
CRISPR-Based Gene Editing Therapy for Epidermolysis Bullosa Simplex: Molecular Targets and Therapeutic Strategies
Abstract
Epidermolysis Bullosa (EB) is a genetic skin condition characterized by extensive skin fragility
with blistering and open sores following mild mechanical stress or injury. Among several subtypes,
Epidermolysis Bullosa Simplex (EBS) is the most common type, usually occurring through mutations
in the KRT5, KRT14, and PLEC genes that weaken the integrity of keratinocytes in the basal
epidermis. Current treatments are mainly supportive care and focus on making the symptoms more
manageable through bandaging wounds, nutritional intervention, and surgical treatment. However,
advances with gene-editing tools like CRISPR-Cas9 offer revolutionary opportunities for therapeutic
strategies seeking a curative advantage. In this paper, we review the genetic basis of EBS, the molecular
consequences of profound mutations, and the utility of CRISPR-based methods to correct these with
high fidelity through homology-directed repair (HDR), base editing, and prime editing. Both in vitro
and in vivo methods used to transplant gene-engineered keratinocytes and the emerging role played
by in vivo delivery systems in targeting epidermal tissue by CRISPR are discussed. While current
issues on delivery efficiency remain to be conquered, cell specificity and the long-term preservation
of the edited phenotype are still matters to be addressed. However, CRISPR-based approaches offer
a promising direction to correct EBS at the molecular level and offer hope for long-term therapeutic
success..
| 12 |
Author(s):
Manya Sikka.
Page No : 112-116
|
Teens’ Perspectives on E-cigarettes vs. Traditional Cigarettes
Abstract
Though e-cigarettes are marketed substantially differently than traditional cigarettes, many
of their potential health risks remain similar. While current social media poses e-cigarettes as a
healthy alternative to traditional cigarettes, research shows that e-cigarettes still carry significant
health risks similar to traditional cigarettes, though sometimes at reduced levels. Many e-cigarette
companies have marketed their products towards adolescents, and there have been rising rates
of teens using e-cigarettes. In this literature review, the current knowledge surrounding teen
perspectives of e-cigarette use compared to traditional cigarettes is summarized, along with
the different factors that contribute to this line of thinking. The findings indicate students seek
additional education involving e-cigarettes and their detrimental effects on general well-being and
mental health to abrogate these misconceived perceptions.
| 13 |
Author(s):
Koeun Kwak.
Page No : 117-123
|
Industry Mix as a Place-Level Heat Risk Indicator: Outdoor-Labor Share and Heat-Related Emergency Department Visit Rates in Virginia, 2025
Abstract
Extreme heat increases emergency department (ED) utilization. However, there are only a few
place-level studies conducted to see whether industry mix in a community may signal vulnerability
to extreme heat. This study specifically seeks to answer whether localities in Virginia with a higher
outdoor-labor employment share tend to experience higher rates of heat-related illness (HRI)
emergency department (ED) visit. This study hypothesized that localities with higher outdoor-labor
share may have higher heat-related illness ED visit rates. Two datasets: Virginia Department of Health
locality HRI counts (VHD HRI, year 2025) and Bureau of Labor Statistics (BLS) Quarterly Census
of Employment and Wages (QCEW, 2023) were merged to generate outdoor-labor share (construction
+ natural resources & mining) / All private industries. Records with jurisdictions combined by VDH
were retained, and labels were programmatically split and allocated with HRI counts in proportion
to QCEW “All industries” employment in each component and rounded with integers. 114 unique
localities (with 125 complete-case entries) were included in the analytic datasets. The primary model
was Poisson generalized linear model applied with log link and log(QCEW “All industries”) size offset.
Incidence rate ratios (IRRs) were estimated per 10-percentage-point increase in outdoor-labor share
with standard errors. With the Poisson (offset) estimates, the hypothesis in this study was supported.
IRR was 1.60 (95% confidence interval 1.10-2.33, p=0.013). A Negative Binomial sensitivity with
Akaike Information Criterion-selected dispersion (α ≈ 0.93) was directionally positive but less precise.
IRR was 1.21 (95% confidence interval 0.96-1.53, p=0.104). The ecological (place-level) analysis in
this study suggests that industry structure can inform targeting of heat-health prevention.
| 14 |
Author(s):
Eugene Choi.
Page No : 124-136
|
Strategic Management of Senior Employment Programs: Expanding Opportunities in a Super-Aged Society
Abstract
South Korea is on the path to becoming a super-aged society, with a rapidly growing elderly
population. This population shift has created significant social challenges, such as high poverty
rates among the elderly and increasing economic pressures on the younger generation. In 2023, the
poverty rate for elderly households in South Korea was 43.4%, which is significantly higher than
the Organization for Economic Co-operation and Development (OECD) average. Consequently, the
Korean government has launched various programs to support elderly employment, focusing primarily
on social service-type employment programs. However, despite their expansion, these programs face
significant challenges: limited differentiation from public service roles and a lack of innovation. Using
a comparative case approach, this review examines the current status of South Korea’s program,
benchmarks it against international models from the U.S., U.K., Japan, and Australia, and proposes a
step-by-step policy roadmap for improvement.
| 15 |
Author(s):
YEWON JUN.
Page No : 137-143
|
Malaria Prevention in Africa and Beyond: A Comparative Data Analysis of Strategies and Outcomes
Abstract
Malaria remains a major global health challenge, with Sub-Saharan Africa (SSA) bearing the
highest burden. Insecticide-treated nets (ITNs) have been widely distributed as an effective intervention
to prevent malaria transmission. However, the effectiveness of ITNs varies across regions. This study
aims to evaluate the relationship between ITN distribution and malaria incidents and deaths, comparing
trends in SSA and the Rest of the World (ROW) over the past two decades. Using comparative data
analysis, malaria incidents and deaths from 2004 to 2023 were collected and categorized into two
groups (SSA and ROW) based on classifications from The Alliance for Malaria Prevention. Pearson
correlation models were used to assess the relationship between ITN distribution and incidents of
malaria and malaria related deaths. Lag models were used to evaluate the delayed impact of ITN
distribution. Contrary to findings suggesting that ITNs reduce malaria cases by over 50%, SSA
revealed a significant increase in malaria cases despite increased ITN distribution (r = 0.5996, p <
0.01). In contrast, ROW showed a strong negative correlation (r = -0.7358, p < 0.01), indicating that
ITNs were effective in reducing malaria cases in non-SSA regions. However, ITN distribution was
significantly correlated with a reduction in deaths in both SSA (r = -0.8254, p < 0.01) and ROW (r = -0.7314, p < 0.01) demonstrating a strong negative correlation. Lag models confirmed that the impact
of ITNs remained for up to 5 years. While ITN distribution effectively reduces malaria deaths, its
impact on malaria incidence remains inconsistent in SSA.
| 16 |
Author(s):
Andrew Kwon.
Page No : 144-151
|
Post-Pandemic Shifts in Background Mortality: A Gompertz-Makeham Analysis of UK Life Tables, 2017-2023
Abstract
This study models adult mortality in the United Kingdom using the Gompertz-Makeham (GM) law
and tests if its parameters were altered by pandemic-era conditions, while preserving model validity.
Life tables from the Office for National Statistics (ONS) in the years from 2017 to 2019 (pre-pandemic)
and 2021 to 2023 (post-pandemic) were used to fit the Gompertz-Makeham models for males and
females, separately, in the range of ages from 30 to 90 with nonlinear least squares, while assessing
the goodness of fit with log scale residual diagnostics. Predictions were validated against empirical
survival curves and life expectancy at age 65 (e65). This study seeks to answer whether the Gompertz
Makeham parameters differed between pre- and post-pandemic periods, and whether the model
remained valid in predicting survival and e65. This study hypothesized that there was no significant
difference in the Gompertz-Makeham parameters for UK adults between pre- and post-pandemic
periods. The age-independent (background) component was higher for both genders on average in
the post-pandemic period, but this pattern was suggestive rather than conclusive based on statistical
tests. However, the age-dependent risk level and rate remained unchanged. Observed vs. fitted hazards
aligned well on the log scale, and residuals remained close to zero in the range of ages from 30 to 90.
There was a slight dispersion at the oldest ages. The Gompertz-Makeham survival supported ONS
survival closely, and the differences of e65 remained small. Background risk was directionally higher
post-pandemic but not statistically significant at the 5% level (males, p=0.10; females p=0.38). Age
dependent terms were stable, and the model validation was strong for both survival and e65. Taken
together, the results in this study were consistent with the background mortality through a level-type
shift rather than a structural change in age-related risk, but these inferences were not statistically
conclusive.
| 17 |
Author(s):
Ryan Verma.
Page No : 152-155
|
The Amyloid Beta Cascade Hypothesis in Alzheimer’s Disease
Abstract
The amyloid-β cascade hypothesis has served for decades as the foremost explanation for
the pathology of Alzheimer’s disease, and it has served as the basis for much research on the
mechanisms of and treatments for Alzheimer’s, fostering countless discoveries in the field. This
paper will review the historical and current evidence both in support of and challenging the
amyloid cascade hypothesis to determine its applicability in modern research. More modern
variations of the hypothesis acknowledge the importance of other factors and focus on the role of
soluble amyloid oligomers have been able to explain many criticisms of the hypothesis, such as
the presence of plaques in healthy individuals, and the weak correlation with cognitive decline,
and additionally support has come from new amyloid-targeting drugs. However, while amyloid-β
likely plays some role in Alzheimer’s pathology, evidence suggests that amyloid-β alone does
not incite pathogenesis. Instead, Alzheimer’s results from a great variety of factors of which
amyloid-β may be one, though it is far from being fully understood.
| 18 |
Author(s):
Asrith Sampath.
Page No : 156-165
|
Effects of Microfinance on Poverty Alleviation in North America and Latin America
Abstract
The paper examines the roles of microfinance in poverty alleviation in North America and Latin
America based on recent empirical research and policy analyses of the region. Since its introduction
in the 1970s, microfinance has been promoted as a development tool defined as the provision of
small-scale financial services to underserved populations. Although microfinance has been adopted
in both North and Latin America, institutional structures, socioeconomic factors, and outcomes
differ substantially. This paper also examines the performance of microfinance in enhancing income,
psychological well-being, entrepreneurship, and social inclusion. Further, it investigates the integration
of complementary services such as technical training, healthcare, and conditional cash transfers.
Evidence from nations such as Mexico, Brazil, Bolivia, Peru, and the United States indicates that
microfinance has the capacity to alleviate multidimensional poverty, especially when programs
incorporate education and complementary support services. Nonetheless, system-wide transformative
effects appear limited unless policies are coordinated across sectors and interventions are appropriately
targeted. The discussion underscores the need for context-sensitive design, intersectional inclusion,
and subnational financial support. The conclusion is that microfinance, when deployed as part of a
multisector development strategy focused on institutional cooperation, financial inclusion, and the
empowerment of disadvantaged communities, yields the strongest results.
| 19 |
Author(s):
Sarah Markowitz.
Page No : 166-172
|
Can Social Media and Media Literacy Reduce Affective Polarization?
Abstract
Affective polarization–when individuals have positive feelings about members of their party and
negative, harsh views about members of the opposing party–has become an ever-growing concern.
In recent years, especially with the rise of social media, many have begun to take notice of affective
polarization. The literature has shown that social media has the effect of creating echo chambers in
which individuals are only exposed to content promoting their own views and biases. While scholars
have explored the potential for media literacy programs to decrease affective polarization, we don’t
yet know whether media literacy programs can reduce the spread of affective polarization on social
media. This paper explores whether media literacy programs could decrease affective polarization on
social media and draws the conclusion that implementing a program like this is not only difficult but
will likely have adverse effects such as fostering cynicism. These findings suggest that addressing the
nation’s polarization will require legal regulations.
| 20 |
Author(s):
Kyan Mui.
Page No : 173-182
|
Strategies and Technologies for Sodium Reduction in Processed Foods
Abstract
Excessive sodium consumption is a major contributor to hypertension, cardiovascular disease,
and other chronic health risks worldwide. While sodium plays critical roles in food--enhancing
f
lavor, preserving quality, and influencing texture--modern intake levels far exceed physiological
needs. Reducing sodium intake through reformulated foods is a key public health goal, yet presents
technological and sensory challenges. This paper examines the physiology of salt taste perception, the
health impacts of excess sodium, and current strategies to reduce sodium in processed foods. It reviews
three primary approaches: the stealth reduction of sodium content, the use of salt alternatives such as
potassium chloride (KCl), monosodium glutamate (MSG), and plant-derived seasonings, and advanced
f
lavor enhancement technologies including salt microspheres, emulsions, and nanotechnology. Real
world examples demonstrate that significant sodium reduction can be achieved while maintaining
consumer acceptance. Together, these innovations offer promising pathways to lower population
sodium intake and improve cardiovascular health outcomes.
| 21 |
Author(s):
Aarnav Bansal, Melanie Ortiz Alvarez de la Campa.
Page No : 183-197
|
COVID-19 and Dietary Trends Impact Depression and the Microbiome in Teens
Abstract
The growing rate of depression in adolescents post-COVID-19 has sparked debates regarding the
best method through which the risk of depression can be decreased in this population. One pathway
of emerging focus is the therapeutic potential of the gut-brain axis. The Western, Keto, and vegetarian
diets have become more common, but their relationship with the gut-brain axis and depression remains
largely unexplored in teens. COVID-19 is associated with a shift towards greater social isolation,
more social media usage, and greater consumption of processed foods. These factors negatively
affect the microbiome, leading to greater neuroinflammation and risk of depression. As depression
becomes increasingly common in adolescents, new avenues to mitigate the effects of antidepressants
are imperative. This review evaluates the current literature on these relationships and proposes
future research directions. Specifically, a high-fiber diet could reduce neuroinflammation, bolster the
microbiome, and help the effectiveness of antidepressants. This implies that dietary guidelines could
serve as therapeutic interventions for depression in teens, as major depressive disorder (MDD) rates
increase in a post-COVID world.
| 22 |
Author(s):
Sierra Anstey.
Page No : 198-207
|
Carvedilol in Pediatric Dilated Cardiomyopathy Patients: A Systematic Review of Clinical Outcomes
Abstract
Dilated cardiomyopathy (DCM) is a cardiac disease that affects the heart’s muscles and makes it
difficult for the heart to pump blood by enlarging and stiffening the heart chamber walls (usually the
left ventricle). DCM is estimated to occur in 1 out of 250-2,500 adults and 0.57-1.13 out of 100,000
children. It is associated with high morbidity and mortality. Carvedilol is used off-label in children
with heart failure, but its effectiveness across pediatric DCM studies remains uncertain. To synthesize
reported clinical outcomes of carvedilol in patients < 18 years with DCM, a comprehensive literature
was conducted in Pubmed and Embase. Eligible designs included randomized trials and cohort studies
reporting carvedilol outcomes in pediatric DCM. Six studies reported improvements in left ventricular
ejection fraction; two studies reported a reduction in heart rate. Across heterogeneous designs,
carvedilol was generally associated with improved cardiac function in most patients, notably left
ventricular ejection fraction (LVEF) and reduction in heart rate. However, dosing, co-therapies, and
follow-up varied, and adverse effects were inconsistently reported. Overall, current evidence suggests
carvedilol may benefit children with DCM, but larger randomized control trials are needed to confirm
efficacy and safety.
| 23 |
Author(s):
Jihyeong Kim, Shin Seo.
Page No : 208-217
|
Exploring the Intersection of Cosmetic Chemical Exposure and Health Disparities in Breast Cancer
Abstract
Parabens and phthalates are increasingly under scrutiny for their adverse biological effects owing
to their ever-widening application in the fields of cosmetics and personal care products. As endocrine
disruptors, these chemicals mimic estrogen, bind to hormone receptors, and cause changes in relevant
cellular pathways that may lead to cancer development. Parabens and phthalates are believed to
stimulate breast cancer cell proliferation, interfere with apoptosis, and activate signaling pathways such
as PI3K/AKT, according to in vitro experiments. Such chemicals can be detected in breast tissues and
urine, and concentrations associated with increased risk of hormone receptor-positive breast cancer
have been confirmed in both studies of environmental contaminants and human population exposures.
Moreover, the consequences of exposure extend far beyond personal health impacts, impacting more
subtly upon public health and environmental justice. Culturally toxic advertising strategies contribute
to restricted access to safer alternatives, hurting women of color and low-incidence populations
the most. With inadequate testing on chemical components not being mandated by US regulations,
vulnerable communities remain unprotected. The review will consider mechanisms of action for
parabens and phthalate toxins, their impact on breast cancer biology, and how those risks may interact
with patterns of social inequality. If these issues are truly to be addressed, comprehensive regulation,
consumer awareness, and health equity research are required. The reckless use of these chemicals
brings the urgency of public health intervention and policy conciseness without further delay to
prevent any preventable harm and create a safer environment for all population strata.
| 24 |
Author(s):
Fan He.
