| 1 |
Author(s):
Rohan Jha, Rishabh Jha.
Page No : 1-9
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Improving Profitability and Reducing Downside Risks using Statistical Models
Abstract
Energy demand will increase due to the increasing population, improved standard of living, and rising artificial intelligence applications. The existing energy sources may not be sufficient, and we need multiple sources of energy in the near future to meet the increased demand. The oil & gas energy sector will face several challenges such as stricter regulation, the rise of renewable energy, and aging assets. The industry, therefore, needs sophisticated tools to forecast the price and cost more accurately than ever for reliable and sustainable profits with reduced downside risks. In this paper, we develop statistical models for a profitable refinery to forecast the key cost driver as crude oil price, and the key revenue driver as gasoline/diesel prices, 6 months in advance. We first identify statistically significant variables and then refine further using collinearity to identify key variables. Our analysis indicates that both oil and gasoline prices depend on the Dow Jones industrial average, WTI oil price, average miles used per gallon, average well production per day, number of refineries, refinery capacity, and rig count. These variables are statistically significant with p-values less than 0.05. We tested the 6-month future price and found that the model can predict the oil price within 5% variability and the gasoline price within 7%. For the oil price variation, the Dow Jones industrial average accounts for ~24%, the number of refineries for ~21%, average well production per day for ~20%, and the remaining variation is attributed to other variables. For the gasoline price variation, oil price contributes ~40%, the Dow Jones industrial average covers ~25%, and the remaining variables account for the remaining ~35%. The Dow Jones industrial average impacts both the cost and revenue aspects of a refinery business. Thus, we recommend contracting crude oil and gasoline using an index tied to the broader economy to reduce the downside risk and improve profitability. These results could enable the refinery management team to seek long-term contracts to lock in high-margin crude oil supply and favorable gasoline price contracts with customers when a decline in price is forecasted to improve the profit margin. This methodology and strategy are applicable beyond the refinery business to any cyclical business to maintain margin, particularly in a down cycle.
| 2 |
Author(s):
Sarina Virmani.
Page No : 10-18
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Investigating the Environmental Sustainability of Data Centers
Abstract
Data centers play a critical role in supporting global IT infrastructure, representing a rapidly growing industry. However, this growth is coupled with significant environmental consequences, such as the consumption of 1-2% of the annual global energy supply, increased carbon emissions, and the loss of valuable agricultural land. This study reviews solutions that address these impacts by evaluating sustainable practices in data center construction, design, and maintenance. The results point to several key strategies that improve environmental sustainability in these categories. In construction, replacing traditional materials, such as concrete and steel, with eco-friendly alternatives such as green concrete and steel slag can reduce carbon footprints. Additionally, permeable pavements can manage the stormwater runoff that was previously absorbed by the farmland on which data centers are built. Design improvements, including underfloor air distribution, economizers, ice storage, and energy recovery wheels can optimize ventilation systems, lowering energy demands by up to 25%. Sustainable maintenance practices emphasize the use of advanced liquid cooling systems, as well as thermal energy storage to reduce peak electricity usage and incorporate more renewable energy sources. Overall, it is vital to implement strategies that prioritize sustainability in data centers in relation to the construction, design, and maintenance to reduce the environmental footprint of this growing industry.
| 3 |
Author(s):
Menghan Xu.
Page No : 19-25
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Advancing PET-Degrading Enzymes through Directed Evolution to Combat Plastic Pollution
Abstract
Plastic pollution poses a significant environmental challenge due to its persistence and widespread distribution. Among various types of plastic, polyethylene terephthalate (PET) is especially problematic due to its resistance to natural degradation. PET-degrading enzymes, particularly PETases and cutinases, have emerged as promising solutions for enzymatic plastic recycling. However, their native catalytic efficiency and thermostability are limited. Directed evolution has enabled the development of improved enzyme variants through techniques such as error-prone PCR, DNA shuffling, and saturation mutagenesis. This review highlights recent advances in engineering Cutinase and PETases, focusing on enhancing catalytic efficiency and thermostability for PET plastic degradation by directed evolution. Key engineered variants, including HotPETase and optimized leaf-branch compost cutinase (LCC) mutants, demonstrate significant progress toward sustainable plastic recycling through enzymatic means.
| 4 |
Author(s):
Donald Price.
