ikatkov/journal-of-student-research-hs-articles huggingface dataset:
A Study of the Endowment Effect in Phase II and III of the EU Emissions Trading System
Authors: Sophia Qin; Edoardo Gallo
Date: 08-31-2022

This paper investigates the endowment effect in the European Union Emissions Trading System (EU ETS) over Phase II and Phase III using complete transaction records from the market. The results show that for most companies in both Phase II and Phase III, their WTA (willingness to accept)/WTP (willingness to pay) ratio is less than or equal to 1, signifying that there is an insubstantial degree of the endowment effect in the EU ETS. This challenges the results of a pioneering study and brings into light the need for a more rigorous study to re-examine the endowment effect in the carbon market.&nbsp;
Prohibition and Suffrage During World War I: The War’s Dual Impact
Authors: Jason Fu; Charles Argon
Date: 08-31-2022

This study analyzes how World War I impacts two Progressive Era reforms—Prohibition and women suffrage—both positively and negatively. While the war promoted the passage of two constitutional amendments, it reduced the two movement’s commitment to reform that would benefit the society. Prohibition became quasi-authoritarian, intruding individual rights; suffrage turned conservative by adopting racist justifications in order to win support. This paper proposes a hypothesis that could explain this turn from progressivism to authoritarianism and conservatism, and discuss the two movements in detail to support the hypothesis.
Impact of the Recent South Korean Presidency Change on Security Relationship with North Korea
Authors: Daniel Ha; Elliot Ji
Date: 08-31-2022

Tensions in the Korean Peninsula have soared with the advancement of North Korea’s (DPRK) nuclear weapons development. Along with Russia’s invasion of Ukraine in early 2022, DPRK’s 7th nuclear test is impending. In the era of a “new Cold War,” the presidency of South Korea (ROK) changed in May 2022. This study examined how the recent ROK presidency change affects its security relationship with DPRK. To analyze this, I performed a literature review of DPRK-related policies that former ROK presidents implemented. I used qualitative data from my three in-depth interviews that focused on Yoon’s policy initiatives in three aspects: DPRK policy, US-ROK alliance, military defense. To obtain updated information on ROK’s international situation, I conducted a debriefing of the 8th Yonhap News Symposium on Korean Peace (June 2022). Throughout past ROK governments, the strategies toward DPRK differed significantly between progressive and conservative parties. Inter-Korean relations were stronger under progressive party governments, but neither made progress towards DPRK’s denuclearization. President Yoon stated his policy would be principled and consistent, with a strong US-ROK alliance and international cooperation. Yoon planned the implementation of ROK’s 3-axis system and the establishment of the Military Strategic Headquarters, including advanced detection and precision strike counter-force capabilities. If he can achieve a US-ROK alliance and attain non-nuclear deterrence, ROK’s security relationship with DPRK will likely be safer than in the past. My research addresses a detailed question that is part of a larger global landscape to analyze ROK’s international affairs and gain insight into effective security policies.&nbsp;
Molecular Mechanisms of Cancer Metabolism and Their Cellular Cycles
Authors: Harshita Ganga; Dr. Raj Appavu
Date: 08-31-2022

Cancer is a prevalent disease, with 1,752,735 new cases reported to the CDC in 2019.&nbsp; The disease is characterized by uncontrolled growth and spread of abnormal cells. Current treatments for cancer can affect the whole body and have detrimental effects. Cancer cells are often programmed metabolically. In recent years, treatments to undermine this metabolic reprogramming have come to the forefront. In this review, we explore some of the molecular mechanisms underlying certain dietary interventions and critical metabolic pathways. Dietary interventions such as chronic calorie restriction (CR) and fasting have been shown to aid in adjusting metabolic reprogramming to help in reducing cancer progression. Other dietary interventions target amino acid (AA) metabolism. Essential AAs are only consumed from the diet and their restriction has been shown to work as a treatment in mice. Lastly, central carbon metabolism includes the TCA cycle and glycolysis, both commonly reprogrammed pathways in cancer cells. Other dietary interventions and the reprogramming of these pathways can be used to treat cancer in other ways, such as knocking out genes and cell cycle arrest.
Using Newton’s Laws to Determine the Quality of Bharatanatyam Dance Movements
Authors: Sidhya Ganesh; Professor Ramachandran
Date: 08-31-2022

