ikatkov/journal-of-student-research-hs-articles huggingface dataset:
Understanding the Role of Leverage in the Outcome of A Nuclear Weapons Program
Authors: Pranav Marneni; Samuel Leiter
Date: 11-30-2021

Why were some countries able to succeed in acquiring nuclear weapons while others didn’t when facing international pressure to stop the development of their nuclear program? I hypothesized that the level of leverage placed over the country trying to acquire nuclear weapons by its main ally and adversary is a key variable affecting the outcome of that country’s nuclear program. To test my hypothesis, I first described the different categories of leverage and I then compared the nuclear programs of North Korea and Taiwan using existing historical research and case studies. I compared the two countries to see if the categories of leverage were in fact different for the two countries. The two countries were chosen since they had different results (Taiwan failed, while the DPRK succeeded) and both had an ally and adversary that had some leverage over it. If leverage was different for the two countries it would be highly likely that leverage had a role in causing the different outcome, thus supporting my hypothesis.&nbsp; If leverage was the same for the two countries, it would mean that leverage was not a factor causing the different outcome and my hypothesis would be incorrect. After comparing the nuclear programs of the two countries it was found that leverage was in fact different for the two countries, thus supporting my hypothesis.
GuideDogNet: A Deep Learning Model for Guiding the Blind in Walking Environments
Authors: Yunseo Hwang; Taeseon Yoon, Kyuyong Park
Date: 11-30-2021

A guide dog is a critical companion for the blind, which enables independent travel of the blind. However, due to the costly and time-consuming training process, only 1.7% of the blind who wish to adopt a guide dog can take it. In order to alleviate this social problem, previous studies have suggested several blind guiding systems heavily based on hardware devices, such as GPS(Global Positioning System), RFID(Radio-Frequency Identification), and ultrasonic devices. However, those techniques lack administrative feasibility to use in real-world environments. Moreover, those techniques are deficient in warning of obstacles, which makes the system non-user-friendly. To guide the blind universally and provide accurate information about the obstacles without cumbersome devices, we propose a novel deep learning-based blind guiding system, GuideDogNet. The proposed system consists of an object detection network, depth prediction network, and post-processing module. To provide user-friendly outputs for the blind, we propose a rule-based post-processing module that outputs the label, direction, and distance of the obstacles by combining the results of the object detection network and the depth prediction network. We achieved an mAP of 67.8 on the AI Hub Sidewalks dataset which is publicly available. To the best of our knowledge, this is the first attempt at a deep learning-based blind guiding system.  &nbsp;  The code will be available on https://github.com/Yunseo-Hwang/AI-GuideDog
The Potala Palace in Tibet  Interweaving of Architecture, Spirituality, and Culture
Authors: Dorinda Xiao; Dr. Michael Shanks
Date: 11-30-2021

The Potala Palace in Lhasa, Tibet is seen as a symbolic center of Buddhism. The specific architecture of the palace, such as the color palette and the rooms, is designed around Tibet's culture and religion, Buddhism.&nbsp; The architecture of the Potala Palace and the culture are interconnected as the color chosen for the palace relates with the history of Tibetan culture and the room designs relate closely to Buddhist practices. While culture has influenced the foundations of the Potala Palace’s architecture, the palace itself also affects Tibetan society since Tibetans center around the economy it created, which they can profit from while also celebrating their traditions. This paper researches the interweaving of the Potala Palace’s architecture, Buddhist spirituality, and Tibetan culture to gain a deeper understanding of the significance of the history and religion rooted in a traditional Tibetan building and how that building acts as a microcosm for Tibetan society today.
Is Science Effectively Conveyed to the Public? A Case Study of Genetically Modified Mosquito Release
Authors: Kailash Vemuri; N. Murti Vemuri, Ph.D, Sita Munukutla
Date: 11-30-2021

Science is the driving force behind the advancement of society making public engagement with science vital. With the rapid pace of scientific discoveries, the availability of well-balanced scientific information is possibly the most important it has ever been. This study aims to determine the effectiveness with which scientific information is disseminated to the public. This was done by conducting a survey in which people were given three articles to read about the release of genetically modified mosquitoes. These three articles were adapted from local news coverage, government authorities, and peer-reviewed scientific literature. Survey participants were queried on their relative preferences for these articles. Additionally, the top 100 hits on Google for the search item “Florida mosquito release” were analyzed to assess the availability of the scientific information preferred by survey respondents. The results of this study showed that the public seeks quality, balanced scientific literature but that these types of articles aren’t easily accessible. Articles that prioritize getting clicks are more prevalent than those that present balanced scientific research.
Religion as Mental Short-Circuit
Authors: Keyue Li; Nanjing Foreign Language School Faculty
Date: 11-30-2021

