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A Multi-Modality Magnetic Resonance Imaging Model for Predicting Traumatic Brain Injury Outcomes | https://www.jsr.org/hs/index.php/path/article/view/5197 | Shruti Vadlakonda; Dr. Raymond Koehler, Janine Sharbaugh | 11-30-2023 | Traumatic Brain Injury (TBI) is a heterogenous injury and a leading cause of long-term deficits and mortality in the United States. In order to improve TBI outcomes, an effective prognostication tool is necessary. Standard imaging modalities, computerized tomography (CT) and magnetic resonance imaging (MRI), have a limited ability to predict TBI outcomes. Currently, advanced MRI techniques are being studied for their efficacy. The aim of this study is to determine whether a multimodality MRI approach is superior to a single modality MRI approach in determining clinical outcomes of TBI. A secondary data analysis was conducted on TBI data obtained from 31 rat brains; 3-day MRI data in the Ipsilateral Perilesion Cortex and 28-day Behavioral Test data (Novel Object Recognition, Barnes Maze, and Open Field Test Total Distance and Total Act Time) were analyzed. A Best Subset Analysis was conducted for each of the behavioral tests. Three out of four behavioral tests show improved adjusted R2 values for models containing more than one imaging modality. A Multiple Linear Regression Analysis was then conducted on the MRIs from the highest predictive model determined by Best Subset Analysis. This analysis shows that a multimodality MRI approach can explain 25.2% of the variability in behavioral outcomes in the Novel Object Recognition Test with a P value of 0.012. Thus, the study demonstrates that a multi-modality MRI approach has a potential for effectively diagnosing and predicting TBI outcomes. |
The Bracero Program: A Catalyst for Social Justice | https://www.jsr.org/hs/index.php/path/article/view/5477 | Teddy Fleiss; Michele Santosuosso | 11-30-2023 | This paper gives a background of the Bracero Program, a little known guestworker program that allowed millions of Mexicans into the United States. The Bracero Program had large-scale impacts, ranging from intertwining Mexican and American economies to impacting social justice movements regarding immigration reform and civil rights. Today, the program holds responsibility for strong links between Mexican and American communities. |
The Role of Central Banks in Managing Monetary Policy and its Effects on the Economy An Empirical Analysis of Policy Tools, Economic Indicators, and Implications | https://www.jsr.org/hs/index.php/path/article/view/5327 | Atharva Singh | 11-30-2023 | This paper examines the crucial role of central banks in managing monetary policy and its profound effects on the economy. It provides an in-depth analysis of the objectives, tools, and strategies employed by central banks to regulate monetary conditions, control inflation, and promote economic stability. Additionally, it explores the transmission mechanisms through which monetary policy decisions impact various sectors of the economy, including interest rates, exchange rates, investment, consumption, and employment. The paper also highlights the challenges and limitations faced by central banks in conducting effective monetary policy, particularly in an era of economic globalization and financial interconnectedness. Overall, this research contributes to a comprehensive understanding of the intricate relationship between central bank actions, monetary policy, and macroeconomic outcomes. |
A Supervised Deep Learning Model for the Detection of Cardiovascular Disease | https://www.jsr.org/hs/index.php/path/article/view/5178 | Ananya Saridena, Abhaya Saridena; Jothsna Kethar | 11-30-2023 | In our world today, cardiovascular disease (CVD) stands as the foremost cause of death worldwide, claiming the lives of nearly 20 million individuals annually. As CVD continues to burden the healthcare industry, there is a critical need for early detection and prevention. The rise of Artificial Intelligence in the medical field offers a range of capable solutions. In order to address the problem, this paper presents the development of a simple, supervised deep learning model for detecting cardiovascular disease in patients. The research focused on creating a model enriched with multiple layers, activation functions, optimizers, and loss functions. The chosen approach leveraged the power of AI to analyze labeled patient data and map input features to corresponding class labels, enabling accurate detection of CVD. The dataset used contained 70,000 patient records with 12 different clinical attributes. In addition, it provides an overview of the most common types of cardiovascular disease, such as coronary artery disease, aortic valve disease, stroke and peripheral artery disease. The accuracy of the obtained results from the deep learning model was up to 73%. The utilization of AI systems can present a novel approach to addressing daily challenges within the rapidly-evolving world of medicine. Health personnel can take advantage of rapidly changing artificial intelligence and user friendly deep learning models to detect similar future medical concerns. |
The Handover of 1997 and Its Effects on the Hong Kong Aviation Industry | https://www.jsr.org/hs/index.php/path/article/view/5448 | Gareth Fung; Suraj Nair | 11-30-2023 | This paper explains the logistics behind the Handover Hong Kong on July 1st, 1997— an event transition Hong Kong from a sovereign British state to the special administrative region status of the People’s Republic of China. More importantly, it propounds that the Handover of Hong Kong had an indirect but nevertheless negative effect on Hong Kong’s Aviation Industry— most notably affecting the leading Hong Kong airline and air transport company Cathay Pacific. It explores this idea through a critical secondary literature review— intended to analyse the events occurring in Hong Kong prior and during the year 1997 alongside its effects on the industry. Furthermore, employing a case study design on Cathay Pacific enables the research paper to carry out a more structural analysis of the company’s performances in the late 20th century. It takes a macro-to-micro approach for its structure; first explaining the general trends and resilience of the global aviation sector, through developing an analytical lens. Then it uses Cathay Pacific’s performance to evidence the generalised theories. Overall, Hong Kong’s aviation industry saw only slightly deviated results to both empirical and theoretical behaviours of global aviation and air transport airlines following events often causing what is known as a career shock: a disruptive and extraordinary event caused by factors outside an individual’s control. |
Music as a Language Assessing the Extent to Which Active Music Therapy Promotes Socialization Development for Children Under 12 with Down Syndrome | https://www.jsr.org/hs/index.php/path/article/view/5277 | Xinzhi Zhang | 11-30-2023 | The number of children in western countries diagnosed with Down syndrome (DS), a disease caused by chromosomal abnormalities, is still increasing. The resulting delayed cognitive development also leads to deficits in social functioning in children under 12. Active music therapy (MT), as a natural intervention to achieve therapeutic functions through improvisation, performance, and singing, has been proven to promote the socialization development of children with DS. To get a better idea of the extent of the promotion and exactly what aspects it has improved, I conducted literature reviews and interviews with a music therapist. The results suggest that active MT can stimulate the socialization development of children under 12 with DS in three aspects: language skills, social-emotional development, and prosocial behavior. Although the improvement effect of active MT is better than that of passive MT, it requires the client to have a basis of music theory, that is, it requires higher requirements on the client, so the treatment method should be selected according to the severity of the client's DS or a combination of the two. Hence, future research could be aimed at finding the simplest interventions with sufficient client engagement and verifying the continuation of the effect of active MT. |
Exploring the Search Behavior of Teenagers: A Comparative Study of Social Media and Browser Usage | https://www.jsr.org/hs/index.php/path/article/view/5172 | Midori Wang; Stephen Lind | 11-30-2023 | As technology advances, the use of social media is becoming more extensive, and many businesses are adapting their marketing plans to take advantage of it. Research has shown that individuals, especially teenagers, appear to be increasingly relying on social platforms like Tiktok as their primary search engine. This study aims to determine whether there is a growing number of people who use social media as their search engine. An online survey was distributed to several high school students who were asked to search for answers to questions across six different categories. The results indicate that most teenagers still use browsers and search engines like Safari, Google, or Chrome for information gathering due to their content diversity, quality, and habit. However, there was a wide variety of social media and other platforms used throughout the research, which demonstrates the potential of social media as a search engine. |
Antibacterial Properties of Manuka Honey and the Role of Methylglyoxal | https://www.jsr.org/hs/index.php/path/article/view/5433 | Youlin Feng | 11-30-2023 | The unique ecosystems of New Zealand have produced a diverse range of honey over the years, with Manuka honey being one of the most renowned. Produced by Western honeybees extracting nectar from Manuka flowers, this monofloral honey has become known for its distinct antibacterial and anti-inflammatory properties. Whilst antibacterial activity in other honey tend to stem from factors such as hydrogen peroxide content, high viscosity, osmotic effect, and acidic pH, the antibacterial activity of Manuka honey is mainly attributed to methylglyoxal (MGO), a dicarbonyl compound which is found in high concentrations in Manuka honey. This review paper will focus on the antibacterial properties of Manuka honey and the role that MGO plays. Understanding the specific chemical mechanisms that of attack on different strains of bacteria by Manuka honey and the role of MGO is crucial to potentially understanding how new drugs or medicines can combat antibacterial resistance to antibiotics. |
Investigating The Performance and Viability of Semiconducting Graphene as A Substitute for Silicon in Field Effect Transistors | https://www.jsr.org/hs/index.php/path/article/view/5222 | Andrew Jiang | 11-30-2023 | This paper investigates the electrical and thermal properties of two competing methods of semiconducting graphene, doped graphene and reduced graphene oxide, and their respective viabilities for implementation in field effect transistors. We used the Graphene Field Effect Transistor (GFET) simulation software on nanohub.com to determine the current, voltage, and max temperature based on variations in the channel length, top gate oxide thickness, electron mobility, and thermal conductivity and then compared these performance results with those of a traditional silicon-based transistor. Our results demonstrated that doped graphene had superior current conductivity, higher electron mobility, higher thermal conductivity, and higher maximum temperature to those of reduced graphene oxide and silicon. Practicality wise, reduced graphene oxide is far easier to mass produce, as was found to still perform better than silicon-based transistors. Transistors form the backbone of the electronics industry; this study proves that a shift toward graphene-based transistors, doped ones especially, would make transistors stronger, more durable, and more efficient. With the already ubiquitous usage of transistors in our everyday lives, a switch to graphene could bring revolutionary benefits for electronics such as smarter cell phones, faster computers, and more accurate biosensors. |
Effect of Weekly Time Spent Learning and Practicing Musical Instruments on the Intensity of Jitteriness among High School Teenagers in Mainland China | https://www.jsr.org/hs/index.php/path/article/view/5515 | Yinfu Lyu | 11-30-2023 | Psychological disorders have become increasingly prevalent [Liang, 2021]. Among 875 cases, 33.03% of high school students in Mainland China possess some psychological problems [Liang, 2021]. Research has shown that successful musical engagement positively affects physical, social, educational, cognitive, and emotional health [Wang (2022).]. Unfortunately, Chinese teenagers aren't thoroughly studied the connection between musical training and mental health [Pang et al. (2017)]. Also, no statistically significant association between music playing and psychological well-being is seen in previous research [Wesseldijk et al. (2019)]. So, this study investigates how time spent practicing musical instruments influences the intensity of jitteriness among high school teenagers (15~18 years old) to provide insights about mental health-directed musical education in mainland China. A web-based, cross-sectional survey was conducted with a convenience and snowball sample of 200 teenagers from mainland China across 11 provinces. Models were conducted hierarchically using linear regression. In the univariate model, time spent practicing musical instruments weekly was associated negatively with the intensity of jitteriness (β=-0.151, p-value=0.033). In the multivariant model, participants' time spent practicing musical instruments per week was significantly and negatively associated with the intensity of jitteriness (β=-0.312, p-value=0.001), adjusted for confounding variables: total time spent on playing musical instruments, positive emotion intensity, negative emotion intensity (other than jittery), and age. The model was built using simple linear regression with r2=0.267. This study shows a significant negative association between weekly time spent practicing musical instruments and the intensity of negative emotions. |
Beyond Language Barriers: Exploring the Effects of Implicit Message Decoding and Memory Retention | https://www.jsr.org/hs/index.php/path/article/view/5133 | Insun Yoon | 11-30-2023 | This study examined the interplay between implicit message decoding, the time living abroad on language learning, and memory retention. The findings showed a link between the time spent studying abroad and the capacity to decode implicit messages. Additionally, having a narrator narrate educational materials visibly improved memory retention. The ability to decode implicit messages and memory retention were found to be correlated. These findings underscore the importance of interactive instruction and an immersive learning environment for language acquisition. |
Potential for Conduit Hydropower at NYC's Newtown Creek Wastewater Treatment Plant | https://www.jsr.org/hs/index.php/path/article/view/5393 | Reece Davidoff; Prathap Ramamurthy | 11-30-2023 | The Newtown Creek facility is New York City's largest wastewater treatment plant, with the capacity to treat up to 2.65 billion liters of combined sewage (rainfall and raw sewage) each day. After treatment at the plant, clean water flows out to the nearby East River via an outfall pipe. On average, the plant treats 810 million liters of combined sewage per day, which means there is potential to extract significant amounts of energy from the water flowing through the outfall. This paper first verifies that hydropower is a viable option at the plant by calculating the theoretical amount of power available from the running water, then determines what type of turbine would be the most appropriate for the outfall, and finally calculates how much electricity could realistically be generated by a turbine in the outfall. The bulb turbine was identified as the most appropriate type of turbine, and it was approximated that a bulb turbine in the outfall could produce, on average, 263 kilowatts of power. Considering that the plant runs year-round, a total of 2.24 gigawatt hours of clean electricity could be generated annually, which could be used to help power the energy-intensive wastewater treatment process or be fed back into New York City's electrical grid, where it could power up to 211 homes annually. |
Treatment Optimization for Tumor Growth by Ordinary Differential Equations | https://www.jsr.org/hs/index.php/path/article/view/5202 | Kenneth Chan; Chiu-Yen Kao, Jennifer Gordinier, Katherine Ganden | 11-30-2023 | Cancer is the second leading cause of death worldwide and with the disease having over 200 variations, it has not been cured yet despite being the priority of the medical field for decades. Due to the difficulty of human subject research, animal studies, e.g., mouse and Chinese hamster V79 tumors have been widely used to test the modeling of tumor growth due to their dynamic nature and ability to grow to high volumes within short periods of time. Mathematical models, including ordinary differential equations (ODEs), have been utilized to model tumor growth and study treatment of cancer. With most current models being selected only for mathematical convenience, recent studies have been focusing on determining the optimal treatment schedule for the most popular existing treatments of chemotherapy and radiation therapy. In this paper, three of the most established ODE models: the Gompertz, Von Bertalanffy, and logistic models are utilized to analyze which model most accurately fits existing tumor growth data for the Chinese Hamster V79 fibroblast tumor, various forms of immunodeficient mice tumors, and glioblastoma based on the minimization of the normalized mean squared error (NMSE). Next, the ODEs themselves were modified to simulate the growth of the tumors when exposed to treatment and determined which treatment schedule produced the lowest final volume of the tumors. The results of this research identify the optimal treatment schedules based on data from all three ODE models and also determine the ODE models that produce curves that most precisely fit the datasets. |
