| 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.