ikatkov/journal-of-student-research-hs-articles huggingface dataset:
A Comparative Analysis of Japanese, Mexican and English Marketing Practices: Examining the Influence of Culture on Marketing
Authors: Stephanie Nelson; Travis Smith
Date: 11-09-2021

This research paper examines how the distinct cultures of Japan, Mexico and Great Britain influence companies’ respective marketing strategies. These three countries were chosen specifically because of their vast cultural differences and their location on three different continents. First, the paper will compare each country’s economic outlook in order to more thoroughly understand each country’s market and consumer behavior. Next, each country’s culture will be explored through several distinguishing aspects such as religion, family structure, gender roles, society, etc. A summary of each country’s consumer behavior and consumer ethics will be given. Next, specific examples of companies that have led successful marketing campaigns in each country will be analyzed in order to determine how they used cross-cultural marketing. The companies used were Coca-Cola for Mexico, Kit-Kat and Louis Vuitton for Japan and Five-Guys for Great Britain. These results can help companies which are trying to launch their products in international markets understand different consumer behavior and markets world-wide.
Trends of industry-leading biotechnology stocks during COVID-19
Authors: Navia Zhang; Meredith Haskins
Date: 11-09-2021

The 2019-nCoV coronavirus has significantly impacted the macroeconomic outlook for countries across the world. The biotechnology sector experienced a relatively positive stock price outlook, which corroborates the trends exhibited by biotechnology stocks in previous pandemics such as SARS (2003) and AH1N1 (2009). During the COVID-19 pandemic, vaccine roll-out rates have been more efficient than in any other pandemic, as companies today are more experienced in combating the time constraint to create vaccines. Gilead Sciences Inc. saw its shares rise 18% after developing the first FDA-approved COVID-19 vaccine, 'remdesivir'. In contrast, AstraZeneca's shares fell 2.28% in 2021 after its vaccine underwent investigations into blood-clotting side effects and subsequent suspension from several countries. Companies developing mRNA vaccines like Moderna, BioNTech, and Pfizer witnessed surges in share prices ranging from 10% to 20%. Many newer biotech companies such as Genexie, Sanovi, OnoSec, and Vaxart have also developed vaccines for COVID-19. Share prices are more volatile for these less established companies. This paper observes how developing new technologies, staging clinical trials, obtaining FDA approvals, gaining publicity, and several other complex factors have profound impacts on the stock prices of these biotechnology companies.
Trends in Clinical Trial Registration in Dentistry: An Analysis of Registered Clinical Trials in the Clinical Research Information Service from 2013 to 2021 in South Korea
Authors: Hye In Lee; Dr. Young-Ran Yoon
Date: 11-08-2021

The Clinical Research Information Service (CRIS) in South Korea provides a clinical trial registry platform in which all clinical trials should be mandatorily and prospectively registered. However, to date, the registration status of clinical trials in the field of dentistry has not been investigated. Therefore, this study aimed to provide an overview of the methodological design and trends of the registered clinical trials over a period of nine years. Information about registered clinical trials in the field of dentistry from the CRIS was comprehensively collected from 2013 to 2021. The details assessed from the collected trials include: type of sponsors, recruitment status, study design, randomization, allocation concealment, single or multi-centric, retrospective or prospective registration, and publication status. A total of 65 registered clinical trials were identified. The number of clinical trials in dentistry in South Korea was found to be less; however, an increasing trend was observed in the recent three years. A majority of the trials were interventional (81.5%), single-centered (86.2%), and conducted on patients (81.5%) and in private hospitals (55.4%). A considerable number of trials had an unclear phase, were retrospectively registered, and rarely published. Regarding the quality, most trials have inadequately reported the method of randomization and allocation concealment. The number of clinical trials in dentistry is still low in South Korea, and most of them were registered retrospectively. A poor-quality reporting of methods at several specific areas was observed. It is necessary for dental investigators to raise awareness of the need to register clinical trials.
Dataset-Agnostic Vessel Segmentation of Retinal Fundus Images by a Vector Quantized Variational Autoencoder
Authors: Tejas Prabhune; David Walz
Date: 11-07-2021