Protein Stability in Pasteurized Cow and Goat Milk using Protein Gel Electrophoresis | https://www.jsr.org/hs/index.php/path/article/view/5490 | Mai Nguyen; Haiyan Zhang, Barbara Schmidt | 11-30-2023 | Milk is a nutritious beverage that contains whey, casein, and milk fat globule membrane (MFGM) proteins. Pasteurization kills pathogenic microorganisms in milk, making it safe to drink. A high heat load during processing can affect the protein quality of milk. In this study, protein gel electrophoresis (Native and SDS-PAGE) was used to view the protein profiles of retail cow and goat milk samples pasteurized at different temperatures (145, 165, or 280 °F) compared to commercially spray dried milk (356–482 °F). SDS-PAGE provided better resolution of the milk proteins compared to Native-PAGE. There were clear species differences in the MFGM proteins. This could be used to spot adulteration of goat milk with cow milk, however none of the samples showed signs of adulteration. There were no overt patterns of protein degradation with increasing pasteurization temperature. However drying reduced band intensity, especially MFGM and whey proteins in the goat milk sample. Whereas most samples came from different herds where genetics and environmental conditions varied, two of the goat milk samples were from the same herd, one fresh and one spray dried. It was evident from these two samples that spray drying can alter proteins in goat milk. Even so, if fresh milk is unavailable or unaffordable, dry milk remains a valuable protein source. |
Towards Sustainable AI: Mitigating Carbon Impact Through Compact Models | https://www.jsr.org/hs/index.php/path/article/view/5340 | Eddie Zhang, Jixiu Chang, Ashley Yang | 11-30-2023 | As AI technology continues to advance rapidly, it is essential to address the environmental concerns associated with the increasing carbon emissions and their contribution to global warming. The expanding AI industry requires significant computing power, making it a potential major contributor to carbon emissions in the future. Unfortunately, our current understanding of AI models is very limited. We conducted a comprehensive analysis involving 12 distinct AI models, encompassing object detection, translation, and text-to-image generation tasks. Our findings revealed that smaller AI models can achieve equal or even better results compared to larger models while offering a significant reduction of carbon emissions. This highlights the potential for environmental savings by prioritizing smaller models. These findings underscore the importance of considering the environmental impact of AI models and encourage the adoption of strategies such as using smaller models and optimizing workload schedules to reduce carbon emissions. By prioritizing sustainability in AI development and deployment, we can work towards a greener and more sustainable future. |
K-band Absolute Magnitude Relations of Red Clump Stars Separated by Age | https://www.jsr.org/hs/index.php/path/article/view/5196 | Tiffany Zhang; Nicole Spinelli | 11-30-2023 | Red clump (RC) stars form a distinguishable clump on the color-magnitude diagram, making it a good distance indicator. Currently, the two main absolute magnitude estimation methods in the I-band (700–900 nm) conflict: one assumes a constant RC magnitude as supported by empirical data and one relates magnitude with other physical characteristics as supported by theoretical models. Studies attribute these discrepancies to population effects, such as dust, and recommend the K-band (2000–2400 nm) to minimize them. Past studies analyzed relations between the K-band magnitude, color, metallicity, and age, including those stratified by age at 2 Gyr. This study aims to investigate these different relations to clarify trends from past studies, discover new trends, and compare them to similar relations in the I-band. After analyzing cluster RC data from Gaia DR3, 2MASS, and Gaia-ESO DR5, K-band magnitude exhibits insignificant correlation in all relations (p>0.05) but has the greatest dependence and the least root mean square error (RMS) with metallicity in the old RC. Significant correlation was found between I-band magnitude and metallicity for all RC and young RC (p<0.05), especially the latter (R2 = 0.804). This consistency with theoretical trends suggests weaker I-band population effects than previously believed. Overall, these three relations yield more accurate predictions than the mean magnitude. Thus, studies cannot solely rely on the mean K-band or I-band magnitude to estimate distance, and magnitude relations stratified by age can potentially lead to more accurate RC distance estimations and a more accurately calibrated distance ladder. |
Towards Generalizable Crop-Agnostic Plant Disease Recognition: An Unsupervised-Learning Approach | https://www.jsr.org/hs/index.php/path/article/view/5472 | Dongmin Choi; Blessina Devakirubai | 11-30-2023 | In recent years, machine learning techniques have been incorporated in the agricultural industry to automate plant disease recognition. However, most existing frameworks are constrained to the recognition of certain species’ diseases, such as those of tomatoes, due to the severe imbalance in the published dataset. These methods tend to exhibit a strong bias towards specific plants, which require extensive retraining if the model were to accurately classify the disease of other plants. To ensure the system functions in a more realistic context, where images of various plants would be given, it is crucial to develop a generalized system that can recognize a diverse set of plants. To address the aforementioned problem, in this research paper, I propose a novel crop-agnostic plant detection framework. The method leverages contrastive learning, a type of unsupervised learning, to extract discriminative features from plant images regardless of their species. Moreover, the generalizable solution is capable of successfully distinguishing diseases from a dataset with imbalanced class and category. The method achieved an accuracy of 85.88% in the plant village dataset. Through experimental results, it has been demonstrated that the proposed method outperforms existing state-of-the-art methods by a significant margin. |
Cytogenetics and Molecular Diagnosis in Horse Infertility | https://www.jsr.org/hs/index.php/path/article/view/5319 | Jiwon Choi; Mayra Cerna, Terje Raupsepp | 11-30-2023 | As the popularity of horse breeding stays steady, many breeders and owners send their horses samples to cytogenetics analysis for signs of infertility or other genetic abnormalities. Here, we report three cases of horses that were subjected to chromosome analysis due to infertility issues. Unfortunately, in the case of the H304 mare, the horse has a normal 64, XX female karyotype and no chromosomal abnormality was observed to explain the infertile issue. In the case of the H305 mare, the horse has a 64, XY male karyotype which indicates genetically male and no sign of chromosomal abnormality under cytogenetic analysis. However, PCR analysis indicates the loss of the SRY in the Y chromosome. This is a typical male to female sex reversal and one of the most common genetic sex abnormalities in horses. In the H306 mare, the horse has only one X chromosome; 63, XO, called X monosomy. This is the most common sex chromosomal abnormality in horses. The combination of clinical cytogenetic analysis and the use of PCR are the strongest tool to determine the chromosomal abnormality in the equine industry and the case H305 is a good example to support how these two different approaches compensate each other to generate a reliable diagnosis. Determination of genetic abnormalities using two techniques will help horse breeders and equine practitioners to make the most informed decisions about breeding plans. |
Period poverty’s impact on the futures of its most marginalized groups How the upward mobility of women and girls in the US is influenced by period poverty. | https://www.jsr.org/hs/index.php/path/article/view/5877 | Karuna Damle; Jaz Riley | 11-30-2023 | The main objective in this paper was to conceptualize how period poverty impacts the upward mobility of women and girls in the United States. With the topic of period poverty gaining awareness and the idea of menstruation becoming more mainstream, the impacts of menstruation on a menstruator’s future must be acknowledged also. One of the main ways to identify these impacts, specifically from a financial perspective, is through socioeconomic growth as it demonstrates an intersection between a person’s economic stability and the opportunities they have been given from a younger age. In this paper, period poverty and its influence on upward mobility is broken into demographic groups of girls in middle and high school, women in college, low-income women, and incarcerated women. This research connects the areas of period poverty and upward mobility to identify how financial precarity and menstruation limit the futures of its most struggling groups. |
Machine Learning for Risk Prediction of Cardiovascular Disease: Current Advances and Future Prospects | https://www.jsr.org/hs/index.php/path/article/view/5177 | Abhaya Saridena, Ananya Saridena; Jothsna Kethar | 11-30-2023 | One of the main causes of death worldwide is cardiovascular disease (CVD). Effective treatment of this global concern depends on early detection, as well as management. Currently, people with established heart issues are treated by physicians and other medical experts, with detection at later stages of CVD. However, the burden of cardiovascular disease treatment can be significantly reduced if it was possible to accurately estimate a patient's CVD risk at the initial stages. Machine learning techniques have emerged as a viable method for improving CVD risk prediction, which enables treatments to be more effectively tailored to each individual patient's needs. An in-depth analysis of current research on machine learning applications for CVD risk prediction is provided in this publication. The paper discusses the benefits of applying machine learning techniques, various prediction algorithms, performance assessment, and current research limits. Our findings suggest that machine learning methods are useful for predicting CVD risk and have the potential to improve clinical judgment, which may help to lessen the burden of cardiovascular disease in the future. This research also helps to shape the medical field by providing insights on treating similar deadly diseases using AI and machine learning models. |
Improving Deforestation Detection Accuracy in Noisy Satellite Images with Contrastive Learning-based Approach | https://www.jsr.org/hs/index.php/path/article/view/5440 | Jitae Kim, Lim Lee, Sihu Park; Lenny Musungu | 11-30-2023 | Deforestation, the large-scale destruction of trees, has far-reaching biological and environmental consequences that pose a significant threat to the environment. Accurate deforestation detection is crucial for successful conservation initiatives and effective land management. Over the last decade, numerous deforestation detection methods utilizing spaceborne photography have been proposed. However, these methods tend to be sensitive to unique image noise in the satellite domain by virtue of the diverse aerial characteristics and air qualities in different regions. To solve this problem, we propose a novel noise-robust deforestation detection framework with a contrastive-learning based approach. The proposed framework consists of two phases: contrastive learning, which aims to extract similar feature embeddings for the same category, proceeded with transfer learning in order to develop the deforestation classifier. Remarkably, the proposed contrastive learning approach successfully handles noisy input satellite images during the feature extraction process. Upon conducting validation, we have found that the proposed method outperforms existing deforestation detection methods by a significant performance gap, highlighting the effectiveness of the proposed contrastive learning approach. |
Deep-Learning Based Automatic Ergonomic Assessment Using Webcam Data | https://www.jsr.org/hs/index.php/path/article/view/5240 | Owen Lu; Clark Hochgraf | 11-30-2023 | Primarily due to increasing computer use, people are spending more and more time sitting in front of a desk every day. However, prolonged sitting has been associated with tiredness, hypertension, and pain in areas like the lower back or shoulders. These symptoms arise for a variety of reasons, but musculoskeletal disorders in particular are largely associated with poor postures. The adverse results caused by poor postures can be controlled with proper training and monitoring. This study attempts to provide automatic ergonomic assessment using only webcam data. Since laptops, desktops, and phones are now widely available and equipped with built-in cameras, this solution is accessible and convenient for most people. More importantly, automatic posture assessment may help to prevent conditions associated with poor posture by giving reminders whenever improper posture occurs. To create our model, we make use of Mediapipe, which provides a solution to identifying keypoint locations from an image. By training our MLP classifier on this key-point data, we achieved a 96.96% test F1 score, indicating that our system serves as a convenient way to assess posture while maintaining high performance. To illustrate our results, we perform a final video classification by overlaying the model’s pre-dictions on each frame. |
Image Quality Enhancement via Machine Learning: A Unified Approach to Super-Resolution, Denoising, and Low-Density Enhancement | https://www.jsr.org/hs/index.php/path/article/view/5541 | Woochan Jung; John Blofeld-Watson | 11-30-2023 | Problem: The escalating demand for high-quality images across various applications has underscored the necessity for advanced image enhancement techniques. Traditionally, denoising, super-resolution, and low-density enhancement, the three key image enhancement techniques, have been approached independently, resulting in separate developments for each. Unfortunately, a unified framework that seamlessly combines all three techniques and surpasses individual method performance has been lacking. Proposed Idea: The objective of this research is to develop a unified image enhancement framework that not only unites these techniques but also substantiates its superiority over existing individual methods through an extensive series of experiments. The proposed method utilizes cascade autoencoder architectures to generate high-quality enhanced images. In addition, an auxiliary artifact type prediction module has been introduced to enhance the noise-awareness, resulting in improved accuracy. Result: The proposed method demonstrates superior performance in achieving state-of-the-art accuracy when evaluated against three image quality metrics on various public datasets. Additionally, the practical application of the proposed method showcases its efficacy in effectively solving real-world problems. |
A Method for Training Object Scale Estimation System using Feature Extraction Enhancement with Depth Estimation | https://www.jsr.org/hs/index.php/path/article/view/5144 | Kyungryun Kim | 11-30-2023 | In recent years, machine learning-based object scale estimation has been growing in popularity, as the significance of the technology lies in its potential for use in many industry fields. Although several methods have been proposed, the possible applications of this technique are limited due to its insufficient accuracy. Hence, a human-level accurate system is needed for the technology to be applied in the real-world domain. This research paper proposes a novel object scale estimation system that incorporates the feature extractor, disentangled feature maps, depth estimator, object localizer, and ground truth depth map. The input of the proposed system is an image, which is inputted into the feature extractor to create disentangled feature maps. These feature maps are then extracted by the depth estimator to generate a depth map, and by the object localizer to create a predicted bounding box around the object. The trained feature extractor can extract disentangled size-related features from the inputted image by jointly training the depth estimator and object localizer. The use of disentangled features boosts the performance of the proposed system. In addition, we propose an actual scale converter module to calculate the actual size of the inputted object. Throughout the experiments, the proposed method has proven that it is superior compared to other state-of-the-art methods. The proposed method achieves an IoU (Intersection over Union) value of 0.8113 on the COCO dataset. |
Kavain Hydroxylation in Kava Metabolism: Computational Analysis | https://www.jsr.org/hs/index.php/path/article/view/5419 | Youlin Feng | 11-30-2023 | Kava, a non-alcoholic beverage derived from the Piper methysticum plant, commonly also known as Kava, has a prominent role in the cultures of Oceania due to its calming and soothing effects. These psychoactive properties have sparked interest beyond Oceania and in the scientific community, who see potential for medicinal applications. However, alongside these beneficial effects, consumption of Kava has been linked to potential hepatotoxicity, raising safety concerns. Understanding the cause of this hepatotoxicity requires a detailed exploration of Kava's metabolic processes, specifically those involving kavain, its primary constituent. Recent studies have found the hydroxylation of kavain to 12-hydroxykavain as a key step in Kava's metabolic pathway. Yet, the precise mechanism of this conversion and the hydroxylation intermediates involved remain poorly understood. To address this knowledge gap, our study employed Spartan, a computational chemistry software, to model the hydroxylation process. We analyzed the stability and chemical properties of the proposed reaction intermediates, providing a detailed view of this critical phase of metabolism. Our analysis reveals that three of the five proposed intermediates appear stable, suggesting they may play significant roles in the hydroxylation process. This finding also enabled us to narrow down the possible reaction pathways of hydroxylation. Having a better understanding of the key step of Kava metabolism could guide the development of safer, more effective Kava-based products, balancing the therapeutic potential of Kava with a reduced risk profile. |