Page No : 218-225
|
Public Perception of CRISPR-Cas9 Among Youth and Young Adults
Abstract
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9, a groundbreaking
gene-editing tool, has transformed medicine, agriculture, and biotechnology by offering precision
and versatility in modifying DNA. Despite its potential to treat genetic disorders and save lives,
the application of CRISPR-Cas9 to human genomes raises significant ethical concerns, including
unintended consequences, societal inequality, and misuse. To date, only four studies have examined
public views on these issues, with the most recent published in 2022. Earlier studies found initial
optimism toward CRISPR-Cas9 that later became more cautious, and younger generations generally
showed greater support and optimism. Given that public opinion may have shifted in the past three
years with the rapid advancement of CRISPR-Cas9, this study examines the ethical perceptions of
CRISPR-Cas9 among 461 individuals aged 26 or younger, a demographic likely to influence future
societal attitudes and policies. Through surveys, data were collected from the participants on public
awareness, familiarity, attitudes, and ethical perspectives toward CRISPR-Cas9. Results reveal that
high school students (ages 14-18) and young adults (ages 19-26) show greater awareness, familiarity,
and optimism, often supporting therapeutic applications while also expressing concerns about ethical
boundaries, equity, overpopulation, and unintended consequences, trends that appear linked to
educational exposure. These findings underscore the importance of education that addresses both the
promise and the ethical challenges of CRISPR-Cas9, promoting responsible innovation and ensuring
its equitable application in society.
| 25 |
Author(s):
Aiden Wang.
Page No : 226-235
|
Modern Deep Learning Accelerometer Denoising Methods For Mobile Robot Dead-Reckoning: A Review
Abstract
This paper reviews recent deep learning methods aimed at reducing random errors in low-cost
microelectromechanical systems (MEMS) inertial sensors for mobile robot dead reckoning. Accurate
localization remains a critical challenge in GPS-denied environments, particularly for platforms that
rely solely on accelerometer data. Four representative studies were selected based on architectural
novelty and relevance to inertial-only dead reckoning. The review analyzes their denoising strategies,
including Generative Adversarial Networks (GANs), Physics-informed Neural Nets, Wave-U-Nets, k
Nearest Neighbors (kNN), as well as their performance across evaluation metrics such as Absolute
Trajectory Error (ATE), Relative Trajectory Error(RTE), and Relative Rotation Error (RRE). Hardware
platforms and tasks are also compared to assess generalizability. Findings indicate that research in
range extension remains limited but suggest that generative architectures are promising for improving
accelerometer signal reconstruction. Further, the lack of unified experimental datasets highlights an
opportunity for standardization in future work. Overall, this review emphasizes that unified metrics
and methods are key to advancing practical inertial-based dead reckoning in low-cost mobile robots.
| 26 |
Author(s):
Michael R Bronshteyn .
Page No : 236-241
|
Race and Achievement Gaps in CAASPP Testing: A Decade of Data from LVUSD
Abstract
This study analyzes racial disparities in educational outcomes. Using California Assessment of
Student Performance and Progress (CAASPP) math and English testing data from the Las Virgenes
Unified School District (LVUSD) spanning 10 years (2015–2024), it highlights the correlation between
race and subsequent test scores. LVUSD is generally regarded as a high-performing district, yet
inequities persist, illustrating how race influences standardized outcomes even in well-resourced
contexts. The forces fueling inequities, resource distribution, implicit bias, and structural barriers
are indicative of national trends despite the single-district focus of analysis. While the LVUSD
case illustrates disparities that mirror national patterns, the findings are specific to one district and
should be interpreted with caution when extrapolated to broader U.S. contexts. For example, African
American students’ math performance showed an R² of 0.689, meaning nearly 69% of the variance
was associated with race, while White students’ scores showed an R² of 0.404. In English, Hispanic
students displayed the strongest correlation (R² = 0.380). ANOVA confirmed significant between
group differences (F = 363.54 for math, 163.29 for English; p < 0.001). Future research could compare
results across additional districts and incorporate contextual factors such as school resources and home
environments. The dataset, covering the 2015–2024 timeframe, excludes long-term outcomes and post
2024 policy reforms, which may also influence performance.
| 27 |
Author(s):
Tiffany Sung.
Page No : 242-248
|
Novel Doxorubicin Derivatives for Reduced Toxicity: An In Silico Study
Abstract
Doxorubicin is a chemotherapy drug, classified as an anthracycline antibiotic, and has been used
as a form of treatment since the 1960s. It is used to treat various cancers, including blood cancers,
such as leukemia and lymphoma, as well as solid tumors, such as breast, bladder, lung, and ovarian
cancer. Doxorubicin can inhibit the growth and kill cancer cells at any stage, making it one of the
most effective chemotherapy drugs. The majority of chemotherapy drugs have severe side effects, as
their cytotoxic nature forces them to target healthy cells in addition to cancerous cells. Doxorubicin,
in particular, is one of the most toxic chemotherapy drugs and can lead to life-threatening cardiac
conditions. Doxorubicin’s toxicity limits its potential and effectiveness, as doses are administered
cautiously, with the maximum lifetime cumulative dose being 550 milligrams per square meter. This
study aims to reduce the toxicity of doxorubicin by developing five alternative derivatives that lower
toxicity levels while maintaining the function of the original compound. All five derivatives showed
improvement in toxicity, with the most significant changes in derivative 4. Derivative 4 completely
removed the risk of neurotoxicity and cytotoxicity and reduced the toxicity of four groups by at least
26%, some up to 33%. Since the backbone structure remained unchanged, the mechanism of action is
likely the same. While these derivatives still need to be further explored and tested through clinical
trials, they are a promising alternative for safer and less harmful versions of doxorubicin.
| 28 |
Author(s):
Alexandra T. Hedrick.
Page No : 249-266
|
An In Silico Analysis of CRISPR Therapy Targeting NPM1 Mutations in Acute Myeloid Leukemia
Abstract
Acute myeloid leukemia (AML) is a blood cancer typically affecting myeloid cells in the bone
marrow. It is most common in adults and is characterized by its aggressive nature and relatively high
likelihood of relapse. One of the most frequent mutations observed in patients with AML is a mutated
NPM1 gene, which may lead to aberrant cytoplasmic localization of the NPM1 protein. FLT3 mutations
are also commonly linked to NPM1 mutations and often signify poor prognosis in individuals with
AML. Though research is being done into the prevention of these mutations, there are still very few
treatments specifically targeting NPM1-mutated AML. In this study, a hypothetical CRISPR/Cas9 gen
editing strategy was proposed as a possible path to study approaches for therapy to target mutant
NPM1 genes and subsequent mutations in FLT3. Techniques such as transmembrane domain analysis
and multiple protein alignment were used to explore protein characteristics such as localization and
amino acid conservation patterns. A hypothetical CRISPR/Cas9 gene editing, polymerase chain
reaction (PCR), and gel electrophoresis were simulated in exon 12 (a region commonly associated with
NPM1 mutations) to propose a future research path for investigating the effects of mutations in the
NPM1 gene. The goal was to generate a strategy to investigate whether a precise gRNA applied as a
CRISPR/Cas9 gene editing could be a potential solution to limit the effect of NPM1 and FLT3 mutated
proteins, therefore decreasing the development and severity of AML in the future.
| 29 |
Author(s):
Navya Narayanan .
Page No : 267-275
|
Efficacy of Long-Distance Versus High-Intensity Running in Alleviating Primary Dysmenorrhea: A Survey of Adolescents
Abstract
Primary dysmenorrhea is known as cramping pain occurring before or during a period in the
absence of pelvic pathology. Exercise, and specifically running, is one of the most effective and
well-known methods to relieve primary dysmenorrhea, but how different intensities affect period
pain remains unknown. Which is why this paper studied the effects long-distance running and high
intensity running had on period pain in adolescents living in Texas. In this paper, a survey was sent
to a high school and a middle school to collect data on adolescents aged 14 to 17 who have some level
of period pain and have had their period for at least two years with no diagnosed abnormal menstrual
conditions. In the end, long-distance running was found to provide more relief on average; however,
high-intensity running was found to provide relief for a few people, sometimes to a higher degree than
long-distance running. This finding indicates that further research on different exercise intensities is
needed to help people get the most relief for primary dysmenorrhea using exercise.
| 30 |
Author(s):
Ayman Ahmed Shaik, Fraulin Joseph.
Page No : 276-281
|
Born Into Risk: How Prenatal Exposure to PM2.5 Shapes Autism Outcomes
Abstract
Autism spectrum disorder (ASD) has been one of the fastest-growing developmental diagnoses
worldwide. While awareness and diagnostic tools have contributed to the rise of case identifications,
environmental factors are emerging as significant contributors. Among these factors, fine particulate
matter (PM2.5), measured in μg/m³, has become of particular interest in the scientific community due
to its potential association with changes in brain development during pregnancy. The purpose of this
study is to explore the relationship between prenatal exposure to PM2.5 and ASD prevalence in the
United States using publicly available datasets from the Centers for Disease Control and Prevention
(CDC) and the CDC’s Tracking Data Explorer. Results suggest that there is a statistically significant
correlation between higher PM2.5 exposure levels and increased ASD rates at the state level. Trends in
PM2.5 levels and exposure, particularly in regions impacted by wildfire smoke and industrial activities,
show overlaps with regions experiencing some of the most prominent increases in ASD prevalence.
These findings suggest that more integrated environmental health policies should be enforced with
early childhood development strategies.
| 31 |
Author(s):
Dylan Li.
Page No : 282-287
|
Applying Object Detection to Automatic Drum Transcription
Abstract
Automatic music transcription (AMT) is a fundamental problem in music information retrieval
(MIR), involving the conversion of audio recordings into symbolic representations such as MIDI.
This study presents a novel approach to automatic drum transcription (ADT) by reframing it as a
computer vision object detection problem. Using the YOLO11 model, drum notes were predicted
and transcribed with bounding boxes in spectrograms generated from the Expanded Groove MIDI
Dataset (E-GMD). Two-second audio segments were extracted via a sliding window, converted into
640×640 grayscale spectrograms, and annotated with bounding boxes corresponding to onset times
and instrument classes. The model achieves strong detection performance, with results [email protected]
of 0.943, precision of 0.892, and recall of 0.846. Results demonstrate YOLO11’s ability to handle
polyphonic, temporally dense drum passages without explicit onset separation. This work highlights
the potential of adapting computer vision techniques to audio-based event detection, paving the way
for broader MIR applications beyond percussion, such as multi-instrument transcription and real-time
performance analysis.
| 32 |
Author(s):
Blake Birenkrant.
Page No : 288-298
|
Raining Money: An Empirical Analysis of the Impact of Severe Weather in The United States on Select Stock Market Performance
Abstract
There are many conditions that can affect a public company’s stock price. One condition that
isn’t completely direct is climate and natural disasters. Previous literature on this topic suggests that
extreme-weather events mostly negatively impact company share prices, valuations, and crash risk,
with hurricanes and earthquakes being focal points of research and S&P 500 effects being minimal.
This project applies to an event study with a 60-day time frame (30 days before and 30 days after)
by researching the prices of 100 public stocks across four types of disasters. The results of this study
revealed that hurricanes have the most positive effect, wildfires have the most negative effect, and
earthquakes have the most ambiguous impact, but these correlations cannot be completely confirmed.
Further results also revealed that stock price dips are mainly temporary, and insurance companies
were the most diversely impacted industry. Reasons for these results are likely the result of how a
company was affected, whether it was disruptions in the supply chain, an increase in product demand,
how much warning was given for the disaster, or other outside factors unrelated to any type of disaster.
The results of this project mostly aligned with those in the previous literature, and when they did not,
it was likely due to differences in project design and collected data. Overall, this study revealed that
climate and natural disasters can have a positive or negative impact on the stock market, but these
effects may be the result of random chance and outside factors.
| 33 |
Author(s):
Rohan Manchanda.
Page No : 299-307
|
Exchange Rate Dynamics and Recent Shocks in India
Abstract
Exchange rate stability in the economy is one of the most important determinants of its economic
performance. This study highlights the role of several macroeconomic variables like trade balance,
Foreign Direct Investment (FDI) inflows, foreign exchange reserves, interest rate differentials, and
GDP growth differential and the influence of volatile events like the 2007-2008 global financial crisis,
India’s 2016 demonetization drive, and the COVID 19 pandemic on the Indian Rupee (INR) against the
US Dollar (USD). The study employs annual time-series data for the 1979-2024 period based on the
Federal Reserve Economic Data (FRED) Database and the World Bank and Ordinary Least Squares
(OLS) regression model as a reference point with Autoregressive Distributed Lag (ARDL) and Error
Correction Models (ECM) to study short-run dynamics and long-run equilibrium relationships. The
INR/USD exchange rate is extremely reliant on trade balance, foreign exchange reserves, GDP growth
differentials, and FDI flows, while interest rate differentials have a relatively weaker relationship. The
study employs ECM and finds that exchange rate volatility due to events or shocks fails to revert to the
level of equilibrium in time. Policymakers can benefit by the findings of this study since it quotes the
determinants of the INR/USD exchange rate to enhance the economic resilience against future shocks.
| 34 |
Author(s):
David Kwon.
Page No : 308-315
|
Effect of Stage Coupling on Optimal Launch Angle in Multi-Stage Projectile Trajectories
Abstract
A practical question is raised when designing Rube Goldberg-style launch system that traditional
single-stage projectile formulas fail to answer well. How would the initial launch angle be selected
when the flight is broken into many segments separated by lossy contacts? Prior studies on single
stage motion, (including sports-tracking studies) indicated that the best angle depended on speed
and context, while more complexity was added through speed losses and changes of the direction
at each contact with multi-stage chains. This study specifically seeks to answer how initial launch
angle interacts with coupling in stages to determine total horizontal range in a multi-stage chain.
This study hypothesized that higher speed retention and more direction carryover in strong coupling
would shift the optimal initial angle upward, while increasing achievable range. Using real Statcast
distance and a large juggling dataset, the empirical coupling was estimated in terms of efficiency and
angular redirection. These were combined in Monte Carlo simulations of three-stage trajectories. The
single-stage baseline was averaged over observed exit speeds and turned out to be peaked near 26°
with an average predicted distance of around 89 feet. In multi-stage analysis, the optimal initial angle
rose as low from 29° to 41° as medium and to 48° as high coupling. Overall performance increased
monotonically, with medians increasing from 106 to 215 and to 326 feet, respectively. The hypothesis
in this study was supported that the high-minus-low shift in the optimal angle turned out to be positive
and sizable in spite of broad variability in redirection. Practical implications are that designers would
need to improve the weakest contact first and retune the initial angle after any coupling improvements.
| 35 |
Author(s):
Gan Chen.
Page No : 316-327
|
Bridging the Gap Between Clinical Reality and Public Perception: A Comparative Analysis of Schizophrenia Symptom Severity Using Social Media and Clinical Datasets
Abstract
Public perceptions of schizophrenia are often shaped by digital narratives that emphasize
certain symptoms while minimizing others. This study examines the divergence between clinical
symptom severity and online perception using two datasets: one from a clinical PANSS-based
schizophrenia assessment and another derived from Reddit posts classified via zero-shot learning.
Eleven overlapping symptoms were extracted and scored on a 1–7 scale. Methods included
comparative boxplots, Chi-square tests, correlation heatmaps, random forest classification, and
logistic regression. The results revealed consistent statistical and perceptual mismatches across
domains. Symptoms such as tension and suspiciousness were overrepresented in Reddit posts,
while cognitive and affective symptoms like guilt and poor attention were underrepresented. The
f
indings underscore the need for public education efforts tailored to underrecognized symptoms,
and highlight the potential of machine learning in digital psychiatry. Bridging these gaps may
improve stigma reduction and enhance digital mental health literacy.
| 36 |
Author(s):
Yun Koo.
Page No : 328-335
|
Quantitative Modeling of Economic Inequalities and the Prevalence of Food Deserts in Urban and Rural U.S. Census Tracts
Abstract
This study investigates the relationship between economic inequality and the prevalence of food
deserts among 300 U.S. census tracts with quantitative model, focusing on the prediction of food
inaccessibility through poverty, unemployment, and lack of transportation access. This study seeks to
answer the research question about whether structural socioeconomic factors influence the prevalence
of food deserts in the United States, and whether their effects may differ between urban and rural areas.