By identifying religion as schema and attribution process, the first two following sections of the essay argues that religions and cults short-circuit normal cognitive process, bypassing the objective evidence and logical argument inconsistent with the belief system. In the last two sections, the essay demonstrates that recognizing religious thinking mode as a mental short-circuit can be extended to the broader application in human cognition. What’s more, the essay examines the perspective of believers who prioritize the fulfillment of their psychological needs over the righteousness of the logic and calls on building new healthy connections with previous victims in cults instead of spending major effort convincing them of the logic flaw in their previous belief.
A Behavioural Perspective on Vietnam's Corporate Safety Measures and Nudges in Covid-19
Authors: Bui Gia Han Pham; Philip Liang
Date: 11-30-2021

Robust enforcement of safety procedures is of critical importance for businesses in Vietnam in their efforts to prepare employees for a return to physical workplaces, especially in a country with only 38.8% of its population fully vaccinated as of late November 2021 (Ritchie et al., 2020). In academic literature, nudges are traditionally believed to enhance compliance to protective measures (Debnath and Bardhan, 2020). The aim of this paper is to test the strength of such theoretical analysis of nudges’ effectiveness by applying it to the context of companies in Vietnam. We performed a survey of 41 companies in various sectors and used regression models to interpret our data. One study found a positive significant relationship between automatic registration, monetary rewards, and percentage of employees vaccinated. In the same study, we found an average increase in vaccine uptake of 27.7% to 45.6% due to vaccination nudges. In our second study, we found no evidence that sanitising nudges encourage employees’ usage of sanitary utensils provided to them. Although our small sample size was a major limitation of this study, our findings put the functionality of nudges into a developing country’s context and analysed socio-economic factors that might have caused our results to differ from prior research. With this study being the first to examine the use of nudges to promote pro-health behaviour in large corporations during COVID-19, future research could delve deeper into the effect of other non-mandatory safety measures on overall workplace health.
Simulated Study of SARS-CoV-2: Contact Tracing and Potential Transmission Networks
Authors: Anjali Iyer; Anupama Shankar
Date: 11-30-2021

During a disease outbreak, contact tracing and epidemiological analysis are of critical importance to analyze disease sources and transmission. To perform this epidemiological analysis, effective data visualization is necessary. In this study, the outbreak of COVID-19 was simulated within three metro Atlanta counties. Data was generated using contact tracing forms and used to create node and edge lists. Each node in the network contained a unique ID representing either a location or individual, as well as any contact tracing information related to each node. Data visualization was performed using MicrobeTrace, an online program developed by the CDC. Visualization of the contact tracing network enabled us to effectively analyze the transmission dynamics of SARS-CoV2. In the simulated network, a singular person node appeared to be linked to the most positive COVID-19 cases in the network. Similarly, a restaurant was identified as the place node with the greatest number of direct connections to positive persons, highlighting it as a potentially major source of exposure to SARS-CoV-2. This study illustrates the benefits of data visualization and demographic analysis using MicrobeTrace, which helps to target mitigation and prevention efforts, while also emphasizing the importance of contact tracing to reduce the transmission of disease.
Solutions to Some Real-Life Problems Based on Mathematical Modeling and Functional Minimization
Authors: Oleksii Babaskin; Mr. Tadeo
Date: 11-30-2021

Building mathematical models that can describe, predict, and explain real-life phenomena is useful. This paper features the functional dependency model and the square of this functional dependency which hold significant information. A mathematical model that relates these functional dependencies with the average value of the function was developed to show that for an arbitrary well-behaved function, the definite integral of the square of the function over a finite interval is minimal when the function is constant over the interval. Finally, the model’s validity and accuracy in representing real-world problems for different situations in physics like mechanics, quantum mechanics, and electricity in economics were evaluated.
Punctuation Restoration for Speech Transcripts using seq2seq Transformers
Authors: Aviv Melamud; Alina Duran
Date: 11-30-2021

When creating text transcripts from spoken audio, Automatic Speech Recognition (ASR) systems need to infer appropriate punctuation in order to make the transcription more readable. This task, known as punctuation restoration, is challenging since punctuation is not explicitly stated in speech. Most recent works framed punctuation restoration as a classification task and used pre-trained encoder-based transformers, such as BERT, to perform it. In this work, we present an alternative approach, framing punctuation restoration as a sequence-to-sequence task and using T5, a pretrained encoder-decoder transformer model, as the basis of our implementation. Training our model on IWSLT 2012, a common punctuation restoration benchmark, we find its performance is comparable to state of the art classification-based systems with an F1 score of 80.7 on the test set. Furthermore, we argue that our approach might be more flexible in its ability to adapt to more complex types of outputs, such as predicting more than one punctuation mark in a row.
A User Study of E-commerce during the Covid-19 Pandemic
Authors: Anika Krishnan; Kavana Ramesh
Date: 11-30-2021