Impact of Non-Thermal Particle Acceleration on Radiative Signatures of AGN Jet-Cloud Interactions | https://www.jsr.org/hs/index.php/path/article/view/5208 | Krish Jhurani; Moninder Modgil | 11-30-2023 | This study investigates the complex dynamics of AGN (Active Galactic Nucleus) jet-cloud interactions, particularly focusing on the impact of non-thermal particle acceleration on the resulting radiative signatures. We utilize advanced computational simulations, tracking changes in jet properties and emissions over a span of 0.2 Myr (millions of years). The research design incorporates the modeling of jet-cloud interactions, with a key focus on variations in the jet's density, velocity, and magnetic field. Findings reveal a two-fold increase in the magnetic field strength up to ~5 μG due to cloud incorporation, which, coupled with an elevated non-thermal particle population, enhances synchrotron emissions, shifting the spectral index from 2.2 to 2.4. Inverse Compton scattering saw a 30% increase within the first 0.125 Myr, reflecting in an abrupt X-ray and gamma-ray emissions spike. Furthermore, the jet's light curve flux variability in the X-ray band showcased an initial peak increase of about 28% by 0.175 Myr, settling to a 20% increase by 0.2 Myr, attributable to cloud disruption and absorption. Conclusions drawn from these findings confirm our hypothesis that non-thermal particle acceleration dramatically influences the radiative signatures of AGN jet-cloud interactions .It underscores the necessity of considering such acceleration processes in modeling AGN jet-cloud interactions and posits that these changes could be instrumental as observational indicators, thereby contributing to more accurate interpretations of AGN activity and evolution. |
The Role of Government in Combating Child Labor: India as a Case Study | https://www.jsr.org/hs/index.php/path/article/view/5501 | Aaliya Gupta | 11-30-2023 | The issue of child labour has been a persistent thorn in India’s growth story. Despite the existence of several national and international level legislations pertaining to this issue, completely eradicating the practice of employing child labour has been a difficult and arduous task. This policy paper attempts to explore the reasons behind the persistence of this issue, analyse the adverse impacts on children engulfed in this practice and further suggest some policy-based solutions to this issue by looking at the impact of landmark court cases. |
The Relationship Between College Experiences and Middle-Aged Entrepreneurs’ Success | https://www.jsr.org/hs/index.php/path/article/view/4708 | Alexander Slater; Soo Park | 08-31-2023 | This study aims to explore the relationship between success in the world of entrepreneurship and the college experience. Colleges have been growing in cost in recent years and it becomes even more imperative to explore the value of a college education when pursuing a career in entrepreneurship. This study collected data using semi-structured interviews with questions revolving around various characteristics learned during college. The data was analyzed with a thematic analysis that was meant to identify the overarching characteristics that entrepreneurs felt were the most important factors for their success. The study concluded that the most important factors for success as an entrepreneur were interpersonal skills, diversification of perspectives, and critical thinking skills. These results demonstrate that college is valuable for the development of well-rounded entrepreneurs and potentially informs future curricula. |
The Impact of the 2009 US-backed Coup on the Political, Social, and Economic Spheres of Honduras | https://www.jsr.org/hs/index.php/path/article/view/4876 | Nashla Turcios | 08-31-2023 | This qualitative study explores the perspectives of seven Honduran citizens regarding the 2009 coup in Honduras, with a focus on themes of political instability, economic struggles, social polarization, migration, and international intervention. The participants expressed a range of views on the coup and its aftermath, with some highlighting the negative impact of the coup on Honduran democracy and others suggesting that it represented a necessary corrective measure. The study also examines the role of the United States, in the coup and its aftermath, with a majority of participants expressing negative sentiments towards US intervention in Honduras. |
Falling Out of Postural Instability: Evaluating the Contribution of Somatosensation to Standing Balance in Parkinson's Disease | https://www.jsr.org/hs/index.php/path/article/view/4914 | Katherine Shi, Andrew Monaghan; Daniel Peterson | 08-31-2023 | People with PD (PwPD) experience a variety of motor symptoms, including postural instability, impaired gait, tremors, and falls. Falls among PwPD are especially debilitating, as they can result in fracture risk, increased progression of the disease, and even death. Previous research has demonstrated that the somatosensory system, consisting of tactile sensation (which is responsible for feelings of touch and pressure) and proprioceptive feedback (which is important in joint position sense), is crucial for reactive balance control. The primary goal of this project was to determine the unique contributions of the tactile and proprioceptive systems to standing balance control in PD. Participants at the Gait and Balance Disorders Lab at Arizona State University were asked to maintain their balance while experiencing 3 sensory vibration conditions from vibrotactile transducers 1) a control condition with no vibration, 2) vibration underneath the feet to disturb tactile sensation, and 3) vibration on top of their feet (dorsiflexor tendon) to manipulate proprioception. Another goal was to identify predictors of somatosensory impairment during standing balance (i.e., participants affected most by sensory vibration) by associating clinical characteristics with change scores in balance outcomes from the no vibration-control condition to the tactile and proprioceptive stimulation conditions. The results of this study indicate that vibrotactile stimulation had minimal impacts on standing balance responses. This study also found few predictors of somatosensory impairments. Further research is needed to enhance clinical efficiency in designing treatments that have the most impact on improving balance control and preventing falls. |
Quantifying the Dynamics of Data Augmentation Hyperparameters for Facial Expression Recognition | https://www.jsr.org/hs/index.php/path/article/view/4646 | Ryan Lin; Peter Washington | 08-31-2023 | Automated recognition of facial expressions is a central component of systems used in an expanding array of domains. For a computer to automatically recognize affect, copious amounts of data are required to successfully train the model. It can often take a lot of work to collect and label data. In recent years, researchers have applied numerous data augmentation strategies to increase the diversity of the data within training datasets. Here, I examined the most common data augmentation strategies to determine which strategies result in higher performance for the facial expression recognition machine learning model. I first tested each data augmentation technique by itself and compared their performances. I next ran an ablation study with the augmentation strategies. I then analyzed the effect of dataset size on the marginal contribution of data augmentation. I find that augmentation does not always improve performance. When the dataset size is small, it results in a degradation of model performance. The accuracy of models with data augmentation starts to outperform the models with no data augmentation when the training dataset size is greater than a certain threshold. These results highlight the importance of considering dataset size when applying data augmentation to computer vision. |
Test Anxiety and Perfectionism | https://www.jsr.org/hs/index.php/path/article/view/4839 | Melissa Landsman; Grace Escamilla, Justin Matyas | 08-31-2023 | Past research demonstrates that test anxiety is an important component impacting academic performance. Perfectionism has been investigated as a factor associated with test anxiety. The purpose of this study is to contribute to an identified research gap by examining the distribution and association of perfectionism and test anxiety among high school students. This study included 74 high school students with the majority consisting of juniors and seniors in a suburban high school in Northeastern United States. Using the Westside Test Anxiety Scale and Short Almost Perfect Scale, 41% self-reported high test anxiety and 66% self-reported perfectionism in the high school student sample. Correlational analyses revealed a strong positive association (r = .47) between perfectionism and test anxiety, a strong positive association (r = .49) between discrepancy perfectionism (i.e., self-criticism) and test anxiety, and a weak positive association (r = .18) between standards perfectionism (i.e., striving) and test anxiety. The findings are consistent with existing studies of other age samples and further the understanding of test anxiety and its association with perfectionism in high school students. Implications for school-based interventions to manage test anxiety and perfectionism and directions for future research are considered. Keywords: Test Anxiety, Perfectionism |
An Analysis of Costs and Solutions to High Recidivism Rates in Florida | https://www.jsr.org/hs/index.php/path/article/view/5008 | Sofia Krivitsky, Aarush Santoshi, Sophia Li, Matthew Diomidous; Krassimir Penev | 08-31-2023 | Recidivism affects a significant portion of convicted offenders. It represents the culmination of many factors like social isolation, a lack of work opportunities, and drug abuse. This project evaluates the risks and costs of recidivism in Florida's correctional facilities in terms of the physical cost of incarceration and the social cost that imprisonment has on communities. We derive and analyze data from six main sources: past recidivism trends from the Florida Department of Corrections, data of police employment, data of median income data, drug arrest data, and data of unemployment trends. We then evaluate the feasibility of measures involving drug rehabilitation, educational programs, police employment increases to discourage recidivism and facilitate reentry into society by using symbolic regression to calculate future trends. The R-squared values ranged from 65.4% to 97.3%. A primary component analysis (PCA) was performed with post hoc Kaiser–Meyer–Olkin, which yielded a value < 0.6, and Bartlett’s Sphericity, which yielded a value <<< 0.0001, tests, suggesting a substantial correlation. A Monte Carlo analysis was then performed to predict the total instances of recidivism through 2024. This research showed that increasing police efficiency and investing in drug rehabilitation services should be prioritized by the state of Florida. |
The Coevolution of the Understanding and Treatment Modalities for Phantom Limb Pain | https://www.jsr.org/hs/index.php/path/article/view/4479 | Rachel Rui Hong; Chloe Cavanaugh | 08-31-2023 | Phantom Limb Pain (PLP), an inappropriate sensation in a missing limb, is a post-amputation phenomenon that occurs in up to 80% of amputees. The specific sensations vary from person to person, but some common reported sensations include warmth or coldness, itching, tingling, and electric shock. Some patients also perceive a specific position or movement of the phantom limb. Most amputees experience PLP with varying degrees of intensity, frequency, and duration. About 5-10% of amputees continue to have severe PLP for many years after amputation. As technology and scientific understanding have evolved, phantom limb pain has become better understood over the centuries, from its first mention from Ambroise Pare in the 1600s to the usage of a variety of medication, medical therapy, and surgery options available today. Although the field of medicine does not yet have a curative treatment for PLP, treatment modalities have advanced from the use of wooden pegs to the latest and advanced prosthetics. By summarizing the growing understanding and evolution of treatment modalities for the medical condition from its first mention in the 16th century to the current 21st century, we can begin to appreciate the years of study and collaboration to current knowledge of phantom limb pain. |
The Impact of Election Laws on the Turnout of Young People An analysis of the relationship between election laws and youth turnout across the United States in the 2020 election | https://www.jsr.org/hs/index.php/path/article/view/4720 | Alyvia Bailey | 08-31-2023 | The twenty sixth amendment of the United States Constitution says that no citizen over the age of 18 years old shall be denied the right to vote. Despite this constitutional amendment, there are many barriers that hinder this act of voting. Multiple types of barriers exist: location, time, money, and most important to this research, legislative barriers. Based on the voter turnout of all Americans across the country, it appears that these barriers seem to disproportionately affect young people and minorities. The low turnout rates among youth and minorities are a serious threat to the effectiveness of our representative democracy in the United States. Since the raw data for the turnout of minorities does not exist, the effects laws have on their turnout will not be determined in this paper. Minorities, however, will still be discussed in the review of literature because of their importance in regards to voter turnout. |
Distractor-Specific Single Neuron Activity Predicts Visual Working Memory Task Outcomes | https://www.jsr.org/hs/index.php/path/article/view/4901 | Jia Lakhamraju; Mare Stewart | 08-31-2023 | This paper explores the relationship between neural activity and behavioral performance in the form of visual working memory (VWM) task outcomes, by answering the question: Are there any significant differences in the firing rates of individual neurons during the distractor presentation period of a VWM task between success and error trials that can predict the outcome of a trial? Distractor-specific single neuron firing rates during a VWM task were analyzed to answer this question. A logistic regression was used to identify the predictive capability of neural firing rate on trial outcome with the neural activity of 51 cells from the lateral prefrontal cortex (LPFC) of a primate. This study found that a best-fit logistic model could predict the behavioral performance of the primate (success or error of the VWM task) with 63.01% accuracy, with additional machine learning techniques producing scores upwards of 68% accuracy. Moreover, greater firing rates in response to the distractor, indicating less efficient distractor suppression, accompanied the error trials of the VWM task. This suggests that stronger neural responses to task-specific distractors can hinder the attentional filtering required for efficient working memory, supporting previous research that found that distractor suppression is a mechanism that heavily influences WM efficiency. These findings indicate that people, particularly children, with disorders that affect WM capacity such as ADHD may experience stronger neural responses to distractors, and therefore inefficient distractor suppression, at the single neuron level when engaging in goal-oriented behaviors, which can significantly impact learning and other developmental processes. |
Media Coverage of Macular Degeneration in Countries of Different Developmental Stages | https://www.jsr.org/hs/index.php/path/article/view/4620 | Miriam Chang | 08-31-2023 | Macular Degeneration (AMD) is a chronic degenerative eye disorder that may not be well reported to the public. Current literature regarding media coverage of eye conditions tends to examine general visual impairment (ex. Tillery, 2017) instead of specific disorders such as AMD. The current research aims to examine how news media cover and frame information regarding AMD. Therefore, the researcher conducted an inductive content analysis on newspaper articles with the keyword AMD in the most circulated newspaper in three countries: The United States, Singapore, and Bangladesh. The three countries were chosen based on their varying socioeconomic status as the are categorized as developed, developing, and underdeveloped countries respectively. Results showed that the developed country reported more on treatments while the developing and developed countries reported mostly on the prevention of AMD. Writing strategies examined from all three news sites indicate episodic framing as the most prominent among all news sites and there is no difference in that aspect. Results are further analyzed, discussed, and implications were made as well. |
