title
stringlengths 21
275
| URL
stringlengths 54
55
| names
stringlengths 8
395
| date
stringlengths 10
10
| abstract
stringlengths 154
2.13k
⌀ |
|---|---|---|---|---|
Exploring the connections between alcohol and chronic traumatic encephalopathy | https://www.jsr.org/hs/index.php/path/article/view/3373 | Arnav Srivastava; Coach Jo | 11-30-2022 | In the world of hard-hitting sports, a deadly consequence has come up in the past years: chronic traumatic encephalopathy (commonly known as CTE). This brain condition has long eluded scientists attempting to find a treatment and the effects of it are some of the worst we have ever seen. Moreover, the appearance of the disease has only increased in occurrence over recent years. Football, hockey, and other physical sports continue to get more and more popular across the world and if treatment for CTE is not found promptly, the effect of the dangerous sports will be seen in the players’ brains like never before. CTE has claimed countless lives on the record and even more that have never quite been proven. However, though most believe the cause is the constant head trauma experienced by players, perhaps this mystery does not stop at just that. The specific causes of CTE and still not completely known, and this paper intends to answer that with at least one cause: alcohol. Alcohol has been a favorite among many players and its presence is undeniable in the sporting community. Its effects on the liver, kidney, and other organs are clear already, and perhaps after this research and more, its effects on the brain can become clearer as well. A connection between alcohol and CTE can be seen here in this research and this link can be built upon in efforts to create a treatment for the horrible disease, eventually hoping to render this issue nonexistent. |
Biocrest: A novel, organic and sustainable alternative to traditional thermoplastic-based packaging | https://www.jsr.org/hs/index.php/path/article/view/3517 | Shalav Kakati, Sriram Seshadri, Mithun Makam | 11-30-2022 | Plastic is handy as an industrial packaging material because it is mouldable, rigid yet flexible, durable, reusable, and cheaper than most alternatives, making it profitable to use. Although it has many advantages, its fair share of drawbacks, the most concerning being the amount of pollution it causes. Although plastics have been in use only since 1907, they have accumulated over time in astronomical quantities, destroying our environment. There are already some excellent sustainable packaging materials out on the market, but it still isn’t as mainstream as it needs to be to put a real dent into plastic pollution. Unless we can find ways to modify plastic to lessen its environmental impact, we must find sustainable packaging alternatives. Our project presents a novel solution to the pervasive plastic problem and sustainably looks into the issue. Our review showcases how materials such as seed extracts and natural binder extracts can be used to develop material that can serve as a potential replacement for the thermoplastic used presently. |
Modeling piezoelectricity’s impact on environmental parameters with real-life applications | https://www.jsr.org/hs/index.php/path/article/view/3609 | Sriram Seshadri, Armaan Sayyad | 11-30-2022 | With a rapid increase in the global human population in recent years, the Earth is in dire need of alternative energy sources. The objective of this paper is to assess the feasibility of implementing piezoelectricity as a primary source of renewable energy. Specifically, this paper looks at its consequent impact if introduced in 3 fundamental areas of implementation: bus tires, train tracks and railway stations. Each of these areas provide input elements at scale to generate electricity and are simple to implement, maintain and measure through government support. This paper limits the data to the city of Cairo, Egypt. Being low cost as well, the three areas come close to an ideal situation from an economic standpoint. Predictive algorithms and existing data are used to evaluate the consequent change in global green-house emissions and other environmental parameters, had piezoelectricity been previously implemented. The results of the equations show that there would be improved environmental conditions - thus, a net positive impact - that switching to piezoelectricity would have had on the atmosphere and environment. The predictions stay true, provided that the efficiency of the piezoelectric crystal remains constant- an outcome which serves to boost output and lower greenhouse emissions |
A Comprehensive Modeling of Bioenhancers Docked to Transport Proteins to Enhance Bioavailability | https://www.jsr.org/hs/index.php/path/article/view/3727 | Via Das, Destiny Pinto, Tejasvi Hariharan, Tanusree Banerjee, Riya Ubale, Avi Uppalapati; Gayathri Renganathan | 11-30-2022 | With pharmaceutical availability being a pertinent issue in modern medicine, the ability of bioenhancers to increase the bioavailability of a drug, thereby reducing the required dosage, can be critical for reducing treatment costs. Flavonoids, one form of bioenhancers, are metabolites that increase the availability through inhibition of key proteins in gut epithelial cells and transport proteins. Bioenhancers have the potential to inhibit proteins that limit absorption, thus increasing the amount of a target drug that can enter systemic circulation, increasing bioavailability. P-glycoprotein (P-gp) is one of the membrane transport proteins whose function is to transport drugs in and out of the cell. Human serum albumin (HSA), the most abundant protein in the human plasma, is a protein that serves to transport several signals and other compounds throughout the circulatory system. This study assessed the binding of various bioenhancers (piperine, quercetin, capsaicin, naringin, genistein, lysergol, sinomenine, tangeretin) to various forms of P-gp, HSA and ABC transporters to improve drug bioavailability. We hypothesized that the bioenhancers would bind to these transport proteins, thereby inhibiting them and increasing bioavailability.An examination of the geometric shape complementarity scores in PatchDock and the binding affinities (ΔG kcal/mol) from three other web servers (Webina, DockThor, CB-Dock) showed that naringin produces the most optimal binding scores overall. Given the promising optimal binding scores, the data provides critical insight into administering bioenhancers with drugs to improve bioavailability, as well as suggesting that naringin may be a valuable compound to conduct further tests in vitro and in vivo. |
A Exploratory data analysis to understand the causes of global warming and application of soft computing techniques to develop its forecasting model | https://www.jsr.org/hs/index.php/path/article/view/3117 | Aarush Mahajan; Reetu jain | 11-30-2022 | Global warming (GW) is one of the major effects of human activity where excessive use of fossil fuels as energy sources has led to an increase in the concentration of greenhouse gases (GHGs), such as CO2, CH4, and water vapour, in the atmosphere one of the main reason to increase the average surface temperature. This study analyzes the time-series data to come to a rational conclusion about the role of GW in increasing sea-water level, the reason for the increase in GHG and the correlation of GHG to GW. In this direction time-series analysis is carried out on four different datasets. The first and second dataset comprises global temperature anomalies data and the cumulative changes in seawater level for the world’s oceans since 1880. The third and fourth dataset comprises the records of concentration of GHGs in the atmosphere since 1st AD and the last 4 ice age years respectively. Finally, forecasting models are developed based on Holt’s and SARIMA techniques to predict the global temperature anomaly, the concentration of GHGs and their correlation with GW. The developed models showed 74.6%, 94.5% and 95.7% accuracy in predicting temperature anomaly, CO2, and CH4 concentration in the atmosphere respectively. The strength of the forecasting model is its ability to compute the critical values of the factors. Therefore, the forecasting models are applied to predict the year in which the critical values of the factors contributing to GW will be attained. |
Factors Contributing to Youth’s Exposure to Mental Health Misinformation on TikTok During the Covid-19 Pandemic | https://www.jsr.org/hs/index.php/path/article/view/3296 | Jimin Lee | 11-30-2022 | There is an increasing number of youth having access to smartphones and technology, especially throughout the COVID-19 pandemic (McClain, 2022). Social media, such as TikTok, grew exponentially during the pandemic alongside increased postings of mental health content. As the majority of TikTok users are young people, this paper examines the question: “what factors have contributed most to the increase in the use of potentially misleading online mental health information among youth during the COVID-19 pandemic?”. Reviewing previous research, this paper mainly applies descriptive and evaluation analysis to study the factors that prompted youth to seek mental health information on TikTok. This paper argues that barriers to mental health care and isolation during the COVID-19 pandemic have led young people to turn to TikTok for mental health information, in turn leading to youth to be more exposed to misinformation. This paper calls for improvements in mental health care accessibility for youth and identifies the root causes of increased misinformation exposure on TikTok. The increased mental health discussions that took place through TikTok should continue but it is imperative to explore ways to prevent information from overflowing and being unreliable for the users. |
Shoulder Dysfunction in High School Tennis Players - an exploratory study | https://www.jsr.org/hs/index.php/path/article/view/3393 | Sandheep Ranganathan; Coach Jo | 11-30-2022 | Previous studies have investigated sports activity related shoulder dysfunction, such as scapular dyskinesis and glenohumeral internal rotation deficit (GIRD), mainly in high-level tennis players. The prevalence of these dysfunctions in comparatively low to moderate level tennis players, such as those at the high school level is poorly understood. The purpose of this study was to explore the prevalence of scapular dyskinesis and GIRD at the high school level and identify some of the factors that makes a high school tennis player more susceptible to developing shoulder dysfunction. A survey related to sports-related shoulder dysfunction was developed in collaboration with physical therapists and was completed by twenty-seven high school level tennis players. The results show that players who have more years of experience, played tennis more often on a weekly basis, and were on the varsity team are more likely to develop shoulder pain and dysfunction. The average number of symptoms increased with years of playing experience and a higher frequency of playing tennis every week, with more than 40% of players on the varsity team reporting a decrease in the velocity, control, and arm motion during their serve. While male players reported more symptoms related to pain, decreased performance and strength, female players reported almost three times more occurrence of lower shoulders compared to male players. Players who consistently did workouts for shoulder and back muscles were less likely to develop shoulder pain and dysfunction, regardless of their level of experience and gender. |
The Effect of Talking to Plants in Order to Improve Emotions and Reduce Stress in High School Students | https://www.jsr.org/hs/index.php/path/article/view/3472 | Amelia Gandhi | 11-30-2022 | This study was designed to see if students could improve their emotional state and/or reduce stress by talking to a plant. One of the major benefits of using plants to study feelings or stress is that implementation of the plant does not need to be standardized in order to measure mood or emotional feeling. Plants make excellent listeners because they do not talk back. They allow a person to express their feelings and emotions without interruption or reciprocal feedback. Volunteer high school students, 9th through 12th grade, were given a plant and asked to document their pre-discussion feelings, talk to the plant for 15 minutes about anything they wanted, then document their post-discussion feelings. The study was conducted for 4 weeks through self-guided surveys. The analysis showed a decrease in stress and nervousness across all grade-levels, with an increase in relaxation. |
The Phenomena of Using Adjectives as Verbs and Using Nouns as Adjectives in Chinese | https://www.jsr.org/hs/index.php/path/article/view/3571 | Puyuan Ye; Deniz Satik | 11-30-2022 | In Chinese, adjectives are sometimes used as verbs and nouns are sometimes used as adjectives, especially online. Usually, although the word occupies only one part of speech, it may be used as another part of speech, which may violate the syntactical rules but make sense to most people. In this paper, various examples of these two phenomena will be closely examined, tests are implemented to verify the original part of speech of the exact word that is used as a different part of speech, and many observations are made. |