The use of retinal fundus images plays a major role in the diagnosis of various diseases such as diabetic retinopathy. Doctors frequently perform vessel segmentation as a key step for retinal image analysis. This is laborious and time-consuming; AI researchers are developing the U-Net model to automate this process. However, the U-Net model struggles to generalize its predictions across datasets due to variability in fundus images. To overcome these limitations, I propose a cross-domain Vector Quantized Variational Autoencoder (VQ-VAE) that is dataset-agnostic - regardless of the training dataset, the VQ-VAE can accurately classify vessel segmentations. The model does not have to be retrained for each different target dataset, eliminating the need for new data, resources, and time. The VQ-VAE consists of an encoder-decoder network with a custom discrete embedding space. The encoder's result is quantized through this embedding space then decoded to produce a segmentation mask. Both this VQ-VAE and a U-Net model were trained on the DRIVE dataset and tested on the DRIVE, IOSTAR, and CHASE_DB1 datasets. Both models were successful on the dataset they were trained on - DRIVE. However, the U-Net failed to generate vessel segmentation masks when tested with other datasets while the VQ-VAE performed with high accuracy. Quantitatively, the VQ-VAE performed well, having F1 scores from 0.758 to 0.767 across datasets. My model can produce convincing segmentation masks for new retinal image datasets without additional data, time, and resources. Applications include using the VQ-VAE after fundus image is taken to streamline the vessel segmentation process.
CRISPR as a Potential Technique to Reduce Suicide Risk
Authors: Hidemi Zamora; Javier Cornejo
Date: 11-07-2021

As suicide is the nineteenth leading cause of death worldwide, it is important to focus on discovering ways to reduce the risk of suicide-related death as much as possible. With CRISPR starting to become increasingly popular over the past few years, this gene editing technique has been used to study how to edit, turn off, or knock out multiple parts of the genome. However, research on genes related to diseases as cystic fibrosis or Alzheimer’s disease has been mainly prioritized and, even though they are of high importance as well, important issues such as suicide have been left into oblivion.  Four genes have been proven to be key in influencing suicide risk, showing that not only environmental factors account for an increased possibility of death by this cause. Therefore, gene editing techniques such as CRISPR could be applied in order to knock out those genes and reduce this risk. This research used Synthego’s guide RNA design tool to predict how the use of CRISPR can be helpful in knocking out those four suicide-related genes and, consequently, in preventing suicide. The top-ranked guide RNAs for each gene were used, showing the best results possible and with the least number of off-targets, which, in turn, demonstrates the effectiveness of CRISPR as a potential technique to reduce the number of suicide-related deaths worldwide.
Predicting drought using Bayesian structural time series model
Authors: Sophia Wang, Connor Lee; Dr. XL Pang
Date: 11-06-2021

The western U.S. has been experiencing a mega-scale drought since 2000. By killing trees and drying out forests, the drought triggers widespread wildfire activities. In the 2020 California fire season alone, more than 10.3 million acres of land were burned and over 10000 structures were damaged. The estimated cost is over $12 billion. Drought also devastates agriculture and drains the social and emotional well-being of impacted communities.&nbsp;  This work aims at predicting the occurrence and severity of drought, and thus helping mitigate drought related adversaries. A machine learning based framework was developed, including time series data collection, model training, forecast and visualization. The data source is from the National Drought Monitor center with FIPS (Federal Information Processing Standards) geographic identification codes. For model training and forecasting, a Bayesian structural time series (BSTS) based statistical model was employed for a time-series forecasting of drought spatially and temporally. In the model, a time-series component captures the general trend and seasonal patterns in the data; a regression component captures the impact of the drought in measurements such as severity of drought, temperature, etc. The statistical measure, Mean Absolute Percentage Error, was used as the model accuracy metric. The last 10 years of drought data up to 2020-09-01 was used for model training and validation. Back-testing was implemented to validate the model . Afterwards, the drought forecast was generated for the upcoming 3 weeks of the United States based on the unit of county level. 2-D heat maps were also integrated for visual reference.&nbsp;  &nbsp;
Quantitative Analysis of the Impact of Microcredit for Women Microentrepreneurs
Authors: Aine Lima; Sandro Cabral
Date: 11-05-2021