A Continuous Oral-fluid Monitoring of Glucose (O.M.G.) Device with Near-field & Bluetooth Communication Capability | https://www.jsr.org/hs/index.php/path/article/view/4805 | George Cheng | 08-31-2023 | Around 34 million Americans have Type 2 Diabetes (T2D), while 88 million adults have prediabetes. Unlike the traditional invasive needle method, our proposed salivary glucose-monitoring device, OMG, can facilitate self-monitoring through a noninvasive method via Bluetooth modulation using cost-effective material (Nafion, Polydimethylsiloxane [PDMS], Bluetooth chips). The electrodes designed were coated with Glucose Oxidase (GOx), where a biological redox reaction occurs after being in contact with salivary glucose. When the interdigitated electrode (IDE) connects to the Bluetooth circuit, the impedance changes and modulates the electromagnetic reflection from the course, reflecting it as the “change of resistance” (which is proportional to the glucose concentration). Afterward, commercial chemical methods, ex-vivo, and in-vivo styles were employed to assess viability and usability. Data were assessed by creating several different comparisons between OMG and existing alternatives. Scanning Electron Microscope (SEM) images captured OMG GOx’s morphology, vector multimeters were used to collect data, and Glucose Assay Kits (Colorimetric) were used for OMG comparative analysis. NOREC (software) transfers measured fluctuations into graphical and numerical data. Testing results suggest that the trendline is reliable: R2 = 0.9292 for colorimetric and R2 = 0.9673 for our Performance Tests (ex-vivo and in-vivo), which was better than the gold standard: R2 = 0.8823. Further, we conducted multiple resistance tests, in which resistance and voltage significance was averaged to be p < 0.001 and p < 0.01, respectively. The non-invasiveness and portability demonstrate the necessity of developing such applications and novel, cost-effective smartwatch-based alternatives. |
A Case Study on the Efficacy and Usage of Assistive Technologies in Howard County Schools, MD | https://www.jsr.org/hs/index.php/path/article/view/4987 | Daniel Bi; Callie Casper | 08-31-2023 | Assistive technology is equipment that is designed to improve the capabilities of students with disabilities. For many students with disabilities, these technologies enable essential life skills such as daily communication and independence inside and outside of the classroom. This study assesses the efficacy, usage, and implementation of assistive technology in Howard County Public Schools (HCPSS) in Maryland, in order to determine any potential barriers and deficiencies towards the effective implementation of the said devices. A voluntary sample of 59 members of 1200 HCPSS staff was asked questions about the assistive technologies used in the county, their effectiveness, potential barriers towards implementation, training given, and available resources. Responses generally indicated that assistive technologies were beneficial, with the 83% of respondents selecting 4 or 5 out of 5 for the effectiveness of assistive technologies in academic and social contexts. Respondents elaborated that technologies allowed students with severe disabilities to communicate, socialize, work independently, and improve reading and writing skills. On the other hand, drawbacks such as distractions and dependencies created by the technologies were noted. Respondents felt confident towards the resources and support provided by the county, noting an assistive technology department and specialists available for support. However, respondents commonly reported that they were under-trained, received only occasional, limited workshop sessions, and were constantly behind on training. Thus, recommendations were drafted to improve training and staff awareness towards assistive technologies, such as required comprehensive training sessions for special education staff and a universal assistive technology guide to be provided. |
Montessori Education: A Study on the Impact of Montessori Preschools in Washington on Short-Term Emotional Development in Children | https://www.jsr.org/hs/index.php/path/article/view/4717 | Casey Tebben | 08-31-2023 | This research paper investigates how Montessori preschool education impacts short-term emotional development in children ages 3-5 in Washington state, compared to conventional forms of education. This study employs a multimethod approach including a quantitative parental survey measuring common adolescent behaviors on a five-point Likert scale along with a qualitative Montessori educator survey coded for key themes of Montessori education that support emotional development. The findings from the quantitative parental survey show that while both Montessori and conventional preschool students are on track for emotional development, there is a significant disparity as Montessori students were found to have higher emotional development. Furthermore, the educator survey suggests that there are four main aspects of Montessori curriculum: respect, independence/individualization, community/diversity, and conflict resolution. Overall, the results of this study provide valuable insights on the effectiveness of Montessori education in regard to promoting emotional development in preschoolers and how it could be further utilized to inform educational practices and curriculum in conventional preschools. |
Women's Labor Participation in Ghana and Effects on Human Development: A Focus on Entrepreneurship | https://www.jsr.org/hs/index.php/path/article/view/4889 | Audrey Wang; Antonio Bojanic, Bridget Hamill | 08-31-2023 | The purpose of this paper is to examine the gender-rooted challenges that women entrepreneurs face in Ghana and to analyze the impacts that increasing women’s rights and entrepreneurship have had on the country’s economy. Several indicators (including labor force participation, women's seats in national parliaments, the Women Business and the Law index, primary completion rate, and the gender inequality index) of gender equality and the prevalence of women’s entrepreneurship are compared with economic and human development trends. Through statistical regressions, the paper’s findings show a positive correlation between greater income equality and women’s seats in national parliament, as well as with the human development index, and conclude that the best way to reduce gender inequality is to increase the number of women in positions of power, as well as improve the education and skill development for women. |
Effect of Brainwave Entrainment Using Binaural Beat Stimulation on Short-Term Memory | https://www.jsr.org/hs/index.php/path/article/view/4589 | Meta VanGilder; Maren LaLiberty, Mindy Ray | 08-31-2023 | Auditory brain entrainment is a response to a rhythmic stimulus that increases the amount of a single brainwave frequency. It has been proposed to act as a key mechanism to heighten sensory intake. Auditory brain entrainment can be induced by listening to binaural beat stimulation. It has been shown that there is a positive effect on memory caused by using binaural beat stimulation. There has been research done on memory in young adults using binaural beat stimulation, but little in adolescents. Due to the lack of research on the effects of brain entrainment on memory in adolescents, this study attempts to show that a teen's working memory will improve after listening to a 40 Hz binaural beat for five minutes as compared to 0 Hz and 4 Hz. Participants were randomly assigned into three groups (0Hz, 4Hz, 40Hz) prior to the experiment. Participants completed the Sternberg Short-term memory test.The participants then listened to a binaural beat of their designated group for 5 minutes, after which they completed the second trial of the Sternberg Short-term memory test. The average change of speed recall and errors from no binaural beat to after the binaural beat stimulus was analyzed using a T-test of independent means. The results do not support the hypothesis that listening to binaural beat stimulation of 40Hz would improve short-term memory compared to 4Hz and 0Hz. |
Detecting Emotions in Audio Data of Patients with Post Traumatic Stress Disorder using Convolutional Neural Networks | https://www.jsr.org/hs/index.php/path/article/view/4776 | Rohan Gupta | 08-31-2023 | As humans, we have an effortless ability and a high accuracy to identify another human's emotions through the tone, pitch and pace of their speech, even the emphasis and stress placed on each word. However, people with a traumatic experience suffering from Post Traumatic Stress Disorder (PTSD), 24.4 million people in the USA, can often repress emotions making it difficult for therapists to identify their patients genuine emotions and to treat them appropriately. Using an upcoming field of emotion detection in Artificial Intelligence (A.I.), I identified the human emotions from speech. Instead of using an audio transcription based model, I opted for a newer image based model, RESNET-18, which is widely used and utilizes spectrograms to preserve the subtleties in speech, critical in distinguishing emotions. To train the model, I used the RAVEDESS dataset which consists of wav files with eight different emotions. I was able to achieve an overall accuracy of 82% (greater than human detection by 25%). Specifically, I achieved 99% for no stress class (happiness), 97% for neutral class, (neutral, calm, and surprised), and 8\5% for stressed class (fearful, sadness, anger, disgust). I also found that the model got an accuracy of 87% when only trained on males, with continued training an overall accuracy above 90% is definitely achievable. In conclusion, it is possible to find the emotions of PTSD patients, and in the future, continued research can help improve the lives of people who are not able to express their true emotions. |
Roscovitine’s Effect on D. melanogaster with TDP-43 Nuclear Loss Amyotrophic Lateral Sclerosis | https://www.jsr.org/hs/index.php/path/article/view/4965 | Mira Ramachandran, Satvika Aruva; Jessica Eliason | 08-31-2023 | Amyotrophic lateral sclerosis (ALS) is a neurological disease that leads to motor neuron death, causing muscle atrophy and paralysis. The majority of ALS patients die from respiratory failure within 2–5 years. By 2040, the incidence of ALS is predicted to increase worldwide by 70%. ALS has no cure. TDP-43 protein dysfunction is present in ~97% of ALS patients. Past ALS research focused on TDP-43 aggregation in the cytoplasm of neuronal cells; however, loss of TDP-43 from the nucleus is now considered the main contributor to neurodegeneration. Drosophila larvae with dTDP-43 nuclear loss exhibit locomotion deficits and reduced levels of cacophony, a neuronal calcium channel required for neurotransmitter release. When cacophony was restored in dTDP-43 nuclear loss larvae, locomotion was rescued. Roscovitine is a drug that increases calcium influx in neuronal calcium channels, essentially performing the same function as increased cacophony. The purpose and novelty of this research are to determine if a roscovitine supplement can improve the locomotion of a TDP-43 nuclear loss ALS model of Drosophila melanogaster. The larval locomotion assay was used to validate the ALS symptom of muscle weakness. The movements of larvae on an agar plate were recorded. Using ImageJ, the displacements and speeds of the larvae were determined. Results indicate that ALS larvae fed roscovitine performed significantly better on the locomotion assay than ALS larvae fed normal food (p-value < 0.0001). This research provides insight into the role of neuronal calcium channels in TDP-43 nuclear loss and calcium channel agonists’ potential in treating ALS. |
The Relationship Between College Experiences and Middle-Aged Entrepreneurs’ Success | https://www.jsr.org/hs/index.php/path/article/view/4708 | Alexander Slater; Soo Park | 08-31-2023 | This study aims to explore the relationship between success in the world of entrepreneurship and the college experience. Colleges have been growing in cost in recent years and it becomes even more imperative to explore the value of a college education when pursuing a career in entrepreneurship. This study collected data using semi-structured interviews with questions revolving around various characteristics learned during college. The data was analyzed with a thematic analysis that was meant to identify the overarching characteristics that entrepreneurs felt were the most important factors for their success. The study concluded that the most important factors for success as an entrepreneur were interpersonal skills, diversification of perspectives, and critical thinking skills. These results demonstrate that college is valuable for the development of well-rounded entrepreneurs and potentially informs future curricula. |
The Impact of the 2009 US-backed Coup on the Political, Social, and Economic Spheres of Honduras | https://www.jsr.org/hs/index.php/path/article/view/4876 | Nashla Turcios | 08-31-2023 | This qualitative study explores the perspectives of seven Honduran citizens regarding the 2009 coup in Honduras, with a focus on themes of political instability, economic struggles, social polarization, migration, and international intervention. The participants expressed a range of views on the coup and its aftermath, with some highlighting the negative impact of the coup on Honduran democracy and others suggesting that it represented a necessary corrective measure. The study also examines the role of the United States, in the coup and its aftermath, with a majority of participants expressing negative sentiments towards US intervention in Honduras. |
The Limits of AI Content Detectors | https://www.jsr.org/hs/index.php/path/article/view/5064 | Hongyu Wu; Tom Flanagan | 08-31-2023 | As ChatGPT became a popular and powerful language model used by people worldwide in 2023, the problem of students using it to cheat on schoolwork became palpable. While many existing AI content detectors can detect AI-generated texts, such as GPT-2 Content Detector and GPTZero, the accuracy of an AI content detector in detecting generated essays that have been post-edited by humans is unknown. This research discovered the limitations of the GPT-2 Content Detector and answered the question, “How does human post-editing of AI-generated high school English essays affect the result of an AI content detector?” Ten English essays were generated using ChatGPT Plus based on prompts from high school English teachers. Each essay was then edited in 5 different ways to create pairs of unedited and edited essays. All unedited and edited essays were evaluated using GPT-2 Output Detector Demo, and then the results from the detector were studied and analyzed. It was found that introducing spelling mistakes in generated essays and processing the essays with QuillBot will make the result of AI content detectors less accurate. The findings from this research can be used as a guide for companies developing AI-generated text detectors, making them more accurate when dealing with edited generated text. The findings can also be helpful for schools and educators, because knowing that students can edit essays to bypass AI content detectors, educators can develop new ways to examine students’ writing ability. |
Impact of Gender Bias in Training Data for Machine Learning Models predicting Myocardial Infarction | https://www.jsr.org/hs/index.php/path/article/view/4532 | Victoria Harding Bradley | 08-31-2023 | The use of biomarkers reference ranges derived from clinical trials to detect and diagnose the presence of cardiovascular disease (CVD) and the occurrence of myocardial infarction (MI) is well established. However, the predominance of older male participants in these trials has been shown to contribute to increased rate of misdiagnoses among women. The application of Machine Learning (ML) to medical diagnosis promises the potential to improve accuracy. However, ML also has the potential to perpetuate this problem of gender bias in trial data leading to worse outcomes for female patients. This research found that models trained using data containing only male patient data were less accurate at predicting MI among female patients than those trained using data sets with greater representation of females. For the model trained only with male patient data, this increased false negative rate corresponds to 2% of female patients with MI not being correctly diagnosed. Addressing this issue will require (a) the collection of more female patient data to support the construction of training data sets which accurately reflect the patient population (b) consistent reporting of gender mix and other demographic information such as age when ML model performance is reported. |
IQ as an Indicator of Academic Stress, Study Habits, and Academic Success | https://www.jsr.org/hs/index.php/path/article/view/4745 | John Shadwell; Justin Matyas, Grace Escamilla | 08-31-2023 | Intelligence quotient (IQ) and its impacts have been studied heavily in previous research. However, studies have not yet sufficiently applied IQ to an academic environment, especially in high-school aged students. To fill this gap in the field of study, this study utilized a mixture of qualitative and quantitative methods to measure trends in the behavior of students at different IQ levels and evaluate the strengths and weaknesses of student populations. The study’s participants, comprising of 21 high schoolers, voiced and quantified their opinions on their personal experiences regarding stress, study habits, and academic success. Ultimately, the trends in high IQ and low IQ groups suggest that IQ is a valuable statistic in educational environments which can be used by educators to improve student weaknesses. The exposure of IQ scores in academic settings would provide crucial insight into the behavioral trends of student groups and can make a lasting positive change in education. |