Page No : 26-35
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Pilot Study on Midfoot Pressure Analysis in Individuals with Flat Feet While Climbing Stairs Using a Pressure Sensing System
Abstract
Flat feet, or pes planus, present a prevalent condition impacting mobility and quality of life, warranting an understanding of its biomechanical implications. This study aimed to quantify pressure differentials in the midfoot region between individuals with flat feet and those without during stair ascent. The pilot study evaluated one individual with clinically diagnosed flat feet and one healthy individual, both meeting specific inclusion criteria. The participants ascended stairs while a pressure-sensing system consisting of force-sensitive resistors (FSRs) recorded midfoot pressures. The results showed that individuals with flat feet exhibited lower pressure along the medial longitudinal arch and higher pressure along the lateral longitudinal arch compared to normal feet participants. Statistical analysis revealed significant differences in pressure for FSRs placed on the medial and lateral arches (p < 0.05). These results suggest a compensatory shift in pressure distributions, highlighting the altered loading patterns associated with flat feet. These findings have significant implications for physical therapy, underscoring the importance of arch-strengthening exercises to improve foot stability and redistribute pressure more effectively. By integrating pressure mapping into rehabilitation strategies, therapists can create personalized treatment plans, ultimately improving outcomes for individuals with flat feet. Future studies with larger participant groups and advanced pressure-sensing technologies are needed to validate these findings and refine therapeutic approaches.
| 5 |
Author(s):
Avi Parkhe.
Page No : 36-49
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Comparative Insights into the Molecular Pathogenesis of Huntington’s Disease
Abstract
The hallmark molecular mechanism of Huntington’s Disease (HD) is neuronal intranuclear inclusion
bodies consisting of polyubiquitinated mutant huntingtin (mhtt) aggregates expressing an expanded
polyglutamine tract. Aggregate-prone fragments of mhtt bind to several intracellular proteins in addition
to the glutamate neurotransmitter receptor N-methyl-D-aspartate (NMDA). This review will detail the
molecular and cellular pathways by which mhtt aggregates form clumps in inclusion bodies (IBs) by the
impairment of the ubiquitin-proteasome system and the autophagy-lysosome system. It will also review
the manner by which intracellular mhtt causes neuronal excitotoxicity via NMDA-receptor mediated
excitotoxicity. Numerous studies on models of HD have presented various hypotheses on the pathogenesis
of neurodegeneration, such as the debate on whether IB formation is a response mechanism of HD or its
cause. This paper will discuss the ongoing debate and suggest future research that may reconcile the
competing theories. Finally, this article will highlight current and future therapeutic targets for HD in the
context of these pathogenesis theories.
| 6 |
Author(s):
Abby Li.
Page No : 50-54
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The Impact of Direct-to-Consumer Pharmaceutical Advertising on Social Media: A Review
Abstract
Direct-to-consumer advertising (DTCA) is a marketing strategy that advertises prescription drugs directly to consumers instead of through healthcare providers. With the rise of social media platforms, pharmaceutical companies have implemented DTCA on social media as a way to promote their products to consumers. The aim of this literature review is to analyze the impacts of social media DTCA on consumer healthcare. I conclude there are benefits to DTCA such as increasing consumer awareness and accessibility; however, there are also concerns over the reliability of information shared on social media which can harm consumers. As the pharmaceutical industry continues to use social media as a way to market prescription drugs, it is important to do so in a way that educates consumers while reducing potential harm.
| 7 |
Author(s):
Aarit Das.