This study hypothesized that each factor of poverty, unemployment, and the lack of transportation
access would influence food accessibility, along with compounded effects from multiple disadvantages.
Multiple regression model was generated by using data from the USDA Food Access Research
Atlas and the American Community Survey, analyzing the stratified modeling and interaction terms
between poverty and vehicle access. With the interaction term-included model, 83% of the variance
was explained in the prevalence of food deserts (=0.83). All predictors were statistically significant (p
< 0.001). Unemployment rate proved to be the strongest influence in the prevalence of food deserts,
followed by poverty and vehicle access. With stratified models generated for each urban-only ( = 0.41)
and rural-only ( = 0.32) settings, vehicle access was shown to have greater relative importance in rural
areas than urban areas. When including the interaction term to generate a unified model, correlation
coefficient increased to 0.85, indicating that the impact of poverty was exacerbated when transportation
access problem was compounded. These findings provide a coherent quantitative framework to
understand food deserts as a structural outcome from intersecting economic inequalities. This study
underscores the role of intersectional and geographically-targeted policy interventions to address these
structural economic barriers and promote equitable food security.
| 37 |
Author(s):
Joonha Park.
Page No : 336-343
|
Balancing Artificial Intelligence Innovation and Job Preservation: A U.S. State-Level Policy Index Using Artificial Intelligence Exposure
Abstract
Artificial intelligence (AI) has been reshaping how work is performed across states, while creating
changes for both growth and concerns about job loss. Leaders are currently in a situation where they
need to make a clear yet fair rule to support innovation, while preserving jobs for workers. This study
particularly asks whether it is possible for a simple, single dataset-based rule can help leaders balance
artificial intelligence with job preservation. This study hypothesized that a rule rewarding higher
artificial intelligence task exposure with gentle penalty on extreme exposure would keep the national
portfolio clustered at a national mean, while maintaining priorities on high-potential places. Using
one publicly available dataset with the score of exposure to artificial intelligence from the Brookings
Institution (standardized state artificial intelligence exposure, 2017), this study analyzed 50 states with
the District of Columbia. Exposure scores were calculated to have the average of -0.007 (SD 0.044),
with Hawaii the lowest (-0.115) and Indiana the highest (0.065). According to ± 1 standard deviation
bands, this study classified 10 innovation-max states, 33 balanced states, and 8 job-preservation support
states. With an equal-weight index of a=0.5 to rank states, the top five states were Indiana, Kentucky,
Michigan, the District of Columbia, and Washington. This ranking stayed unchanged when shifting
weights towards innovation (a=0.7) or to job protection (a=0.3) through sensitivity analysis. Results
in this study supported the hypothesis in this study about how most states remained clustered around
the center, while maintaining priorities on high-potential places. The method taken in this study was
transparent, offering a practical initiative for policy design.
| 38 |
Author(s):
Mira Nutakki.
Page No : 344-352
|
Efficacy, Persistence And Safety of Inorganic vs. Organic Sunscreens: A Narrative Review
Abstract
As concerns arise regarding skin cancer and photoaging in individuals, understanding the
effectiveness of inorganic and organic sunscreen formulations is an essential matter for both healthcare
providers and consumers. This literature review analyzes relevant peer-reviewed studies published
between the years 2005 and 2024, focusing on matters of efficacy such as overall clinical performance,
photostability, user safety, and persistence. Inorganic sunscreens, primarily composed of zinc oxide and
titanium dioxide, function by reflecting and scattering UV rays; organic sunscreens, primarily composed
of oxybenzone, avobenzone, and octinoxate, absorb UV radiation instead. Findings suggest that, while
having different mechanisms, both inorganic and organic sunscreens provide efficient UV protection.
Inorganic sunscreens are found to possibly be more safe, persistent and effective for individuals with
sensitive skin barriers and prolonged water exposure; organic sunscreens are found to possibly be
more effective for individuals expecting minimal water exposure. However, direct comparison between
the two sunscreen agents is limited in factors of consumer application and regulated human testing
conditions. Despite technological advancements and concern regarding sunscreen efficacy, a gap is still
present; a need is highlighted for an increase in controlled standardized clinical trials to assess specific
sunscreen efficacy more accurately.
| 39 |
Author(s):
Ava Park.
Page No : 353-366
|
Evaluating the Fairness of Michelin Star Ratings as Indicators of Restaurants’ ESG Performance and Sustainable Culinary Quality
Abstract
This study quantitatively analyzes how fairly the Michelin Guide’s star ratings reflect restaurants’
ESG (Environmental, Social, and Governance) management and sustainable gastronomy quality. Using
open access data, the research statistically examines the relationships between Michelin stars and
Green Stars (sustainability certification), as well as the effects of various factors such as price, region,
descriptions, facilities, and menus. The results show that restaurants with the Green Star certification
are more likely to receive higher star ratings. Still, this tendency is mainly concentrated among high
end restaurants, and there is significant inequality across regions and price levels. While eco-friendly
keywords, facilities, and menu items are effective in earning the Green Star, they have a limited
impact on star ratings. Although Michelin still holds considerable authority, the study concludes that
true fairness requires the official expansion of ESG criteria and improvements in the transparency and
balance of the evaluation system.
| 40 |
Author(s):
Karen Nguyen.
Page No : 367-375
|
Beyond the City Limits: The Causes and Consequences of the Stigmatization of Homelessness in Suburban Areas
Abstract
Since urban and suburban homelessness manifests differently, suburban homelessness is
underresearched and underserved. Despite the documented prevalence of suburban homelessness, a
large portion of suburban homeless individuals still go unnoticed. While urban homelessness most often
manifests as easily visible by being on the streets of compacted cities, suburban homelessness may
manifest itself in less apparent forms, including individuals couch-surfing, living in cars, or doubling
up living spaces with friends and family. Stigma is a universal challenge for individuals experiencing
homelessness, regardless of location; both individuals experiencing homelessness in urban areas and their
suburban counterparts suffer from stigma. Specifically, stigma leads to a range of negative outcomes,
including avoidance of help-seeking behavior, worsened mental health disorders, and reduced access to
healthcare. In suburban areas, these effects are often compounded by limited resources and lower public
visibility. Therefore, more in-depth research on stigma specifically in the context of suburban areas is
needed. Furthermore, the development and testing of interventions tailored to address stigma and the
unique challenges faced by the suburban homeless population are also critically necessary. The central
goal of this paper is to fill a research gap by achieving several key objectives, including exploring how
stigma uniquely affects individuals experiencing homelessness in suburban areas and examining the
significant negative outcomes of this stigma, which are often compounded in suburban environments
due to fewer available resources. Lastly, the ultimate purpose of this research is to emphasize the urgent
need for new, tailored intervention, arguing that solutions developed for urban homelessness may not
always be effective in the suburbs.
| 41 |
Author(s):
Minkyung Kim.
Page No : 376-382
|
Do Emotional and Storytelling Boost Engagement? A Simple Decision Model Using Advertisements for the Super Bowl on YouTube
Abstract
Storytelling and emotional appeals are often recommended advertising strategies. However, it
remains unclear about whether they reliably improve audience response during high-attention events
like the Super Bowl. This study used a simple but transparent decision rule to pick the creative style
with the higher expected engagement per view on advertisements. This study particularly seeks to ask
whether emotional and storytelling advertisements on the Super Bowl generate higher engagement on
YouTube than non-emotional or product-first advertisements. This study hypothesizes that emotional
and storytelling advertisements would generate more per-view outcomes on likes-per-views and
comments-per-views. Assembling a publicly available dataset of 219 Super Bowl commercials and
merging it with basic YouTube metadata (views, likes, and comments) with independent creative
labels, this study normalized outcomes by views to compare advertisements. Compared group means
were calculated by using Welch’s unequal-variance t-test. Across both outcomes, differences between
emotional vs. non-emotional and storytelling vs. product-first advertisements turned out to be small and
not statistically significant (all p>0.05). Confidence intervals overlapped. Therefore, hypothesis in this
study was not supported. In a highly optimized setting, high-level creative labels alone did not much
increase observable social engagement.
| 42 |
Author(s):
Tvisha R. Yadiki.
Page No : 383-399
|
Investigating the Enzymatic Mechanism in Polystyrene Degradation: The Computational Modeling Approach
Abstract
Polystyrene, commonly known as Styrofoam, poses an urgent problem in today’s environmental
context. The material resists degradation, allowing it to accumulate in aquatic environments and
indirectly enter the food chain as microplastics. While current research has focused on the merits of
biodegrading this material, and several microorganisms have been identified to have this capability, the
specific enzymatic mechanism through which degradation occurs has not been identified. This research
aims to identify a potential mechanism between an identified enzyme (alkane-1-monooxygenase (AlkB)
from Acinetobacter johnsonii JNU01) and the substrate, polystyrene. A robust understanding of this
mechanism could lead to potential development of a widespread solution that can mitigate polystyrene
pollution. This paper will review the problems posed by polystyrene, benefits of biodegradation, current
research into plausible enzymes, the specific characteristics of the JNU01 AlkB enzyme, and conclude
with a computational docking experiment that demonstrates the interaction between the JNU01 AlkB
enzyme and polystyrene molecule. This study concluded that the most likely mechanism by which
polystyrene is degraded enzymatically is through backbone cleavage, in which the enzyme hydrolyzes
the carbon-carbon backbone in order to depolymerize the molecule, and allowing for subsequent styrene
monomer degradation.
| 43 |
Author(s):
Jeong-Pyo Han.
Page No : 400-406
|
Quantifying Minute-by-Minute Modeling of Cognitive Fatigue in a Stroop Task: Slower Exponential Decay and the Effect of a Brief Rest
Abstract
Sustained attention usually deteriorates during hour-scale tasks. However, it remains unclear
whether this attention decline is the same at a minute-by-minute scale, and also if there would be a
benefit of having very short rests. This study specifically seeks to answer which simple fatigue process
best identifies performance over a 60-minute Stroop-type task, and whether having a brief mid-task
rest significantly improves the performance of a task. This study hypothesized that a slower exponential
decline of attention would fit better than a standard or faster decline, and also that adding a one-minute
passive rest with a small post-break boost would improve task performance without affecting the fit
before the break. This study implemented four fatigue regimes (standard, slower, faster, and recovery)
as one-minute-step exponential models with Gaussian observation noise. Grid search was conducted to
set parameters by minimizing mean squared error against the benchmark, while estimating uncertainty
for error metrics with bootstrap confidence intervals and the one for correlation with Fisher-z intervals.
For each regime, this study ran R=10,000 simulations (seed=2025). Run-mean trajectories were reported
with 95% pointwise bands, while conducting sensitivity analyses varying the fatigue rate, noise level,
recovery magnitude, and break timing. Results in this study supported the hypothesis that the slower
model provided the best overall performance (e.g. r=0.89, mean squared error = 0.0035), followed by
the recovery model (r=0.86, mean squared error =0.0043), and the faster model (r=0.71, mean squared
error = 0.0117). These findings were supported by the sensitivity analysis that deviating fatigue rate
from its fitted value degraded the fit of the model, while higher noise widened bands without increasing
means. In addition, more end-of-task performance was preserved by earlier breaks.
| 44 |
Author(s):
Nhan Vuong.
Page No : 407-422
|
PARP Inhibitors-Associated Adverse Effects Across Multiple Organ Systems: A Review of Case Reports from 2022 to 2025
Abstract
Poly (ADP-ribose) polymerase (PARP) inhibitors have emerged as a groundbreaking therapeutic
class for cancers associated with Breast Cancer gene (BRCA)1/2 mutations and other homologous
recombination deficiencies. By disrupting Deoxyribonucleic Acid (DNA) repair pathways, these agents
demonstrate substantial efficacy in treating breast, ovarian, prostate, and pancreatic cancers. However,
PARP inhibitors also pose risks of adverse effects, some of which may be serious or life-threatening.
This review synthesizes case reports published between 2022 and 2025 documenting adverse effects
associated with PARP inhibitors. Emerging evidence highlights the diverse spectrum of adverse events,
including hematologic, dermatologic, gastrointestinal, hepatic, renal, cardiovascular, neurologic, and
pulmonary toxicities. Hematologic complications, particularly anemia, are most common, ranging from
mild anemia to severe pancytopenia and myelodysplastic syndrome. Dermatologic reactions, such as
erythema nodosum, cutaneous vasculitis, and Sweet syndrome, though uncommon, require timely
recognition and management. Gastrointestinal, hepatic, and renal toxicities are generally manageable
but occasionally severe, especially in older patients. Cardiovascular, neurologic, and pulmonary events
remain rare yet clinically significant. Adverse events profiles vary across PARP inhibitors. Olaparib
exhibits a broad spectrum of severity and organ systems, Niraparib frequently induces reversible
cytopenia, Talazoparib shows favorable long-term tolerability but can affect neurologic, cardiovascular,
or pulmonary systems, and Rucaparib is usually associated with mild hematologic effects but can also
involve gastrointestinal, hepatic or renal toxicities. As PARP inhibitors are relatively new, continued
pharmacovigilance remains essential to identify evolving safety concerns. Personalized risk assessment,
vigilant monitoring, timely dose adjustments, and supportive care are essential for optimizing
therapeutic outcomes and ensuring patient safety.
| 45 |
Author(s):
JIALE HUANG.
Page No : 423-436
|
Are the Economic Conditions of Fleet Electrification Sufficient to Support A Cap-And-Trade Market for Carbon Emissions of MHDV Transportation in the U.S.?
Abstract
This paper explores whether the financial conditions facing fleet electrification today are sufficient
for Medium and Heavy-Duty Vehicle (MHDV) operators in the U.S. and if these conditions ensured
a meaningful entered in the cap-and-trade market. Research used a forecast computational model that
combined Net Present Value (NPV) and total annual cost (TAC) analyses with simulated cap-and
trade market mechanics against true vehicle ownership costs which include for example, purchasing
cost and operating cost. The model assessed the economic viability of diesel and electric MHDVs
with respect to various carbon credit price scenarios. The findings suggest that the credit price needed
for electric trucks to compete under the current cost structure was much greater than allowance
prices in more established carbon markets such as California or the EU ETS, especially for medium
duty trucks. For heavy-duty trucks, the carbon price needed for the lifetime cost difference was close
to prevailing market values but still above current market rates. These results implied that at this
point in time, the cap-and-trade market alone would not be sufficient to get diesel MHDV operators
to adopt large-scale fleet electrification in the U.S. Thus, additional support, such as direct subsidies,
tax incentives, or increased carbon prices, will be necessary. These supported policies should remain
until further technological or market changes reduce the cost gap. This paper’s conclusions were
limited by the used of static cost assumptions and simplified market dynamics which may not fully
capture some future changes.
| 46 |
Author(s):
Sophie Tsui.
Page No : 437-445
|
Immune Reset: CAR T Cell Therapy as a Novel Approach in Autoimmune Disease Treatment
Abstract
Autoimmune diseases arise from immune system dysregulation and lead to chronic inflammation
and tissue damage. Aberrant B cell behavior, which includes autoantibody production and epitope
spreading, plays a crucial role in disease exacerbation. Traditionally, therapies like corticosteroids,
methotrexate, and monoclonal antibodies show efficacy in managing symptoms. However, they often
fail to achieve durable remission, leading to patients requiring lifelong treatment. Recent advancements
such as Chimeric Antigen Receptor (CAR) T cell therapy, bispecific T cell engagers (BiTES), and
Bruton’s tyrosine inhibitors (BTK) offer a novel approach for precisely targeting pathogenic immune
cells, but most importantly, achieving immune reset. CAR T therapy demonstrates great potential
in reducing patient reliance on immunosuppressive drugs while achieving sustained remission. This
review discusses the history of autoimmune disease treatment and how the field evolves away from
broad-spectrum immune suppressors towards targeted cell therapies which demonstrate curative
outcomes for patients.
| 47 |
Author(s):
Herbert Qin .
Page No : 446-453
|
Drones Under Weather Pressure: Analyzing Environmental Impacts on Detection Accuracy in Disaster Response Using SUR and Traditional Models
Abstract
The use of unmanned aircraft systems (UAS) in disaster response within densely populated urban
areas has continued to evolve. This study examines the deployment of drones in disaster management
in Tokyo, with particular attention to the environmental factors of wind speed, temperature, and
precipitation, using a filtered dataset of 44,569 entries obtained from Kaggle. Specifically, the study
evaluates how these environmental variables affect the efficacy of drone missions in completing
surveillance tasks, drawing on Tokyo’s urban disaster response simulations as well as anthropological
observations of drone flight practices using an array of regression models including a binary logit
regression model, negative binomial model, and multiple linear models for individual variables
affecting flight and ground detection. Finally, a joint model will be performed to determine any
differences between the three individual models and determine any correlation between variables. By
understanding the multi-factor influences on drone performance, disaster response teams can strengthen
operational strategies for unmanned aerial vehicle (UAV) deployment in relief missions. The findings
of this research can contribute to improving the strategic implementation of drones during both natural
and human-made disasters in highly populated areas such as Tokyo.
| 48 |
Author(s):
Silvana A. Sabrina Leddy.