Interleukin-6 Levels in Nasal Secretion as a Potential Diagnostic Tool for Alzheimer’s Disease Exploring the Feasibility and Clinical Significance of IL-6 Measurements in Nasal Secretions | https://www.jsr.org/hs/index.php/path/article/view/4925 | Lailla Burka; Jessica Lancaster | 08-31-2023 | Alzheimer's disease (AD) is a debilitating condition affecting millions worldwide, and early detection is crucial for effective treatment and management. Due to the cluster of amyloid beta plaques and neurofibrillary tangles, the neurons in the brain begin to undergo gradual and irreversible neuronal loss. This is why early detection of AD is crucial for effectively treating and managing the disease. However, the current diagnostic methods, such as imaging scans, are not always accessible and affordable and cannot be diagnosed early on. This study investigated the potential of nasal secretion as a non-invasive diagnostic tool for AD. The study employed two assays, Bicinchoninic acid (BCA) and Enzyme-Linked Immunosorbent Assay (ELISA), to measure protein and Interleukin-6 (IL-6) levels in nasal secretion samples. Blood samples were also collected to serve as a comparison tool. The findings suggest that nasal secretion may be a promising diagnostic tool for AD, with elevated levels of IL-6 found in the nasal secretion of mice with AD-like pathology. The total interleukin-6 concentration in Alzheimer’s disease mice was between 0.1367 pg/mL and 0.14233 pg/mL, compared to the nasal secretion in the healthy mice cohort between 0.094 pg/mL and 0.11 pg/mL. The study contributes to the research on the IL-6 biomarker in AD. It shows that utilizing nasal secretion as a diagnostic tool could allow for early detection and improved quality of life for patients. Future research should investigate the accuracy of nasal secretion as a diagnostic tool and compare it to other current methods. |
Rice Fields as Mosquito Density Indicators for Malaria Prediction in Nigeria: An Anthropological View | https://www.jsr.org/hs/index.php/path/article/view/4695 | Gabrielle Wong; Heidi Cooke | 08-31-2023 | The World Health Organization (WHO) identifies high-risk areas for disease outbreaks in African countries (WHO, 2019a). Sub-Saharan Africa, including Kebbi state in Nigeria, is particularly susceptible to vector-borne diseases (WHO, 2019a). Malaria is a significant health concern in Kebbi state, where rice fields serve as breeding sites for mosquitoes (CDC, 2020). This paper proposes an early warning system that utilizes satellite imagery and household data to predict mosquito populations in Kebbi State. Integrating machine learning and satellite imagery can inform disease control strategies and public health interventions. Additionally, this approach presents opportunities for anthropological research into the political aspects of malaria and rice farming in Kebbi state, Nigeria. Anthropologists can analyse the socio-political and economic factors influencing malaria persistence while considering the perspectives of local communities. Understanding the intricate relationships between farmers, mosquitoes, and public health officials can contribute to the development of more effective and equitable malaria control strategies. The poverty rate of approximately 72.0% in Kebbi state further complicates healthcare accessibility (Nigeria Health Watch, 2021). By focusing on this region and employing a multidisciplinary approach, this paper aims to address the urgent health challenges and support sustainable solutions for malaria prevention in Kebbi state, Nigeria. |
Determining the Efficacy of Polyphenols in Inhibiting the Aggregation of Amyloid Beta Proteins | https://www.jsr.org/hs/index.php/path/article/view/4848 | Gayathri Renganathan; Bridget Liu, Bhoomi Jain, Sumayyah Ismail, Kavya Patel, Ayush Patel, Alyssa Halvorsen, Nandini Mannem | 08-31-2023 | Alzheimer's Disease is caused by an aggregation of amyloid beta and tau proteins in the brain. Polyphenols, a broad class of naturally-existing compounds, have been shown to inhibit the aggregation of those proteins. This project aims to focus on expressing different combinations of those proteins, as well as assaying those proteins for aggregation inhibition using polyphenols such as curcumin, caffeic acid, epigallocatechin gallate (EGCG), and more to determine which polyphenol is most effective in doing so. We chose to use these polyphenols because of their past precedence in other work, along with their widespread prevalence. However, this project focused more on the biological and in-vitro aspect of polyphenols inhibiting amyloid beta, such as conducting multiple assays including Congo Red, Avoidance, and Dynamic Light Scattering in order to receive tangible results. Through our studies, we found that polyphenols do produce an inhibitory effect on the aggregation of amyloid-beta. |
Exploring the Role of Interaction in Engagement and Satisfaction Within Virtual Learning Environments | https://www.jsr.org/hs/index.php/path/article/view/5014 | Abe Shin | 08-31-2023 | Empirical studies have recognized the significant role of student engagement and interaction in determining satisfaction within high-quality, synchronous virtual learning environments. A prevailing concept in research surrounding synchronous virtual satisfaction suggests that interaction is a key driver of learner engagement. However, very few research has delved into the underpinnings of this relationship. This study, therefore, aims to examine the potential mechanisms that link student engagement and satisfaction through interactions within a synchronous virtual learning environment. A sample of 200 South Korean secondary school students, comprising a balanced gender ratio (51% male, 49% female), was included in this research. The findings demonstrate a series of positive correlations among student engagement, interaction, and satisfaction. Furthermore, mediation analysis revealed a positive relationship between student engagement and satisfaction, with interaction serving as a mediating variable. The study's results suggest that high school students derive benefits when teachers take active steps to engage them. The findings of this study could guide future planners of synchronous virtual learning environments to prioritize student engagement as a strategic initiative for boosting satisfaction levels. |
An Analysis of Interventional Clinical Trials and Trends in Potential Glioblastoma Therapeutics | https://www.jsr.org/hs/index.php/path/article/view/4500 | Ananya Uddanti | 08-31-2023 | Glioblastoma Multiforme (GBM), an aggressive malignant tumor of the central nervous system, carries a poor prognosis. This research aimed to analyze the current and future trends of interventional GBM clinical trials. Analyzed trials met the following eligibility criteria: registration between January 1st, 2012, and July 19, 2022, of interventional study type, in trial phases II-IV, and were either completed, recruiting, or active. Of 1,728 GBM-related trials, 336 were eligible. A majority of trials were of open-label masking (89.58%, n=301), academia-sponsored (44.94%, n=151), and systemic interventions (87.20%, n=293). Despite an increasing trend in the number of trials initiated, other findings provided a basis for concern: negligible focus on localized interventions, minimal funding by industry, and widespread use of open-label maskingof funding by industry and minimal trials examining localized therapies hinders the availability of interventions and the improvement of treatment techniques, respectively. Likewise, open-label masking is not the standard, nor is the use supported in clinical trial studies, as it does not eliminate placebo responses. These conclusions are the basis of concerns and areas of improvement in the GBM clinical trial landscape. |
Factors Contributing to Heightened Anxiety in Airline Pilots During the COVID-19 Pandemic | https://www.jsr.org/hs/index.php/path/article/view/4729 | Madeleine Hontz; Jennifer Osborne | 08-31-2023 | This study analyzed the specific effects that the COVID-19 pandemic has had on the mental health of airline pilots. Using an exploratory research methodology, the researcher sent a self-designed questionnaire to seventeen (17) currently registered pilots that flew before, during, and after the pandemic. The intent of the survey was to measure anxiety levels and explore causes of anxiety. The results showed that there were three (3) common causes of post-pandemic anxiety: lack of job security, decreased social interactions, and lack of control. This study analyzed mental health, which is less commonly talked about within the aviation industry. Future research should continue to explore the impacts of the COVID-19 pandemic on airline pilots, and how to manage a comparable situation again in the future. |
Analyzing Twitter Data to Understand Stigmatization of Schizophrenia Before and After Elon Musk | https://www.jsr.org/hs/index.php/path/article/view/4637 | Melinda Mo; Daniel Olivo | 08-31-2023 | Stigmatization of mental health has become an increasingly prevalent issue in recent years, particularly on social media. The perpetuation of online stigma has significant negative impact on those with schizophrenia, affecting their social lives, self-esteem, ability to succeed in treatment, and more. One major factor that may affect stigmatization on social media is how content moderation is perceived by the users of the platform, as well as the social norms surrounding acceptable discussions on said platform. This relationship has not yet been examined in the context of schizophrenia stigma on Twitter. Elon Musk’s recent acquisition of Twitter has provided an opportunity to do just this, as his public statements and goals for the platform have suggested increased “freedom of speech” and decreased restrictions on content posted, changing how Twitter users perceive allowed conversations. The current study analyzed discussions of schizophrenia on Twitter before and after Elon Musk’s acquisition, coding individual Tweets based on the extent to which they indicated a stigmatizing attitude towards schizophrenia. Main findings include a marginally significant positive association between schizophrenia stigmatization and Musk’s acquisition of Twitter, with an increase in stigmatizing attitudes. Further, in agreement with previous literature on this topic, this study reveals that the stigma of schizophrenia is widespread on Twitter both prior and following Musk’s acquisition. The results of the study may be useful in guiding social networking companies and advocacy efforts to create programs or restrictions that counters stigmatization and further protects those with schizophrenia. |
An Innovative Alternative to Plastic Straws with Bacterial Cellulose | https://www.jsr.org/hs/index.php/path/article/view/4809 | Sean Lee, Kevin Lee; Joshua Whang | 08-31-2023 | This study aims to introduce the usage of biodegradable bacterial cellulose as an alternative material to straw production. Cellulose is a crystalline linear chain polysaccharide found in various organisms with cell walls. Known for its strength and durability, cellulose is also biodegradable due to its organic nature. Through a series of different experiments that include the production of cellulose from SCOBY (symbiotic culture of bacteria and yeast) and the subsequent creation of straws from the cellulose and food-safe glue, this study proposes a more environmentally friendly alternative to plastic straws. Further experiments were done to compare the functionality of the cellulose straw to that of plastic straws and other alternatives currently in the market, including paper and metal straws. This was done using a strength test to see how much weight the straws could hold before breaking, a test to see how long the straws could maintain their integrity with water running through them, and an experiment where different drinking liquids were used. It was found that the cellulose straws displayed no loss in functionality when compared to the other straws and displayed similar levels of durability as the plastic straws. |
Exploring the Influence of East Asian Culture Tendencies to Judge Others Based on Familial Factors | https://www.jsr.org/hs/index.php/path/article/view/4994 | Hidan Kim; EunHye Song | 08-31-2023 | This study aimed to explore the influence of familial factors on prejudice among East Asians, considering the ambiguous impact of Confucian collectivism. To achieve this, a literature review was conducted to examine previous research on prejudice and its association with familial factors. The study employed the Implicit Bias Test and collected data from a voluntary sample of 33 East Asian individuals. The results of a logistical regression test (p=4.31 e -0.5) demonstrated that the participants placed considerable importance on familial factors: parental income, parental occupational prestige, and parental education. These findings indicate a significant influence of familial qualities in the judgments made by East Asians. However, further investigation is necessary to understand the specific role of Confucian culture in shaping these dynamics (Rsq =0.532). Overall, this study contributes to the existing literature and highlights the need for additional research to fully comprehend the complex interplay between familial factors, prejudice, and cultural influences among East Asians. |
Student Perceptions of Involvement in Secondary-Level Competitive Forensics Organizations | https://www.jsr.org/hs/index.php/path/article/view/4467 | Nikhil Pochana; Esohe Egiebor, Jeff Baker | 08-31-2023 | Previous literature in the field of education highlighted the impacts of student involvement in extracurricular activities on student academic and personal development; however, much of this research is oriented towards postsecondary students and not secondary-level students, and the research is broadly focused on extracurricular activities generally rather than focusing on specific categories of activities that require different levels of student involvement. This study explores specifically competitive forensics (speech and debate) and its impacts on student development at the secondary education level based on student perceptions of their own involvement. A mixed methods phenomenology was used for data collection and analysis where students responded to quantitative Likert items and qualitative short answer items through an online survey. These items collectively discussed the categories of academic development, professional and social communication skills, and mental health and personal wellbeing to explore general student development. Data analysis showed that sampled students perceived their involvement in forensics to have improved academic performance and development and generally improved social and professional communication abilities. However, the sample is in disagreement in regards to mental health and personal wellbeing; a small majority hold the perception that forensics has improved their mental health, while a significant amount hold the opposite perception. Ultimately, analysis of these student perceptions on forensics provides education professionals a greater understanding of the impacts of forensics and similar extracurriculars on secondary student development. This understanding could further opportunities for learning and development beyond the classroom through extracurriculars such as forensics. |
Distractor-Specific Single Neuron Activity Predicts Visual Working Memory Task Outcomes | https://www.jsr.org/hs/index.php/path/article/view/4901 | Jia Lakhamraju; Mare Stewart | 08-31-2023 | This paper explores the relationship between neural activity and behavioral performance in the form of visual working memory (VWM) task outcomes, by answering the question: Are there any significant differences in the firing rates of individual neurons during the distractor presentation period of a VWM task between success and error trials that can predict the outcome of a trial? Distractor-specific single neuron firing rates during a VWM task were analyzed to answer this question. A logistic regression was used to identify the predictive capability of neural firing rate on trial outcome with the neural activity of 51 cells from the lateral prefrontal cortex (LPFC) of a primate. This study found that a best-fit logistic model could predict the behavioral performance of the primate (success or error of the VWM task) with 63.01% accuracy, with additional machine learning techniques producing scores upwards of 68% accuracy. Moreover, greater firing rates in response to the distractor, indicating less efficient distractor suppression, accompanied the error trials of the VWM task. This suggests that stronger neural responses to task-specific distractors can hinder the attentional filtering required for efficient working memory, supporting previous research that found that distractor suppression is a mechanism that heavily influences WM efficiency. These findings indicate that people, particularly children, with disorders that affect WM capacity such as ADHD may experience stronger neural responses to distractors, and therefore inefficient distractor suppression, at the single neuron level when engaging in goal-oriented behaviors, which can significantly impact learning and other developmental processes. |
Media Coverage of Macular Degeneration in Countries of Different Developmental Stages | https://www.jsr.org/hs/index.php/path/article/view/4620 | Miriam Chang | 08-31-2023 | Macular Degeneration (AMD) is a chronic degenerative eye disorder that may not be well reported to the public. Current literature regarding media coverage of eye conditions tends to examine general visual impairment (ex. Tillery, 2017) instead of specific disorders such as AMD. The current research aims to examine how news media cover and frame information regarding AMD. Therefore, the researcher conducted an inductive content analysis on newspaper articles with the keyword AMD in the most circulated newspaper in three countries: The United States, Singapore, and Bangladesh. The three countries were chosen based on their varying socioeconomic status as the are categorized as developed, developing, and underdeveloped countries respectively. Results showed that the developed country reported more on treatments while the developing and developed countries reported mostly on the prevention of AMD. Writing strategies examined from all three news sites indicate episodic framing as the most prominent among all news sites and there is no difference in that aspect. Results are further analyzed, discussed, and implications were made as well. |