Covid-19 has forced most people around us with access to the internet to begin shopping online. For some, it is the efficiency, and for others, it is the fear of the virus. Items that were rarely bought online, are now becoming a commodity for viewing online. Groceries and thrifted items are some examples. Most websites have increased traffic because of how prevalent shopping at online sites has become in the past year and a half. For this experimental study, I interviewed multiple people and deduced some central ideas about online shopping during and following the pandemic. I interviewed each person about their day to day lives and how online shopping has played a role in it during the pandemic. I recorded these responses and found surprising similarities between each person. Everyone that I interviewed said that they would continue online shopping after the pandemic. Most people found that the pandemic had been an “eye-opener”, in that, online shopping saved an astounding amount of time. Overall, buying things online has become somewhat of a habit for people during the pandemic.&nbsp;
Comparing Different Data Types for Predicting the Apple Stock
Authors: Amanda Guan; Dr. Ellsworth
Date: 11-30-2021

Stock markets are at the heart of market economies, and stock market prediction is a hot topic in research. There are many methods of prediction, and they often use different types of data. The two main types are technical and fundamental data. This paper explores company-specific prediction through predicting the direction of the Apple stock. Three neural networks that use different input data are compared. The Tech model uses technical data, the Comp model uses numerical fundamental data with an emphasis on company data, and the Text model uses textual news data. Several metrics, including ones useful for preventing bias when dealing with imbalanced data, were used to compare the models. The Comp and Text models showed prediction bias, and two more models, W-Comp and W-Text, were trained to attempt to mitigate that bias. The Comp model performed the best out of the original models, and W-Comp also showed good performance. W-Text performed the best out of all the models. This suggests that numerical fundamental data is useful in predicting the market, and textual data also has potential. Future research could be used to improve the performance of all the models and more thoroughly compare the types of data used.
The Potential for Liberation Feminism in Hindu Practices and its Patriarchal Origins  Does original knowledge facilitate the perception of liberation feminism in Hindu practices?
Authors: Naisha Didwania; Maya Novak-Herzog
Date: 11-30-2021

Hinduism is accused of suppressing its women devotees, despite a history suggesting a matriarchal approach. Over the years, original knowledge surrounding religious practices have been lost due to misinterpretation, misinformation and autonomy over said knowledge by certain groups. The purpose of this essay is to explore the various practices that accuse Hinduism of being anti-feminist, and to identify their origins to understand the role that both culture and religious doctrine played in promoting women's inferiority, as well as which had greater influence. Previous research relies heavily on scriptural understanding and secondary data analysis, despite the fact that overreliance on scriptures is one of the major contributors to the spread of false information regarding the divorce between the intentions of the religious doctrine and subsequent traditions and customs. I interviewed practitioners of the religion coming from various backgrounds and used the primary data to theorise the origination of women's oppression and means to reduce its continuation. The understanding behind religious practices such as Sati, Pativrata and taboos surrounding female priesthood and menstruation yield results that attribute the patriarchy to factors that were not intrinsic to Hinduism. Hence, my findings conclude that women’s original knowledge of the fundamental tenets of Hinduism understood as anti-feminist facilitate their empowerment. Therefore, furthering original knowledge of ‘sexist ideals’ can increase the potential for liberation feminism for Hindu women by reducing the prevalence of conservative practices.&nbsp;
Application of Artificial Intelligence for the Prediction of Solvation Free Energies for Covid-19 Drug Discovery
Authors: Sampreeth Immidisetty; Deepak Agrawal
Date: 11-30-2021

Solvation free energy is a key indicator of the effectiveness of a drug molecule. There are several applications of predicting the solvation free energies of chemical compounds using quantum mechanical methods. However, these methods take a long time and are costly. For that reason, the application of recently developed artificial intelligence techniques for the prediction of solvation free energies is becoming increasingly valuable in drug discovery to address time and the high-cost issues with traditional quantum mechanical approaches. In this paper, we present application of two different artificial intelligence models for predicting solute-solvent free solvation energy for Covid-19 drug design. The research involves building, training, evaluating and comparing the performances of the two models on a large dataset, then predicting solvation free energies for 138 known APIs and 28 organic solvents that could potentially be used as a Covid-19 medicine. The potential repurposing of 138 drugs for Covid-19 from solubility perspective is novel. We demonstrate the application of the AI models and derive several conclusions regarding suitability of the APIs and their efficacy. We conclude our research by providing insights on how our work can be put to future use towards drug development.
Warburg Effect and Cancer Survival
Authors: William Panosyan, Daniel Panosyan; Eduard Panosyan
Date: 11-30-2021