Biocrest: A novel, organic and sustainable alternative to traditional thermoplastic-based packaging | https://www.jsr.org/hs/index.php/path/article/view/3517 | Shalav Kakati, Sriram Seshadri, Mithun Makam | 11-30-2022 | Plastic is handy as an industrial packaging material because it is mouldable, rigid yet flexible, durable, reusable, and cheaper than most alternatives, making it profitable to use. Although it has many advantages, its fair share of drawbacks, the most concerning being the amount of pollution it causes. Although plastics have been in use only since 1907, they have accumulated over time in astronomical quantities, destroying our environment. There are already some excellent sustainable packaging materials out on the market, but it still isn’t as mainstream as it needs to be to put a real dent into plastic pollution. Unless we can find ways to modify plastic to lessen its environmental impact, we must find sustainable packaging alternatives. Our project presents a novel solution to the pervasive plastic problem and sustainably looks into the issue. Our review showcases how materials such as seed extracts and natural binder extracts can be used to develop material that can serve as a potential replacement for the thermoplastic used presently. |
Modeling piezoelectricity’s impact on environmental parameters with real-life applications | https://www.jsr.org/hs/index.php/path/article/view/3609 | Sriram Seshadri, Armaan Sayyad | 11-30-2022 | With a rapid increase in the global human population in recent years, the Earth is in dire need of alternative energy sources. The objective of this paper is to assess the feasibility of implementing piezoelectricity as a primary source of renewable energy. Specifically, this paper looks at its consequent impact if introduced in 3 fundamental areas of implementation: bus tires, train tracks and railway stations. Each of these areas provide input elements at scale to generate electricity and are simple to implement, maintain and measure through government support. This paper limits the data to the city of Cairo, Egypt. Being low cost as well, the three areas come close to an ideal situation from an economic standpoint. Predictive algorithms and existing data are used to evaluate the consequent change in global green-house emissions and other environmental parameters, had piezoelectricity been previously implemented. The results of the equations show that there would be improved environmental conditions - thus, a net positive impact - that switching to piezoelectricity would have had on the atmosphere and environment. The predictions stay true, provided that the efficiency of the piezoelectric crystal remains constant- an outcome which serves to boost output and lower greenhouse emissions |
A Comprehensive Modeling of Bioenhancers Docked to Transport Proteins to Enhance Bioavailability | https://www.jsr.org/hs/index.php/path/article/view/3727 | Via Das, Destiny Pinto, Tejasvi Hariharan, Tanusree Banerjee, Riya Ubale, Avi Uppalapati; Gayathri Renganathan | 11-30-2022 | With pharmaceutical availability being a pertinent issue in modern medicine, the ability of bioenhancers to increase the bioavailability of a drug, thereby reducing the required dosage, can be critical for reducing treatment costs. Flavonoids, one form of bioenhancers, are metabolites that increase the availability through inhibition of key proteins in gut epithelial cells and transport proteins. Bioenhancers have the potential to inhibit proteins that limit absorption, thus increasing the amount of a target drug that can enter systemic circulation, increasing bioavailability. P-glycoprotein (P-gp) is one of the membrane transport proteins whose function is to transport drugs in and out of the cell. Human serum albumin (HSA), the most abundant protein in the human plasma, is a protein that serves to transport several signals and other compounds throughout the circulatory system. This study assessed the binding of various bioenhancers (piperine, quercetin, capsaicin, naringin, genistein, lysergol, sinomenine, tangeretin) to various forms of P-gp, HSA and ABC transporters to improve drug bioavailability. We hypothesized that the bioenhancers would bind to these transport proteins, thereby inhibiting them and increasing bioavailability.An examination of the geometric shape complementarity scores in PatchDock and the binding affinities (ΔG kcal/mol) from three other web servers (Webina, DockThor, CB-Dock) showed that naringin produces the most optimal binding scores overall. Given the promising optimal binding scores, the data provides critical insight into administering bioenhancers with drugs to improve bioavailability, as well as suggesting that naringin may be a valuable compound to conduct further tests in vitro and in vivo. |
A Exploratory data analysis to understand the causes of global warming and application of soft computing techniques to develop its forecasting model | https://www.jsr.org/hs/index.php/path/article/view/3117 | Aarush Mahajan; Reetu jain | 11-30-2022 | Global warming (GW) is one of the major effects of human activity where excessive use of fossil fuels as energy sources has led to an increase in the concentration of greenhouse gases (GHGs), such as CO2, CH4, and water vapour, in the atmosphere one of the main reason to increase the average surface temperature. This study analyzes the time-series data to come to a rational conclusion about the role of GW in increasing sea-water level, the reason for the increase in GHG and the correlation of GHG to GW. In this direction time-series analysis is carried out on four different datasets. The first and second dataset comprises global temperature anomalies data and the cumulative changes in seawater level for the world’s oceans since 1880. The third and fourth dataset comprises the records of concentration of GHGs in the atmosphere since 1st AD and the last 4 ice age years respectively. Finally, forecasting models are developed based on Holt’s and SARIMA techniques to predict the global temperature anomaly, the concentration of GHGs and their correlation with GW. The developed models showed 74.6%, 94.5% and 95.7% accuracy in predicting temperature anomaly, CO2, and CH4 concentration in the atmosphere respectively. The strength of the forecasting model is its ability to compute the critical values of the factors. Therefore, the forecasting models are applied to predict the year in which the critical values of the factors contributing to GW will be attained. |
Factors Contributing to Youth’s Exposure to Mental Health Misinformation on TikTok During the Covid-19 Pandemic | https://www.jsr.org/hs/index.php/path/article/view/3296 | Jimin Lee | 11-30-2022 | There is an increasing number of youth having access to smartphones and technology, especially throughout the COVID-19 pandemic (McClain, 2022). Social media, such as TikTok, grew exponentially during the pandemic alongside increased postings of mental health content. As the majority of TikTok users are young people, this paper examines the question: “what factors have contributed most to the increase in the use of potentially misleading online mental health information among youth during the COVID-19 pandemic?”. Reviewing previous research, this paper mainly applies descriptive and evaluation analysis to study the factors that prompted youth to seek mental health information on TikTok. This paper argues that barriers to mental health care and isolation during the COVID-19 pandemic have led young people to turn to TikTok for mental health information, in turn leading to youth to be more exposed to misinformation. This paper calls for improvements in mental health care accessibility for youth and identifies the root causes of increased misinformation exposure on TikTok. The increased mental health discussions that took place through TikTok should continue but it is imperative to explore ways to prevent information from overflowing and being unreliable for the users. |
Shoulder Dysfunction in High School Tennis Players - an exploratory study | https://www.jsr.org/hs/index.php/path/article/view/3393 | Sandheep Ranganathan; Coach Jo | 11-30-2022 | Previous studies have investigated sports activity related shoulder dysfunction, such as scapular dyskinesis and glenohumeral internal rotation deficit (GIRD), mainly in high-level tennis players. The prevalence of these dysfunctions in comparatively low to moderate level tennis players, such as those at the high school level is poorly understood. The purpose of this study was to explore the prevalence of scapular dyskinesis and GIRD at the high school level and identify some of the factors that makes a high school tennis player more susceptible to developing shoulder dysfunction. A survey related to sports-related shoulder dysfunction was developed in collaboration with physical therapists and was completed by twenty-seven high school level tennis players. The results show that players who have more years of experience, played tennis more often on a weekly basis, and were on the varsity team are more likely to develop shoulder pain and dysfunction. The average number of symptoms increased with years of playing experience and a higher frequency of playing tennis every week, with more than 40% of players on the varsity team reporting a decrease in the velocity, control, and arm motion during their serve. While male players reported more symptoms related to pain, decreased performance and strength, female players reported almost three times more occurrence of lower shoulders compared to male players. Players who consistently did workouts for shoulder and back muscles were less likely to develop shoulder pain and dysfunction, regardless of their level of experience and gender. |
The Effect of Talking to Plants in Order to Improve Emotions and Reduce Stress in High School Students | https://www.jsr.org/hs/index.php/path/article/view/3472 | Amelia Gandhi | 11-30-2022 | This study was designed to see if students could improve their emotional state and/or reduce stress by talking to a plant. One of the major benefits of using plants to study feelings or stress is that implementation of the plant does not need to be standardized in order to measure mood or emotional feeling. Plants make excellent listeners because they do not talk back. They allow a person to express their feelings and emotions without interruption or reciprocal feedback. Volunteer high school students, 9th through 12th grade, were given a plant and asked to document their pre-discussion feelings, talk to the plant for 15 minutes about anything they wanted, then document their post-discussion feelings. The study was conducted for 4 weeks through self-guided surveys. The analysis showed a decrease in stress and nervousness across all grade-levels, with an increase in relaxation. |
The Phenomena of Using Adjectives as Verbs and Using Nouns as Adjectives in Chinese | https://www.jsr.org/hs/index.php/path/article/view/3571 | Puyuan Ye; Deniz Satik | 11-30-2022 | In Chinese, adjectives are sometimes used as verbs and nouns are sometimes used as adjectives, especially online. Usually, although the word occupies only one part of speech, it may be used as another part of speech, which may violate the syntactical rules but make sense to most people. In this paper, various examples of these two phenomena will be closely examined, tests are implemented to verify the original part of speech of the exact word that is used as a different part of speech, and many observations are made. |
Digital Marketing in the Makeup Industry - Attraction and Retention of Generation Z | https://www.jsr.org/hs/index.php/path/article/view/3204 | Meghna Sahu; Kyle Karnuta | 11-30-2022 | This study investigates the changing nature of marketing, especially by the makeup industry, as Generation Z increasingly employs its growing purchasing power. What do attraction and retention marketing tactics look like as brands seek to win Generation Z consumers? The research investigated the significance of Generation Z’s purchasing power, and found that younger consumers value personal connections, authenticity, and engaging with brands over digital platforms. Specifically in the makeup industry, social media, beauty influencer partnerships, and storytelling are employed to attract Generation Z. Brand communities, satisfying consumers, and loyalty programs are used to retain the younger consumers. A case study of the makeup brand Glossier illustrates how a digitally native brand uses digital tactics to win over the tech-savvy generation. |
Analysis of PyroTamer’s Effect on Current Wildfire Situations | https://www.jsr.org/hs/index.php/path/article/view/3434 | Jaein Kim, Jermaine Lei, Matthew Lee, Daniel Cha | 11-30-2022 | Wildfires have been devastating Earth’s lands since its birth, but only recently have the fires become more rampant and increasing in numbers due to poor human decisions and excruciatingly worsening climate crisis. Our protectors, the firefighters, are constantly on an uphill battle to fight the numerous wildfires surrounding them during fire season, let alone risk their precious lives. To make matters worse, critical amounts of time are wasted as firefighters are still using old technology from decades ago like hand radios as they have been proven for a long time to be reliable. Although the reliability of hand radios is strong, they have extremely limited range and make communication onerous as verbal communication is not that efficient and prone to errors. PyroTamer is developing an application that focuses on reliability and efficiency to ensure firefighters are able to effectively communicate quickly in order to put out fires faster. |