Bharatanatyam, an ancient Indian Classical dance form, places a heavy emphasis on dancers’ body positioning and usage of space, categorizing movements as ‘Good’ or ‘Bad’ qualitatively. The present experiment investigated the extent to which statics/kinematics can be used to evaluate the quality of a Bharatanatyam dance movement. The declared hypothesis was that the dancer’s body could be approximated as a rigid body/simple object, for analysis. Two Bharatanatyam movements, a one-dimensional jump, and a two-dimensional parabolic leap were each performed in a ‘Good’ and ‘Bad’ manner, recorded with calibration sticks in the background, and analyzed using Tracker. Inconsistencies within acceleration due to gravity values disproved the hypothesis. However, kinematics/statics comparisons between ‘Good’ and ‘Bad’ versions of both movements resulted in the following quantitative takeaways. In the one-dimensional movement, the ‘Good’ movement had a longer duration of free fall, a higher maximum vertical height, and a smaller horizontal displacement than the ‘Bad’ movement. The force exerted by the floor on the dancer was around 100 times the dancer’s body mass in the ‘Good’ movement vs. only 72 times in the ‘Bad’ movement. In the two-dimensional ‘Good’ movement, the dancer vertically jumped 2.15% of their body height and horizontally jumped 16% of their body height. In the ‘Bad’ movement, the same values were 0.895% and 21%. Calculating torque during launch revealed that the launch leg in the ‘Good’ movement was closer to &nbsp;than in the ‘Bad’ movement. The ratio of horizontal to vertical displacement was also 3 times lower for the ‘Good’ movement.
Equality Means Business: Factors Affecting Indian Women-Owned Small Business’s Scalability & Impact of Entrepreneurship On Financial Independence
Authors: Maanya Singh
Date: 08-31-2022

The lack of women’s economic participation and financial independence is a major contributor to gender inequality in India. The creation of women-owned MSME businesses in the&nbsp; cottage and F&amp;B&nbsp; industry&nbsp; not&nbsp; only provides women with job opportunities, but also empowers them in the sense that they no longer need to be socioeconomically subordinate to their male representatives. &nbsp; Towards this need, the aim of this study was to understand the factors that impact the financial independence of India’s urban-based women entrepreneurs owning small F&amp;B businesses, as well as evaluate the impact of entrepreneurship on their social and economic empowerment. The sample set of the data were 21 urban India-based female entrepreneurs, between the ages of 20-60 years of age, owning small (less than 10 employees) businesses. The interviews and surveys were conducted in English. The results of this research study have established that the creation of MSME enterprises results in a significant increase in Indian women’s financial independence and social empowerment. While the 95% entrepreneurs aspire to upscale their business ventures, they are being held back by a lack of access to mentorship from experienced entrepreneurs and financial support. Qualitative analysis evidenced the ability of entrepreneurship to socially empower Indian women, through the formation of a professional identity, as well as newfound economic self-sufficiency. These findings imply that entrepreneurship is a tool that can be leveraged by government and non-profit organizations to radically increase Indian women’s financial independence and economic participation, leading to an increase in social empowerment as well.&nbsp;
The Artificial Synthesis of Raphide
Authors: Shoki Matsushima; Yuko Morimoto
Date: 08-31-2022