Page No : 454-458
|
The Gut Microbiome and Mental Health: Mechanisms and Therapeutic Interventions
Abstract
The gut-brain axis comprises several components and mechanisms that affect mental health,
including the vagus nerve, gut microbiome, neurotransmitters, and the stress response. The gut
microbiome, a complex community of bacteria, plays a crucial role in regulating the brain’s emotional
state and behavior. Recent research emphasizes the profound influence of the gut-brain axis on mental
health. Furthermore, therapeutic interventions, such as probiotics, prebiotics, and phage therapy, offer
promising alternatives for influencing gut health, therefore influencing mental health. This literature
review explores those pathways and the effects of probiotics, synbiotics, diet, and phage therapy,
highlighting the role that gut-brain axis manipulation can have on mental health. Research has
shown that the gut microbiome heavily influences the gut-brain axis and can influence anxiety,
depression, and post-partum depression in mothers. Consuming prebiotics and probiotics could help
reduce the effects and symptoms of anxiety and depression. While prebiotics and probiotics play a
key role in supporting microbiomes, emerging alternatives, such as phage therapy and a balanced diet,
offer promising opportunities for improving mental health. Future research will continue to explore
additional strategies for developing more personalized treatments.
| 49 |
Author(s):
Will Teitelbaum.
Page No : 459-465
|
The Current Knowledge and Treatment of SHOX Deficiency
Abstract
One of the most common genetic causes of short stature is the haploinsufficiency of the Short-stature
Homeobox (SHOX) gene. In this group of SHOX-related disorders, SHOX deficiency is one of the most
severe forms, resulting from the loss of function of one SHOX allele. This literature review discusses
the current knowledge of SHOX deficiency, including its manifestation, diagnosis, major symptoms,
and treatments. It is estimated that SHOX deficiency is responsible for about 6.8% of individuals with
short stature-related diseases. The use of Recombinant Human Growth Hormones (rhGH) to alleviate
growth impairment has been proven effective in treating prepubertal patients who begin therapy at a
young age. An Italian study on adolescents with SHOX deficiency discovered that rhGH therapy yielded
an overall height gain of +0.80 ±0.98 standard deviation score (SDS) from the start of treatment to the
attainment of final height, with a duration of 5.94 ± 2.00 years. However, the often mild and complex
symptoms in prepubertal patients make early diagnosis challenging, and treatment occurring after
the onset of puberty can limit the positive growth effects of this therapy. This review also analyzes
alternative treatment options to rhGH therapy, including the use of Gonadotropin-releasing hormone
agonists (GnRHa) as a way to slow down puberty progression. However, studies on the effectiveness of
GnRHa remain inconclusive. Lastly, this review evaluates the potential role of the emerging CRISPR
Cas9 gene-editing technology, and emphasizes the importance of and need for continued research into
new methods for early diagnosis.
| 50 |
Author(s):
Jiarui Liu.
Page No : 466-474
|
Could LLMs Systems be Self-Conscious in The Future?
Abstract
Despite claims that escalating computational complexity and sophisticated learning architectures
could potentially enable AI systems to attain self-awareness, numerous scholars and technologists
maintain that, regardless of the advancement in their linguistic proficiency and contextual
comprehension, Large Language Models (LLMs) inherently lack the subjective experiences essential
for authentic self-consciousness. The article explores the philosophical underpinnings that differentiate
basic awareness, an entity’s ability to process and react to environmental cues, from higher-order self
reflection, which involves an agent’s introspective recognition and contemplation of its own mental
states. In the paper, it has been analyzed the central theoretical constructs proposed by Thomas Nagel,
José Luis Bermúdez, and David Rosenthal. Moreover, the paper employs the red dot (mirror) test and
consider digital adaptations to assess LLM’s detection of hidden changes in their outputs. LLMs exhibit
reliable recall of previous responses within a single session; however, their episodic retrieval lacks the
necessary continuity to sustain personal identity across interactions. Ultimately, despite their advanced
functionalities, LLMs are devoid of authentic subjective experience and individuality. The separation of
simulated self-awareness from genuine consciousness is essential for the responsible progression of AI.
Philosophical delineations are crucial for distinguishing simulations from real experiences, a factor vital
for ethical guidelines and policy frameworks in AI’s societal integration. Philosophical delineations
are crucial for distinguishing simulations from real experiences, a factor vital for ethical guidelines
and policy frameworks in AI’s societal integration. The objective of this paper is to examine whether
Large Language Models could develop self-consciousness by analyzing philosophical definitions,
reviewing current cognitive science perspectives, and evaluating experimental approaches designed to
test machine awareness.
| 51 |
Author(s):
Rishabh Chakraborty.
Page No : 475-483
|
Adrenaline and the Heart: Physiology, a History, and Clinical Implications
Abstract
The fight-or-flight response triggers rapid-acting cardiac effects to enhance survival by increasing
heart rate and contractility. These effects arise from adrenaline’s effect on calcium ion channels
and preexisting electrical signaling in cardiac muscle. Literature exploring the adrenergic pathway
is well-established, as it includes the discovery of the funny current in 1979 and the “calcium
clock,” both of which are altered contractile mechanisms in the myocardium that play a key role
in the heart’s automaticity, as well as the expanding knowledge of adrenaline’s several molecular
pathways in cardiac tissue in modern literature. Modern clinical applications of adrenaline include
heart conditions such as atrial fibrillation and genetic arrhythmias like Long QT Syndrome, of which
adrenaline is a major trigger. Major therapies for these cases, such as beta-blockers or Ivabradine, are
widely used in modern medicine and relate to adrenaline’s cardiac pathway. Ultimately, this review
aims to consolidate the extensive history of cardiac-adrenergic signaling in literature to further
potential usage of signaling-related therapies in a clinical setting for treatment of adrenaline-related
heart conditions.
| 52 |
Author(s):
Sophia Han.
Page No : 484-493
|
Mandated Reporting in Education: A Review of Educators’ Confidence, Accuracy, and Impact
Abstract
Mandated reporting laws require educators to report suspected child abuse or neglect, but inadequate
training often leaves them uncertain and underprepared. This raises critical questions about the accuracy
of reporting, teacher confidence, and the unintended impact on students and families. To write this
narrative review, the author compiled information from existing literature reviews, government records,
educator surveys, and statistics on abuse and racial profiling. This paper identifies key barriers to
reporting, such as unclear legal terminology, inadequate training, personal attitudes toward discipline,
and fear of damaging relationships with families. Educators, who have significant interaction with
children, are often found to be undertrained for this responsibility. Findings show that educators file
more unsubstantiated reports than any other profession. This leads to systemic inefficiencies, emotional
distress, and a disproportionate impact on marginalized communities. The author was motivated by the
significant gaps in existing literature, as most studies focus on the experiences of school counselors,
medical professionals, or mental health professionals. This paper aims to highlight gaps in the existing
literature on educators’ experiences with mandated reporting, with the goal of informing reforms in
training and support systems to reduce unintended harm.
| 53 |
Author(s):
Haokun Chen .
Page No : 494-500
|
Blood-Based Phosphorylated Tau Isoforms as Emerging Biomarkers for Alzheimer’s Disease
Abstract
Alzheimer’s disease (AD) is a progressive, currently incurable neurodegenerative disorder
characterized by cognitive impairment. The neuropathology of AD is defined by two hallmark
features: the extracellular deposition of amyloid-β (Aβ) plaques and the intracellular accumulation
of neurofibrillary tangles composed of hyperphosphorylated Tau protein. Though cerebrospinal fluid
(CSF) testing and imaging techniques such as positron emission tomography (PET) currently serve
as diagnostic gold standards, CSF testing is invasive, and the latter is expensive and less accessible.
Recent studies document the blood-based phosphorylated Tau (p-Tau) isoforms, particularly p-Tau181,
p-Tau217 and p-Tau231, as promising next-generation noninvasive biomarkers for the early diagnosis
of AD and disease monitoring. This review summarizes present evidence for clinical utility of blood
based p-Tau isoforms, specifically in terms of diagnostic validity, early detection ability, and ability
to discriminate AD from other neurodegenerative disorders. Blood-based p-Tau testing holds the
possibility to revolutionize AD diagnostic models, with prospects of far-reaching dissemination and
early intervention.
| 54 |
Author(s):
Misha Kalava.
Page No : 501-508
|
Secrets Behind Scrolling: How Nighttime Screen Exposure Affects Sleep, Health, and Daily Life
Abstract
We are exposed to blue light today more than ever in history. However, little is known about the long
term impact of this societal shift. The objective of this review is to critically evaluate the health effects
associated with exposure to light emitted from technological devices—particularly during the pre
sleep period—with a focus on its impact on sleep quality, overall health, daily routines, and cognitive
performance. The studies in this review demonstrate that light has a negative impact; therefore, we
provide advice on navigating this in the real world. To minimize blue light’s effects, individuals should
try restricting technology usage before bed and ensuring you have plenty of exposure to natural blue
light during the day.
| 55 |
Author(s):
Canseli Durmaz.
Page No : 509-515
|
Cancer Immune Evasion and Immunotherapies: Progress and Challenges of CAR-T in Solid Tumors
Abstract
Solid tumors account for nearly 90% of the global cancer diagnoses, which is over 20 million annually,
making them a central focus in the global fight against cancer. Specifically, by downregulating antigen
presentation and reprogramming innate immune cells, tumors can evade the immune system, creating
a significant challenge for effective treatment. Furthermore, to overcome these challenges, multiple
immunotherapies, including checkpoint inhibitors, vaccines, and adoptive immunotherapies, have
been developed. While checkpoint inhibitors and vaccines have demonstrated progress, they depend
on major histocompatibility complex-I (MHC-I)-mediated antigen recognition, causing cancer cells
with mutated antigen presentation to remain undetected. On the other hand, chimeric antigen receptor
T cell (CAR-T) therapy, a type of adoptive immunotherapy, involves engineering classical immune T
cells in an ex vivo environment to bypass the MHC-antigen requirement. This MHC-independence
allows CAR-T cells to recognize tumors more efficiently, overcoming the challenge posed by other
recognized immune therapies. However, CAR-T therapies are primarily recognized for their success
in treating B-cell leukemia, a type of white blood cell cancer, and their clinical application in solid
tumors is limited. This review examines the current literature on cancer immune escape mechanisms
and immunotherapies, with a focus on the obstacles that limit the effectiveness of CAR-T therapies in
solid tumors. Additionally, it evaluates clinical trial findings, which indicate progress in survival and
tumor control in the short term. Through these examinations, the review underscores the potential of
CAR-T therapy for effective treatment of solid tumors.
| 56 |
Author(s):
Elizabeth Cameron,.
Page No : 516-524
|
Dance Movement Therapy: Improving Adolescent Mental Health
Abstract
Cognitive Behavioral Therapy (CBT) is a key treatment for anxiety and depression. However, CBT
alone has limitations in adolescents due to emotional imbalances. Dance Movement Therapy (DMT)
allows adolescents to express emotions in a way that is active and socially acceptable. In adults, DMT
in combination with CBT is an effective approach for treating mental health conditions. However, there
is limited literature on the impact of DMT in adolescents and no studies on potential long-term benefits.
This paper reviews current publications on DMT as a therapeutic tool for mental health treatment in
adolescents, including background on DMT, neurophysiological concepts, the mirror neuron system
(MNS) and the potential benefits of combined CBT/DMT. This review suggests that due to the
challenges of studying DMT (e.g., limited use of functional MRI (fMRI) in a moving dancer), more
studies are necessary to evaluate the efficacy and application of combined therapy. This review also
recommends exploration of new platforms to deliver DMT, such as smartphone apps, metaverse and
virtual reality (VR). This could make combined therapy more successful, affordable, and accessible to
a wider population. Future research should be focused on longitudinal studies on combined CBT/DMT
in adolescents.
| 57 |
Author(s):
Mahnur Zeshan, Kiara L. Rodriguez-Acevedo.
Page No : 525-535
|
CRISPR-Cas9 and Parkinson’s Disease: A Review of Gene Editing Strategies and Therapeutic Potential
Abstract
Parkinson’s Disease (PD) is a progressive neurodegenerative disorder characterized by the loss of
dopaminergic neurons, leading to motor impairments such as tremors, rigidity, and bradykinesia, as
well as cognitive decline. Current treatments, including dopaminergic medications and deep brain
stimulation, manage symptoms but do not stop disease progression. Genetic mutations in SNCA,
LRRK2, and PARKIN, along with environmental factors, contribute to PD’s development. CRISPR
Cas9 presents a potential therapeutic avenue by enabling precise gene modifications to correct PD
related mutations, reduce toxic protein accumulation, and improve mitochondrial function. It also
enhances stem cell therapies, offering new possibilities for disease modification. However, challenges
such as targeted gene delivery, off-target effects, and ethical concerns must be addressed before clinical
implementation. This paper explores PD’s underlying mechanisms, current treatment limitations, and
CRISPR’s role in developing novel therapies. It also examines the scientific and ethical challenges that
must be navigated to bring CRISPR-based interventions into practical use for PD patients.
| 58 |
Author(s):
Yael Amematekpo.
Page No : 536-540
|
Gene Editing with CRISPR: A New Era for Treating Beta Thalassemia
Abstract
Beta thalassemia is a serious genetic blood disorder that affects thousands of people around the
world, especially in regions like the Mediterranean, the Middle East, South Asia, and parts of Africa.
It happens when a person inherits mutations in the HBB gene, which is responsible for making
hemoglobin, the protein in red blood cells that carries oxygen throughout the body. These mutations
reduce or block the production of healthy hemoglobin, leading to chronic anemia, fatigue, organ
complications, and in severe cases, lifelong dependence on blood transfusions. Despite the availability
of supportive treatments like iron chelation therapy and stem cell transplants, most options only
manage symptoms rather than cure the disease. This is where CRISPR-Cas9, a powerful tool that can
directly modify the DNA responsible for the condition. Instead of treating symptoms over a lifetime,
CRISPR offers the possibility of a one-time, long-lasting solution. Casgevy is a new CRISPR-based
therapy developed by Vertex Pharmaceuticals and CRISPR Therapeutics, and is currently being used
in clinical trials to help patients with transfusion-dependent beta thalassemia and sickle cell disease
by reactivating fetal hemoglobin production. Early results are promising: patients who once needed
frequent transfusions have been able to live transfusion-free for over a year. This paper explores beta
thalassemia, the science behind CRISPR-Cas9 gene editing, the mechanism and outcomes of Casgevy,
and the ethical and medical considerations of deploying such technologies.
| 59 |
Author(s):
Jinjida Wongsurakiat.
Page No : 541-548
|
The Correlation Between Sleep and Academic Performance: A Literature Review
Abstract
Sleep is a fundamental biological function experienced by everyone. Sleep occurs every night, but
it is far more than just a period of rest. Sleep is an important function that supports both physical and
mental health. This review examines the effects of sleep on academic performance, and the correlation
between sleep and school performance. Specifically, how the quality of sleep, quantity of sleep, and
sleepiness during the day affect a student’s academic performance. How sleep contributes to in-class
performance, and whether lack of sleep or gain in sleep can affect exam scores or grade point average
(GPA). At the end, this review discusses whether a change in school start time is necessary, and the
benefits and disadvantages of a later school start time on students’ sleep. The results show that sleep does
have an effect on school performance. Whether it be maintaining focus in class, memory stabilization,
or the ability to transcribe information studied into memory, sleep plays an important role in these
functions. Most research supports a positive association between sleep and higher GPA, as well as better
school performance. These findings underscore the importance of sleep as a foundation for learning and
cognitive development during childhood and adolescence. At the same time, important uncertainties
remain. Some studies report weak or inconsistent links between sleep duration and standardized test
scores, suggesting that academic outcomes may depend on additional factors. Moreover, the relative
contributions of sleep duration, sleep quality, and timing are not yet fully disentangled, leaving open
questions about which aspects of sleep are most influential for academic success. More work should
examine how sleep interventions, such as delayed school start times, or digital media restrictions
affect both sleep patterns and academic outcomes. Overall, this body of research highlights sleep
as an educational priority. Improving adolescent sleep habits has the potential to enhance academic
performance.
| 60 |
Author(s):
Rebecca Koleth.