A Continuous Oral-fluid Monitoring of Glucose (O.M.G.) Device with Near-field & Bluetooth Communication Capability | https://www.jsr.org/hs/index.php/path/article/view/4805 | George Cheng | 08-31-2023 | Around 34 million Americans have Type 2 Diabetes (T2D), while 88 million adults have prediabetes. Unlike the traditional invasive needle method, our proposed salivary glucose-monitoring device, OMG, can facilitate self-monitoring through a noninvasive method via Bluetooth modulation using cost-effective material (Nafion, Polydimethylsiloxane [PDMS], Bluetooth chips). The electrodes designed were coated with Glucose Oxidase (GOx), where a biological redox reaction occurs after being in contact with salivary glucose. When the interdigitated electrode (IDE) connects to the Bluetooth circuit, the impedance changes and modulates the electromagnetic reflection from the course, reflecting it as the “change of resistance” (which is proportional to the glucose concentration). Afterward, commercial chemical methods, ex-vivo, and in-vivo styles were employed to assess viability and usability. Data were assessed by creating several different comparisons between OMG and existing alternatives. Scanning Electron Microscope (SEM) images captured OMG GOx’s morphology, vector multimeters were used to collect data, and Glucose Assay Kits (Colorimetric) were used for OMG comparative analysis. NOREC (software) transfers measured fluctuations into graphical and numerical data. Testing results suggest that the trendline is reliable: R2 = 0.9292 for colorimetric and R2 = 0.9673 for our Performance Tests (ex-vivo and in-vivo), which was better than the gold standard: R2 = 0.8823. Further, we conducted multiple resistance tests, in which resistance and voltage significance was averaged to be p < 0.001 and p < 0.01, respectively. The non-invasiveness and portability demonstrate the necessity of developing such applications and novel, cost-effective smartwatch-based alternatives. |
A Case Study on the Efficacy and Usage of Assistive Technologies in Howard County Schools, MD | https://www.jsr.org/hs/index.php/path/article/view/4987 | Daniel Bi; Callie Casper | 08-31-2023 | Assistive technology is equipment that is designed to improve the capabilities of students with disabilities. For many students with disabilities, these technologies enable essential life skills such as daily communication and independence inside and outside of the classroom. This study assesses the efficacy, usage, and implementation of assistive technology in Howard County Public Schools (HCPSS) in Maryland, in order to determine any potential barriers and deficiencies towards the effective implementation of the said devices. A voluntary sample of 59 members of 1200 HCPSS staff was asked questions about the assistive technologies used in the county, their effectiveness, potential barriers towards implementation, training given, and available resources. Responses generally indicated that assistive technologies were beneficial, with the 83% of respondents selecting 4 or 5 out of 5 for the effectiveness of assistive technologies in academic and social contexts. Respondents elaborated that technologies allowed students with severe disabilities to communicate, socialize, work independently, and improve reading and writing skills. On the other hand, drawbacks such as distractions and dependencies created by the technologies were noted. Respondents felt confident towards the resources and support provided by the county, noting an assistive technology department and specialists available for support. However, respondents commonly reported that they were under-trained, received only occasional, limited workshop sessions, and were constantly behind on training. Thus, recommendations were drafted to improve training and staff awareness towards assistive technologies, such as required comprehensive training sessions for special education staff and a universal assistive technology guide to be provided. |
Montessori Education: A Study on the Impact of Montessori Preschools in Washington on Short-Term Emotional Development in Children | https://www.jsr.org/hs/index.php/path/article/view/4717 | Casey Tebben | 08-31-2023 | This research paper investigates how Montessori preschool education impacts short-term emotional development in children ages 3-5 in Washington state, compared to conventional forms of education. This study employs a multimethod approach including a quantitative parental survey measuring common adolescent behaviors on a five-point Likert scale along with a qualitative Montessori educator survey coded for key themes of Montessori education that support emotional development. The findings from the quantitative parental survey show that while both Montessori and conventional preschool students are on track for emotional development, there is a significant disparity as Montessori students were found to have higher emotional development. Furthermore, the educator survey suggests that there are four main aspects of Montessori curriculum: respect, independence/individualization, community/diversity, and conflict resolution. Overall, the results of this study provide valuable insights on the effectiveness of Montessori education in regard to promoting emotional development in preschoolers and how it could be further utilized to inform educational practices and curriculum in conventional preschools. |
Women's Labor Participation in Ghana and Effects on Human Development: A Focus on Entrepreneurship | https://www.jsr.org/hs/index.php/path/article/view/4889 | Audrey Wang; Antonio Bojanic, Bridget Hamill | 08-31-2023 | The purpose of this paper is to examine the gender-rooted challenges that women entrepreneurs face in Ghana and to analyze the impacts that increasing women’s rights and entrepreneurship have had on the country’s economy. Several indicators (including labor force participation, women's seats in national parliaments, the Women Business and the Law index, primary completion rate, and the gender inequality index) of gender equality and the prevalence of women’s entrepreneurship are compared with economic and human development trends. Through statistical regressions, the paper’s findings show a positive correlation between greater income equality and women’s seats in national parliament, as well as with the human development index, and conclude that the best way to reduce gender inequality is to increase the number of women in positions of power, as well as improve the education and skill development for women. |
Effect of Brainwave Entrainment Using Binaural Beat Stimulation on Short-Term Memory | https://www.jsr.org/hs/index.php/path/article/view/4589 | Meta VanGilder; Maren LaLiberty, Mindy Ray | 08-31-2023 | Auditory brain entrainment is a response to a rhythmic stimulus that increases the amount of a single brainwave frequency. It has been proposed to act as a key mechanism to heighten sensory intake. Auditory brain entrainment can be induced by listening to binaural beat stimulation. It has been shown that there is a positive effect on memory caused by using binaural beat stimulation. There has been research done on memory in young adults using binaural beat stimulation, but little in adolescents. Due to the lack of research on the effects of brain entrainment on memory in adolescents, this study attempts to show that a teen's working memory will improve after listening to a 40 Hz binaural beat for five minutes as compared to 0 Hz and 4 Hz. Participants were randomly assigned into three groups (0Hz, 4Hz, 40Hz) prior to the experiment. Participants completed the Sternberg Short-term memory test.The participants then listened to a binaural beat of their designated group for 5 minutes, after which they completed the second trial of the Sternberg Short-term memory test. The average change of speed recall and errors from no binaural beat to after the binaural beat stimulus was analyzed using a T-test of independent means. The results do not support the hypothesis that listening to binaural beat stimulation of 40Hz would improve short-term memory compared to 4Hz and 0Hz. |
Detecting Emotions in Audio Data of Patients with Post Traumatic Stress Disorder using Convolutional Neural Networks | https://www.jsr.org/hs/index.php/path/article/view/4776 | Rohan Gupta | 08-31-2023 | As humans, we have an effortless ability and a high accuracy to identify another human's emotions through the tone, pitch and pace of their speech, even the emphasis and stress placed on each word. However, people with a traumatic experience suffering from Post Traumatic Stress Disorder (PTSD), 24.4 million people in the USA, can often repress emotions making it difficult for therapists to identify their patients genuine emotions and to treat them appropriately. Using an upcoming field of emotion detection in Artificial Intelligence (A.I.), I identified the human emotions from speech. Instead of using an audio transcription based model, I opted for a newer image based model, RESNET-18, which is widely used and utilizes spectrograms to preserve the subtleties in speech, critical in distinguishing emotions. To train the model, I used the RAVEDESS dataset which consists of wav files with eight different emotions. I was able to achieve an overall accuracy of 82% (greater than human detection by 25%). Specifically, I achieved 99% for no stress class (happiness), 97% for neutral class, (neutral, calm, and surprised), and 8\5% for stressed class (fearful, sadness, anger, disgust). I also found that the model got an accuracy of 87% when only trained on males, with continued training an overall accuracy above 90% is definitely achievable. In conclusion, it is possible to find the emotions of PTSD patients, and in the future, continued research can help improve the lives of people who are not able to express their true emotions. |
Roscovitine’s Effect on D. melanogaster with TDP-43 Nuclear Loss Amyotrophic Lateral Sclerosis | https://www.jsr.org/hs/index.php/path/article/view/4965 | Mira Ramachandran, Satvika Aruva; Jessica Eliason | 08-31-2023 | Amyotrophic lateral sclerosis (ALS) is a neurological disease that leads to motor neuron death, causing muscle atrophy and paralysis. The majority of ALS patients die from respiratory failure within 2–5 years. By 2040, the incidence of ALS is predicted to increase worldwide by 70%. ALS has no cure. TDP-43 protein dysfunction is present in ~97% of ALS patients. Past ALS research focused on TDP-43 aggregation in the cytoplasm of neuronal cells; however, loss of TDP-43 from the nucleus is now considered the main contributor to neurodegeneration. Drosophila larvae with dTDP-43 nuclear loss exhibit locomotion deficits and reduced levels of cacophony, a neuronal calcium channel required for neurotransmitter release. When cacophony was restored in dTDP-43 nuclear loss larvae, locomotion was rescued. Roscovitine is a drug that increases calcium influx in neuronal calcium channels, essentially performing the same function as increased cacophony. The purpose and novelty of this research are to determine if a roscovitine supplement can improve the locomotion of a TDP-43 nuclear loss ALS model of Drosophila melanogaster. The larval locomotion assay was used to validate the ALS symptom of muscle weakness. The movements of larvae on an agar plate were recorded. Using ImageJ, the displacements and speeds of the larvae were determined. Results indicate that ALS larvae fed roscovitine performed significantly better on the locomotion assay than ALS larvae fed normal food (p-value < 0.0001). This research provides insight into the role of neuronal calcium channels in TDP-43 nuclear loss and calcium channel agonists’ potential in treating ALS. |
The Relationship Between College Experiences and Middle-Aged Entrepreneurs’ Success | https://www.jsr.org/hs/index.php/path/article/view/4708 | Alexander Slater; Soo Park | 08-31-2023 | This study aims to explore the relationship between success in the world of entrepreneurship and the college experience. Colleges have been growing in cost in recent years and it becomes even more imperative to explore the value of a college education when pursuing a career in entrepreneurship. This study collected data using semi-structured interviews with questions revolving around various characteristics learned during college. The data was analyzed with a thematic analysis that was meant to identify the overarching characteristics that entrepreneurs felt were the most important factors for their success. The study concluded that the most important factors for success as an entrepreneur were interpersonal skills, diversification of perspectives, and critical thinking skills. These results demonstrate that college is valuable for the development of well-rounded entrepreneurs and potentially informs future curricula. |
The Impact of the 2009 US-backed Coup on the Political, Social, and Economic Spheres of Honduras | https://www.jsr.org/hs/index.php/path/article/view/4876 | Nashla Turcios | 08-31-2023 | This qualitative study explores the perspectives of seven Honduran citizens regarding the 2009 coup in Honduras, with a focus on themes of political instability, economic struggles, social polarization, migration, and international intervention. The participants expressed a range of views on the coup and its aftermath, with some highlighting the negative impact of the coup on Honduran democracy and others suggesting that it represented a necessary corrective measure. The study also examines the role of the United States, in the coup and its aftermath, with a majority of participants expressing negative sentiments towards US intervention in Honduras. |
The Limits of AI Content Detectors | https://www.jsr.org/hs/index.php/path/article/view/5064 | Hongyu Wu; Tom Flanagan | 08-31-2023 | As ChatGPT became a popular and powerful language model used by people worldwide in 2023, the problem of students using it to cheat on schoolwork became palpable. While many existing AI content detectors can detect AI-generated texts, such as GPT-2 Content Detector and GPTZero, the accuracy of an AI content detector in detecting generated essays that have been post-edited by humans is unknown. This research discovered the limitations of the GPT-2 Content Detector and answered the question, “How does human post-editing of AI-generated high school English essays affect the result of an AI content detector?” Ten English essays were generated using ChatGPT Plus based on prompts from high school English teachers. Each essay was then edited in 5 different ways to create pairs of unedited and edited essays. All unedited and edited essays were evaluated using GPT-2 Output Detector Demo, and then the results from the detector were studied and analyzed. It was found that introducing spelling mistakes in generated essays and processing the essays with QuillBot will make the result of AI content detectors less accurate. The findings from this research can be used as a guide for companies developing AI-generated text detectors, making them more accurate when dealing with edited generated text. The findings can also be helpful for schools and educators, because knowing that students can edit essays to bypass AI content detectors, educators can develop new ways to examine students’ writing ability. |
Impact of Gender Bias in Training Data for Machine Learning Models predicting Myocardial Infarction | https://www.jsr.org/hs/index.php/path/article/view/4532 | Victoria Harding Bradley | 08-31-2023 | The use of biomarkers reference ranges derived from clinical trials to detect and diagnose the presence of cardiovascular disease (CVD) and the occurrence of myocardial infarction (MI) is well established. However, the predominance of older male participants in these trials has been shown to contribute to increased rate of misdiagnoses among women. The application of Machine Learning (ML) to medical diagnosis promises the potential to improve accuracy. However, ML also has the potential to perpetuate this problem of gender bias in trial data leading to worse outcomes for female patients. This research found that models trained using data containing only male patient data were less accurate at predicting MI among female patients than those trained using data sets with greater representation of females. For the model trained only with male patient data, this increased false negative rate corresponds to 2% of female patients with MI not being correctly diagnosed. Addressing this issue will require (a) the collection of more female patient data to support the construction of training data sets which accurately reflect the patient population (b) consistent reporting of gender mix and other demographic information such as age when ML model performance is reported. |
IQ as an Indicator of Academic Stress, Study Habits, and Academic Success | https://www.jsr.org/hs/index.php/path/article/view/4745 | John Shadwell; Justin Matyas, Grace Escamilla | 08-31-2023 | Intelligence quotient (IQ) and its impacts have been studied heavily in previous research. However, studies have not yet sufficiently applied IQ to an academic environment, especially in high-school aged students. To fill this gap in the field of study, this study utilized a mixture of qualitative and quantitative methods to measure trends in the behavior of students at different IQ levels and evaluate the strengths and weaknesses of student populations. The study’s participants, comprising of 21 high schoolers, voiced and quantified their opinions on their personal experiences regarding stress, study habits, and academic success. Ultimately, the trends in high IQ and low IQ groups suggest that IQ is a valuable statistic in educational environments which can be used by educators to improve student weaknesses. The exposure of IQ scores in academic settings would provide crucial insight into the behavioral trends of student groups and can make a lasting positive change in education. |