The Effectiveness of Counterconditioning and Extinction in Extinguishing Learning | https://www.jsr.org/hs/index.php/path/article/view/3605 | Pradnya Rajalakshmi | 11-30-2022 | Counterconditioning and extinction are two different forms of learning that inhibit the expression of a learned unwanted behavior by either eliminating the behavior (extinction) or replacing it altogether with a wanted behavior (counterconditioning). While counterconditioning has been shown to be more effective than extinction in some cases, both of these techniques can be vulnerable to the relapse of an unwanted behavior. Separate work has also shown that learning to inhibit unwanted behavior can be more effective if done across multiple different contexts rather than a single experimental context. A systematic comparison of extinction and counterconditioning across single and multiple contexts is, however, lacking. This research paper aims to identify the effectiveness of each of these learning techniques across a single context as well as multiple contexts to identify which is the most suitable for removing unwanted learned behavior. A two-by-two between-subjects design was used wherein four groups completed a learning task in either single or multiple contexts and with either extinction or counterconditioning. It was hypothesized that the counterconditioning group in multiple contexts should turn out to be more effective in extinguishing learning. The results did not support this hypothesis and instead suggest that these methods were all similarly effective at reducing unwanted behaviors. |
Supply Chain Disruption Factors and Influences in Industrial Manufacturing and Technology Industries | https://www.jsr.org/hs/index.php/path/article/view/3725 | Adrish Kar; Joshua Eaton | 11-30-2022 | Objective: This paper investigates the main supply chain disruption factors and influences in a set of industrial manufacturing and technology industries as well as the relationships that exist between them. Background: Disruption factors are obstacles that impede a manufacturing company filling customer orders and are treated as the main causal factors in this study. The number of unfilled orders of an industry is any obligation to provide a good or service that has not been met and is used as the main response variable in this research. Methods: Principal component analysis and exploratory factor analysis are both variable reduction techniques that were utilized together in order to isolate latent constructs behind disruption factors and identify significant disruption factors contributing to the unfilled orders for each industry. Results: Across a majority of manufacturing industries, insufficient supply of materials, equipment limitations, logistics/transportation constraints, and storage limitations were observed to be amplified significantly as disruption factors by the pandemic. Conclusions: This research reveals the disruption factors that were exacerbated by the pandemic in a set of certain industrial manufacturing and technology industries that were not extensively examined by previous research and strongly corroborate existing literature on the general challenges imposed by the pandemic on supply chain networks. This work also provides a future research objective of improving supply chain resilience. |
How Changes in Individual Spending Habits Under COVID-19 Impact SMEs in Sports Industry in Guangzhou | https://www.jsr.org/hs/index.php/path/article/view/3390 | Zhengnan Liu; Cody Dodd | 11-30-2022 | Starting from 2020, life for everyone has shifted due to the unprecedented pandemic (Coronavirus, COVID-19), and so do SMEs (Small and Medium Enterprises). The purpose of the present study is to examine the relationship in what COVID impacts SMEs in Sport industry and whether structural changes have occurred for those firms due to the transformation of customers' spending habits. The study mainly focuses on a regional scale in Guangzhou, one of the cities in Guangdong Province, China. Five Interviews had conducted via phone call or personal meeting about the current situation of sport-related firms and their experiences about their past two years. Through those interviews, it can be concluded that SMEs in the Sports Industry have been devastating in the past two years, and most of them have to make structural changes to the structure of the firm to keep the firm functioning under current circumstances. Through past literatures, a social phenomenon has shown that people started to change their spending habits after COVID through reasons of anxiety and higher tension in their financial situation. |
The Role of American NGOs in International Development | https://www.jsr.org/hs/index.php/path/article/view/3462 | Emma Crasnitchi; Svetlana Crasnitchi | 11-30-2022 | In this paper, I will examine the role of American nonprofit NGOs - specifically D.C. located CNFA (Cultivating New Frontiers in Agriculture), Inc. - on the long-run input into agricultural growth and sustainability of third-world countries. Such NPOs render production successful. I surveyed various employees from CNFA to understand the commercial and humanitarian principles behind international development and collaboration with foreign agribusiness companies. I will describe the methods of helping food security, program development, and financing to reduce the cleavage of modern-day society. |
Is Gene Therapy a Band-aid or a Cure? | https://www.jsr.org/hs/index.php/path/article/view/3566 | Sanjitha Sadhneni; Rajagopal Appavu, Coach Jo | 11-30-2022 | The goal of innovation in treating diseases is to provide a long-lasting solution. For rare diseases such as sickle cell disease (SCD) and hemophilia, this can mean reducing the number of complications or even increasing life expectancy. One of the innovations that is having increasing attention is gene therapy. Gene therapy entails substituting flawed genes with normal ones by utilizing vectors derived from the outer shells of viruses, retaining the inherent properties of being able to target and enter specific cells. The modified gene is placed within this shell. Gene therapy can target germline or somatic cells - the latter being the most commonly used. The process for gene therapy is in-vivo or ex-vivo, depending on whether the transduction of the cells happens within or outside the body. Clinical trials in gene therapy have progressed tremendously, and even a few have reached approval by the FDA - but none yet for SCD or hemophilia. For both these diseases, the current treatments provide symptomatic relief but not long-lasting benefits. Currently, there are several gene therapy clinical trials ongoing for both conditions. This paper focuses on published results of sickle cell diseases and hemophilia and examines whether they are pointing towards short-term benefits or whether the effect is long-term. |
Public Healthcare Policies for the Elderly in the United States: Suggestions from a Comparison between South Korea and the United States | https://www.jsr.org/hs/index.php/path/article/view/3650 | Jooyoung Choi; Deepon Bhaumik | 11-30-2022 | As the aging population percentage rapidly increases across the world, leading to an increase in the necessity of long-term care, it is crucial for the government of the United States to implement changes to create more sustainable, and sufficient programs. This policy brief intends to identify problems in the current United States long-term health care system, and will try to find a possible suggestion to impede the gaps in the system. To bring a direct comparison and possible solutions, this brief will also investigate South Korea, a country with similar aging demographics and economic development as the United States. South Korea ranks 10th in GDP, and the elderly population comprise of 17.5% of the entire population (compared to 16% for the U.S). The South Korean examples of the policy suggest a few practical solutions to the issue, such as an increase in basing long term care eligibility on health status of an individual, rather than an emphasis on income eligibility. Targeted policies such as South Korea’s Alzheimer detection program should be more widely utilized for most chronic diseases in the United States. These types of prevention services will be able to help decrease the total amount of funding spent on these patients. Learning from South Korea’s policies can provide the U.S. with services that can adequately address the elderly population’s need for assistance and care. |
Exploring Cryptocurrency: How do individual behaviors in the financial world affect the potential of economic bubbles? | https://www.jsr.org/hs/index.php/path/article/view/3758 | Ren Leong; Stefano Benigni | 11-30-2022 | Cryptocurrency has made waves recently with its absurd increase in prices and volume. In this paper, I sought to understand, fundamentally, what factors could have helped its rise to the top. On the other hand, large ascents like this in the past have shown to be fatal, such as the housing market bubble of 2008. It struck me that cryptocurrency seemed to be heading down a similar path, especially with its unpredictable volatility and lack of practical usage in daily life. I explored some of the behavioral trends that are prevalent in finance, and used them to understand the 2008 bubble. I then further explored cryptocurrency behavior to draw comparisons, which were not lacking. By understanding what was behind cryptocurrency’s incredible rise and what behaviors and trends may factor into its volume, I was able to come to the conclusion that cryptocurrency is an asset class that treads dangerously along the lines of forming bubbles. |
Military Conscription in the 21st Century: Obsolescence or Relevance? | https://www.jsr.org/hs/index.php/path/article/view/3422 | Glenn Lee; Ja Kyung Han | 11-30-2022 | Post Russian invasion of Ukraine, questions about conscription have come into focus, prompting questions about military readiness and the value of such a policy. In analyzing the policy, international relations theories can act as a useful framework, and help elucidate conflict dynamics. In particular, Realism and Liberalism have contrasting depictions of the world, with the former characterizing it as an anarchic system in which states compete for power and security and the latter as a system in which states allay tensions through cooperation. This research draws upon these theories as it uses hypothesis testing—t-tests, ANOVA, and chi-squared statistics—to investigate the different attributes of countries as they relate to conscription policies. A wide range of variables were chosen including military expenditure, imports and exports, the Human Development Index, and the EIU Democracy Index in order to test statistically significant differences through the aforementioned tools. Overall, this research finds that both realist and liberal theories have explanatory power and provide insight into how desire for hard and soft power may impact decisions to enact and maintain conscription policies. Data and graphs were interpreted alongside such concepts in order to reach this conclusion. |
Sustaining Green Efforts: How Tech Parks in Bangalore Address Environmental Crises | https://www.jsr.org/hs/index.php/path/article/view/3594 | Arshia Mehra; Courtney | 11-30-2022 | Bangalore, the capital of Karnataka is known as the Silicon Valley of India for the high number of ICT(Information and Communications Technology) companies and tech parks it has. The ICT industry has providedmillions of people with jobs in this city and has resulted in a population explosion, which has over time led toBangalore facing infrastructural crises along with strain on its natural resources. This paper discusses howsustainable architecture can set up a model for sustainability in perpetuity in Bangalore’s tech parks in the 21 stcentury. |
International Law and The Responsibility to Protect | https://www.jsr.org/hs/index.php/path/article/view/2605 | Sophia Sultan; Christopher Michael Garrity | 08-31-2022 | In the UN, there is a doctrine called the Responsibility to Protect that allows the blue helmets from the UN to intervene in a country if a country violates international human rights laws. This doctrine was created to aid refugees and the international community when their own countries abuse power and, as a result, them. My question was what determines when the UN decides to intervene under R2P. My hypotheses theorized that GDP, nuclear weapons, or race demographics must influence the verdict of when the UN intervenes. I thought that countries that had a higher GDP probably had a lower chance of being intervened even if they had committed humanitarian crimes. I also figured that any country with nukes would have high unlikeliness to be intervened upon, and finally, I hypothesized that countries with a white majority population were less likely to be intervened in. I found that a combination of portions from all three hypotheses was ultimately correct. Of the countries I tested most countries that had been intervened in under R2P were poorer than countries that had not been protected by the UN despite being guilty of similar injustices. My second hypothesis was arguably arbitrary since no country that owns a nuke has been intervened in by the UN. Lastly, the countries I tested for their race demographics were mainly non-white countries, and, therefore, the countries that had and had not been intervened in under R2P were isolated from the race debate. |