Page No : 549-555
|
Deep Learning Approaches for Ground Penetrating Radar Detection for Archaeological Applications
Abstract
Ground Penetrating Radar (GPR) is an essential non-invasive method in archaeology for finding
archaeological features below the surface. However, interpreting the data can be difficult due to its
complexity and noise. This research investigates the application of deep learning models to enhance the
detection and interpretation of subsurface archaeological features using GPR data. Due to the scarcity
of publicly available annotated GPR datasets, simulated data generated using the gprMax software
is utilized. A Convolutional Neural Network (CNN) is built with TensorFlow and Keras. It focuses
on creating bounding boxes around hyperbolic reflection signatures in B-scan radargrams. These
simulations feature a buried perfect electric conductor (PEC) cylinder in a dielectric half-space. The
model showed promising results, with Intersection over Union (IoU) scores of 0.93 reflecting accurate
localization on test samples. This study establishes the foundation for future applications of deep
learning to archaeological GPR data analysis. It also demonstrates that simulation-based training can
be effective and provides a basic model where annotated samples are often scarce. This contribution is
important because it positions simulation-driven training as a cost-effective option for archaeological
geophysics. Data shortages have often limited the use of AI in this field. By presenting a CNN
framework that adapts well to new simulated conditions, the study emphasizes the future potential of
hybrid methods that combine synthetic and real data.
| 61 |
Author(s):
Prisha Suresh.
Page No : 556-564
|
Applications of Stem Cell Therapy and Gene-Editing Technologies in Leukemia Treatments
Abstract
Leukemia, especially acute myelogenous leukemia, affects millions across the globe and has been the
focus of many new and emerging treatment opportunities, including stem cell therapy. Hematopoietic
stem cells, a type of stem cell that eventually develops into blood cells or platelets, have been a crucial
part of many of these emerging treatments. This article focuses on how genetic engineering of stem
cells can enhance their therapeutic potential in treating various forms of leukemia. Some promising
applications of genetically modified stem cells include modifying stem cells with an apoptosis gene to
selectively kill the cancerous cells and create a suicide gene mechanism, using modified hematopoietic
stem cells (HSCs) to create chimeric antigen receptor T-cells (CAR T-cells), and modifying induced
pluripotent stem cell derived natural killer (iPSCs-derived NK) cells to target tumors at multiple
antigen sites. In addition to this, this mechanism has shown significant promise in the treatment of
leukemic stem cells, which can aid in preventing relapse. Despite major success in the field of genetically
modified stem cell (GMSC)-based treatment, more research is needed to determine how this technique
can translate to patient-based care and be used in clinical settings.
| 62 |
Author(s):
Vindhya Vasanthan.
Page No : 565-577
|
Populism, Postcolonial States and the Contestation of International Legal Authority
Abstract
This paper examines how populist movements in postcolonial states challenge the authority of
international legal institutions, focusing on the Philippines under Rodrigo Duterte and Indonesia under
Joko Widodo. It argues that these leaders do not reject international law outright but strategically
reframe it as a neocolonial imposition incompatible with sovereignty and self-determination. Using
a framework informed by populism theory, Third World Approaches to International Law (TWAIL),
and legitimacy theory, the study identifies three modes of contestation—rhetorical, institutional, and
doctrinal. Duterte pursued open confrontation through anti-ICC rhetoric and treaty withdrawal, while
Jokowi adopted subtler disengagement by privileging ASEAN mechanisms and national priorities over
global norms. The comparative analysis shows that neither case fully delegitimizes international law;
instead, both erode its universality and recast its authority as conditional on domestic and postcolonial
narratives of justice. These findings highlight the need for international legal institutions to adapt to
plural sovereignties and historically grounded claims of legitimacy.
| 63 |
Author(s):
Christian Gorgy.
Page No : 578-587
|
Social Media Influence on Real Estate Decision-Making Among Generation Z
Abstract
In a world where TikTok, Instagram, and algorithmic aesthetics prevail, real estate has evolved
beyond traditional measures of square footage and location. Instead, it morphs into an exercise in
presentation, perception, and performance. This paper takes a plunge into examining the dynamic
continuums of engagement between social media and real estate, specifically how generational
meta-preferences and Gen Z’s norms of interacting with tightly curated digital lifestyle content have
impacted housing aspirations, market behaviors, and the real estate industry’s responses. Through
analysis of trending reports, subject-matter expert evidence, and available market data, this case study
examines the influence of perceived housing desirability on attitudes and behaviors, the cultivation of
a comparison culture, and social media’s expectations for designing and presenting spaces with visual
narratives in mind. The case study analyzes which features younger buyers value - given demographic
proportions - based on property visibility in “camera-ready” formats, aesthetic cues, and the
“Instagrammability” of spaces. It further considers how real estate professionals are shifting business
practices, gesturing toward short videos, emotionally loaded marketing, and curated brand identities
that enter the consciousness of this generation. These shifts promote visibility and engagement while
raising questions about affordability, loyalty, and longevity.
| 64 |
Author(s):
Arjun Makineni .
Page No : 588-596
|
A Comparative Analysis of Deep Learning Models for Automated Snakebite Wound Classification
Abstract
Snakebite envenomation remains a severe global health challenge, responsible for millions of
cases and over 100,000 deaths each year, particularly in rural and underserved regions. This study
compares multiple convolutional neural network (CNN) architectures, including EfficientNet variants
(B0, B3, B4, V2B0, V2L), ResNet50, MobileNetV3-Large, and ConvNeXt-Large, for the classification
of snakebite wounds. After minimal preprocessing through normalization, data augmentation, and
class weighting due to a limited dataset size, the models are evaluated through metrics such as
accuracy, precision, recall, F1-score, Matthews Correlation Coefficient, Cohen’s Kappa, and Average
Precision, with bootstrap resampling ensuring statistical rigor. EfficientNetV2B0 achieved the highest
accuracy, 91.53%, and perfect recall for venomous bites, minimizing life-threatening false negatives.
These findings highlight the potential of AI-based snakebite diagnostics to provide immediate,
reliable guidance. The discussion emphasizes the clinical implications of this performance, and
this study concludes that integrating the top model into a mobile health application could improve
survival rates by enabling effective initial care before patients reach a doctor.
| 65 |
Author(s):
Allison Hsieh.
Page No : 597-606
|
Recent Advancements in Targeted Breast Cancer Treatments: A Review of Clinical Trials
Abstract
Despite developing standard treatments, breast cancer remains a global challenge due to its high
recurrence rates and treatment-resistant tumors, emphasizing a need for more targeted treatment
strategies. Standard treatments such as chemotherapy, radiation therapy, and surgery are nonspecific
and significantly reduce patient quality of life. This review presents recent clinical trial findings on both
single-line and combination targeted therapies, focusing on their efficacy, safety, and how biomarkers
help optimize patient outcomes. The four main results of this paper indicate: PARP and PD-L1 inhibitors
significantly benefit certain subgroups, an antibody drug-conjugate (ADC) is effective regardless of
Trop-2 expression, adoptive cell transfer (ACT) shows promise for extremely personalized treatment,
and dietary restrictions further induce anti-tumor activity. While challenges such as increased toxicity
and little improvement in overall survival (OS) were observed, targeted therapies are a significant step
towards creating effective, personalized treatments for breast cancer.
| 66 |
Author(s):
Noah Vassilev.
Page No : 607-614
|
Hierarchical Deep Neural Network for Child Brain Health Assessment
Abstract
Early assessment of mental health in youth is vital for prevention and timely intervention, yet current
clinical practice relies on subjective, labor-intensive questionnaires. This study presents a hierarchical
deep neural network that predicts dimensional psychopathology scores from electroencephalography
(EEG). Task-specific encoders are trained on power spectral density (PSD) and Hjorth features,
demographics, and task annotations, and a second-stage Long Short-Term Memory (LSTM) fuses per
task embeddings to produce subject-level scores. Using the Healthy Brain Network EEG (HBN-EEG)
dataset, evaluation occurs under a leave-one-release-out protocol with 5-fold cross-validation. The
proposed model achieves a higher R2 and lower root mean square error (RMSE) than the baselines
with statistically significant gains in most comparisons, and shows robustness to heterogeneity in task
completion, run counts, and session durations. These results demonstrate considerable robustness
against dataset subject- and task-level heterogeneity. This study highlights great potential for an effective
and comprehensive AI-driven evaluation method for mental healthcare.
| 67 |
Author(s):
Isabelle Kirsten Sophia Hibbert.
Page No : 615-625
|
CRISPR-Cas9 and Tissue Engineering: A Synergistic Approach to Correcting TEK Gene Mutations in Localized Vascular Anomalies
Abstract
Vascular anomalies, which include both vascular tumors and malformations, can result in significant
complications such as chronic pain, physical disfigurement, and impaired joint function. Many vascular
anomalies are often caused by mutations in the TEK gene, which lead to the overactivation of the PI3K
AKT-mTOR signaling pathway. This dysregulation contributes to the formation of weak, malformed
vessels. Current treatments, such as sclerotherapy and surgical intervention, are not curative and are
associated with a risk of recurrence. Given the limitations of current treatments, there is growing
interest in next-generation regenerative approaches. The synergistic integration of gene-editing
technology such as CRISPR-Cas9 and tissue engineering holds promise. CRISPR-Cas9 provides the
potential to correct pathogenic mutations at the genomic level by targeting specific DNA sequences
within the TEK gene. Additionally, tissue engineering could enable the replacement of damaged blood
vessels using bioengineered scaffolds and stem cell derived vascular tissues, potentially reducing the
risk of immune rejection. Despite these promising developments, several challenges remain, including
surgical risks, the possibility of off-target gene editing and ongoing ethical concerns. This paper reviews
and synthesizes current literature on CRISPR-Cas9 and tissue engineering, with the aim of exploring
their combined potential as a novel, personalized therapeutic strategy for treating vascular anomalies.
By identifying both the opportunities and limitations of this approach, this paper contributes to the
growing body of knowledge guiding the development of mutation-targeted, regenerative treatments that
address the root causes of vascular disease.
| 68 |
Author(s):
Nidhi Vaddi.
Page No : 626-636
|
Flashbacks and Friendships: How Autobiographical Memory Can Be Used to Foster Social Learning
Abstract
There is a rising prevalence of children with Autism Spectrum Disorder in the current status quo.
Autism Spectrum Disorder is known for causing issues in social functioning for children who are
affected by the disorder, so it is necessary to identify best practices when it comes to social learning for
said children. Differences in the use of memory have often been identified when looking at children with
Autism Spectrum Disorder in comparison to their typically developing peers, as their autobiographical
memory seems to be diminished. The present study involves a meta analysis of 14 autobiographical
memory recall methods as well as social learning methods that have been proven to work for children
with Autism Spectrum Disorder. Through the use of an Ex-Post Facto research method, 14 methods
were narrowed down to just two: the most compatible and highly effective autobiographical memory
recall method and social learning method. The findings suggest that the use of images from the
perspective of the child showing the child being placed in social situations will be an effective method
to facilitate social learning through autobiographical memory recall. This method should increase
detail and quantity of memories by 93% while increasing social behavior by over 7.5%, as taken from
previously completed studies. This provides a way for children to build social connections in a way that
is not otherwise possible.
| 69 |
Author(s):
Siya Paigude.
Page No : 637-650
|
Automated Dyslexia Screening In Czech Elementary Students Through LSTM Analysis Of Eye Tracking Data
Abstract
Dyslexia is a neurodevelopmental reading disability affecting the speed and accuracy of word
recognition in 5-10% of the population, as well as reading fluency and comprehension. Early
intervention is essential, yet existing screening methods are often unreliable, slow, and may take months
to produce results. Limited accessibility increases the risk of under-diagnosis, leaving many children
without proper identification. This research explores the potential of a deep learning-based approach
for preliminary dyslexia screening in Czech 4th-grade students (ages 9-10) through analysis of eye
tracking data from the ETDD70 dataset. The dataset contains eye-tracking recordings from 70 Czech
participants (35 dyslexic, 35 non-dyslexic) aged 9-10 years, comprising over 7.2 million eye movement
data points across three distinct reading tasks: syllable reading, meaningful text comprehension, and
pseudo-text decoding. We developed a novel model consisting of three parallel bidirectional Long
Short-Term Memory (LSTM) networks with 128-dimensional hidden vectors and multi-head attention
mechanisms with 3 attention heads, trained using AdamW optimizer with learning rate scheduling. The
primary contribution of this model is its innovative architecture, which enables simultaneous processing
and extraction of information from three distinct eye-tracking datasets. Within our limited dataset of
70 participants (train: 46, validation: 12, test: 12), the model demonstrated 83.33% overall accuracy
with perfect sensitivity (100% recall) for dyslexic identification, alongside 75% precision for dyslexic
classification, 100% precision for non-dyslexic identification, and an F1-score of 85.71%. As a proof-of
concept study with a limited sample of 70 participants, these preliminary results demonstrate technical
feasibility but lack baseline model comparisons to establish architectural advantages. Validation through
larger-scale studies with diverse populations and systematic comparison against traditional machine
learning approaches is required before clinical application can be considered.
| 70 |
Author(s):
Ruilang Li.
Page No : 651-658
|
Fostering Emotional Well-Being Through Human-Centric Design: Transforming Architecture for Honor and Belonging
Abstract
As people spend less time in natural environments due to factors such as urbanization, cultural
and lifestyle changes, and technological shifts reducing the need to be outdoors, the need for
humanistic architecture has become more and more prevalent in order to maintain mental well-being.
Advancements are being made in the research and implementation of architectural design to address
emotional needs, but to aid future research, this work aims to emphasize the importance of building
structures as environments that truly support and enhance human life. Human-centric architectural
design can transform rationalist and modernist paradigms into spaces that foster deep emotional
connections between people and their environments. Here, “emotion” transcends aesthetic preference,
encompassing complex psychological and social states that promote self-preservation, incorporate
collective and individual memory, and foster a sense of belonging on both unique and shared levels.
Through an analysis of architectural case studies and interdisciplinary research, this work evaluates
design techniques, such as participatory processes, multi-sensory integration, and culturally responsive
forms, that translate these emotions into tangible spatial experiences. By examining the interplay
between human-centered design and mental health, this research demonstrates how architecture can
actively support emotional well-being, addressing challenges like anxiety and disconnection in urban
environments. Drawing on examples like the Maison Bordeaux and Ningbo Museum, the paper argues
that architecture must prioritize embodied cognition and cultural identity to create spaces that inspire,
sustain, and nurture human existence and community cohesion.
| 71 |
Author(s):
Hanming Li.
Page No : 659-674
|
Immune Disruption and Disease Development by Microplastic Exposure
Abstract
Global plastic production will grow from 464 tons in 2020 to 884 tons in 2050, and microplastics
(MPs) and nanoplastics (NPs) resulting from the decay of larger pieces have become ubiquitous. Thus,
almost all humans are exposed to these particles through ingestion, inhalation, and dermal contact.
Research on MPs has grown significantly since their major start in 2018, but because of their novelty,
MPs’ full effects on human health are not well defined, especially in the immune system. This paper
aims to provide a review of this topic. An array of contemporary data has been gathered regarding the
effect of MPs on the different types of cells and responses involved in the immune system. This paper
also explores the roadblocks in researching this topic. It is concluded that MPs weaken the innate and
adaptive immune system, can accumulate in lymphatic tissue, cause inflammation and inflammation
related processes across the body, which result in a variety of negative health effects from autoimmune
reactions to cancer susceptibility. This paper provides a comprehensive foundation for the current
understanding of the impacts of microplastics on human health and underscores the numerous aspects
in which further research is needed.
| 72 |
Author(s):
Ananya Thota.
Page No : 675-683
|
Understanding Endometriosis from an Interdisciplinary Lens: A Literature Review
Abstract
Endometriosis (EMS) is a chronic, estrogen-dependent, and progesterone-resistant inflammatory
condition in which endometrial-like tissue is found outside the uterus, affecting 6-10% of reproductive
age women. Research has emerged on the genetic and biological associations of EMS, identifying
biological pathways such as sex steroid hormone pathways and specific genes that may contribute to
the disease phenotype. Despite this, there is uncertainty on how different findings across different
scientific disciplines compare and inform the public on EMS pathogenesis. This paper synthesizes
f
indings from the emerging genetic research and hormonal-associated studies and discusses how these
f
indings contribute to our existing knowledge of EMS causes and progression. Understanding the
intersectionality of biological mechanisms from different regulatory systems, relevant pathways, and
how they contribute to the chronic and inflammatory nature of EMS, will deepen our knowledge of the
disease pathology. Thus experts should also consider examining EMS from a more interdisciplinary
perspective, such as conducting multi-system EMS studies and including diverse populations in EMS
research as novel approaches for studying EMS and other reproductive-related diseases.
| 73 |
Author(s):
Jeffrey Huang.