Microcredit has a fundamental role as a tool for financial inclusion. It is estimated that there are almost 50 million microentrepreneurs in Brazil, of which two-thirds are women. This work aims to analyze the impact of microcredit for women microentrepreneurs in comparison with men, based on data collected in northeastern Brazil in partnership Avante, a fintech specialized in microcredit. Data were collected from microentrepreneurs who had access to credit (treatment group) and those who did not have their credit granted (control group) so that they could be compared. The analysis was divided into two parts. In Part I, a descriptive statistical analysis of the collected data was performed. In Part II, some simplified causal inference techniques were applied to validate whether the impact of microcredit existed for women microentrepreneurs. The results give strong indications that women, despite having a lower income, grow more than men after access to microcredit. The annualized growth in income of women was 19.87%, while that of men was 14.66%.
AI Democratization in Optometry: Developing a Prototype with Azure Cognitive Services Platform
Authors: Shaun Baek; Ryan Johnson, Claire Saunders, Debora Lee Chen, Katherine Lai
Date: 11-05-2021

As Artificial Intelligence (AI) technology advances, it is used in almost every aspect of our lives. However, AI is still complicated to implement without help from computer engineers. In the health care field, knowledge of medical and computer knowledge is necessary to create AI-based medical systems. Close cooperation between medical experts and computer experts is essential. For this reason, even if there has been a continuous effort to apply AI into the medical field, it has yet to be universalized. In particular, in the field of optometry and ophthalmology, more complex technology is required than in other medical fields because it is necessary to analyze an eye image to diagnose a disease. Therefore, this study explores the possibility for medical professionals with little computer knowledge in the field of ophthalmology to develop an AI-based diagnostic system without the help of computer engineers. In addition, it explores not only the possibilities but also the diagnostic accuracy of the developed system. Our results show that the diagnostic system discriminates against five common eye diseases to some extent. This study explores whether AI democratization is possible even in the field of ophthalmology that requires advanced skills and knowledge.
Classification Using 3D Point Cloud and 2D Image on Abstract Objects
Authors: Mark Yang; Guillermo Goldsztein
Date: 11-04-2021

While classification using machine learning is exceptionally successful with 2D images, it is more challenging to classify 3D objects. However, 3D objects classification is critical because of its application in autonomous vehicles and robotics. This paper compared neural networks with similar structures using 3D point clouds and 2D images on the same objects. We also generated objects with abstract design and input them into the neural networks we created. We find clear disadvantages with classifying abstract objects compared to ordinary objects for both neural networks. We believe having contextual information will help to address this problem. We also observed that the neural network based on images performs worse than that based on point clouds. However, image based classification takes less time to train compared to point cloud based classification.
A Novel Thermoplasmonic Paint with Titanium Nitride Nanoparticles
Authors: Rhiaan Jhaveri; Dr. Ravi Mariwala
Date: 11-04-2021

Several studies have reported the photothermal heating of colloidal nanoparticles due to plasmon-enhanced light absorption, and Titanium Nitride has emerged as a promising nanomaterial for the practical application of this phenomenon. Here, we developed a novel paint that is infused with Titanium Nitride nanoparticles. Varying concentrations of this paint were applied to copper plates and tested under natural light. Substantial heating was observed under both high-grade and low-grade light for higher concentrations. The uses of this source of heat extend to long-term solutions for reducing the prevalence of waterborne diseases in remote, rural settings via pasteurization.
COVID-19 & Anti-Mask Movement: How Jingoism is Bringing the United States Down
Authors: Colin Kim; Brian Oh
Date: 11-02-2021