Analysis of Anxiety and Depression in the Context of Commercially-Available Energy Beverage Consumption | https://www.jsr.org/hs/index.php/path/article/view/2681 | Nathan Ming; Chloe Cavanaugh | 08-31-2022 | Energy drinks are common in the diets of teenagers. Despite the increase in consumption in American teenagers, little has been done to study its effects on the anxiety and depressive behaviors of teenagers. 25 participants were selected including a majority of Asians and Caucasians between the ages of 12 to 22. The participants filled out a survey that recorded a baseline for a week, and then drank increasing dosages of energy drinks the following week while continuing to fill out a survey. They filled out a survey that was designed with SIG E CAPS indicators on each day, and the results were compared using a student’s t-test. The results were not statistically significant, but this supports that the caffeine limit set by the Food and Drug Administration does indeed prevent negative effects of caffeine on adolescents. One participant, with a pre-existing psychiatric condition, withdrew from the study after his markers of anxiety were significantly higher in the week that he took the energy drinks. While the study was limited in both scale and dosage, it did fall in alignment with the body of literature that preceded it. To formulate a statistically significant study with results that have a higher confidence level, the dosage of caffeine and the number of participants who consume it would need to be increased. The study, while not being statistically significant, reinforced the pediatric limit of caffeine and opened the door to further studies that involve a higher dosage or more participants. |
Prediction of Chronic Graft vs. Host Disease Using Machine Learning | https://www.jsr.org/hs/index.php/path/article/view/2910 | Sanay Bordia; Professor Ramezani | 08-31-2022 | This paper attempts to predict the onset of chronic Graft vs. Host Disease (GVHD) in children with blood cancers who have received a bone marrow or stem cell transplant using machine learning models. It analyzes and compares the results of three different models in terms of how accurate they each are in predicting chronic GVHD. These models are Logistic Regression, J48 algorithm using decision trees, and Multilayer Perceptron. The models are formed using a dataset containing 36 attributes, excluding chronic GVHD itself. Through data preprocessing and analysis in Weka, these 36 attributes are narrowed down for each model to figure out which combination of attributes leads to the best predictive accuracy. The study uses 10-fold cross validation for each model and uses the Receiver Operating Characteristic (ROC) Area as a measure of the accuracy for each model. The study found that Multilayer Perceptron is the best predictor of chronic GVHD. In comparison, Logistic Regression was the worst predictor of chronic GVHD. The J48 algorithm used the least number of attributes to make its prediction. |
Examining the predictive power of moving averages in the stock market | https://www.jsr.org/hs/index.php/path/article/view/3382 | Arjun Chaddha; Shilpa Yadav | 08-31-2022 | Moving averages are common technical analysis tools which investors use to generate buy and sell calls in the stock market. The purpose of this research paper is to analyse whether common moving average techniques can reliably predict stock market behaviour. Using hypothesis testing, this paper tests whether the percentage return yielded by using moving average combinations to trade stocks in the S&P 500 index was significantly higher than a) the percentage return yielded by randomly buying and selling the stocks and b) the market percentage return. The tests were conducted for the S&P 500 stocks in four different time frames to understand the performance of moving averages during different stock market trends (uptrend, sideways trend, downtrend). Moreover, the performance of three different buying and selling techniques which use moving averages were compared. The results of the paper indicate that an investor should not use moving averages to trade stocks owing to their limited predictive power. There were only a few moving average combinations which were significantly better than randomly buying and selling. Even those few combinations could not yield higher percentage returns than the market percentage return. |
Deep Neural Network Classifier for Alzheimer’s Disease Omics biomarker prediction for early and quantitative Alzheimer's Disease diagnosis | https://www.jsr.org/hs/index.php/path/article/view/3553 | Jason Lin; Dr. Hayan Lee, Dr. Michael Snyder | 08-31-2022 | Alzheimer's disease (AD) is a neurodegenerative disease characterized by dementia and, eventually, a loss of cognitive abilities. Two histopathological features are associated with AD, neurofibrillary tangles, and amyloid-beta plaque. Both contribute to neuron cell death, neuron dysfunction, and AD pathogenesis. Current methods to diagnose AD remain reliant on symptomatic diagnosis with interviews that can be time-consuming, costly, and inaccurate. Alternative methods such as brain imaging are expensive and require extensive laboratory setup for accurate results. Thus molecular-level quantitative approaches are necessary. Omics datasets and machine learning technology advancements have opened new avenues to diagnose AD. This paper proposes using statistical methods such as principal component analysis, t-distributed stochastic neighbor embedding, and Kolmogorov-Smirnov test combined with Benjamini-Hochberg correction through feature selection and dimensionality reduction to isolate significant features associated with AD. Furthermore, we developed machine learning models based on logistic regression, random forest classifier, and deep neural network (DNN) classifier to predict AD diagnosis. Eight unique genes (TGM2, NKIRAS1, SYK, GABARAPL2, ABCC12, NDEL1, TEP1) were identified as significant biomarkers of AD and confirmed previous works identifying prognoses' roles in AD. After extensive hyperparameter tuning, the DNN model showed the best prediction performance for AD diagnosis among the three machine learning algorithms. The DNN model and preprocessed dataset demonstrated a 5-fold cross-validation accuracy of 0.823 and AUC-ROC of 0.940. Its code is publicly available at https://www.kaggle.com/neobrando/ml-dnn. |
A Study of the Endowment Effect in Phase II and III of the EU Emissions Trading System | https://www.jsr.org/hs/index.php/path/article/view/2761 | Sophia Qin; Edoardo Gallo | 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. |
Prohibition and Suffrage During World War I: The War’s Dual Impact | https://www.jsr.org/hs/index.php/path/article/view/2967 | Jason Fu; Charles Argon | 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 | https://www.jsr.org/hs/index.php/path/article/view/3330 | Daniel Ha; Elliot Ji | 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. |
Molecular Mechanisms of Cancer Metabolism and Their Cellular Cycles | https://www.jsr.org/hs/index.php/path/article/view/3418 | Harshita Ganga; Dr. Raj Appavu | 08-31-2022 | Cancer is a prevalent disease, with 1,752,735 new cases reported to the CDC in 2019. 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 | https://www.jsr.org/hs/index.php/path/article/view/3672 | Sidhya Ganesh; Professor Ramachandran | 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 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 | https://www.jsr.org/hs/index.php/path/article/view/3830 | Maanya Singh | 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 cottage and F&B industry not 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. 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&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. |
The Artificial Synthesis of Raphide | https://www.jsr.org/hs/index.php/path/article/view/2896 | Shoki Matsushima; Yuko Morimoto | 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 | https://www.jsr.org/hs/index.php/path/article/view/2963 | Aditya Jain; Allison Hussenet | 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) | https://www.jsr.org/hs/index.php/path/article/view/2659 | Lorenzo Pulmano; Leya Joykutty, Dr. Juliana Carvalho De Arruda Caulkins | 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. Intensity forecasting is one of the most difficult aspects of TC analysis forecasting, with RI prediction being one of the most challenging issues. Predicting intensity and RI is critical for emergency responses, including evacuation and disaster prevention. Deep learning (DL) and its application in TC analysis holds much potential. Morphed Integrated Microwave Imagery at the Cooperative Institute for Meteorological Satellite Studies (MIMIC) is a product that synthesizes “morphed” images of TCs. MIMIC-TC is a product that uses 85-92 GHz microwave imagery to create the images. 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). Six members comprise PRIME, split into three 10 and 20 epoch models. Each model has either 2, 3, or 4 convolutional layers. 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. After running the Ensemble on all available storms from 2019 and 2020, it appeared all models were overfit, and subsequently gave inaccurate classifications. 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%. |
Effect of Taurine on the Proliferation of Leishmania tarentolae Cells in Culture | https://www.jsr.org/hs/index.php/path/article/view/3014 | Srihas Rao | 08-31-2022 | null |
Electric Potential Analysis of Contaminated Lands in Idaho for Utility-scale Solar Energy | https://www.jsr.org/hs/index.php/path/article/view/3368 | Cindy Su; Erin Stutzman | 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 | https://www.jsr.org/hs/index.php/path/article/view/3726 | Samirakhon Makhkamjonova; Rebecca Totton | 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 | https://www.jsr.org/hs/index.php/path/article/view/3951 | Rohan Phanse | 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 | https://www.jsr.org/hs/index.php/path/article/view/2690 | Ure Nwokoji; Dr. Sullivan | 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 | https://www.jsr.org/hs/index.php/path/article/view/2951 | Ishani Das; Mr. | 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. Utilizing classification models in deep learning, an advanced subfield of machine learning based on neural networks, offers 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 | https://www.jsr.org/hs/index.php/path/article/view/3110 | bai bairuiyang | 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 | https://www.jsr.org/hs/index.php/path/article/view/2654 | Oleksii Babaskin; Mr. Babaskin | 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 | https://www.jsr.org/hs/index.php/path/article/view/2857 | Amy Park | 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 | https://www.jsr.org/hs/index.php/path/article/view/2989 | Aarush Kachhawa; Jeremy Hitt | 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. |
Treating Dilated Cardiomyopathy with Methylene Blue Using the Drosophila melanogaster Heart Model | https://www.jsr.org/hs/index.php/path/article/view/3361 | Tiffany Zhang, Aiden Pan; Nicole Spinelli | 08-31-2022 | Dilated cardiomyopathy (DCM), the most common cardiomyopathy, is characterized by ventricular dilation and impaired heart contractility. Past studies found that the inhibition of the ubiquitin-proteasome system (UPS), a crucial protein degradation system that removes dysfunctional proteins, plays a key role in the pathogenesis of DCM. Since treatments for DCM only aim at alleviating heart failure symptoms, a new therapeutic was sought. Methylene blue (MB) was selected because of its cardioprotective properties and ability to increase proteasome activity, potentially allowing it to revert the impact of an impaired UPS. The Drosophila melanogaster strain wupA, which presents DCM symptoms, was used and treated with MB (30 μM). The flies’ lifespans and negative geotaxis were assessed, and dissections were conducted to analyze heart rates (HR), heart diameters, and fractional shortening (FS) with ImageJ. The log-rank test and t-tests were used to analyze statistical significance. Results showed that DCM increased the heart diameters (p<0.01) and decreased the HR (p<0.05), FS (p<0.01), and negative geotaxis (p<0.01). MB fully restored the dilated heart diameters and impaired FS as there was no significant difference between control and experimental groups (p>0.05), exhibiting potential in treating DCM. However, MB didn't affect the impaired HR and negative geotaxis of flies with DCM. Hence, future studies should investigate supplemental treatments to fully restore those properties. |
Denoising Speech Signals with Hifi-Coulomb-GANs | https://www.jsr.org/hs/index.php/path/article/view/3501 | Anirudh Satheesh; Karthick Muthu-Manivannan | 08-31-2022 | Recorded speech signals often contain noise that affects the quality of the signal and reduces intelligibility. Several studies have used Generative Adversarial Networks (GANs) to remove noise artifacts and improve speech intelligibility. However, GANs can suffer from gradient vanishing or gradient explosion that can reduce their effectiveness in denoising. To mitigate gradient vanishing, we applied the CoulombGAN architecture to speech denoising using a model structure similar to Hifi-GAN, the current state of the art speech denoiser. We call this new model Hifi-CoGAN. We used a WaveNet generator to denoise signals, a PostNet for general cleanup, and a Multi-Resolution Discriminator to evaluate the signal quality relative to the clean signal. Our results show that Hifi-CoGAN was able to outperform Hifi-GAN in many of the narrowband signals (signals with a limited range of frequencies) in terms of the Short-Term Objective Intelligibility (STOI) and Perceptual Evaluation of Speech Quality (PESQ) metrics. However, the model did not perform as well as Hifi-GAN with wideband noise signals (signals with a wider range of frequencies) such as white noise, so future work must be done to improve the model for these noise signals. |