Page No : 55-61
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How will Artificial Intelligence Effect Unemployment? A Predictive Study Utilizing Past Trends
Abstract
The adoption of artificial intelligence (AI) has a profound impact not only on the broader economy
but also on the unemployment rate. In this study, we aimed to better understand the effects of AI on
the unemployment rate by collecting the unemployment data from the Bureau of Labor Statistics Data
(BLS). This data is considered reliable since the government collects, updates and consolidates the
data from a large population in the US. The collected unemployment data was then correlated with
different sectors of the economy. Each sector of the economy was represented by its corresponding
Vanguard exchange-traded fund (ETF). Our analysis showed that as a result of the advent of AI, the
unemployment rate correlated the most with the technology sector. This result was in concurrence
with similar upheavals of the past. A major event, whether technological or non-technological, initially
caused the unemployment rate to increase. Gradually, as society absorbed the impact of the event, the
unemployment rate returned to previous levels. During this cooling off period, the new innovations
steadily transitioned into critical components of daily life upon which a society became dependent
leading to the creation of new kinds of jobs.
| 8 |
Author(s):
Shravan Saranyan.
Page No : 62-73
|
AlphaFold: A Comprehensive Guide to the Revolutionary AI Tool and Its Methodology
Abstract
AlphaFold is a machine learning program that predicts a protein’s 3D structure from its sequence by
analyzing evolutionary history, protein similarities, and pairwise correlations. This review explores the
purpose, methodology, and customizable features of AlphaFold’s neural networks and code, including
options for adjusting model types, MSA, and pair modes based on user preferences. While AlphaFold
faces challenges with novel and dynamic proteins, newer versions continue to expand its capabilities,
including predictions for ligands, nucleic acids, and protein complexes.
| 9 |
Author(s):
Ari Shukla.
Page No : 74-83
|
Duckweed as a Natural Bioremediation Agent for the Removal of Auxin Herbicides
Abstract
Auxin herbicides are widely used in agriculture and gardening. Auxin herbicides mimic the natural
plant hormone auxin and result in abnormal cell division which leads to the death of broadleaf weeds
while not affecting monocot plants such as grasses and grain crops. While auxin herbicides have been
widely regarded as safe, there is growing evidence about their impact on non-target organisms and
groundwater contamination. In this study, I used duckweed (Lemna minor) to assess its ability to absorb
quinclorac (carboxylic acid of 3,7-dichloroquinoline) and 2,4-D (2,4-Dichlorophenoxy acetic acid)
which are widely used auxin herbicides. To analyze for the concentration of quinclorac and 2,4-D in
solution, we developed a Reversed-phase high-performance liquid chromatography (RP-HPLC) method
by measuring absorbance at 254 nm. The analytical method successfully separated the two chemicals
and showed linearity and sensitivity over a wide range of concentrations. Duckweed successfully
removed 30-50% of the initial 2,4-D and quinclorac from water. These results demonstrate that natural
duckweed-based bioremediation is viable way of removing auxin herbicides from water bodies.
| 10 |
Author(s):
Aarav Patel.
Page No : 84-92
|
Advances in Therapeutic Strategies for the Genetic Disorder Cystic Fibrosis
Abstract
First discovered in 1938, cystic fibrosis was determined to be a disease affecting the pancreas,
gastrointestinal tract, reproductive organs, and lungs. It was later discovered to be a recessively inherited
autosomal disease characterized by mutations in the cystic fibrosis transmembrane conductance
regulator gene which results in dysfunctional ion transport proteins in epithelial cells. Impaired ion
transport leads to viscous mucus, which can cause pulmonary infection, pancreatitis, malabsorption, and
infertility. Cystic fibrosis can be diagnosed during newborn screenings either by the sweat chloride tests
or trypsinogen tests. It is estimated that 105,000 people worldwide have cystic fibrosis, and Caucasian
people are known to have the highest prevalence. Treatments do exist to lessen the symptoms of cystic
fibrosis, but they do not ensure a lifetime cure. Current research is focused on developing modern
types of treatments for cystic fibrosis, such as gene editing therapies. Early results from studies with
mRNA therapies and CRISPR/Cas9 technology show promising results for future treatment. Potentially
curative therapies like CRISPR could lead to improvement in the quality of life of cystic fibrosis patients
and an increase in life expectancy.