Interleukin-6 Levels in Nasal Secretion as a Potential Diagnostic Tool for Alzheimer’s Disease Exploring the Feasibility and Clinical Significance of IL-6 Measurements in Nasal Secretions | https://www.jsr.org/hs/index.php/path/article/view/4925 | Lailla Burka; Jessica Lancaster | 08-31-2023 | Alzheimer's disease (AD) is a debilitating condition affecting millions worldwide, and early detection is crucial for effective treatment and management. Due to the cluster of amyloid beta plaques and neurofibrillary tangles, the neurons in the brain begin to undergo gradual and irreversible neuronal loss. This is why early detection of AD is crucial for effectively treating and managing the disease. However, the current diagnostic methods, such as imaging scans, are not always accessible and affordable and cannot be diagnosed early on. This study investigated the potential of nasal secretion as a non-invasive diagnostic tool for AD. The study employed two assays, Bicinchoninic acid (BCA) and Enzyme-Linked Immunosorbent Assay (ELISA), to measure protein and Interleukin-6 (IL-6) levels in nasal secretion samples. Blood samples were also collected to serve as a comparison tool. The findings suggest that nasal secretion may be a promising diagnostic tool for AD, with elevated levels of IL-6 found in the nasal secretion of mice with AD-like pathology. The total interleukin-6 concentration in Alzheimer’s disease mice was between 0.1367 pg/mL and 0.14233 pg/mL, compared to the nasal secretion in the healthy mice cohort between 0.094 pg/mL and 0.11 pg/mL. The study contributes to the research on the IL-6 biomarker in AD. It shows that utilizing nasal secretion as a diagnostic tool could allow for early detection and improved quality of life for patients. Future research should investigate the accuracy of nasal secretion as a diagnostic tool and compare it to other current methods. |
Effects of Work-Family Conflict on Working Women | https://www.jsr.org/hs/index.php/path/article/view/4329 | Jean Kim | 05-31-2023 | This paper is mainly about the work-family conflict women face in this society. This paper shows the relationship between work-family conflict and various factors such as social support, turnover intention, and low job engagement. To find the effects of work-family conflict on working women, the survey was sent out to the people who currently have a workplace. The majority of the participants were women, as the research’s main focus was on working women. The results proved the positive correlation between work-family conflict and turnover intention. In addition, surprisingly, the survey showed that the control variables such as age, tenure, gender, and the number of children had insignificant impacts on the work-family conflict. |
The Behavioral and physiological impacts of the hormesis of chemical contaminants on embryonic zebrafish | https://www.jsr.org/hs/index.php/path/article/view/4409 | Akshay Kumar; Leya Joykutty , Juliana Caulkins | 05-31-2023 | Pharmaceutical chemicals are being produced, consumed, and excreted in human civilization at an increasing rate. These chemicals have the capacity to accumulate, especially in environments such as freshwater systems, but there have not been any major responses to this threat yet as the present concentrations of the chemicals is not viewed as dangerous. Previous research has shown that the developing concentrations of chemicals is an issue, supporting that these chemicals, though not present in large doses, have impacts on exposed organisms. However, prior research has not been conducted to examine the specific effects of chemicals at hormetic concentrations on freshwater organisms. “Hormetic concentration” defines the concentrations of chemicals at specific levels where the response to a low dose of chemical differs from the response to the high dose, and these were the ranges of concentration that were tested in this experiment. Zebrafish were acquired at zero days post fertilization, transferred to the medium containing the appropriate concentration of chemicals for the group that they would be a part of, and used as a model for aquatic organisms to show the resulting chemical, neural, and physical response to the chemical concentrations. The zebrafish were euthanized via bleaching and freezing prior to seven days post fertilization. The results of this experiment show that there is an ecological risk associated with the environmental accumulation of pharmaceutical chemical contaminants that is inherent to their use in human civilization, a result which makes it clear that this issue needs to be addressed. |
Solving Partial Differential Equations for Physical and Chemical Problems Using Physics-Informed Neural Networks | https://www.jsr.org/hs/index.php/path/article/view/4200 | Xiaorui Yang; Haotian Chen | 05-31-2023 | Numerous physical and chemical problems at a high school level can be described by ordinary differential equations (ODEs) and partial differential equations (PDEs). However, the underlying equations troubled high school students because they often lack advanced mathematical skills, such as discrete calculus. Our goal is not to elaborate on those skills, but to offer a shortcut to the solution. In this paper, we demonstrated the use of Physics-Informed Neural Networks (PINNs), a neural network which solves the PDEs by incorporating the PDEs into the loss functions. The heat transfer equation and second order chemical kinetics are the two chosen model problems for high school seniors. Using PINNs, we were able to solve these two problems without recurring to university math. Hence, we strongly recommend peers to employ this method for physical or chemical problems for high school students and beyond. |
The Aerospace Industry’s Impact on 20th Century American Society | https://www.jsr.org/hs/index.php/path/article/view/4268 | Aniket Martins | 05-31-2023 | Since the dawn of mankind, the stars have been an inspiration for humanity. From the studies of the Greeks and the observations of the Indians and Chinese to Da Vinci’s plans and the research of the Wright Brothers, exploring the sky, space and stars has always been at the forefront of human ingenuity. In the United States, the idea of flight exploration began in the early 1900s: a true embodiment of the American dream. This paper examines developments in politics, economics and social movements in 1900s America while contrasting claims with counter arguments and exposing continuities in U.S. history to discuss the impact of the aerospace and defense industry on U.S. society. From Women’s Rights and Civil Rights to military and economics, the growth of the aerospace and defense industry paralleled a period of radical growth for American society creating lasting changes in the process. |
Mass-Market Augmented Reality: The Difficulty behind its Integration and the Path to Success | https://www.jsr.org/hs/index.php/path/article/view/4905 | Roman Guthrie McNerney; Brandon Galang | 05-31-2023 | The failure of Google Glass changed the path of augmented reality (AR), delaying its integration into a mass market by years. Google Glass contained numerous technical limitations that companies are still facing today. The product also showcased the social issues that come with the technology. Shared privacy concerns among many cause consumer reluctance, with information tyrants such as Google leading and largely controlling AR development. In addition to privacy concerns, health concerns steer people away from the technology. Worse yet, the many negative connotations associated with AR give it a stigma that causes major social limitations. Without normalization of the technology, people will not be interested to invest large sums of money in a product centered on convenience rather than purpose. This lack of purpose and perceived unknowns, combined with the pragmatic elements of a low battery life and glitchy, bulky design, makes the technology unappealing. Companies today are attempting to circumnavigate these problems in multiple ways. Some are attempting to create a product with a centralized purpose that solves a problem. Others are using already established industries such as the smartphone or gaming market to sell a more manageable product. Some companies have abandoned the idea of selling AR products, and are instead using it as a service. Augmented reality is a field that still must develop due to its initial setbacks, compelling companies to become creative with the technology’s usage. The consumer market is not adapted to wearable AR, making normalization necessary for further progression in the field. |
Stem Cells and Regenerative Medicine in the Treatment of Musculoskeletal Disorders | https://www.jsr.org/hs/index.php/path/article/view/4223 | Pranay Mehta; Jothsna Kethar | 05-31-2023 | Regenerative medicine is a field of medicine focused on the repair or replacement of damaged or diseased cells, tissues, and organs through the use of various medical technologies. These technologies include stem cell therapy, tissue engineering, and gene therapy, among others. Millions across the globe are plagued with musculoskeletal disorders (MSD) with ranging debilitating effects that are detrimental to the functionality of one's life. The healing process of MSD can be arduous and sometimes worse than the injury itself. The various methods of treatment including stem-cell based therapy and the origin and composition of these stem cells has been reviewed in this paper, in order to present a way in which the natural healing process of MSD can be amplified and catalyzed. |
A study on US Mass Shooting using data analysis and machine learning | https://www.jsr.org/hs/index.php/path/article/view/4321 | Andrew Fang | 05-31-2023 | Many years ago, mass shootings have become one major problem in our country. In 2021, more than 45,000 people were murdered in mass shootings. And I started to wonder, why are people doing this? If we can get some clues with existing data, it might help prevent future tragedies from happening. In many shooting incidents, the shooters seem to massacre without any reason. Many people wonder if it’s related to the murderer’s mental health. I started to gather some data and found two datasets about mass shootings and mental health on Kaggle, a public data-sharing website. First, I performed data analysis and statistical testing with the two datasets To further investigate the relationship between mass shootings and mental health, I fitted a linear regression model with the merged datasets. I found out that there’s an obvious correlation between these two variables, which means mental illness was one of the direct reasons that caused mass shootings. In addition, I want to help people avoid mass shootings. So I made a linear regression model, which helps to predict how many total victims there will be based on input factors, like location, race, age, etc. Using this model, people can put more security in dangerous locations to best avoid mass shootings. |
The Application of Artificial Intelligence and Machine Learning to Anesthesiology | https://www.jsr.org/hs/index.php/path/article/view/4403 | Srinithya Kothapalli; Dr. Rajagopal Appavu PhD. | 05-31-2023 | This research paper explores the application of artificial intelligence (AI) and machine learning (ML) in anesthesiology. AI and ML have the potential to improve patient outcomes and enhance clinical decision-making by enabling anesthesiologists to monitor patient vital signs in real-time, predict the likelihood of complications, and optimize drug dosages to minimize side effects and enhance efficacy. The Hypotension Prediction Index algorithm is a compelling example of how AI and ML can be utilized to improve intraoperative patient care. However, there is a need for further research and validation to ensure the safety and efficacy of these technologies in clinical practice. Future advancements in AI and ML techniques are likely to result in more sophisticated and accurate predictive models, decision support tools, and monitoring systems that will ultimately benefit patients undergoing anesthesia. Overall, the application of AI and ML in anesthesiology presents a promising avenue for improving patient care and outcomes. |
The Effect of IMS on Cognitive and Behavioral Abilities of mutant Drosophila, causing Neuroplasticity Finding a Preventative Mechanism for Alzheimer’s Disease | https://www.jsr.org/hs/index.php/path/article/view/4358 | Emma Colarte Delgado, Leya Joykutty, Juliana Caulkins Caulkins | 05-31-2023 | The goal of this experiment was to determine the effect of the Intermediate Metabolic Switching (IMS) diet on the short and long-term memory of mutant Drosophila due to neuroplasticity. Neuroplasticity creates new neural networks and can be measured in ketone count. The IMS diet includes two components: fasting and a low-carbohydrate, high-fat diet. The Phenol-Sulfuric Acid Test and the Hanus Iodine Solution Test were both used to quantify two ratios, a 2:2 ratio carbs to fats, and the 4:1 ratio fats to carbs. It was hypothesized that if fruit flies are fed the IMS diet, leading to plasticity, then their overall memory and behavioral health will increase because of the amount of ketones released, increasing memory formation. Mutant Drosophila tested, which lacked the Amyloid-Precursor Protein-like gene (APPL), exhibited similarities to early-stage Alzheimer's patients. Assays include the Aversive Phototaxic Suppression Assay to measure short term memory, the Aversive Pavlovian Olfactory Assay to measure long-term memory, the Drosophila Activity Monitor software to track movement of Drosophila, the Drosophila Stress Odorent (dSO) Assay to measure mood changes, and the ß-Hydroxybutyrate Ketone Quantification assay to measure ketone levels and ensure the IMS diet worked. Results were all conclusive, establishing that the flies in the 4:1 diet were more sensitive but retain short and long term memory, showing IMS could be used as a preventative mechanism for Alzheimer’s. |
Artificial Intelligence Assisted Mobility Device Development | https://www.jsr.org/hs/index.php/path/article/view/4401 | Shivali Upadhyay; Jothsna Kethar | 05-31-2023 | Artificial intelligence is rapidly gaining attention in the world for assisting humans with tasks that they could not achieve otherwise. In the medical industry specifically, artificial intelligence has made it possible to almost connect the original human body with another perfected body. This paper is intended to summarize the different conditions that may lead to someone needing a mobility device in the first place, what companies have preexisting parts that we can repurpose for the ideal artificial intelligence assisted mobility device, and the different AI technology that we can use to build this machine. The main methods utilized to collect the data used in this paper were collecting research from various scientific journals on the different conditions that can lead to the need for a mobility device, data collected from medical technology companies, and research on different artificial intelligence tools. Combining these pieces of research from different scientific journals and technological sources, it was found that the leading causes of falls are a result of cognitive impairment and balance-related issues. It was also concluded that the main pieces of equipment, are already present and would need to be manufactured in a way that the elderly user could use it on a daily basis. The overall research concluded to find that the artificial intelligence device would need to be flexible, durable, and greatest of all, prevent the user from falling or alarm a medical professional that someone is at risk of falling. |
A First Step Toward Ontic Pluralism in Mathematical Explanation | https://www.jsr.org/hs/index.php/path/article/view/4239 | Wenshi Zhao; Blake | 05-31-2023 | Although discussions about the nature of mathematical explanation are scarce in the philosophy literature, mathematical explanation plays an integral role in the philosophy of mathematical practice and has important consequences in other branches of philosophy. Various proposals are given to describe the criteria that make certain mathematical proofs more explanatory than others; however, none has been free from objections. These proposals also differ in important ways, which leads to the divergence of the two approaches to mathematical explanation: the ontic approach and the epistemic approach. This paper analyzes the strengths and weaknesses of the popular proposals, defends the ontic approach, and proposes the ontic pluralism account. This new account addresses a significant problem of previous ontic proposals. |
Displaced By Words: How Does Media Impact Gentrification? | https://www.jsr.org/hs/index.php/path/article/view/4345 | Linxiang Sheng; Chyng Sun | 05-31-2023 | To put it simply, gentrification is a process where capital investment in a previously neglected area leads to the influx and eventual takeover of middle-class groups, displacing the original working-class residents in the area during the process. This research paper is a literature review that discusses the background of gentrification, how it is portrayed and facilitated by the media, and how it could be countered through media. I specifically examined different forms of media that can either facilitate or counteract gentrification, while closely relating these examinations with societal factors of class and race. Overall, the media has an affirmative role in gentrification, with some forms more so than others. This can be largely attributed to the fact that mainstream media typically supports the stance of the middle class, which is the primary gentrifier in the process of gentrification. The media can also be used to combat gentrification, both for promoting anti-gentrification movements and for identifying gentrification. However, there are significant challenges in these methods that are yet to be fully overcome. |