Machine Learning for Policy Guidance | https://www.jsr.org/hs/index.php/path/article/view/3597 | Justin Chae; Timothy Raines | 08-31-2022 | This paper leverages machine learning algorithms and techniques to create models that can assist in a country's policy guidance. The machine learning process used to conduct research is discussed with steps such as preprocessing, feature selection, model selection, and model interpretation. Specifically, using datasets from the CIA's World Factbook and the United Nations' Human Development Index (HDI), machine learning models are created that use select features from several counties (e.g., real gross domestic product (GDP), population, and area). Then, the models make predictions on the countries' HDI scores. Model interpretation methods are used to find the most important features in predicting a country's score. This paper argues that important features can be derived through machine learning and guide government policy relevant to human development. Supply-side policies are discussed based on the results from the machine learning models. The use of machine learning with other indexes is also explored. |
Ursula Le Guin’s Refutation of Gendered Traits in ‘The Left Hand of Darkness’ | https://www.jsr.org/hs/index.php/path/article/view/2686 | Avni Bansal | 08-31-2022 | In her novel ‘The Left Hand of Darkness’, Ursula Le Guin challenges the idea that certain human behaviors are fundamentally feminine or masculine, or that gendered traits exist. Firstly, she cleaves gender and personality apart by setting the novel on a planet of androgynes. Secondly, she creates complex characters that exhibit both stereotypically masculine and feminine behaviors. Thirdly, she presents an allegory that criticizes the idea of gendered traits as irrational and unnecessary. Finally, the novel is peppered with subversive images like that of a pregnant king, which are designed to challenge gender roles. |
The Move Towards Sustainable Aviation | https://www.jsr.org/hs/index.php/path/article/view/2923 | Ishaan Jain; Dr. Mritunjay Sharma | 08-31-2022 | This paper discusses how the aviation industry has been shaped by sustainability and examines how the aviation industry is progressing towards a more sustainable future. It compares the fuel usage of similar aircraft between aircraft manufacturers, Airbus and Boeing. The research also looks at how aircraft designs have evolved over time to reduce fuel usage and cut down carbon emissions. This can be seen in the fuel usage of aircraft. For example, if you compare the fuel usage of the Airbus A340 to the Airbus A350, the Airbus A350 uses significantly less fuel as it has improved engines and aerodynamics, allowing it to transport a similar number of passengers over a similar range. Airbus managed to make a better and far more fuel-efficient aircraft within 20 years. The aim of this research study was to examine how the commercial aviation industry can promote sustainable aviation in the future through a mixed-method approach. First, by using a quantitative approach, the impact of all the aircraft designs of Boeing and Airbus for commercial aircraft carrying 40 passengers and above on fuel usage and CO2 emissions would be compared, followed by a qualitative analysis explaining the varying fuel usage of similar aircraft and comparing which aircraft manufacturer holds the upper hand going into the future. |
Identifying the difference in bacterial composition and life history strategies between high versus low nutrient soils | https://www.jsr.org/hs/index.php/path/article/view/3271 | Felix Tuchscherer | 08-31-2022 | In this study, we aim to identify bacterial composition in soils treated with and without wood chips, as well as high levels and low levels of nitrogen. In order to do this, we used both culture dependent methods including plating, observing, and GenIII plates; as well as culture independent methods which include microbiome sequencing and EcoPlates. By doing this, we concluded that the bacterial communities differ between unamended and wood-chipped treated soils. Multiple differences were identified: rate of carbon consumption, bacterial diversity, rRNA gene copy number, and colony morphologies. Identifying the bacteria in wood-chipped soils will allow us to understand their effect on biogeochemical cycles, plant pathogens, and relationship with the trees (symbiotic/pathogen). Additionally, understanding the effect lower nitrogen levels have on the bacterial composition of soils can lead to reduction of synthetic fertilizer use, therefore lessening the environmental impact of nitrogen. |
Bioartificial Liver Manufacturing Methodologies in Comparison to Hepatogenesis | https://www.jsr.org/hs/index.php/path/article/view/3385 | Aanya Roy; Coach Jo | 08-31-2022 | End-stage organ failure is a major global issue, with the liver being the second-highest transplanted organ due to lifestyle choices or other conditions. In the field of biomedical engineering, artificial organ manufacturing has been a possible alternative to organ transplants by aiming to achieve less immune rejection, more efficient production, and higher accessibility. Of the biological manufacturing methods today, two up-and-coming technologies for the liver include 3D bioprinting and decellularized organ regeneration. By analyzing general stages of 3D bioprinting and decellularization for liver development and comparing it to the cellular and genetic stages of hepatic development in the embryo, dilemmas and successes in bioartificial manufacturing can be identified. Overall, neither artificial methodology can replicate the genetic influence or non-liver based influence of hepatogenesis. 3D bioprinting is similar to hepatogenesis in cell development and construction, but contains shortcomings in vascularization, which can be addressed using the vasculogenesis and angiogenesis processes in hepatic development. Decellularization allows for cell differentiation, although it is unable to instill natural cellular distribution and gradual ECM development. This may cause blockages for clinical use in the future. Both methods have potential for bioartificial liver development and clinical application, but 3D bioprinting technology is more aligned with the stages of hepatic development, which has proven to induce fewer errors in the physiological nature of the manufactured liver. In the future, modification and research must be conducted on the specific stages of these methodologies for either to create an operational bioartificial liver for clinical use. |
Does the U.S. Federal Reserve Consider the Credit Cycle Theory When Trying to Predict Recession? | https://www.jsr.org/hs/index.php/path/article/view/3565 | Tommy Heaton; Niklas Schmitz | 08-31-2022 | The credit cycle theory states that credit build-ups and their subsequent crashes are the common cause of recessions. If true, this theory could be used to both predict and prevent future recessions. However, it is unclear if policymakers do in fact take the theory into account when crafting monetary policy. Using the U.S. Federal Reserve (the Fed) as a case study, this paper seeks to answer if policymakers consider the credit cycle theory when attempting to predict recessions and determine optimal monetary policy. This paper analyzes Federal Open Market Committee minutes from meetings prior to four previous recessions: the Savings and Loan Crisis, the Dot-Com Bubble, the Great Recession, and the Covid Recession. The results indicate that the Fed did not begin to consider the credit cycle theory when implementing monetary policy until after the Great Recession. Credit was not addressed prior to the Savings and Loan Crisis and was only substantially mentioned on the eve of the Dot-Com Bubble and the Great Recession. This indicates that instead of continually discussing credit, the Fed was only concerned with credit when it began to tighten. While it did mention credit build-up, especially before the Great Recession, the Fed did not adjust its monetary policy accordingly. Instead, it primarily adjusted policy to manage inflation. However, after the Great Recession, the Fed began adhering more closely to the credit cycle theory both in terms of what was discussed in each meeting, as it consistently discussed credit, and how it implemented monetary policy. |
Effects Of Online Tutoring On Test Scores, Confidence, and Future Career Paths During The Pandemic | https://www.jsr.org/hs/index.php/path/article/view/3753 | Grace Gao; Rodion Kosovsky | 08-31-2022 | Since the outbreak of COVID-19 in 2020, online learning has rapidly begun to replace in-person learning and demand for online tutoring has grown. The switch to remote learning has also exacerbated learning inequality, as shown by students’ test scores. The paper examines the efficacy of ManhattanACE’s mathematics online tutoring model to provide a template for creating a valuable online tutoring experience. To understand the main aspects of online learning and its effects on students’ learning outcomes, an electronic survey was created and sent to the students. The survey contained both Yes/No questions and scaled 1-5 questions. Analysis of the survey responses shows that through a combination of factors such as passionate tutors and a responsive learning environment that feels like a community, online learning can boost both students’ grades in math class and the effectiveness of virtual learning, while fostering students’ confidence in their skills and future career choices. These three outcomes can, in turn, work to minimize educational and resource inequality. |
Melanoma Skin Cancer Classification via Region-Aware Hierarchical Feature Aggregation | https://www.jsr.org/hs/index.php/path/article/view/2817 | Kyungryun Kim | 08-31-2022 | Melanoma is a type of skin cancer with the highest risk of death. It is critical to identify these early, as the chances of survival significantly drop after stage 2 melanoma. The use of many technologies has lessened this risk but is still limited when correctly identifying malignant ones. Classifying malignant skin cancers is difficult for the following reasons: the shapes and sizes of melanomas are irregular. It is also challenging to visually distinguish between melanomas and non-melanoma regions. The performance of the previous research is based on the depth of the networks. This has a significant trade-off as using more layers adds to the computational cost of the process. Also, their methods use melanoma segmentation as an auxiliary input to the classification network. Thus, the performance of the classification significantly drops when the segmentation task fails. To address this issue, I propose a novel melanoma classification network that uses hierarchical feature aggregation with an attention mechanism. The overall architecture of the proposed network is as follows: The melanoma feature extractor takes the melanoma image as input and produces the image feature related to melanoma. The second module, the attention network, takes the same melanoma image and outputs the attention map which provides the melanoma feature extractor with feature-level regions of interest. The proposed network achieves an accuracy of 82.7% on the melanoma detection dataset which is publicly available online. Throughout the experiments, I have shown that the proposed method outperforms the previous state-of-the-art methods. |
Nuclear Energy as a Highly Viable Source to Mitigate Rapid Warming | https://www.jsr.org/hs/index.php/path/article/view/3145 | Huaxu Zhang; Joel Morrissey | 08-31-2022 | The longstanding issue of global warming has taken its toll on countries around the world. Global warming has become one of the major issues that humans need to face together in the 21st century. A highly viable solution to this issue is adopting nuclear energy as one of the world’s major energy sources. Nuclear energy is more reliable and consistent than renewable energy and cost-efficient in energy generation in the long run, making it a suitable replacement for acquiring energy from traditional fossil fuels. In addition, nuclear power and renewable energy should both be considered as possible solutions for mitigating global warming, rather than as rivals contending for superiority. Currently, the two major challenges of using nuclear energy include the high short-term cost of building nuclear power plants and nuclear fear by the general public. At the current rate of warming, it is necessary to use every viable means to slow down the process of warming enough for better solutions to climate change to be devised. |
Machine Learning Methods for Breast Cancer Diagnosis | https://www.jsr.org/hs/index.php/path/article/view/2676 | Matthew Lee; Zhaonan Sun | 08-31-2022 | As many modern diseases begin to surface especially as of late, such as the Ebola and COVID-19 epidemics, scientists have begun developing new and innovative tactics to combat them. While new medicine and vaccines may be developed, one area that needs special attention is the diagnosis of diseases – this is because without a proper and speedy diagnosis, scientists wouldn’t be able to detect diseases, rendering treatment ineffective. Scientists have begun using machine learning algorithms to help ensure an accurate and speedy diagnosis. One specific disease that has seen frequent testing around machine learning diagnosis is breast cancer. Breast cancer is one of the deadliest and common cancers around the world for women, and due to its effects, the doctrine of speed in diagnosis is essential. This study will attempt to find out, out of three machine learning algorithms (neural networks, logistic regression and K-nearest neighbours), which one is the most effective at diagnosing breast cancer using the Wisconsin Breast Cancer Dataset. Results suggest that neural networks perform the best in diagnosing breast cancer, however only by a small margin compared to other results. |