Page No : 684-691
|
Functionalized Lipid Nanoparticles Show Efficacy in Glioma Animal Models
Abstract
Gliomas, particularly glioblastomas, are brain tumors characterized by aggressive growth, high
recurrence rates, and a median 5-year survival rate of ~5%. Treatment of brain tissue is highly restricted
due to the blood-brain barrier’s (BBB) selective permeability, which makes gliomas incredibly difficult
to target. In recent years, there have been many developments in the use of lipid nanoparticles (LNPs)
as drug delivery systems. Specifically, functionalized LNPs have shown promise in treating gliomas
due to their ability to cross the blood-brain barrier. This review presents the surface-modified LNPs
designed for glioma treatment that have demonstrated efficacy in in vivo animal studies. Presented
here are LNPs loaded with chemotherapy and functionalized with transferrin, lactoferrin, Angiopep-2,
ApoE, and cell-penetrating peptides that demonstrate a promising ability to treat gliomas.
| 74 |
Author(s):
Charlotte Brard.
Page No : 692-700
|
Beyond the Forecast: A Comparative Study of Turbulence Prediction Systems in Aviatio
Abstract
Turbulence remains one of the most persistent and unpredictable hazards in aviation, yet little
research has conducted an integrated comparative analysis of turbulence prediction systems across
methodological categories. Most studies have evaluated individual models in isolation, leaving a gap in
understanding how different approaches perform relative to one another. This study aimed to examine
the strengths and limitations of four representative systems for turbulence forecasting: statistical
learning using PCA with support vector classification, the GEKO turbulence model based on generalized
k–ω equations, the sensor-driven FUTURA model for real-time anomaly detection, and the ECMWF
ensemble-based Integrated Forecasting System. Each system was evaluated on four operational criteria:
accuracy, adaptability, efficiency, and performance under adverse weather conditions. Results showed
that GEKO achieved the highest accuracy but was computationally too demanding for real-time use.
FUTURA excelled in adaptability and speed, although its alerts were limited to short-range predictions.
The ECMWF ensemble system demonstrated strong coverage and reliability in adverse weather but
suffered from delays. The statistical learning model produced balanced results but remained constrained
by data sparsity. The findings suggest that no single model can address all operational needs, but
combining complementary approaches into a hybrid framework offers the most effective pathway. This
research contributes an evidence-based foundation for developing integrated turbulence forecasting
systems to improve aviation safety, efficiency, and reliability.
| 75 |
Author(s):
Chloe Chen.
Page No : 701-709
|
Advances and Challenges in Gastric Cancer Management: Chemotherapy, Radiation, and Targeted Therapy
Abstract
Gastric cancer continues to rank as one of the most prevalent and deadly cancers globally. There is an
overall five-year survival rate of less than 40% with worse outcomes in advanced stages. Gastric Cancer
(GC) has poor prognosis indicators due to late diagnosis and therapy resistance. Standard treatment for
gastric cancers includes surgery with systemic or localized therapies. Chemotherapy, which is often
administered in neoadjuvant and adjuvant settings, employs combinations of drugs to shrink tumors,
decrease the risk of recurrence, and improve survival. These therapies are successful but have some
challenges, like toxicity and resistance remaining huge. Radiation therapy can be delivered as three
dimensional conformal radiotherapy (3D-CRT) or intensity-modulated radiation therapy (IMRT),
as a means to offer enhanced local tumor control. When combined with chemotherapy, radiotherapy
has shown greater survival benefits, like in clinical trials such as INT-0116. Targeted therapies like
trastuzumab for HER2-positive disease and claudin 18.2 antibodies represent a change towards precision
by offering improved selectivity, but this is restricted to groups with specific biomarkers. This paper
reviews current treatments, chemotherapy, radiation, and targeted therapies, while highlighting their
benefits, weaknesses, and the growth of individualized treatment in improving outcomes for patients.
| 76 |
Author(s):
Nikita Efimov.
Page No : 710-716
|
Detecting Fake Accounts on Instagram using Machine Learning
Abstract
The existence of fake users on social media platforms like Instagram creates significant challenges
for marketers and platform integrity. Fake users are usually used for engagement manipulation such
as spamming and fake followings. This study investigates the problem of identifying fake users using
machine learning techniques, leveraging rich metadata from a dataset with 65326 Instagram accounts.
Using analysis of 18 metadata features, two models -Random Forest and XGBoost-were trained and
evaluated using precision, recall and F1-score. XGBoost achieved the best performance, with F1-score
of 0.91 for real users and 0.9 for fake users. Feature importance analysis using SHAP, underlined link
availability, engagement rate (comments), and engagement rate (likes) as the most predictive features.
This study underscores the potential of machine learning in combating fake user expansion and provides
insights for improving model interpretability and efficiency. Future research could explore larger
datasets, integrate more advanced techniques and incorporate additional metadata to further refine
detection models.
| 77 |
Author(s):
Tharun Mukesh.
Page No : 717-728
|
AI Powered Crop Rotation: Optimizing Plant Selection and Timing for Sustainable Farming
Abstract
As fears of worldwide water shortage rise, finding sustainable solutions for water usage in
agricultural fields is of utmost importance. The agricultural sector is the cause of approximately
70% of freshwater use globally, which is why the adaptation of techniques such crop rotation would
potentially be pivotal in ensuring sustainable utility of the water consumption by encouraging soil
health, water conservation and enhancing long-term resilience of the farmland. However, deducing
appropriate crop rotations and optimal planting times is a challenge for farmers because it depends
on a myriad of factors such as soil composition, rainfall patterns, temperature fluctuations and the
life cycles of pests. This study investigated how data-driven tools can be used to aid improved crop
rotation planning through the use of a broad set of agricultural and environmental variables. Based on
a dataset from the FAO and World Data Bank of more than 28,000 entries spanning multiple countries
and years, this project examined how rainfall, temperature, pesticide application, and other variables
affect crop yield. The approach involved data processing by removing redundant columns, one-hot
encoding of the categorical variables, numerical feature scaling by standardization and missing value
handling. This was followed by the development of predictive regression models aimed at estimating
crop yield and suggesting suitable crops and planting schedules. Model performance was measured
in terms of standard metrics including mean absolute error, mean squared error, and R2. The tuned
K-Nearest Neighbours model achieved the best performance with R2 = 0.99, MAE = 3257 hg/ha, and
MSE = 78.5 million, showcasing high accuracy when predicting crop yield. The aim of this study
was to help farmers seamlessly integrate crop rotation into their practice through a tool that provides
straightforward insights to aid in maintaining soil health, controlling pest cycles, and reducing water
consumption.
| 78 |
Author(s):
Bella Brumana.
Page No : 729-737
|
Dance Movement Therapy and Executive Function in Multiple Sclerosis: A Literature Review
Abstract
While the physical impairments of multiple sclerosis are commonly acknowledged and targeted for
treatment, cognitive impairments, including executive function deficits, often receive less recognition.
Although pharmacological treatments are the main form of disease mitigation, non-pharmacological
therapies are another promising management method that can address both cognitive and physical
deficits. Dance movement therapy is an emerging intervention that has been commonly used in
neurodegenerative disease rehabilitation, multiple sclerosis included. This literature review examines
the effect of dance movement therapy on executive functions in multiple sclerosis patients through
the analysis of four key studies that implemented varying dance modalities with some emphasis on
executive function measures. Despite differences in the methodology, duration, and type of cognitive
assessments, all four studies demonstrated executive function improvements which can suggest that the
memorization of choreography, coordination, and dual tasking involved in dancing contribute towards
executive function engagement. While these are promising findings, this review also emphasizes
the need for more research that can incorporate larger sample sizes and various executive function
standardized measures to obtain a better understanding of the benefits of dance movement therapy for
multiple sclerosis.
| 79 |
Author(s):
Ian Seungbin Shin.
Page No : 738-746
|
Influence of 3D Printing Filament Properties on Rebound Performance of Airless Tennis Balls
Abstract
Traditional sports balls use an internal pressurized rubber core for bounce but suffer from pressure
loss and limited lifespan. Airless sports balls replace this core with a rubber or plastic lattice structure,
mitigating these issues. This study examines material properties influencing the rebound performance
of airless tennis balls, using seventeen 3D printing filaments in a standardized design compared against
a regulation pressurized ball. Mechanical properties (Young’s modulus, tensile strength, elongation at
break, and impact strength) were sourced from manufacturer datasheets, while damping behavior was
measured via free-vibration decay of printed cantilever beams. Each filament had one cantilever beam
with three filmed trials, averaged for analysis. Rebound performance was evaluated through coefficient
of restitution (COR) and rebound reliability (success rate) across repeated drop tests, which were
continued until three vertical rebounds were achieved. Results show damping time as the strongest
predictor of COR, with longer damping times yielding higher values. Rebound reliability correlated
negatively with Young’s modulus and tensile strength, suggesting that moderate stiffness and strength
favor consistent vertical rebounds. Impact strength was linked to durability, with low values correlating
with fracture under repeated impact. A performance map plotting COR against rebound reliability
identified optimal filament candidates for replicating pressurized ball performance, excluding fragile
f
ilaments. Materials with moderate stiffness, low damping, and high impact strength demonstrated the
best balance of rebound magnitude, consistency, and durability. Future work should investigate filament
blending to optimize stiffness and damping, lattice geometry effects, and long-term durability.
| 80 |
Author(s):
Daniel Guo.
Page No : 747-754
|
The Impact of Armed Conflict on the Psychological and Developmental Well-Being of Adolescents: Comparing Ukrainian and Syrian Adolescents’ Psychological Welfare
Abstract
One widely popular topic of research for many adolescent psychologists is examining the field of
war trauma in adolescents in nations in active conflict, and the effects of war on the psychological and
developmental welfare of adolescents in different contexts. The aim of this synthesized, narrative review
is to analyze studies of war-related stressors on adolescents’ psychological health in the Ukrainian and
Syrian contexts to map the pathways from how structural collapse, environmental trauma, and social
stressors contribute to certain mental health outcomes. In this sense, the paper aims to make a further
contribution to the array of studies comparing the adolescents’ welfare from different psychological
factors, while also addressing an underexplored intersection by maintaining an exclusive focus on
comparing the mental welfare of adolescents in the Ukrainian and Syrian contexts. I conclude that war
profoundly disrupts adolescence for Ukrainian and Syrian youth by dismantling essential developmental
and social support structures; however, addressing trauma requires more than clinical treatment alone.
Therefore, comprehensive interventions that rebuild educational, social, and psychological structures
are crucial to fostering resilience and supporting healthy transitions to adulthood.
| 81 |
Author(s):
Nihal Kadamba, Mauricio Hernandez.
Page No : 755-763
|
Leveraging Machine Learning to Optimize Modern Renewable Energy Implementation
Abstract
The increasing use of renewable energy sources such as solar and wind power has led to significant
challenges with energy curtailment, causing substantial losses in energy efficiency. To address this, we
investigated the use of machine learning models to predict solar energy output and mitigate curtailment
across California, Nevada, Arizona, and New Mexico from 2018 to 2022. We hypothesized that time
of the day, temperature, and irradiance would be the factors most predictive of energy curtailment
across the aforementioned states. Specifically, we used XGBoost and Random Forest to predict solar
curtailment and evaluate if such predictors can be used to accurately estimate curtailment in each state.
Using historical weather, the characteristics of solar power plants, and energy data, we found that these
models effectively predicted general energy patterns. Notably, we found that the hour of the day and
the average temperature across all solar plants in each state were the main predictors in the models.
Using a set of 16 predictors, the evaluated models reported mean absolute errors ranging from 1.8% to
4.8% of the historical solar energy curtailed. These results highlight the potential of machine learning
to optimize renewable energy use, reduce curtailment, and improve grid reliability, offering a scalable
solution to address the challenges of oversupply in renewable energy systems.
| 82 |
Author(s):
Ishani Sogi.
Page No : 764-776
|
Epigenetic Biomarkers In Early Alzheimer’s Diagnosis In Aging Populations
Abstract
Epigenetics reveals how gene expression can be modified through the interaction between
environmental influences and genetics, without altering the underlying DNA sequence. The main
epigenetic mechanisms include DNA methylation, histone modifications, miRNA gene silencing,
and mitochondrial epigenetics. These mechanisms can activate or repress genes, changing cellular
processes, which increase the risk of errors in DNA, leading to mutations that can also be carried
through generations. These epigenetic modifications have been linked to many diseases, like mental
health disorders, diabetes, cancer, and Alzheimer’s Disease (AD). The most common form of dementia
is AD, and it is known for its cognitive decline, memory loss, and behavioral decline. AD accounts
for 60-80% of the dementia cases and is predicted to affect 13.8 million individuals globally by 2060.
At a molecular level, it involves the extracellular accumulation of β-amyloid (Aβ) plaques, leading to
neuroinflammation, neuronal loss, and synaptic dysfunction. Current methods of diagnosis include
neuroimaging and cerebrospinal fluid (CSF) biomarkers, which detect the disease after substantial
neurodegeneration has occurred in late-stage AD patients. Epigenetic changes present a new avenue for
early detection of AD using patient samples such as brain tissue, CSF, or blood. This paper examines
DNA methylation and histone modifications in AD-related genes, such as PSEN1 (Presenilin 1) and APP
(Amyloid Precursor Protein), which influence inflammation, neuron survival, and tau phosphorylation.
Studying epigenetic changes provides hopeful opportunities for early diagnostic and personalized
treatment strategies.
| 83 |
Author(s):
Anna Coleman.
Page No : 777-785
|
Barriers to Healthcare for Queer People in the US: A Review
Abstract
The queer community has historically been marginalized and discriminated against and
consequently faced worse outcomes in the healthcare system. This review aims to identify major
barriers to healthcare that affect the LGBTQIA+ community and suggest ways to overcome them.
To do this, a PubMed search was conducted with terms such as “queer,” “barriers,” and “healthcare
access” to collect articles relating to barriers to healthcare. Included studies had to be original
research published in the last ten years that were in English. The selected studies were then analyzed
for trends and categorized by the barriers they mentioned. The main barriers identified in this review
are discrimination, undertraining of medical staff, disclosure of queer identity, socioeconomic status,
and societal stigma. These barriers all intersect and coincide to create the disparities in healthcare
that we see. The results of this search emphasize the importance of updating our healthcare system
to better accommodate queer patients who may feel hesitant to get the care they need. Requiring
more training for medical staff and using more inclusive language on medical documents and forms
are examples of recommendations for healthcare policy and practice to improve queer people’s
experiences with the healthcare system and encourage them to seek care in the future when they
need it.
| 84 |
Author(s):
Abhigya Bandugula.
Page No : 786-799
|
Comparison of RNA-Seq Data from Primary and Recurrent Acute Myeloid Leukemia Patients
Abstract
Acute Myeloid Leukemia (AML) is associated with a high relapse rate due to the persistence of
leukemia cell clones. Risk prediction of relapses can be helpful to create specialized therapies that
increase chances of long-term survival for those at risk, especially pediatric patients. Therefore,
genomic-expression patterns that are useful in predicting risk of recurrence in patients were focused
on for analysis. Using RNA-seq data from the GDC’s TARGET-AML cohort, various feature selection,
dimensionality reduction, machine learning, and differential expression analysis methods were applied
to find the differences in expression. Mitochondrial and ribosomal protein genes were found to have
the largest variation. Genes upregulated in primary patients were involved in cellular respiration and
ATP production and genes upregulated in recurrent patients were involved in DNA organization. These
results highlight the underlying mechanisms behind primary and recurrent AML and provide insight on
further risk assessment and therapy methods.
| 85 |
Author(s):
Armaan Sharma, Miles Stopher.
Page No : 800-811
|
Nuclear Thermal Propulsion and Flight Safety: A Review
Abstract
Nuclear thermal propulsion (NTP) has long been regarded as a promising technology for advancing
the efficiency and scope of space exploration. Originating in the mid-twentieth century through
programs such as Project Rover and NERVA, NTP systems demonstrated the technical feasibility of
nuclear-powered rocketry, offering substantial gains in specific impulse and payload capacity over
chemical propulsion. Despite program cancellations and decades of limited progress, more recent
initiatives—including the Space Nuclear Thermal Propulsion (SNTP) program, Project Icarus, and
DARPA’s DRACO project—have revitalized interest in NTP development. However, persistent public
concerns regarding nuclear safety, coupled with the absence of standardized regulatory protocols,
remain significant barriers to widespread adoption. This paper traces the historical development of
NTP systems, evaluates recent technological advancements, and examines the regulatory landscape
governing their deployment. Particular attention is given to probabilistic risk assessment (PRA), Safety
Analysis Reports (SARs), and evolving U.S. policy frameworks, including NPR 8715.26 and NSPM
20, which collectively shape the future of nuclear flight safety. However, there are considerable gaps
in the testing and modelling of NTP systems that must be filled to meet revised safety regulations.