Have you ever had an itchy mouth after eating yam? This is because the calcium oxalate needle shaped crystals, known as raphide, is contained in the plant that irritate the skin. raphide has been studied in various fields such as medicine and agriculture because of their characteristic effects. Although previous studies have reported useful effects, no successful artificial synthesis of raphide crystals has yet been reported. Therefore, I researched for factors that affect the synthesis of raphide. First, I conducted targeted experiments on drop rate, rotation speed, and concentration. As a result, it was found that the drop rate and rotation speed are factors that change the crystal structure. When these crystals were analyzed by X-ray crystallography, it was confirmed that they were calcium oxalate crystals. However, they were not raphide, so I attempted to synthesize them using a catalyst. For the catalyst, I decided to use the cell fluid part of aloe vera and an aqueous solution of amino acids. When the synthesized crystals were observed under a microscope, there were few raphide could be seen. Furthermore, since the extracted crystals may be the catalytic amino acid, ninhydrin reaction was performed on the filtrate and crystals, and no reaction was observed in both. Since it reacted in the solution before the experiment, I can say that it is calcium oxalate crystal. Therefore, it can be said that the synthesis of raphide was successful and the purpose of the research was achieved.
Profitability and Polarization: TikTok's Dominance of the Attention Economy
Authors: Aditya Jain; Allison Hussenet
Date: 08-31-2022

With increased access to technology, our dependency on Internet platforms for information has increased. The COVID-19 pandemic-related lockdown measures, such as stay-at-home orders and quarantines, seem to have accelerated the natural drift towards greater technological usage. One Internet platform that individuals use to consume online content is TikTok, a rapidly growing entertainment source that uses algorithms to curate and prioritize user preferences. Increasing technological dependence, however, may be tied to rising concerns about polarization associated with online content. This research explores if and in what way users perceive that Tikok benefits from polarizing content in terms of increasing user engagement and profits. This study of high school TikTok users found that these consumers believe engagement and profits thrive because of the algorithm’s increased frequency of displaying divisive content to active users, increasing their use of TikTok.
Python-based Prediction of Rapid Intensification from MIMIC-TC Ensemble (PRIME)
Authors: Lorenzo Pulmano; Leya Joykutty, Dr. Juliana Carvalho De Arruda Caulkins
Date: 08-31-2022

Rapid intensification (RI), as defined by the National Hurricane Center (NHC), is an increase in the maximum sustained winds of a tropical cyclone (TC) of at least 30 knots (~34-35 mph) within a 24-hour period.&nbsp; Intensity forecasting is one of the most difficult aspects of TC analysis forecasting, with RI prediction being one of the most challenging issues.&nbsp; Predicting intensity and RI is critical for emergency responses, including evacuation and disaster prevention.&nbsp; Deep learning (DL) and its application in TC analysis holds much potential.&nbsp; Morphed Integrated Microwave Imagery at the Cooperative Institute for Meteorological Satellite Studies (MIMIC) is a product that synthesizes “morphed” images of TCs.&nbsp; MIMIC-TC is a product that uses 85-92 GHz microwave imagery to create the images.&nbsp; Using the Python programming language, a DL convolutional neural network (CNN) ensemble was developed as a proof-of-concept for prediction of RI, known as the Prediction of Rapid Intensification from MIMIC-TC Ensemble (PRIME).&nbsp; Six members comprise PRIME, split into three 10 and 20 epoch models.&nbsp; Each model has either 2, 3, or 4 convolutional layers.&nbsp; A MIMIC-TC dataset was created using available North Atlantic Basin (NATL) storms from 2019 and 2020, and a total of 1508 images were used for training the models.&nbsp; After running the Ensemble on all available storms from 2019 and 2020, it appeared all models were overfit, and subsequently gave inaccurate classifications.&nbsp; The average percentage of correct classifications of “No RI” (nRI) was 30%, and the average percentage of correct classifications of “Possible RI” (pRI) was 27%.
Electric Potential Analysis of Contaminated Lands in Idaho for Utility-scale Solar Energy
Authors: Cindy Su; Erin Stutzman
Date: 08-31-2022