Predicting the Chance of Heart Attack with a Machine Learning Approach – Supervised Learning | https://www.jsr.org/hs/index.php/path/article/view/3380 | Lanting Zhu; Guillermo Goldsztein | 08-31-2022 | Machine learning is a multidisciplinary field combining statistics, computer science and artificial intelligence. This research finds a way to use machine learning to predict the chance of heart attack based on information about the patient. There are 13 features collected about each patient which are age, sex, cholesterol, chest pain type, maximum heart rate achieved, resting blood pressure, resting electrocardiographic results, fasting blood sugar, exercise-induced angina, previous peak, slope, number of major blood vessels, and thalassemia. The information of all the patients is put into a dataset. The dataset is split into two sets, one for training and another for validation. A computer model using a supervised learning algorithm is developed and trained to predict the chance of heart attack. During training, the training set is used for training the model, while the validation set is used for evaluating the accuracy of the model. |
An Analysis of COVID-19 Fiscal Policies in the US and Japan | https://www.jsr.org/hs/index.php/path/article/view/3733 | Avinash Gogineni; Mr. Martin | 08-31-2022 | In 2020, the COVID-19 disease created an unprecedented impact on the world. It created a health crisis in many countries, causing a pandemic. Along with the health crisis, most countries fell into an immediate economic recession including the US and Japan. This paper focuses on the fiscal policies used in the US and Japan due to the COVID-19 pandemic-related economic recession in both countries. First, a detailed analysis of the US and Japanese fiscal policies is presented, analyzing their effectiveness. Subsequently, these policies were compared and contrasted to obtain a better understanding of fiscal responses around the world. Overall, this paper aims to provide a new global perspective on the implementation of fiscal policies while also aiding policy-makers in making more educated decisions for future recessions caused by COVID-19 or other pandemics. |
NFTs: License to Own? | https://www.jsr.org/hs/index.php/path/article/view/2757 | Jeremy Freeman | 08-31-2022 | In recent years, NFTs have burst onto the global scene, quickly going from an internet meme to a multi-billion dollar digital industry. These digital assets have everyone talking, but nobody seems to know what they are or whether you actually own anything when you buy one. This article uses extensive philosophical, legal, copyright, and empirical research to explore what is actually being purchased with an NFT. With everything from the morale words of John Locke to warnings from the district office of Manhattan, this article quantifies what NFT ownership entails, which is, essentially, nothing. Although governments acknowledge the possibility of legitimate ownership for NFTs, the lack of regulations and protections, as well as the unclear copyright laws and shady ownership claims make NFTs, for our current legal system at least, essentially worthless. |
Deep Learning for MS2 Feature Detection in Liquid Chromatography Mass Spectrometry | https://www.jsr.org/hs/index.php/path/article/view/2964 | Jonathan He, Olivia Liu; Xuan Guo | 08-31-2022 | Accuracy of peptide identification is crucial for LC-MS analysis to reveal information regarding many different aspects of proteins that aid in the discovery of biomarkers and profiling of complex proteomes. Preprocessing steps such as feature detection are crucial yet challenging; current feature detection tools are not robust enough to detect low-abundance, low-peak fragments of peptides found in MS2 data from tandem mass spectrometry. In this study, we developed a deep learning-based model with an innovative sliding window process that enables high-resolution processing of quantitative MS/MS data to conduct accurate feature detection on MS2 data. Experimental results show that our model is able to produce more accurate values and identifications than existing feature detection tools. Therefore, we believe that our model can realize the full potential of neural networks in the field of bioinformatics and yields long-term benefits in the advancement of proteomic inquiry. |
Profit and Stock Prices: New Evidence Contrasting the General Consensus of Their Relationship | https://www.jsr.org/hs/index.php/path/article/view/3813 | Ziyang Zhong | 08-31-2022 | Ever since the early 17th century, the stock market has become one of the most important aspects of economy in modern society. Which is why is it important to clearly understand the stock market and invest in the companies that would bring profit. When profit and stock prices are discussed together, people tend to assume that there is a correlation between the two. This is because profit is the monetary representation of that company outside of the stock market, and stock prices are the monetary representation within the stock market. However, while there are countless articles proving why there are such relationships between the two, there are also articles disputing that there are any significant relationships. Due to this disagreement in the literature, this paper is going to investigate the relationship between profit and stock prices. |
The Censorship Continues to Sail: The Relationship Between Political Ideology and Book Challenging | https://www.jsr.org/hs/index.php/path/article/view/2690 | Ure Nwokoji; Dr. Sullivan | 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 | https://www.jsr.org/hs/index.php/path/article/view/2951 | Ishani Das; Mr. | 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. Utilizing classification models in deep learning, an advanced subfield of machine learning based on neural networks, offers 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 | https://www.jsr.org/hs/index.php/path/article/view/3110 | bai bairuiyang | 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. |
Machine Learning for Policy Guidance | https://www.jsr.org/hs/index.php/path/article/view/3597 | Justin Chae; Timothy Raines | 08-31-2022 | This paper leverages machine learning algorithms and techniques to create models that can assist in a country's policy guidance. The machine learning process used to conduct research is discussed with steps such as preprocessing, feature selection, model selection, and model interpretation. Specifically, using datasets from the CIA's World Factbook and the United Nations' Human Development Index (HDI), machine learning models are created that use select features from several counties (e.g., real gross domestic product (GDP), population, and area). Then, the models make predictions on the countries' HDI scores. Model interpretation methods are used to find the most important features in predicting a country's score. This paper argues that important features can be derived through machine learning and guide government policy relevant to human development. Supply-side policies are discussed based on the results from the machine learning models. The use of machine learning with other indexes is also explored. |
Partial Solution-preserving Integrable generalization Method for Autonomous ODE Systems | https://www.jsr.org/hs/index.php/path/article/view/2654 | Oleksii Babaskin; Mr. Babaskin | 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 | https://www.jsr.org/hs/index.php/path/article/view/2857 | Amy Park | 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 | https://www.jsr.org/hs/index.php/path/article/view/2989 | Aarush Kachhawa; Jeremy Hitt | 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. |
Treating Dilated Cardiomyopathy with Methylene Blue Using the Drosophila melanogaster Heart Model | https://www.jsr.org/hs/index.php/path/article/view/3361 | Tiffany Zhang, Aiden Pan; Nicole Spinelli | 08-31-2022 | Dilated cardiomyopathy (DCM), the most common cardiomyopathy, is characterized by ventricular dilation and impaired heart contractility. Past studies found that the inhibition of the ubiquitin-proteasome system (UPS), a crucial protein degradation system that removes dysfunctional proteins, plays a key role in the pathogenesis of DCM. Since treatments for DCM only aim at alleviating heart failure symptoms, a new therapeutic was sought. Methylene blue (MB) was selected because of its cardioprotective properties and ability to increase proteasome activity, potentially allowing it to revert the impact of an impaired UPS. The Drosophila melanogaster strain wupA, which presents DCM symptoms, was used and treated with MB (30 μM). The flies’ lifespans and negative geotaxis were assessed, and dissections were conducted to analyze heart rates (HR), heart diameters, and fractional shortening (FS) with ImageJ. The log-rank test and t-tests were used to analyze statistical significance. Results showed that DCM increased the heart diameters (p<0.01) and decreased the HR (p<0.05), FS (p<0.01), and negative geotaxis (p<0.01). MB fully restored the dilated heart diameters and impaired FS as there was no significant difference between control and experimental groups (p>0.05), exhibiting potential in treating DCM. However, MB didn't affect the impaired HR and negative geotaxis of flies with DCM. Hence, future studies should investigate supplemental treatments to fully restore those properties. |
Denoising Speech Signals with Hifi-Coulomb-GANs | https://www.jsr.org/hs/index.php/path/article/view/3501 | Anirudh Satheesh; Karthick Muthu-Manivannan | 08-31-2022 | Recorded speech signals often contain noise that affects the quality of the signal and reduces intelligibility. Several studies have used Generative Adversarial Networks (GANs) to remove noise artifacts and improve speech intelligibility. However, GANs can suffer from gradient vanishing or gradient explosion that can reduce their effectiveness in denoising. To mitigate gradient vanishing, we applied the CoulombGAN architecture to speech denoising using a model structure similar to Hifi-GAN, the current state of the art speech denoiser. We call this new model Hifi-CoGAN. We used a WaveNet generator to denoise signals, a PostNet for general cleanup, and a Multi-Resolution Discriminator to evaluate the signal quality relative to the clean signal. Our results show that Hifi-CoGAN was able to outperform Hifi-GAN in many of the narrowband signals (signals with a limited range of frequencies) in terms of the Short-Term Objective Intelligibility (STOI) and Perceptual Evaluation of Speech Quality (PESQ) metrics. However, the model did not perform as well as Hifi-GAN with wideband noise signals (signals with a wider range of frequencies) such as white noise, so future work must be done to improve the model for these noise signals. |
Effects Of Online Tutoring On Test Scores, Confidence, and Future Career Paths During The Pandemic | https://www.jsr.org/hs/index.php/path/article/view/3753 | Grace Gao; Rodion Kosovsky | 08-31-2022 | Since the outbreak of COVID-19 in 2020, online learning has rapidly begun to replace in-person learning and demand for online tutoring has grown. The switch to remote learning has also exacerbated learning inequality, as shown by students’ test scores. The paper examines the efficacy of ManhattanACE’s mathematics online tutoring model to provide a template for creating a valuable online tutoring experience. To understand the main aspects of online learning and its effects on students’ learning outcomes, an electronic survey was created and sent to the students. The survey contained both Yes/No questions and scaled 1-5 questions. Analysis of the survey responses shows that through a combination of factors such as passionate tutors and a responsive learning environment that feels like a community, online learning can boost both students’ grades in math class and the effectiveness of virtual learning, while fostering students’ confidence in their skills and future career choices. These three outcomes can, in turn, work to minimize educational and resource inequality. |
Ursula Le Guin’s Refutation of Gendered Traits in ‘The Left Hand of Darkness’ | https://www.jsr.org/hs/index.php/path/article/view/2686 | Avni Bansal | 08-31-2022 | In her novel ‘The Left Hand of Darkness’, Ursula Le Guin challenges the idea that certain human behaviors are fundamentally feminine or masculine, or that gendered traits exist. Firstly, she cleaves gender and personality apart by setting the novel on a planet of androgynes. Secondly, she creates complex characters that exhibit both stereotypically masculine and feminine behaviors. Thirdly, she presents an allegory that criticizes the idea of gendered traits as irrational and unnecessary. Finally, the novel is peppered with subversive images like that of a pregnant king, which are designed to challenge gender roles. |