With the growing commercial and state interest in space exploration, particularly in the US, there is
considerable potential for new NTP designs to transform long-duration space missions, with robust
and transparent safety measures to ensure public acceptance and regulatory approval.
| 86 |
Author(s):
Durva Dhok.
Page No : 812-823
|
Menstruation and Marginalization: A Survey-Based Study of Menstrual Health Education and Facility Access as Determinants of Student Confidence in Maharashtra High Schools
Abstract
Adolescent girls around the world often struggle to manage menstruation due to poor access to
sanitary products, inadequate school facilities, and harmful social taboos. In India, where a large
portion of the world’s adolescent population lives, these barriers significantly affect girls’ education
and well-being. The city of Solapur in Maharashtra, marked by socioeconomic diversity, offers a
focused setting to explore how menstrual health education and school infrastructure influence girls’
confidence and academic engagement during their periods. This survey-based study was conducted
in five randomly selected high schools and middle colleges in Maharashtra, India, involving 96
female students aged 13 to 24. Participants completed a structured questionnaire assessing menstrual
education, school facilities, and confidence in managing menstruation. Data was analyzed using
descriptive statistics to explore relationships between school resources and students’ menstrual
confidence. The study reveals that while many schools provide basic menstrual hygiene resources,
inconsistencies in essential supplies and persistent social stigma significantly impact students’ comfort
and participation during menstruation at school. These challenges lead to reduced attendance, limited
physical activity, and social withdrawal, highlighting the need for integrated strategies that address
both infrastructural gaps and cultural barriers to improve menstrual health management and support
girls’ full engagement in school.
| 87 |
Author(s):
Misha Dadlani.
Page No : 824-831
|
Current Constraints and Possibilities Using Mesenchymal Stem Cells for Regenerating Cardiac Tissues in Patients with Myocardial Infarction
Abstract
Myocardial Infarction (also commonly known as Heart attack or Cardiac arrest) is a predominant
cause of mortality and hospitalization worldwide. Current treatments such as use of stents and open
heart surgery carry risks and have their own limitations. However, the use of regenerative medicine
offers promising potential and effective treatment therapies using mesenchymal stem cells (MSCs) due
to their potent properties and self-renewal capabilities. This literature review does a comprehensive
assessment of the studies, research and clinical trials involving MSCs to find a more effective and
durable cure for myocardial infarction. The studies and clinical trials conducted worldwide using both
allogenic and autologous MSCs show positive signs of myocardium tissue regeneration and improvement
of cardiac functions. Positive outcomes carried over a decade of preclinical and clinical trials using
MSC therapies to treat myocardial infarction are very promising offering significant potential for cure.
Further research and clinical trials are required to standardize protocols for administration of MSCs
and provide cohesive guidance on use of optimal dosing, administration routes, and frequency to ensure
safety and efficacy of this treatment.
| 88 |
Author(s):
Sanjana Shekar.
Page No : 832-841
|
Comparative Analysis of Hyperinflation in Brazil and Israel: Causes, Consequences and Stabilisation Lessons
Abstract
In order to maintain economic stability, economies and central banks aim for an inflation rate of
2-3%. This is to avoid a hyperinflation crisis, which is defined as an annual inflation rate exceeding
50%. Understanding how and why inflation transmutes into hyperinflation has proved to be vital
for public economic and monetary policy. Through detailed case studies of Brazil’s and Israel’s
hyperinflationary experiences in the 1980s, economic principles and analysis are employed. It also
uses detailed comparison to better understand the causes and consequences of hyperinflation and
to study the effectiveness of different stabilisation approaches. The analysis reveals that while both
countries were in similar situations, Israel achieved faster stabilisation due to stronger government
credibility and beneficial external factors, whereas Brazil’s recovery was held up by multiple failed
attempts and deeper economic turmoil. The findings show that successful stabilisation requires
addressing root causes rather than implementing temporary solutions, maintaining public trust, and
developing comprehensive long-term strategies. This research contributes to economic understanding
by highlighting the importance of approaching hyperinflationary episodes through solutions based on
specific country contexts. This analysis suggests that effective stabilisation strategies must consider
both domestic economic conditions and external factors while prioritising the restoration of public
confidence.
| 89 |
Author(s):
Khushee Goel.
Page No : 842-848
|
An EEG-Based Approach for Identifying Biomarkers of Internet Addiction Disorder
Abstract
As smartphones became readily accessible to teenagers in 2010, longstanding trends for anxiety
and depression skyrocketed. While statistics indicate that social media addiction is to blame, others
argue that social media is more good than bad. This bears the question of how to distinguish between
the productive and harmful use of social media. Employing EEG (electroencephalography) to measure
brain activity, this research aims to identify biomarkers for internet addiction disorder (IAD). This
study employed an open source Kaggle dataset of behavioral addiction disorders, with feature selection
conducted through the Random Forest algorithm. This process led to the identification of 15 EEG
biomarkers for addiction disorder, and then Odds Ratio analysis was used to identify the most significant
ones. T-tests were conducted, beta coefficients were extracted, and logistic regression was used to
further validate the findings. The discovered biomarkers now fill the void for quantitative measures of
monitoring brain health upon social media consumption.
| 90 |
Author(s):
Yuhan Dong.
Page No : 849-858
|
Factors Influencing the Use of AI Tools Among Undergraduate Students in the UK: Differences by Year of Study and Subject Area
Abstract
As Artificial Intelligence (AI) becomes increasingly prevalent, questions have arisen regarding
the motivations that drive students to rely on it. This study investigates the factors influencing the
likelihood of AI use among undergraduate students, and how these factors vary by year of study
and broad subject area. A Chi-Square Test for Homogeneity was conducted for each factor within
these groups to determine whether significant differences existed in the proportions of students
selecting particular motivations or uses. The dataset analyzed was drawn from a survey of 1,041
undergraduate students in the United Kingdom. The findings indicate that students primarily use
AI to save time, improve the quality of their work, and obtain instant support, while they are less
likely to use AI when concerned about accusations of cheating or the risk of false or biased results.
Significant differences emerged in students’ use and motivations behind the likelihood of AI for data
analysis, summarization, and improving work quality across years of study. Differences were also
observed in generating text, summarizing, coding, saving time, and concerns about cheating across
subject areas. These results underscore the need for educators to provide greater support to younger
students, as well as equitable education and access to AI resources across disciplines. Moreover,
educators should refine guidelines for AI use to reflect disciplinary differences, and future research
should examine how these needs evolve within specific fields.
| 91 |
Author(s):
Amandine Becle.
Page No : 859-866
|
RET Gene Mutations in Infants: A Literature Review of Implications on MEN2 syndrome
Abstract
MEN2 is a rare autosomal dominant endocrine cancer syndrome caused by germline mutations in
the RET proto-oncogene and includes three subtypes — MEN2A, MEN2B and fMTC — which all
carry the risk of medullary thyroid carcinoma (MTC) in infants. This narrative review synthesizes
current research on RET mutations, malignancy risk, long-term outcomes, current treatments and
newborn screening ethics. Findings indicate that the malignancy risk is largely related to the RET
mutation subtype, with MEN2A being the most common accounting for 55% of cases and MEN2B
presenting the most aggressive progression in infancy. An early diagnosis done through the use of CT
and CEA biomarkers leads to an early form of treatment, usually an early prophylactic thyroidectomy
and substantially decreases the risk of metastasis and mortality, though lifelong surveillance is required
for some possible long-term outcomes. In addition, the diagnosis of MEN2A in infants often requires
screening which raises many important ethical, clinical and social dilemmas especially in parental
decision-making and equitable care. The review highlights the importance of genetic testing for at-risk
infants and timely surgery to reduce mortality. Disparities in healthcare access and strengthening long
term outcomes to improve care for children with MEN2 could be addressed in future research.
| 92 |
Author(s):
Vivan Patel.
Page No : 867-892
|
Harnessing A CRISPR-Cas9-Based Approach to Stimulate T Cells in Multiple Myeloma Patients by Targeting the PDCD1, HAVCR2 and LAG3 Genes
Abstract
Multiple myeloma (MM) is an incurable cancer that manifests within the bone marrow, affecting
plasma cells. Although incidence and prevalence rates remain low, there has been a gradual increase
worldwide in the incidence rates of MM over the past few decades. In the tumor microenvironment,
plasma cells undergo mutations during development, leading to uncontrolled cell growth in the
bone marrow and the production of abnormal monoclonal antibodies. These malignant plasma cells
downregulate the T cell response via upregulated signaling pathways associated with the PDCD1,
HAVCR2, and LAG3 genes in T cells. To reinvigorate deactivated T cells, this proposal puts forward an
evidence-based approach that uses CRISPR-Cas9 to knock out the PDCD1, HAVCR2, and LAG3 genes
in T cells to restore T cell cytotoxic functions against MM. Multiplex gene editing appears promising;
however, additional research is required to fully encapsulate the complex nature of their interactions
with MM. Since many cancers persist through the activation of redundant signaling pathways that
are co-expressed, editing three genes simultaneously is essential to preventing MM from surviving
or adapting through alternate pathways. This CRISPR-Cas9-based approach holds immense potential
to advance patient outcomes through ex vivo T cell editing, but also raises considerations regarding
the effectiveness of triple gene knockout. This proposal discusses in vivo and in vitro research that
support such treatment, along with future considerations of coupling CRISPR-Cas9 with other known
MM treatment mechanisms.
| 93 |
Author(s):
Sansan Lu.
Page No : 893-900
|
CRISPR-Cas Technology: Mechanisms, History, and Emerging Clinical Applications
Abstract
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and their associated Cas
proteins form the CRISPR–Cas system, one of the most prominent genome-editing technologies to
date. Originally discovered as an immune system in bacteria against viral infection, the system has
since been adapted into a precise genome-editing tool. CRISPR-Cas technology has reshaped modern
biology and medicine, with applications spanning basic research, agriculture, and clinical medicine.
Promising outcomes include the correction of genetic disorders and the engineering of immune cells
for cancer therapy. This review outlines the fundamental mechanisms of CRISPR-Cas technology,
traces key milestones in its development, and highlights recent advances in the field. Emerging clinical
applications and ongoing trials are also discussed, along with ethical considerations and the importance
of appropriate regulatory oversight.
| 94 |
Author(s):
Madhav Soni.
Page No : 901-911
|
The Strain Amplitude Spectral Density of a Michelson Interferometer Compared to That of LIGO
Abstract
The existence of gravitational waves was predicted by Einstein’s General Theory of Relativity. In the
modern world, LIGO (Laser Interferometer Gravitational-Wave Observatory) represents the pinnacle of
groundbreaking technology. There are 2 LIGO observatories in the United States of America: One
in Hanford, Washington, and the other in Livingston, Louisiana. The total estimated cost of LIGO
is 1 billion USD. Now, this is a high expense when compared to other observatories; therefore, cost
effective techniques like the usage of a table-top Michelson Interferometer need to be introduced.
LIGO’s sensitivity is incredibly accurate; however, it is still affected by seismic factors. Therefore,
tabletop Michelson Interferometers can be used to identify and limit these factors while also focusing
on low-frequency signal detection. By building small-scale Michelson Interferometers, we can conduct
different seismic tests and use computational methods to calculate sensitivity (strain noise). Using these
interferometers will also help us validate noise reduction techniques that can then be applied to the
data LIGO captures. This could then have the potential to improve the current sensitivity of LIGO.
This study mentions the different pins of the Raspberry Pi and the sensor. The frequency of 1 provided
the most accurate sensitivity. The final strain noise of the table-top Michelson interferometer gives a
sensitivity between 10-5 and 10-7. Overall, Michelson Interferometry has the potential to develop current
vibration isolation techniques, detect low-frequency signals, and also be used in future missions such as
the LISA detector, which aims to detect low-frequency gravitational waves in deep space.
| 95 |
Author(s):
Regina Kim , Vincent H. Tam .
Page No : 912-916
|
Behavioral Modification and Cognitive Development in Children with Autism — A Pilot Case Series
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges
in communication, social interaction, and behavior. This paper explores the behavioral development of
individuals with autism through the game of Go, with a focus on Areum Go. Areum Go is a simplified
and adapted version of the game designed for individuals with developmental disabilities. Traditional
methods such as speech therapy, sensory development therapy, music therapy, and art therapy often
do not help foster intrinsic motivation or social engagement. Additionally, most of these methods take
place in a one-on-one setting, which reduces opportunities for peer learning, socialization, and natural
reinforcement. Areum Go integrates principles of Applied Behavior Analysis (ABA), including physical
or verbal prompts, task modification, discriminative stimuli, reinforcement, errorless teaching, and
individualized adaptations to each learner’s receptive and expressive language abilities. Instructors
employ both positive and negative reinforcement, personalized interventions, strong nonverbal feedback,
and systematic checking of student responses. This structured yet adaptable approach fosters focus,
perseverance, and problem-solving skills while minimizing incorrect learning pathways. Through
qualitative instructor interviews with Go professionals and instructors, there were improvements
in: (1) Attention and cognitive engagement, (2) Increased social interaction and peer awareness, and
(3) emotional regulation and resilience. Our findings support Areum Go having a positive impact
on cognitive skills, social engagement, and emotional regulation in neurodiverse learners. As this
study included only three instructors, the results may be interpreted as preliminary and may not be
generalizable to broader populations.
| 96 |
Author(s):
Prakhar Shukla.
Page No : 917-923
|
Prescribing Intelligence: How Machine Learning Can Help Combat Antimicrobial Resistance
Abstract
While Clinical Decision Support Systems (CDSS) are widely used in clinics and medical settings,
machine learning (ML) based systems are only recently being explored, especially in the context
of recommending treatments based on previous data. This literature review addresses this gap by
comparing the impact of ML-based CDSS to clinician performance in antibiotic treatment in hopes of
improving diagnostic accuracy and decreasing chances of antimicrobial resistance (AMR) development.
PubMed and Google Scholar were used to identify 11 studies that were categorized based on their
diagnostic accuracy, type of ML model used, and the difference in outcomes from physicians. The
evidence shows that ML-based CDSS had an average of 16% increased accuracy compared to clinicians.
Even though the studies used a variety of models and training sets, the findings indicate that ML can
help clinicians in their treatment selection. However, due to the diversity in data sources, model design,
and evaluation methods, generalizing these results is difficult. Overall, ML-based CDSS seems like a
promising way to reduce overprescription of unnecessary antibiotics and improve diagnostic accuracy.
| 97 |
Author(s):
Jonathan Moon.
Page No : 924-933
|
US Soft Power: An Investigation on the Effects of USAGM’s Shutdown
Abstract
In March of 2025, President Trump signed the executive order “Continuing the reduction of federal
bureaucracy,” which shut down various agencies that the administration considered to be wasteful,
including the United States Agency for Global Media (USAGM). Critics were quick to condemn
USAGM’s defunding, arguing that abandoning such an outlet would result in a significant decline of
US soft power. However, such critiques have not analyzed the impacts of USAGM’s defunding on US
soft power through a replicable methodology, failing to establish what soft power is, how it is measured,
and situate USAGM’s defunding within such contexts. This study seeks to fill this gap, answering the
question of how USAGM’s defunding will impact US soft power in a way that more thoroughly explores
the trajectory of US soft power to this point and USAGM’s impact on it. Conducting a comparative
review of global soft power indices and an analysis of website traffic data, this paper ultimately
concludes that, while US soft power is in decline, USAGM’s defunding is not a significant driver of
this trend. These results imply the existence of a cyclical decline in US soft power caused by factors
other than USAGM’s defunding, as well as a long term need to shift soft power projection away from
traditional media outlets.
| 98 |
Author(s):
Irmak Özkaya.
Page No : 934-942
|
Personalized Medicine in the Treatment of Melanoma: Advances and Current Approaches
Abstract
Melanoma remains a major global health concern due to its high mortality rate and resistance to
conventional therapies. While standard approaches such as surgery, radiation, chemotherapy, and
radiation are effective in early stages, they are insufficient in cases of advanced disease. Personalized
medicine, which tailors interventions to the unique molecular and immunological profile of each tumor,
has transformed melanoma management. Molecular profiling has identified key driver mutations,
including BRAF and NRAS, as biomarkers guiding targeted therapies. In parallel, immunotherapies,
and particularly immune checkpoint inhibitors, have significantly improved survival, although
resistance remains a major challenge. Combination strategies, such as pairing immunotherapy with
targeted therapy or radiotherapy, have been explored to enhance treatment efficacy and overcome
resistance, but their safety profiles require further evaluation. Collectively, these advances demonstrate
that personalized medicine has shifted the field of melanoma treatment and will continue to play
a central role in improving patient outcomes. This review aims to summarize recent advances in
personalized medicine for melanoma, with a particular focus on molecular profiling, targeted therapies,
immunotherapy, and combination strategies.
| 99 |
Author(s):
Jisu Yu, David Moon.