Is Gen Z in India Moving Towards Financial Independence? - A Study of Their Investment Preferences | https://www.jsr.org/hs/index.php/path/article/view/4446 | Mahek Dugar; Vinodh Madhavan | 05-31-2023 | Gen Z are financially more sophisticated than any previous generation was at their age and are only at the beginning of their journey to financial independence. With increasing evidence of Gen Z investing in India, the current study aims to explore their investment preferences. A survey was conducted for age group 15-25 asking them about their source of monthly funds, proportions and reasons for saving, investment preferences including proportions, avenues, time frame, risk perceptions and behaviour of investing. The study finds that saving habits of Gen Z are significantly different across gender, age and annual family income and they are gradually moving towards financial independence by relying on their own earnings. Consequently, we found that Gen Z’s investments were largely influenced by higher saving proportions and investing experience of their family members. We also observe that Gen Z is investing long term in assets like Equity Shares, Mutual funds, Fixed Deposit and Gold/Silver, and intraday in risky assets like Crypto. Factors like rate of return, long term gains and historical performance were found to influence their investment decisions as more than 50% of the Gen Z were found likely to invest in Growth and SIP’s of mutual funds, Growth and Value equity stocks and in Banking and Information Technology sector. Lastly, we see that majority of Gen Z follows a herd behaviour, uses new age investing apps, fearing losses find it difficult to take the first step in investing but are optimistically ready to learn and improve their investing skills. |
Brain Tumor Detection Using Convolutional Neural Network | https://www.jsr.org/hs/index.php/path/article/view/4213 | Falak Chhatre, Sudhanva Deshpande , Sidhant Malik , Grace Yan ; Suresh Subramaniam | 05-31-2023 | Early and accurate diagnosis of brain tumors, a lethal disease caused by the abnormal growth of cells in the brain, is imperative to increase survival rates. A popular method for detection, diagnosis, and treatment is magnetic reasoning imaging (MRI) because it is non-invasive and provides high-quality visuals. Unfortunately, analyzing them manually can often be time-consuming and requires medical expertise. Image classification, a subset of computer vision, is a computer’s ability to classify and interpret objects within images. It can support a doctor’s diagnosis and serve as an entry-level screening system for brain tumors. This study aims to build an accurate machine learning model to predict the existence of brain tumors from magnetic resonance images. We used the Br35H dataset to build two different convolutional neural network (CNN) models: Keras Sequential Model (KSM) and Image Augmentation Model (IAM). First, images from our dataset were preprocessed, augmented, and standardized to improve efficiency and reduce inaccuracies. Then, the data was normalized, and our models were trained. Lastly, aside from the validation accuracy and loss observed while training, we cross-referenced the accuracy of our model using the accuracy validation dataset. Of our two models, the IAM outperformed the KSM. The IAM had a validation accuracy of 97.99% and a validation loss of 4.94% on the Br35H dataset, and a 100% accuracy when classifying MRIs from the accuracy validation dataset. |
AI and the Neurobiology of Consciousness | https://www.jsr.org/hs/index.php/path/article/view/4283 | Chandni Kumar; Tom McClelland | 05-31-2023 | Artificial Intelligence (AI) is a method used to teach machines to process and experience data/information the way humans do. The claustrum, the cellular unit of the nervous system that communicates with the body through electrical patterns, is an excellent model for AI when trying to derive consciousness. It has been used as a model for neural networks to teach machines to process, experience, and process information the way people do. This paper discusses the need to understand what makes a human conscious in order to determine if an inorganic addition affects this consciousness in the face of innovations such as neural implants and other brain-computer interface technologies that aim to merge the human brain and computers. It is important to examine the impact AI has on the conscious mind and the possibility of extended consciousness. |
A First Step Toward Ontic Pluralism in Mathematical Explanation | https://www.jsr.org/hs/index.php/path/article/view/4239 | Wenshi Zhao; Blake | 05-31-2023 | Although discussions about the nature of mathematical explanation are scarce in the philosophy literature, mathematical explanation plays an integral role in the philosophy of mathematical practice and has important consequences in other branches of philosophy. Various proposals are given to describe the criteria that make certain mathematical proofs more explanatory than others; however, none has been free from objections. These proposals also differ in important ways, which leads to the divergence of the two approaches to mathematical explanation: the ontic approach and the epistemic approach. This paper analyzes the strengths and weaknesses of the popular proposals, defends the ontic approach, and proposes the ontic pluralism account. This new account addresses a significant problem of previous ontic proposals. |
Displaced By Words: How Does Media Impact Gentrification? | https://www.jsr.org/hs/index.php/path/article/view/4345 | Linxiang Sheng; Chyng Sun | 05-31-2023 | To put it simply, gentrification is a process where capital investment in a previously neglected area leads to the influx and eventual takeover of middle-class groups, displacing the original working-class residents in the area during the process. This research paper is a literature review that discusses the background of gentrification, how it is portrayed and facilitated by the media, and how it could be countered through media. I specifically examined different forms of media that can either facilitate or counteract gentrification, while closely relating these examinations with societal factors of class and race. Overall, the media has an affirmative role in gentrification, with some forms more so than others. This can be largely attributed to the fact that mainstream media typically supports the stance of the middle class, which is the primary gentrifier in the process of gentrification. The media can also be used to combat gentrification, both for promoting anti-gentrification movements and for identifying gentrification. However, there are significant challenges in these methods that are yet to be fully overcome. |
Is Gen Z in India Moving Towards Financial Independence? - A Study of Their Investment Preferences | https://www.jsr.org/hs/index.php/path/article/view/4446 | Mahek Dugar; Vinodh Madhavan | 05-31-2023 | Gen Z are financially more sophisticated than any previous generation was at their age and are only at the beginning of their journey to financial independence. With increasing evidence of Gen Z investing in India, the current study aims to explore their investment preferences. A survey was conducted for age group 15-25 asking them about their source of monthly funds, proportions and reasons for saving, investment preferences including proportions, avenues, time frame, risk perceptions and behaviour of investing. The study finds that saving habits of Gen Z are significantly different across gender, age and annual family income and they are gradually moving towards financial independence by relying on their own earnings. Consequently, we found that Gen Z’s investments were largely influenced by higher saving proportions and investing experience of their family members. We also observe that Gen Z is investing long term in assets like Equity Shares, Mutual funds, Fixed Deposit and Gold/Silver, and intraday in risky assets like Crypto. Factors like rate of return, long term gains and historical performance were found to influence their investment decisions as more than 50% of the Gen Z were found likely to invest in Growth and SIP’s of mutual funds, Growth and Value equity stocks and in Banking and Information Technology sector. Lastly, we see that majority of Gen Z follows a herd behaviour, uses new age investing apps, fearing losses find it difficult to take the first step in investing but are optimistically ready to learn and improve their investing skills. |
Brain Tumor Detection Using Convolutional Neural Network | https://www.jsr.org/hs/index.php/path/article/view/4213 | Falak Chhatre, Sudhanva Deshpande , Sidhant Malik , Grace Yan ; Suresh Subramaniam | 05-31-2023 | Early and accurate diagnosis of brain tumors, a lethal disease caused by the abnormal growth of cells in the brain, is imperative to increase survival rates. A popular method for detection, diagnosis, and treatment is magnetic reasoning imaging (MRI) because it is non-invasive and provides high-quality visuals. Unfortunately, analyzing them manually can often be time-consuming and requires medical expertise. Image classification, a subset of computer vision, is a computer’s ability to classify and interpret objects within images. It can support a doctor’s diagnosis and serve as an entry-level screening system for brain tumors. This study aims to build an accurate machine learning model to predict the existence of brain tumors from magnetic resonance images. We used the Br35H dataset to build two different convolutional neural network (CNN) models: Keras Sequential Model (KSM) and Image Augmentation Model (IAM). First, images from our dataset were preprocessed, augmented, and standardized to improve efficiency and reduce inaccuracies. Then, the data was normalized, and our models were trained. Lastly, aside from the validation accuracy and loss observed while training, we cross-referenced the accuracy of our model using the accuracy validation dataset. Of our two models, the IAM outperformed the KSM. The IAM had a validation accuracy of 97.99% and a validation loss of 4.94% on the Br35H dataset, and a 100% accuracy when classifying MRIs from the accuracy validation dataset. |
AI and the Neurobiology of Consciousness | https://www.jsr.org/hs/index.php/path/article/view/4283 | Chandni Kumar; Tom McClelland | 05-31-2023 | Artificial Intelligence (AI) is a method used to teach machines to process and experience data/information the way humans do. The claustrum, the cellular unit of the nervous system that communicates with the body through electrical patterns, is an excellent model for AI when trying to derive consciousness. It has been used as a model for neural networks to teach machines to process, experience, and process information the way people do. This paper discusses the need to understand what makes a human conscious in order to determine if an inorganic addition affects this consciousness in the face of innovations such as neural implants and other brain-computer interface technologies that aim to merge the human brain and computers. It is important to examine the impact AI has on the conscious mind and the possibility of extended consciousness. |
The Effects of Musical Genres on Emotion | https://www.jsr.org/hs/index.php/path/article/view/4383 | Michael Li | 05-31-2023 | The purpose of this research was to establish a connection between a specific genre of music and the emotions they elicit in listeners. The study included seven genres, musical theater, African tribal, pop, jazz, Chinese folk, sitar, and classical. After listening to each piece participants were asked a series of questions including their emotions when listening to it, if they enjoyed it, and if they recognized it in hopes of answering the question “How do different genres of music affect people’s mood after listening?” The participants’ responses showed that in general, listening to music would elicit positive emotions no matter the genre. Additionally, pieces that elicited more powerful reactions from the listener correlated with how enjoyable the piece was. Overall, the results of this study highlight how individuals can potentially alter their mood by enjoying music from different genres and by being aware of the factors in music that go beyond just the genre. |
Alzheimer's Disease: Why is Early Detection Important? | https://www.jsr.org/hs/index.php/path/article/view/4233 | Emma Zhang | 05-31-2023 | Early detection of Alzheimer’s disease (AD) can bring benefits to the patient by giving them time to process and prepare for the development of the disease in the future. To detect the early stages of AD, patients can take brain imaging tests, auto-encoders, genetic tests, mental state tests, and cerebral spinal fluid tests. Through these tests, patients can determine their amyloid build-up levels, tau build-up levels, possible chromosomes related to AD, and mental health illnesses related to AD. |
Caravaggio’s Loyalty to “the Truth”: The Accessibility of His Paintings | https://www.jsr.org/hs/index.php/path/article/view/4340 | Wanqing Gao; Dr. Nagel , Paul Ashton | 05-31-2023 | Caravaggio is famous for his mastering of chiaroscuro and controversial subject matters. From both a technical and social perspective, Caravaggio’s works were revolutionary. As he broke the decorums, he was redefining aestheticism and pushing the boundaries of the artistic society, sometimes also facing rejections. This paper will examine how Caravaggio committed to paint truthfully, thus, making his works accessible to the general public and changing the artistic landscape. By looking into both Caravaggio’s artistic compositions and his interactions with the society at large, this paper examines his unique loyalty to truthfulness and the consequences to his artistic choices. |
What the COVID-19 Pandemic has Taught Us About Future Health Standards | https://www.jsr.org/hs/index.php/path/article/view/4204 | Brandon Bao; Reto Asmis | 05-31-2023 | The COVID-19 pandemic has been the greatest global health crisis of the 21st century, responsible for over six million deaths and half a billion cases in the past three years. Unfortunately, the world was unprepared for the pandemic and, as a result, struggled to respond to the outbreak with effective public health measures. In order to prepare for the next pandemic, this paper seeks to explore the effectiveness of many different public health policies. This paper examines whether implementing mask policies, social distancing, targeted lockdowns, efficient testing, and strict quarantining controls are the best tactics for combating the next virus outbreak. The burden caused by the next pandemic could be radically reduced if all of these policies are implemented strategically. |
The Pathogenesis of Adrenoleukodystrophy | https://www.jsr.org/hs/index.php/path/article/view/4272 | Kyle Wang; Sajeth Dinakaran | 05-31-2023 | Adrenoleukodystrophy (ALD) is a rare, inherited disorder that affects the brain, spinal cord, and adrenal glands. It is caused by mutations in the ABCD1 gene, which provides instructions for making a protein called ABCD1, which is involved in the metabolism of very long-chain fatty acids (VLCFAs). In ALD, the body cannot properly break down and clear VLCFAs, which can lead to the accumulation of these fatty acids in the brain and other tissues. This accumulation can cause inflammation and damage to cells and tissues, leading to various symptoms. Symptoms of ALD may vary depending on the type of ALD and the severity of the condition. Common symptoms include neurological problems, such as difficulty walking, speaking, behavioral changes, and problems with the adrenal gland, such as adrenal insufficiency which is a condition in which the adrenal glands do not produce enough hormones. ALD is a progressive disorder, meaning symptoms may worsen over time if left untreated. Treatment for ALD typically involves medications and supportive care to manage symptoms and prevent complications. Sometimes, a bone marrow transplant may be recommended to replace damaged cells and tissues. Genetic testing is available for ALD and can be used to diagnose the disorder and identify people at risk of developing it. Early diagnosis and treatment can help improve the chances of a full recovery and a good quality of life for people with ALD. |
The Effects of Congenital Heart Disease on the Development of Autism Spectrum Disorder in Pediatric Patients | https://www.jsr.org/hs/index.php/path/article/view/4224 | Dhriti Shah; Jothsna Kethar | 05-31-2023 | It is a well-known fact that congenital heart disease (CHD) can cause life-long health complications, especially if it impairs other bodily functions early in life. One of these complications is the risk of developing a serious neurodevelopmental disorder known as autism spectrum disorder (AuSD). With some case studies identifying the linkage of CHD and AuSD, it has been successfully established that being diagnosed with CHD does increase a child’s chances of developing AuSD later in life. There is not a simple answer for why this occurs. However, there are several factors that can contribute to why CHD increases the risk of developing autism. Some possible explanations may include synthetic factors such as the alteration of blood flow in genetic pathways due to early cardiac surgery. These explanations can also include uncontrollable factors such as demographics, maternal conditions, and viral infections, all of which are just as likely as synthetic factors. This research, based on case studies conducted recently, further reinforces the conclusion that the diagnosis of certain lesions of CHD results in an elevated risk of developing AuSD. |
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