The Move Towards Sustainable Aviation | https://www.jsr.org/hs/index.php/path/article/view/2923 | Ishaan Jain; Dr. Mritunjay Sharma | 08-31-2022 | This paper discusses how the aviation industry has been shaped by sustainability and examines how the aviation industry is progressing towards a more sustainable future. It compares the fuel usage of similar aircraft between aircraft manufacturers, Airbus and Boeing. The research also looks at how aircraft designs have evolved over time to reduce fuel usage and cut down carbon emissions. This can be seen in the fuel usage of aircraft. For example, if you compare the fuel usage of the Airbus A340 to the Airbus A350, the Airbus A350 uses significantly less fuel as it has improved engines and aerodynamics, allowing it to transport a similar number of passengers over a similar range. Airbus managed to make a better and far more fuel-efficient aircraft within 20 years. The aim of this research study was to examine how the commercial aviation industry can promote sustainable aviation in the future through a mixed-method approach. First, by using a quantitative approach, the impact of all the aircraft designs of Boeing and Airbus for commercial aircraft carrying 40 passengers and above on fuel usage and CO2 emissions would be compared, followed by a qualitative analysis explaining the varying fuel usage of similar aircraft and comparing which aircraft manufacturer holds the upper hand going into the future. |
Identifying the difference in bacterial composition and life history strategies between high versus low nutrient soils | https://www.jsr.org/hs/index.php/path/article/view/3271 | Felix Tuchscherer | 08-31-2022 | In this study, we aim to identify bacterial composition in soils treated with and without wood chips, as well as high levels and low levels of nitrogen. In order to do this, we used both culture dependent methods including plating, observing, and GenIII plates; as well as culture independent methods which include microbiome sequencing and EcoPlates. By doing this, we concluded that the bacterial communities differ between unamended and wood-chipped treated soils. Multiple differences were identified: rate of carbon consumption, bacterial diversity, rRNA gene copy number, and colony morphologies. Identifying the bacteria in wood-chipped soils will allow us to understand their effect on biogeochemical cycles, plant pathogens, and relationship with the trees (symbiotic/pathogen). Additionally, understanding the effect lower nitrogen levels have on the bacterial composition of soils can lead to reduction of synthetic fertilizer use, therefore lessening the environmental impact of nitrogen. |
Bioartificial Liver Manufacturing Methodologies in Comparison to Hepatogenesis | https://www.jsr.org/hs/index.php/path/article/view/3385 | Aanya Roy; Coach Jo | 08-31-2022 | End-stage organ failure is a major global issue, with the liver being the second-highest transplanted organ due to lifestyle choices or other conditions. In the field of biomedical engineering, artificial organ manufacturing has been a possible alternative to organ transplants by aiming to achieve less immune rejection, more efficient production, and higher accessibility. Of the biological manufacturing methods today, two up-and-coming technologies for the liver include 3D bioprinting and decellularized organ regeneration. By analyzing general stages of 3D bioprinting and decellularization for liver development and comparing it to the cellular and genetic stages of hepatic development in the embryo, dilemmas and successes in bioartificial manufacturing can be identified. Overall, neither artificial methodology can replicate the genetic influence or non-liver based influence of hepatogenesis. 3D bioprinting is similar to hepatogenesis in cell development and construction, but contains shortcomings in vascularization, which can be addressed using the vasculogenesis and angiogenesis processes in hepatic development. Decellularization allows for cell differentiation, although it is unable to instill natural cellular distribution and gradual ECM development. This may cause blockages for clinical use in the future. Both methods have potential for bioartificial liver development and clinical application, but 3D bioprinting technology is more aligned with the stages of hepatic development, which has proven to induce fewer errors in the physiological nature of the manufactured liver. In the future, modification and research must be conducted on the specific stages of these methodologies for either to create an operational bioartificial liver for clinical use. |
Does the U.S. Federal Reserve Consider the Credit Cycle Theory When Trying to Predict Recession? | https://www.jsr.org/hs/index.php/path/article/view/3565 | Tommy Heaton; Niklas Schmitz | 08-31-2022 | The credit cycle theory states that credit build-ups and their subsequent crashes are the common cause of recessions. If true, this theory could be used to both predict and prevent future recessions. However, it is unclear if policymakers do in fact take the theory into account when crafting monetary policy. Using the U.S. Federal Reserve (the Fed) as a case study, this paper seeks to answer if policymakers consider the credit cycle theory when attempting to predict recessions and determine optimal monetary policy. This paper analyzes Federal Open Market Committee minutes from meetings prior to four previous recessions: the Savings and Loan Crisis, the Dot-Com Bubble, the Great Recession, and the Covid Recession. The results indicate that the Fed did not begin to consider the credit cycle theory when implementing monetary policy until after the Great Recession. Credit was not addressed prior to the Savings and Loan Crisis and was only substantially mentioned on the eve of the Dot-Com Bubble and the Great Recession. This indicates that instead of continually discussing credit, the Fed was only concerned with credit when it began to tighten. While it did mention credit build-up, especially before the Great Recession, the Fed did not adjust its monetary policy accordingly. Instead, it primarily adjusted policy to manage inflation. However, after the Great Recession, the Fed began adhering more closely to the credit cycle theory both in terms of what was discussed in each meeting, as it consistently discussed credit, and how it implemented monetary policy. |
Melanoma Skin Cancer Classification via Region-Aware Hierarchical Feature Aggregation | https://www.jsr.org/hs/index.php/path/article/view/2817 | Kyungryun Kim | 08-31-2022 | Melanoma is a type of skin cancer with the highest risk of death. It is critical to identify these early, as the chances of survival significantly drop after stage 2 melanoma. The use of many technologies has lessened this risk but is still limited when correctly identifying malignant ones. Classifying malignant skin cancers is difficult for the following reasons: the shapes and sizes of melanomas are irregular. It is also challenging to visually distinguish between melanomas and non-melanoma regions. The performance of the previous research is based on the depth of the networks. This has a significant trade-off as using more layers adds to the computational cost of the process. Also, their methods use melanoma segmentation as an auxiliary input to the classification network. Thus, the performance of the classification significantly drops when the segmentation task fails. To address this issue, I propose a novel melanoma classification network that uses hierarchical feature aggregation with an attention mechanism. The overall architecture of the proposed network is as follows: The melanoma feature extractor takes the melanoma image as input and produces the image feature related to melanoma. The second module, the attention network, takes the same melanoma image and outputs the attention map which provides the melanoma feature extractor with feature-level regions of interest. The proposed network achieves an accuracy of 82.7% on the melanoma detection dataset which is publicly available online. Throughout the experiments, I have shown that the proposed method outperforms the previous state-of-the-art methods. |
Nuclear Energy as a Highly Viable Source to Mitigate Rapid Warming | https://www.jsr.org/hs/index.php/path/article/view/3145 | Huaxu Zhang; Joel Morrissey | 08-31-2022 | The longstanding issue of global warming has taken its toll on countries around the world. Global warming has become one of the major issues that humans need to face together in the 21st century. A highly viable solution to this issue is adopting nuclear energy as one of the world’s major energy sources. Nuclear energy is more reliable and consistent than renewable energy and cost-efficient in energy generation in the long run, making it a suitable replacement for acquiring energy from traditional fossil fuels. In addition, nuclear power and renewable energy should both be considered as possible solutions for mitigating global warming, rather than as rivals contending for superiority. Currently, the two major challenges of using nuclear energy include the high short-term cost of building nuclear power plants and nuclear fear by the general public. At the current rate of warming, it is necessary to use every viable means to slow down the process of warming enough for better solutions to climate change to be devised. |
An Analysis of COVID-19 Fiscal Policies in the US and Japan | https://www.jsr.org/hs/index.php/path/article/view/3733 | Avinash Gogineni; Mr. Martin | 08-31-2022 | In 2020, the COVID-19 disease created an unprecedented impact on the world. It created a health crisis in many countries, causing a pandemic. Along with the health crisis, most countries fell into an immediate economic recession including the US and Japan. This paper focuses on the fiscal policies used in the US and Japan due to the COVID-19 pandemic-related economic recession in both countries. First, a detailed analysis of the US and Japanese fiscal policies is presented, analyzing their effectiveness. Subsequently, these policies were compared and contrasted to obtain a better understanding of fiscal responses around the world. Overall, this paper aims to provide a new global perspective on the implementation of fiscal policies while also aiding policy-makers in making more educated decisions for future recessions caused by COVID-19 or other pandemics. |
Machine Learning Methods for Breast Cancer Diagnosis | https://www.jsr.org/hs/index.php/path/article/view/2676 | Matthew Lee; Zhaonan Sun | 08-31-2022 | As many modern diseases begin to surface especially as of late, such as the Ebola and COVID-19 epidemics, scientists have begun developing new and innovative tactics to combat them. While new medicine and vaccines may be developed, one area that needs special attention is the diagnosis of diseases – this is because without a proper and speedy diagnosis, scientists wouldn’t be able to detect diseases, rendering treatment ineffective. Scientists have begun using machine learning algorithms to help ensure an accurate and speedy diagnosis. One specific disease that has seen frequent testing around machine learning diagnosis is breast cancer. Breast cancer is one of the deadliest and common cancers around the world for women, and due to its effects, the doctrine of speed in diagnosis is essential. This study will attempt to find out, out of three machine learning algorithms (neural networks, logistic regression and K-nearest neighbours), which one is the most effective at diagnosing breast cancer using the Wisconsin Breast Cancer Dataset. Results suggest that neural networks perform the best in diagnosing breast cancer, however only by a small margin compared to other results. |
Predicting the Chance of Heart Attack with a Machine Learning Approach – Supervised Learning | https://www.jsr.org/hs/index.php/path/article/view/3380 | Lanting Zhu; Guillermo Goldsztein | 08-31-2022 | Machine learning is a multidisciplinary field combining statistics, computer science and artificial intelligence. This research finds a way to use machine learning to predict the chance of heart attack based on information about the patient. There are 13 features collected about each patient which are age, sex, cholesterol, chest pain type, maximum heart rate achieved, resting blood pressure, resting electrocardiographic results, fasting blood sugar, exercise-induced angina, previous peak, slope, number of major blood vessels, and thalassemia. The information of all the patients is put into a dataset. The dataset is split into two sets, one for training and another for validation. A computer model using a supervised learning algorithm is developed and trained to predict the chance of heart attack. During training, the training set is used for training the model, while the validation set is used for evaluating the accuracy of the model. |
Increase in Stress and Post-Traumatic Stress During 6 Month Quarantine in Various Demographics | https://www.jsr.org/hs/index.php/path/article/view/2186 | Claire Padilla | 06-10-2022 | Due to the Coronavirus, people have quarantined for periods of at least six months all over the world. In the United States, there have been over six hundred thousand Coronavirus deaths and over 33 million cases of COVID-19 as of May 2021(World O Meter 2021). When the pandemic first struck, 23 million people in the U. S. lost their jobs. Today's unemployment rate is higher than it was during the Great Depression, which lasted from the 1920s to the late 1930s. People are stressed about COVID, according to John Hopkins (Maguire 2020), and they encourage people to find coping mechanisms. When a person is stressed, they experience physical or emotional tension (MedlinePlus 2020). Since coping can have a detrimental effect on the immune system, coping in necessary (Maguire 2020). This study sought to determine whether people aged 18 and up experienced a rise in stress levels during a 6-month quarantine period. Then, based on the Impact of Event Scale - Revised (IES-R) score, this study would determine which coping mechanism, if any, is most successful in alleviating quarantine-induced stress. It was found that there was a significant increase in stress levels after a six-month quarantine period with a confidence level of 95% and a p-value of 0.00000031. The data also showed that there was not a significant difference in the stress levels between varying coping mechanisms with a p-value of 0.23. It is recommended to use a coping mechanism, all coping mechanisms are effective when matched properly to each individual. |