The objective of this study was to provide insight into the anti-mask phenomenon that has been occurring throughout the world. Widely broadcasted through different forms of media, these anti-mask movements are a growing concern to the scientific community, as such exposure will only deter the progress towards ending the pandemic. In order to understand the psychological motivations behind the anti-mask sentiment, the present studies 29 videos, over 120 minutes of content covering anti-mask protests in Canada, Europe, and the United States. I also used East Asia as a control variable, as I reviewed 5 videos, around 35 minutes of footage to understand the psychology that makes East Asia more receptive towards mask use. By implementing a qualitative research design, I looked for key language themes (interviews, chants, signs) in order to apply thematic analysis to connect their negative sentiments that are associated with confirmation bias and motivated reasoning. Findings regarding confirmation bias and motivated reasoning have been linked to concerns regarding personal rights and distrust with the government, media, and science communities. In particular, the United States has an issue regarding national pride in connection to individuals’ personal rights. The goal is to give insight into ways the United States can improve mask adherence for future potential pandemics.
Investigation of Benford’s Law with YouTube Social Media Statistics
Authors: Chi-Wei Chen, Shao-Yu Yu; Hsin-Yi Chen
Date: 11-02-2021

In this study, we used social media data to investigate Benford’s Law. In our experimental analysis, we used three control variables: Total Subscriptions, Total Views, and Video Uploads of Youtube channels to verify if the data is artificial and whether or not it fits Benford’s Law. We noticed how Total Subscriptions does not fit Benford’s Law for the top 5000 most-subscribed channels, and Total Views doesn’t fit for the top 5000 most-viewed channels. The reasons that cause this difference are further investigated in this paper. We also proposed a mathematical model to verify if other datasets fit Benford’s Law. After curve fitting the experimental data, results revealed that closer a and b values in our mathematical model indicate that a dataset fits Benford’s Law.
Calming the Waters of the South China Sea: Solving Territorial Disputes over Artificial Islands
Authors: Arjun Anand; Lisa Forbes
Date: 11-02-2021

The South China Sea region has been a site of conflict for decades, with numerous states holding competing territorial claims due to its abundance of resources and strategic importance. Recently, China’s construction of artificial islands in the South China Sea has escalated tensions in the region and has strained efforts to bring peace. This paper observes the role of intergovernmental organizations such as the United Nations (UN) and the Association of South East Asian Nations (ASEAN) in resolving the conflict in the South China Sea. First, this paper studies the ASEAN-China code of conduct, the dispute management approach currently being negotiated between ASEAN and China. This code of conduct will govern the conduct of the countries involved in the South China Sea disputes. Furthermore, this paper proposes key provisions that should be incorporated into this code of conduct to make it more effective. Second, this paper reviews the conflicting views of ASEAN member states that impede the creation and adoption of the code of conduct. To conclude, this paper recommends an alternative solution through the United Nations Convention on the Law of the Sea (UNCLOS), proposing that the conciliation procedure provided in UNCLOS be adopted to resolve the long standing South China Sea disputes.
Western Feminism and Rescuing Non-Western Women
Authors: Manha Waheed; César Cabezas
Date: 11-02-2021

Western feminism has become one of the most widespread feminist ideologies in our world today and it continues to gain popularity among those in the West who attempt to aid women in foreign nations. This particular feminism is rooted in “saving” non-Western women by attempting to mould their lives so that they may feel “empowered,” much like women in the West. What Western feminism fails to account for, however, is the lack of knowledge towards cultural contexts and the harm caused by Western feminists as they attempt to save these women who they deem oppressed due to their culture. The purpose of this paper is to analyze Western feminism from a variety of perspectives and find the flaws that prevent it from actually having a positive impact on women in the Global South. This essay includes references to prominent philosophic literature as well as present and historical examples of Western feminism that prove that the White Ignorance prevents these types of feminists from actually “rescuing” oppressed women. Through analyzing Western feminism from different lenses of White Ignorance, this paper provides an answer for how feminism can have a genuinely positive impact on non-Western women through the abolition of Structural White ignorance found in Western institutions and corporations.
How is economic growth correlated to index growth?
Authors: Aryan Chordia; Karan Gurbani
Date: 11-02-2021