In the state of Idaho, major electric utilities, such as Idaho Power, have shown a growing interest in solar energy. Because utility-scale solar energy (USSE) requires large land usage, this aspect may be especially problematic for indigenous communities and wildlife when siting USSE. Though less problematic, the proximity of transmission networks to a new USSE site may also be a drawback because of the cost associated with building new networks. However, the use of contaminated sites listed in EPA’s RE-Powering Initiative may be an effective solution for reducing the difficulties associated with siting USSE. Within Idaho borders, the estimated electric potential of such contaminated sites within Idaho Power’s service area was evaluated in this study. This was done through map overlays and simple mathematical calculations that consider factors that affect PV performance. The RE-Powering sites were found to be of use for providing energy to Idaho Power’s customers in Idaho and reducing greenhouse gas. Thus, this study may be of use in mitigating the challenges associated with siting USSE so that further solar energy adoption may be achieved.
Investigating the Central Asian Perspective on Working Women’s Level of Competence
Authors: Samirakhon Makhkamjonova; Rebecca Totton
Date: 08-31-2022

Numerous studies have revealed that women do not get equally paid as men do, and this can specifically impact working mothers to a higher extent. In Central Asian communities many women are underrepresented in high-status professions. Previous research has found that this can be from cultural influence, religious beliefs, and the consequence of the Soviet Union event that Central Asian countries were affected. The overall goal of this research was to find evidence to support that Central Asian women are affected by stereotypes and thus are seen as incompetent in the professional field. This is a follow-up study to Cuddy and Fiske (2004) that examined the Stereotype Content Model, with personalities competence versus warmth. A Google Forms survey was used, to record and compare the responses that rated people's personalities from four different conditions. The participants included were audience from Central Asian organizations and content creators, their ages ranged from 18 to 55 and up. The gathered data was examined through JASP (Anova). The results of this study suggest that working mothers are most impacted, as they are viewed as less competent and warm. With this information, future researchers should look into understanding how these stereotypes towards women, could influence the younger generations of girls in Central Asia.
Designing a Unified Healthcare Data System with Blockchain and Cryptography
Authors: Rohan Phanse
Date: 08-31-2022

The majority of public and private healthcare data systems across the globe are proprietary, making it difficult to coordinate and share data between medical institutions on different systems. For the United States, a technically and economically advanced nation, patients still face significant issues with healthcare data sharing, which contribute to inefficiencies in the healthcare system. Friction in data sharing is also prevalent in developing nations like India, where the lack of shareability of patient data leads to redundant tests and unnecessarily high healthcare costs. To improve the integrity and shareability of patient data, we propose a Unified Healthcare Data System, built with blockchain and cryptography. Under this system, patients are in control of their data, and can choose to share their data with doctors and institutions without traditional barriers. To ensure data integrity, blockchain is used to provide immutability and data ownership while cryptography is used to encrypt patient data and implement permissioned access. In this paper, we provide a working implementation of Unified Healthcare Data System and expand on the viability, impact, and evolution of this blockchain-based healthcare data system.
The Censorship Continues to Sail: The Relationship Between Political Ideology and Book Challenging
Authors: Ure Nwokoji; Dr. Sullivan
Date: 08-31-2022

The aim of this study was to explore the extent to which political ideology affects the quality of the book challenge process, with a special focus on the motivations for a challenge and push in political agenda. The approach will be a qualitative one, involving the use of open-ended questions and interviews to extract subjective responses. This approach was taken to encourage authentic answers and data. It concludes with an analysis of the data that reveals that there is a conservative attitude in recent initiation of book challenges.
A Deep Learning-Based Approach for Adaptive Virtual Learning with Human Facial Emotion Detection
Authors: Ishani Das; Mr.
Date: 08-31-2022

Classroom learning has become difficult since COVID-19 began. Students and educators have had to adapt to virtual learning by using the available tools and technologies. However, a virtual classroom does not simulate the same experience as a real, in-person classroom.  In this setting, teachers can immediately receive feedback on the students’ understanding of content by analyzing their facial expressions. By doing so, they can take immediate action to create a more effective learning experience. For example, teachers can individually help students that express an emotion of confusion by reiterating the concept privately and in greater detail. This style of teaching allows educators to ensure every student is receiving the appropriate amount of support and guidance. With online learning, this method of adaptive teaching is compromised. In a virtual class with video conferencing software such as Zoom, it is not practical for a teacher to be able to constantly check each students’ webcam while also teaching and managing technical difficulties.&nbsp;  Utilizing classification models in deep learning, an advanced subfield of machine learning based on neural networks, offers&nbsp; a novel approach to potentially working towards solving this issue. These models are trained with large datasets to mimic human behavior and achieve Artificial Intelligence (AI). The software simulates an effective virtual learning environment by using these methods to detect students’ emotions from facial expressions and providing educators this real time feedback. In this study, it was discovered that a convolutional neural network classification model produced results with the highest accuracy of 55.0%.
The Effects of bride price on the Chinese marriage market
Authors: bai bairuiyang
Date: 08-31-2022