Public Opinion of WA Residents on Free-range Parenting and Its Legal Implications on Child Neglect | https://www.jsr.org/hs/index.php/path/article/view/2136 | Ruoya Huang, Lauren Barry, Sam Niehl, Rielly Springer ; Elizabeth Mader, Tara Maloney | 06-10-2022 | Free-range parenting is the practice of giving children more freedom to act independently. However, in recent years, many proponents of this practice got into legal trouble or faced social criticism for being neglectful and were labeled as “bad parents.” Most of them are low-income families that cannot afford babysitters. Others are well-off parents that advocate for fostering independence. Nevertheless, their actions incurred various consequences due to their socioeconomic status as helicopter parenting becomes increasingly popular. The lack of specific laws to clarify the difference between neglectful parenting and free-range parenting cause poorer or uneducated parents to suffer from serious legal charges unjustly. Washington is among those states that have not updated its laws to keep up with the heated debate over parenting preference, so gathering input from WA residents on this topic is essential for highlighting the controversy and providing necessary insights into the social trend to inform the policymakers when evaluating and amending neglect laws. 222 WA residents were conveniently selected to answer a 30+ question survey over two months. This study found that younger generations, high-income parents, and people with higher education are more disapproving of free-range parenting. It was also found that average WA residents believe parents have the responsibility to always accompany children under 12 years old, presenting a more conservative/pro-helicopter parenting preference. The reasons behind the inclination were explored. Based on those results, the researchers discussed legal recommendations for the WA legislature to reduce ambiguity to better protect parental rights while sustainably alleviating child neglect. |
Quantitative Comparison of a Hierarchy of Commonly Used Planetary Climate Energy Balance Models | https://www.jsr.org/hs/index.php/path/article/view/2174 | Mihir Dasgupta; Joy Merwin Monteiro | 06-10-2022 | The objective of this paper is to examine the effect of the various simplifications inherent in commonly-used planetary energy balance climate models (EBMs). Specifically, we look at the zero-dimensional (0-d) radiative equilibrium model, the 1-d radiative equilibrium model, and the 1-d radiative-convective equilibrium (RCE) model. Each of these models make fundamental steps towards a well-represented Earth system model, and make different simplifications and assumptions in the process. We seek to evaluate the effects these assumptions have on key thermal quantities of the system (OLR / outgoing longwave radiation, surface temperature, etc.). These evaluations lead us to identify contexts for each model wherein it remains a valid option to accurately replicate a system. The 0-d model fails to account for the greenhouse effect’s impact on energetics, thus predicting an erroneously-low surface temperature and low OLR. It instead requires an emissivity coefficient ~ 0.619 to balance OLR and temperature and model the Earth system. The 1-d radiative equilibrium model is a significant improvement on its predecessor, creating a stratospheric thermal profile reasonably similar to that of the Earth. The strong low-altitude temperature lapse rate and convective instability near the surface, however, slightly diminishes the validity of the low-level thermal profile – a drawback the RCE model appears to resolve with the addition of convective and boundary layer components. We conclude that the 0-d radiative equilibrium is best suited to isothermal atmospheres, the 1-d radiative equilibrium model to non-isothermal atmospheres where convection is suppressed, and the 1-d RCE model to convectively-active atmospheres. |
Discovering B/T Cell-Cancer Antigen Affinity for Targeted Cancer Drug Therapy and Diagnosis Through Deep Neural Network Models | https://www.jsr.org/hs/index.php/path/article/view/2065 | Aryansh Shrivastava; Vaishnavi Shrivastava | 06-10-2022 | Cancer, one of the leading causes of death worldwide, derives from an uncontrolled division of abnormal cells in a given part of the body. Targeted immunotherapy is a promising avenue of cancer treatments, galvanizing the body's own immune system to marshal B and T cells against abnormal cell growth, pathologically inhibiting antigen function and proliferation. In the current landscape of cancer immunotherapy, however, medicine industries are belabored with the need to use painstaking trial and error and numerous wet-lab investigations to test amino acid sequences' affinities to cancer antigens. Furthermore, most cancer antigens and the structures of their epitopes are unknown, and although most malignancies can be cured when diagnosed early, organ-specific assessments cannot be used for early-stage cancers. To bridge this gap, I innovate a deep convolutional neural network (CNN) model pipeline, which analyzes the complex amino acid makeup of tumor infiltrating B/T cell receptors based on the relationships of biochemical properties among adjacent amino acids predictive of how these receptor polypeptides fold in three-dimensional space, computing high affinity amino acid sequences to revolutionize both targeted drug discovery and early diagnosis. |
The Connection between COVID-19 Variants (Gamma and Delta Variant) and Demographics Using Python | https://www.jsr.org/hs/index.php/path/article/view/2138 | Sneha Nangunoori; Rajagopal Appavu, Jothsna Kethar | 06-10-2022 | From schools shifting to virtual learning and offices promoting work from home, COVID-19 transformed the way the world functions. Like any other virus, the coronavirus has many variants. This research paper discusses the connection between two prominent variants: the Gamma variant and the Delta variant and certain demographic features like gender, age, and location. The method used in this research paper includes finding data from credible sites and other evidence and using python to extract the needed data to support theories. The theories stated in this research paper are not completely valid due to the lack of strong evidence. So, instead of concluding with a strong thesis, this research paper aims to motivate other researchers to delve even deeper into this topic. Basically, this study focuses on the importance of future research and acts as a stepping stone for other researchers who are interested in learning more about COVID-19 variants and their connection with different demographic features. |
Manufacturing Firms Leaving China and Moving into Southeast Asia | https://www.jsr.org/hs/index.php/path/article/view/2184 | Eudora Chi; Tim Cavnar | 06-10-2022 | Over the past twenty years, a growing number of manufacturing firms have left China. This paper explains the three principal reasons behind this exodus: disadvantages of Chinese manufacturing, US-China trade-war tariffs, and manufacturers’ emphasis on diversification. This study analyzes the current trend with an economic model to examine the relationship between manufacturing firms and the Southeast Asian host countries. As foreign direct investment (FDI) tends to shift from higher to lower-cost regions, manufacturing firms are now leaving China and moving into Southeast Asia. This paper also suggests the option of reshoring and manufacturers’ concerns about moving. This paper is useful for investors in the manufacturing industry. |
Name and Personality: Is There a Similarity Between You And Others With The Same Name? | https://www.jsr.org/hs/index.php/path/article/view/2002 | Michael Wang, Sophie | 06-10-2022 | Previously, researchers have determined that people tend to attribute certain personality traits with certain names. For this reason, we conducted a research study to determine whether or not a person’s name actually has an effect on their personality. We surveyed people with the given name “Ryan” and asked them to take the HEXACO personality trait, which tests for six traits: honesty, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience. We averaged our sample’s results for each trait and compared them with the HEXACO medians for each trait in the general population. We hypothesized that if name indeed has an impact on personality, people with the same name would have distinctly disparate trait scores than the general population. We found that between our “Ryan” sample and the general population, there was a significant difference in scores for five of six personality traits. Compared to the general population, Ryans are more likely to be more honest, less emotional, less extraverted, more agreeable, and less conscientious. The sixth HEXACO trait, openness to experience, has no statistical significance. Because five of six traits had significance, we were able to conclude that names are likely to have an influence on personality traits. |
Design of a Physical Therapy Device for Lower Leg Recovery | https://www.jsr.org/hs/index.php/path/article/view/2139 | Ashna Khemani, Katie Hahm | 06-10-2022 | Currently, some physical therapy requires another person to assist in exercises that rehabilitate patients with leg injuries such as sprains and fractures. In this paper, we propose a device that can help strengthen muscles that have weakened due to injury without the help of another person. The device is portable and can be used in a home setting, and the amount of resistance it provides can be adjusted by the patient. We suggest a design that aids patients in lower leg rehabilitation and can adjust for the patient’s preference in exercise type and intensity. |
Designing a Science-based Strategy to Prepare for the Next Pandemic | https://www.jsr.org/hs/index.php/path/article/view/2238 | Ningrui Zhang; Reto Asmis, Mark Crowder | 06-10-2022 | For the last nearly two years, the world and its peoples have been on edge, dealing with a pandemic that killed millions of people and altered forever the lives of many others. The COVID-19 pandemic is a once in a generation event that provides an opportunity, despite its horrible impact, for us to be better prepared for future pandemics. This aim of this work is to investigate strategies that were used to combat COVID-19 and develop improved ones that will mitigate both the spread and mortality of similar episodes for the next generation. A review of public health guidance and primary literature suggests many currently used strategies were effective, but additional strategies and guidance are proposed here. These proposed strategies will improve not only preparedness, but also the responses used to tackle and defeat the next COVID pandemic. |
An Analysis of Gender Gap in Computer Science in High School | https://www.jsr.org/hs/index.php/path/article/view/2572 | Kashika Mahajan; Gayathri Thirumalai | 05-31-2022 | Computer Science has been a male-dominated field even at its beginning, and it continues to be so. A distinct gap has developed between the number of women and men studying and working in Computer Science, commonly termed as the Gender Gap. Previous studies have uncovered this gap at its worst during college education, where women occupy a small fraction of the STEM-related classes. Surveys and data were taken from a high school to be analyzed. These provide insight into why female students are not as encouraged as their male counterparts regarding the subject. The results show that even at a stage as early as high school, differences in confidence, upbringing and exposure have often deterred female students from pursuing Computer Science. Contrary to the belief that due to the rising dependency on technology more women are pursuing Computer Science, a four-year plot shows that in high schools there is rather a widening gender gap. |
The Effects of Social Isolation From The COVID-19 Lockdown on Social Anxiety in Individuals | https://www.jsr.org/hs/index.php/path/article/view/2599 | Mina Kim; Dr. Barker | 05-31-2022 | As the world continues its second year of the COVID-19 pandemic with varying degrees of lockdown, not much is known yet about how the extended periods of social isolation have affected individuals. This study used an online survey of individuals with varying levels of social anxiety to find that social isolation from the COVID-19 lockdown exacerbated self-rated social anxiety severity in individuals and led to new problems such as feelings of depression, loneliness, and worse self-esteem. As individuals with social anxiety already struggle to or avoid seeking out help or treatment, these findings have concerning implications for the mental health treatment of individuals with social anxiety after the pandemic. |
Subsets and Splits