This study will mainly focus on the relation between GDP growth and stock market index growth through various methods like the Pearson product-moment coefficient correlation, comparing the theoretical world to the real-world situation, and finally by looking at consumer sentiments and confidence. This could help various analysts, economists, and even the general public. Through the course of our study, we find out various trends in this study, at some point, the results were contradicting themselves but then our last test made it all clear, which proves that there is no correlation between GDP growth and stock market index growth, but then both of them drives from consumer confidence and consumers future actions.&nbsp;
Conviction, Votes, or Nationalism?  How intrinsic and contextual factors drives cultural policymaking
Authors: Jinxin Xu; Simone Paci
Date: 11-02-2021

Why do policymakers pursue cultural policies? The existing literature presents several potential answers but no study has surveyed them in a comprehensive way. In this essay, I examine a diverse array of factors behind cultural policymaking. Combining domestic and international perspectives, I identify three major motivations: intrinsic demand, constituency demands and nation-building objectives. I employ a mix of qualitative and quantitative evidence to explore the hypotheses stemming from these different decision-making dynamics.
An Unforgettable Ordeal: Chinese ‘Comfort Women’ in World War II
Authors: Yuting Xie; Emily Kraeck
Date: 10-28-2021

Using methods including analyzing firsthand testimonies, images, and secondary sources, this paper explores the multiple factors that resulted in the silence of Chinese comfort women survivors in both wartime and the postwar period: shame culture, patrichy, and lack of political and cultural support for comfort women. Due to both patriarchy and related shame culture and a lack of political, cultural, and international support for survivors, few Chinese women spoke up about their experience within the comfort women system prior to the redress movement beginning in 1991; in the 1990s, societal and government support for comfort women increased, leading many comfort women to not only share their experiences but seek justice in the process. To begin, this paper provides an overview of essential historical context, including Japanese colonialism, the establishment of “comfort women” systems, Chinese comfort womens’ suffering, and the post-war struggles and ongoing plight of victims and survivors. Next, this paper argues that due to shame, culture and patriarchy; the lack of political, cultural, and international support for comfort women; and the mental and physical trauma that they experienced, comfort women survivors refused to speak up or seek justice for decades during and after World War II. Finally, this paper investigates key differences between the Cultural Revolution and redress movement, analyzing why comfort women spoke out during the latter period but largely remained silent during the postwar period from 1945 to 1990.&nbsp;
Examining the Influence of Genes Linked to Comorbidities on the Development of Diabetic Retinopathy
Authors: Ishani Das; Larry DeMuth
Date: 10-28-2021

Diabetic retinopathy (DR) is a complication in diabetic patients that can cause vision loss and even blindness12 {Healthline}. The condition causes bleeding in the blood vessels of the retina and ultimately interferes with the capture of photons and the transmission of neural signals to the brain3 {National Eye Institute}. Unfortunately, there is no cure available for the approximately 200,000 US citizens currently affected by DR8 {Lucas Research}. Current treatments are merely palliative and rarely restore vision. The best approach to combating DR is prevention. Understanding the root genetic causal links of DR is crucial to developing effective prevention plans.&nbsp;  Unlike Huntington’s Disease, which has well defined genetic origins, no single gene has been pinpointed as a causative factor for DR, despite having been extensively researched. Since diabetes alone isn’t enough to predict the progression to DR4{NCBI}, one can hypothesize that a combination of diabetes and at least one other comorbidity, such as high blood pressure, high cholesterol, etc., may be essential to the development of DR. In this way, single nucleotide polymorphisms (SNPs) associated with other comorbidities could increase the likelihood of retinal bleeding in diabetic populations. The identification of these SNPs would offer valuable insight into the development of a genetically-driven prevention plan for diabetic retinopathy.