Warburg effect is a major metabolic shift of glycolysis in cancer cells towards anaerobic fermentation. Key reaction here overproduces lactate from pyruvate catalyzed by lactate dehydrogenase-A (LDHA). Augmented Warburg effect and oncometabolism may contribute to cancer progression worsening patients’ survival. Expressions of various key enzymes were used as surrogates to validate the clinical influence of metabolic alterations in cancers. Expression and Kaplan-Meier survival data were extracted from the R2 Genomics Analysis and Visualization Platform (R2) and Human Protein Atlas (HPA). Expression of LDHA gene was 2-4 times higher than normal tissues in certain cancers including breast, colon, genitourinary and B-cell lymphomas. No cancer specificity or strong associations were observed between RNA and protein expressions of LDHA. However, higher LDHA gene expression correlated with poorer survival in renal, liver, lung, pancreatic, cervical and breast cancers. These cancers moderately or strongly stained for LDHA protein. Per HPA, gliomas had low LDHA without survival correlation. Nevertheless, this correlation was observed in the largest glioblastoma database (R2). Furthermore, 3 of 4 medulloblastoma subtypes showed poor survival with higher LDHA. Contrarily, in B-cell lymphomas and colon cancer high LDHA was a favorable prognostic marker. Poor survival correlated with high expression of other enzymes for glycolysis and amino acid metabolism (PFK-isoenzymes, GFPT2 and BCAT1). Warburg effect may not be universally dominant for all cancers, but most cancers have high LDHA and/or associated poor survival, confirming importance of this metabolic derangement in cancers. Heterogeneity of metabolic alterations can serve to diversify anti-metabolic strategies for targeted anti-cancer therapies.
Pretibial Lacerations in Young Athletes: Evaluating Who is at Risk, and Methods in Reducing Infection
Authors: Meghan Dougherty; Kim Bauer
Date: 11-30-2021

This study begins research in identifying risks factors youth athletes face when it comes to their probability of getting a pretibial laceration; which is seen more often in elderly populations. The data of shin skin thickness in athletes and non-athletes were compared in this research, as well as methods to decrease rates of infection in pretibial lacerations. The hypothesis of this research is to test if youth athletes are the most susceptible to pretibial lacerations compared to youth non-athletes. Data showed that athletes have “thicker” skin than non-athletes, which meant that they had more muscle mass surrounding their tibia bone which meant they have less skin to protect their tibia which leads to an increased risk of pretibial lacerations compared to other youth populations.&nbsp;
Artificially Intelligent Food Assistant for the Visually Impaired
Authors: Sarthak Jain; Evan Brociner
Date: 11-30-2021

Vision disability is a prevalent condition that affects the lives of many adults and children. Previous research has established that it is harder for the visually impaired to evaluate the nutritional value of food. Therefore, by applying concepts used in agriculture and optical character recognition, we engineered a system that can make these perceptual evaluations on a variety of fresh and packaged foods and linguistically relay that info to a visually impaired user. We utilized some of the most memory-cheap and accurate object detection models to evaluate and then detect lesions in peaches, apples, tomatoes, and strawberries. Table 3 shows that our models performed with high accuracy as EffecientDet d0, SSD Lite Mobilenet, and Faster RCNN MobileNet all had higher than 40% mAP and 50% mAR. Figure 2 portrays how our interface was able to detect, determine, and relay surface spoilage percentage(s) to a user. Figure 3 shows that our OCR integration successfully was able to gather nutritional data on packaged goods and relay nutritional information to a user. Our system provides the brain for future applications that plan to deploy our code to devices like smart glasses or other hardware. We have made our source code available on GitHub through this link: https://github.com/SarthakJaingit/Artificially-Intelligent-Food-Assistant-for-the-Visually-Impaired. Our repository provides instructions about running our system through the command line and also a notebook demo that a less technical person can run to see how one of our models performs on a computer webcam with no video optimization.&nbsp;&nbsp;&nbsp;
The Gender Disparity of Refugee Earnings in the United States
Authors: Subhadra Vadlamannati; Holly Dykstra
Date: 11-30-2021

The refugee crisis impacts both low and high-income countries alike, and the question of refugee assimilation receives much attention worldwide. While all refugees face various challenges in assimilating to their host countries, female refugees face additional challenges. This paper focuses on the earnings of refugees upon arrival to their host countries. The 2018 Annual Survey of Refugees was used to study the earnings trajectory of male and female refugees who arrive in the United States. Results reveal a significant earnings gap of approximately $1.70 an hour, which is equivalent in pay to male refugees receiving almost eight more years of schooling. To examine the underlying mechanism behind this result, this paper studies how the predicted earnings trajectory varies when including the UNDP Human Development Index and the World Economic Forum Global Gender Gap variable, using refugees’ country of birth. Findings indicate robust results that female refugees do not benefit from increases in human development, while both male and female refugees benefit from increases in gender equality. These results have important implications for refugee policy in the form of cash assistance or vocational training.