Page No : 943-951
|
Porcelain White or Bronze Tan? Conflicting Beauty Ideals among East Asian Americans and the Consequences of Skin-Altering Practices
Abstract
Poor sun protection, extreme UV exposure, low outdoor activity hours, and use of toxic skin products
are seen in people who want to achieve their preferred skin tone. Previous studies have found that
different cultures have unique skin tone preferences. However, to our knowledge, limited studies have
looked at the complexity of skin tone preference in East Asian culture in America and its implications
for skin health. Historically, East Asian culture has favored lighter skin as a symbol of wealth and
beauty. On the other hand, Western ideals prefer tanned skin as healthy and attractive. Acculturation
to Western countries gives a complex internalization of beauty standards to East Asian immigrants
caused by peer and family pressure of two contradicting ideals. This cultural dissonance tends to result
in psychological distress, confusion, and rejection of one’s self identity. To attain ideal skin tone, either
bronze or pale, East Asian individuals often involve themselves in unhealthy beauty practices and
skin products. In this review, we find that two beauty standards, grounded deeply in both history and
contemporary culture, play a significant role in promoting practices to achieve ideal skin tone, which
carry both benefits and serious health risks that require public health and clinical intervention.
| 100 |
Author(s):
Tillie Pepos-Lebrun.
Page No : 952-968
|
Exploring Relationships Between Childhood Adversities and Homicides
Abstract
Despite decades of research, there is still a limited understanding of the psychological and social
drivers of homicide. A prominent factor is childhood adversity, which is shockingly influential and
could cause numerous problems in later adolescence and adulthood. Adverse childhood experiences are
associated with increased prevalence of mental illness and substance abuse issues later in life and could
result in violent behavior, which in extreme cases could escalate to homicide. While aspects of these
relationships are well documented by prior research, most papers only examine a few risk factors at a
time and do not provide a comprehensive overview of how childhood adversity may influence homicidal
behavior. This review paper discusses the specific impacts of varying forms of childhood adversity and
its downstream consequences, including its effects on the occurrence of school shootings, domestic
homicide, and serial homicide. Case studies are incorporated to provide real-world perspectives to
complement the theories presented, and recommendations for future research and interventions are
discussed.
| 101 |
Author(s):
Ziyan Zhang .
Page No : 969-974
|
Analyzing Investor Sentiment, Monetary Policy Shocks, and Company Fundamentals Impacts On Stock Returns
Abstract
What factors impact stock prices the most has always been a mystery in our world. Up till this date,
nobody has come up with a foolproof way of predicting the market. Consequently, the impact of various
economic factors on stock returns should be analyzed to determine which factor will influence the
market the most. This research studies the core factors affecting the stock market for the finance and
technology sector. Utilizing linear regression and data from different sources, the study evaluated the
factors of company earnings, consumer sentiments, and monetary policy shocks in relation to changes
in stock prices for technology and finance companies. However, the analysis is illustrative and does not
establish causality. It is found that monetary policy shocks usually have the biggest influence on stock
prices both negatively and positively compared to other factors.
| 102 |
Author(s):
Eleanor Gil.
Page No : 975-986
|
The Effects of Linguistic Framing on Environmental Empathy and Willingness to Take Climate Action
Abstract
The framing effect has been studied widely across contexts, yet it may reveal especially important
insights about how people perceive climate change when presented with certain language about the
issue. From a humanities lens, solving climate change requires using language that clearly connects
people’s values with climate action or policies. This study investigated the effects of valence equivalency
framings (positive, negative, and neutral messages) on people’s climate empathy and willingness to take
climate action. Survey research was conducted on 114 participants through convenience sampling by
having them answer a questionnaire. This survey randomly and evenly distributed one of three message
framings to each participant, after which both qualitative and quantitative data were collected and
analyzed. The results found no statistically significant difference in climate empathy or willingness
to take climate action across the three framing groups. My results indicate that valence framing is not
universal, and framing effects are mediated by background values, worldviews, and knowledge, or lack
thereof. Therefore, instead of a valence framing, there exists greater promise within clear, relatable and
value-driven messages that align with people’s values. This presents implications for areas such as the
media, which have potential to mobilize widespread support for climate action.
| 103 |
Author(s):
Matthew Balaban.
Page No : 987-997
|
Impacts of Artificial Intelligence on Asset Management
Abstract
Artificial intelligence (AI) is rapidly transforming the asset management industry by enhancing
investment strategy formulation, portfolio construction, and risk management. This study investigates
the performance impacts of AI integration in asset management using a ten-year panel (2015–2024) of
institutional fund holdings derived from SEC Form 13F filings via Whalewisdom. Funds were classified
as traditional or quantitative based on turnover and holdings concentration, serving as proxies for AI
adoption. Literature review findings reveal that leading institutions such as JPMorgan and BlackRock
leverage AI for alternative data analysis, risk oversight, and hybrid human–machine decision-making.
Results show that quantitative funds consistently exhibited higher volatility and greater market
sensitivity (beta), while both fund types saw declining downside-adjusted performance (Sortino
ratio). Notably, Sortino ratios converged over time, suggesting narrowing differences in downside-risk
efficiency. Alpha was persistently negative for quantitative funds, indicating limited excess returns
beyond market exposure. Overall performance differences were negligible except during the onset
of COVID-19, when quantitative funds briefly outperformed. These findings highlight AI’s dual role
as both a source of adaptability and a driver of higher systemic risk, underscoring the importance of
governance and transparency in its deployment.
| 104 |
Author(s):
Anika Huralikoppi.
Page No : 998-1008
|
Genetic Determinants of CAR T-Cell Therapy Outcomes: A Comparative Analysis of DLBCL and Glioblastoma
Abstract
CAR T-cell therapy has become a revolutionary option for patients with certain cancers, but its
effectiveness remains uneven across cancer types. This study is particularly interested in why CAR T
treatment produces stronger and more durable responses in diffuse large B-cell lymphoma (DLBCL),
compared to glioblastoma (GBM). It is hypothesised that differences in the genetic mutations
commonly found in each cancer may underlie these differences in treatment response. To investigate
this, cBioPortal is used, an open-access cancer genomics database, to analyze the mutation and clinical
data of patients with DLBCL (n=2143) and GBM (n=881), respectively. Because patient-level genomic
data from CAR T clinical trials is not directly available, a matching process was created to align real
world patient data from cBioPortal with the demographic and clinical characteristics reported in trial
populations. Using this matched dataset, a survival analysis was performed to examine how specific
genetic mutations may be associated with patient outcomes after CAR T therapy. Our findings suggest
that while DLBCL patients with mutations in genes like PIM1 and IGHV2-70 had poorer survival, GBM
patients with EGFR and PIK3R1 mutations faced even worse prognoses. These patterns, combined with
factors like heterogeneity in cell-surface antigens and tumor location, help explain why CAR T therapy
remains far more effective in blood cancers than in solid tumors like GBM. By identifying genetic
profiles associated with survival outcomes, our study may inform future iterations of CAR T design
and provide insights to predict the efficacy of CAR T therapy, especially for solid tumors.
| 105 |
Author(s):
Adora Elizabeth Yin.
Page No : 1009-1025
|
The New ‘Sputnik Moment’: An In-Depth Analysis of the US-China AI Race Amidst a Shifting Geopolitical Landscap
Abstract
The emergence of DeepSeek, a Chinese AI model, has disrupted global perceptions about
technological dominance, marking a pivotal moment in the U.S.-China AI race. Framed through
the historical analog of the 1957 Sputnik launch, this paper argues that both events represent
technological shocks that reshape global power dynamics and strategy. It first examines the historical
context of Sputnik and its geopolitical implications, before drawing parallels to DeepSeek’s impact
on the AI race. DeepSeek’s efficiency-driven advancements challenge U.S. beliefs about the resourceintensive nature of AI innovation, while exposing vulnerabilities in America’s strategy centered on
export controls, talent restrictions, and efforts to limit China’s global influence. The paper analyzes
China’s state-driven approach to leveraging AI for economic stabilization, domestic confidence, and
geopolitical reach, while underscoring its constraints in international trust and data governance.
It then examines how the AI race accelerates a transition from unipolarity toward a fragmented,
multipolar world order, emphasizing the importance of alliance trust and cooperation —areas
strained by U.S. tariffs and semiconductor reshoring. Drawing on precedents such as Apollo–Soyuz,
the paper argues that rising costs, domestic pressures, and shared AI risks may push rivals from zerosum competition toward managed coexistence. The likely equilibrium is an uneasy hybrid: inevitable
short-term rivalry alongside guarded, rules-based cooperation on safety, standards, and global public
goods to sustain long-term stability. Ultimately, the paper contends that the trajectory of global AI
leadership will hinge not only on innovation but also on strategic collaboration, alliance cohesion,
and effective governance mechanisms to address shared challenges.
| 106 |
Author(s):
Albert Aslan Yelken.
Page No : 1026-1032
|
Quantum Generative Adversarial Networks for Learning and Generating Noisy Entangled Quantum States
Abstract
Quantum computing hardware is prone to decoherence and control errors, which can reduce
entanglement and lead to mixed states. Practical quantum algorithms must extract insights from this
noisy data. We test the hypothesis that a compact, circuit-based Quantum Generative Adversarial
Network (QGAN) trained against a moving, noise-scheduled target can learn the action of a depolarizing
channel and generate a family of noisy entangled two-qubit states that match state-level similarity
and reproduce entanglement trends. We implement a compact QGAN in PennyLane with TensorFlow
and train it against a moving target formed by Bell-pair states passed through a depolarizing channel
whose strength is scheduled during training. The generator and discriminator are variational circuits;
learning is assessed by state-level similarity (fidelity and trace distance) and by entanglement measures
(concurrence and negativity). Our model learns the action of the noise channel and reproduces a family
of noisy, entangled two-qubit states. Our results indicate that QGANs can capture hardware-relevant
noise while preserving essential structure in the data. Such models can serve as error-aware state
preparers, compact surrogates for device noise, and practical tools for quantum data augmentation and
benchmarking on near-term quantum computing hardware. To our knowledge, this is the first systematic
QGAN evaluation combining dynamic depolarizing noise schedule, finite-shot/readout-noisy training,
and entanglement-aware metrics.
| 107 |
Author(s):
Navami Muglurmath.
Page No : 1033-1045
|
The Accuracy, Effectiveness, and Psychosocial Benefits of Continuous Glucose Monitors as Compared to Traditional Fingerstick Blood Glucose Monitoring in Type 1 Diabetic Populations: A Systematic Review
Abstract
Type 1 diabetes (T1D) management relies on accurate and consistent glucose monitoring. While
self-monitoring of blood glucose (SMBG) has long been the standard for type 1 diabetes (T1D) care,
continuous glucose monitoring (CGM) technologies have gained prominence due to their ability to
provide real-time glucose trends. This systematic review’s objective is to analyze seventeen studies
(2015-2025) to evaluate clinical and psychosocial outcomes of CGM versus SMBG in T1D, with
attention to device type, accuracy constraints (exercise, medication interference), and user factors.
Previous research has demonstrated the effectiveness of CGM in lowering hemoglobin A1c (HbA1c)
levels and improving glycemic control, but few have reviewed holistically comparing variations in study
design, response variables, and type influence outcomes. This study addresses that gap by analyzing
key response variables (HbA1c, time in range, hypoglycemia, and glycemic variability), CGM accuracy
metrics, study design features, and patient-reported outcomes such as behavioral changes and quality
of life. The findings show that CGM use typically increased time in range by 5-10 percentage points
and reduced time below range by 2-7 percentage points. HbA1c levels ranged from no change to about -0.5% over 12-16 weeks. In children with elevated HbA1c using isCGM 2.0, time below range fell by 6.4
percentage points over 12 weeks without an HbA1c change; these time below range benefits and higher
testing frequency were sustained to 24 weeks after crossover to isCGM in both arms. Psychosocially,
early CGM after diagnosis was widely endorsed by parents for reduced worry, better sleep, and
remote monitoring benefits. Primary limitations in this review include heterogeneity in device types,
populations, durations, and co-interventions. These results highlight the clinical value of CGM in
improving both physiological and psychosocial outcomes. Differences in CGM technology, calibration
needs, and adherence also impacted outcomes. These results reinforce the clinical value of CGMs while
highlighting the need for standardized protocols and broader inclusion across demographic groups to
optimize diabetes care.
| 108 |
Author(s):
Nitya Mandowara.
Page No : 1046-1050
|
The Role of the Circadian Clock in Glioblastoma Progression and Treatment
Abstract
Glioblastoma (GBM) is the most aggressive and treatment-resistant malignant brain tumor in
adults. Current therapies, including surgery, radiation, and chemotherapy with temozolomide (TMZ),
offer subtle improvements in terms of survival. New and upcoming research highlights the role of
the circadian rhythm, the body’s internal 24-hour clock, in tumor growth and treatment response.
Disruptions in core clock genes such as BMAL1 and CLOCK are common in GBM and have often
been linked to increased tumor cell survival and resistance to therapies. Preclinical studies show that
targeting the circadian clock, either by inhibiting key clock genes or by timing treatments to align
with natural biological rhythms (chronotherapy), can slow tumor progression and improve survival in
models. However, clinical trials have shown mixed results, and challenges remain in translating these
strategies to practice due to differences in individual circadian timing and various ethical implications
about access, safety, and feasibility. Despite these obstacles, the circadian system represents a promising
direction for future GBM therapies that may enhance treatment precision and effectiveness. This review
analyzes current therapeutic approaches for GBM and investigates how circadian rhythm mechanisms
affect tumor progression, with the goal of identifying strategies to develop more effective and targeted
treatments.
| 109 |
Author(s):
Jack Baer.
Page No : 1051-1067
|
Total Financial Burden Of Cancer: Differences Between Rural And Urban Patients Globally
Abstract
It is known that financial burden can have a large effect on patient outcomes during the course of
the disease. However, there is a lack of research on how these costs vary between urban and rural
residents. A recurrent topic found between the studies is that they have a compounding socioeconomic
disadvantage. Rural residents already have a preexisting socioeconomic disadvantage, with their job
type and lack of medical resources stemming from this inherent disadvantage. In the case of cancer,
these preexisting factors stimulate a need for travel to undergo treatment. This results in additional
travel, accommodation, and food costs. These out-of-pocket costs are exacerbated by rural patients
lacking insurance from their job type. This paper analyzes five papers to examine how the total
f
inancial burden of cancer differs between rural and urban patients. Patients’ increased treatment costs,
which stem from a rural patient’s socioeconomic disadvantage, lead to a financial burden, as well as a
decrease in the patient’s socioeconomic status. Furthermore, there is no blanket solution to this problem,
as pathways of financial burden vary by a region’s development. However, there are general ideas that
can be applied, such as transportation infrastructure, aid systems, and education improvement, that
could be beneficial. These would need to be varied depending on where they are implicated, and their
viability in certain regions is questionable due to their political climate. Ultimately, the financial burden
of rural patients is higher because of the compounding socioeconomic burden, and policies need to be
implemented to rectify this disparity.
| 110 |
Author(s):
Aarushi Sanganeria.
Page No : 1068-1077
|
How Suitable is the Ringsail Parachute to Facilitate the Descent of NASA’s Mars Sample Retrieval Lander into the Martian Atmosphere?
Abstract
The Mars Sample Retrieval mission demands high-performance parachutes capable of surviving
supersonic deceleration in Mars’ low-density atmosphere, specifically for the Lander. This study
evaluates the suitability of a Ringsail parachute through computational fluid dynamics (CFD) simulations
at supersonic (500 ms-1), low density (0.02 kgm-3) conditions. Velocity magnitude analysis revealed
significant flow separation and turbulent wake formation. Stagnation zones posed localized stress
risks, while asymmetric vorticity suggested susceptibility to collapse. This paper used computational
f
luid dynamics to evaluate the performance of a Ringsail parachute designed in Fusion360 in Martian
atmospheric conditions through analysing lift and drag forces and coefficient of drag. The results are
then validated against a previous study regarding the performance of Supersonic Ringsail Parachutes
on Mars. Future work could explore transient inflation dynamics, material thermal limits, and varying
porosity.