This paper will mainly focus on the marriage market of China and how bride price affects it through diverse methods like analyzing the amount of bride price in different parts of China, using the economics models including demand and supply curve and the indifference curves to figure out whether bride price will affect the marriage rate, and finally developing a theory to depict a females’ psychological and economics evaluation on whether a male is worth marrying. The author finds that if the bride price is too high, then it will negatively affect the marriage rate. The bride price will also affect some of the females’ decisions in choosing their lifestyles. However, for more educated women, the theory suggests that the bride price is no longer the most important factor in their marriage decision.
Partial Solution-preserving Integrable generalization Method for Autonomous ODE Systems
Authors: Oleksii Babaskin; Mr. Babaskin
Date: 08-31-2022

In this paper, we propose a method for the generalization of some generic fundamental, abstract differential equations into generalized systems. We hypothesize that these generalized systems are fit to model some real-life phenomena, which can be of practical interest. We confirm our hypothesis by considering examples that are known to be confirmed with the experiment as well as examples that are still to be discovered.
Regional Disparities in Youth Marijuana Use Before and After Recreational Marijuana Legalization: A Longitudinal Examination from 2010 to 2020
Authors: Amy Park
Date: 08-31-2022

Studies have argued that the recent recreational marijuana legalization should increase the accessibility and acceptability of marijuana for youth and elevate youth marijuana use. While many empirical studies have supported this argument and presented the increase in youth marijuana use after the legalization, there has been no study that examines regional disparities in the effect of legalization on youth marijuana use. The examination of regional disparities is required because the different sub-culture and attitudes across regions should generate differentiated situations for youth marijuana use. The current study analyzes eleven-year datasets, “Monitoring the Future: A Continuing Study of American Youth - 12th-Grade Survey ” from 2010 to 2020, and investigates the distinctive temporal changes in youth marijuana use across regions before and after marijuana legalization. The results show that the legalization effect is critical in some regions without pre-existing availability of marijuana but not in the other regions with pre-existing availability. This study concludes that policymakers should consider local situations to deter youth marijuana use more effectively.
An Intelligent System for Early Prediction of Cardiovascular Disease using Machine Learning
Authors: Aarush Kachhawa; Jeremy Hitt
Date: 08-31-2022

Cardiovascular disease (CVD) remains the leading cause of death, responsible for 18.6 million deaths globally in 2019. Given the wide availability of several effective therapeutic treatment options, early diagnosis of CVD is critical for timely intervention and slowing down the progression of the disease. CVD is associated with a multitude of risk markers with non-linear interactions among them, making accurate diagnosis of CVD quite challenging, especially for non-specialized clinicians and under-resourced facilities in developing countries. In recent years, machine learning based computational techniques have shown great promise in becoming a great diagnostic tool. The goal of this research is to leverage multiple machine learning methods such as random forest, gradient boosting, logistic regression and artificial neural network and evaluate their prediction efficacy. This study also evaluates the feasibility of combining multiple UCI datasets in order to improve the prediction accuracy of the models. On a merged dataset of over 700 patients from the UCI machine learning repository, the most accurate model was found to be the random forest classifier, showing an accuracy and F1 score of 94% and AUC of 0.98. It was found that ensemble learning methodologies along with data optimization and hyperparameter tuning techniques were able to achieve higher accuracy relative to prior published studies on these datasets. Finally, this study also proposes how these machine learning workloads can be incorporated into a distributed cloud connected healthcare system to make them widely accessible to practicing doctors and enable them to assess CVD risk of their patients.