ikatkov/journal-of-student-research-hs-articles huggingface dataset:
Predicting the Severity of Coronavirus Cases Given Demographics and Pre-existing Conditions
Authors: Mahi Ravi, Jackie Li, Vineet Burugu, Sarvagya Goyal, Sireesh Pedapenki, Aditya Goel, Nandana Nambiar, Aadhya Subhash; Larry McMahan
Date: 10-10-2021

Beginning in early 2020, coronavirus disease (COVID-19) has rapidly spread all over the world. As of now there have been over 102.52 million confirmed cases along with 2.21 million deaths worldwide. Our objective is to create an algorithm that will predict the severity of a COVID-19 case for an individual based on demographic data such as race, age, gender, and location. Using international, national and local datasets, we collected the demographic data and organized them into their respective categories, namely age, race, gender, and location of origin. We then inputted this data into an algorithm that works around the principle of probability. Our algorithm uses such trends to develop a risk assessment and create a model. While compiling that data we noted common trends within the three demographics. Specifically, around the age thirty, cases were higher compared to other age ranges. The data collected and trends noted can be used to prioritize and prepare for patients that may be in critical danger, providing a chance for hospitals and vaccine distribution centers to preemptively address higher risk cases early.&nbsp;
Uniting the Nation- Rethinking Adversity of the Poor
Authors: Qiyang Yu; Joseph Vignolini
Date: 10-10-2021

A root cause of today’s social tensions and divisions rest with poverty. Studies suggest that that individuals who grow up in poverty-stricken families are much more likely to be in poverty during their early adulthood, and the poverty rate in African American children is astoundingly high. This paper adopts data science approaches to identify drivers behind childhood poverty in the United States, and finds that these factors tend to reinforce each other and go hand in hand with poverty. Specifically, common factors are found to be driving childhood poverty, a weak healthcare system, inadequate education resources, lack of public safety infrastructure and insufficient job opportunities.  The current social safeguard framework, supported by both the government and private institutions, appears fragmented and lacks the necessary alignment across healthcare, education, public safety and job creation. The study shows that barring a systematic approach to address the drivers of childhood poverty, the poverty problem is unlikely to be fundamentally addressed. Building on these findings, the paper calls for a number of mutually coherent policies, including introducing a more effective financing scheme for the children in poverty, creating an enabling job market environment for the poor, reforming the funding pattern of schools, creating a safe environment for all children, and enhancing health services for those living in poverty.
Comparison of Neural Network and Machine Learning Approaches in Prediction of Chronic Kidney Disease
Authors: Shreya Nag; Nimitha Jammula
Date: 10-10-2021

The diagnosis of a disease to determine a specific condition is crucial in caring for patients and furthering medical research. The timely and accurate diagnosis can have important implications for both patients and healthcare providers. An earlier diagnosis allows doctors to consider more methods of treatment, allowing them to have a greater flexibility of tailoring their decisions, and ultimately improving the patient’s health. Additionally, a timely detection allows patients to have a greater control over their health and their decisions, allowing them to plan ahead. As advancements in computer science and technology continue to improve, these two factors can play a major role in aiding healthcare providers with medical issues. The emergence of artificial intelligence and machine learning can aid in addressing the challenge of completing timely and accurate diagnosis. The goal of this research work is to design a system that utilizes machine learning and neural network techniques to diagnose chronic kidney disease with more than 90% accuracy based on a clinical data set, and to do a comparative study of the performance of the neural network versus supervised machine learning approaches. Based on the results, all the algorithms performed well in prediction of chronic kidney disease (CKD) with more that 90% accuracy. The neural network system provided the best performance (accuracy = 100%) in prediction of chronic kidney disease in comparison with the supervised Random Forest algorithm (accuracy = 99%) and the supervised Decision Tree algorithm (accuracy = 97%).
Understanding Neutrino Oscillations with Particle Accelerator Experiments
Authors: Jiwon Woo; Gyuhyeon Lee
Date: 10-10-2021

Matter-dominant universe cannot be explained with the Standard Model. In order to understand why the current universe mainly consists of matter particles, scientists turned their attention to neutrino oscillations, and conducted research on the properties of the particle and its potential relationship with the matter-antimatter asymmetry observed in the universe. In this research, the probability function of a neutrino oscillation was studied for 2-neutrino case to understand neutrino oscillation in particle accelerator experiments. For a more practical study, the neutrino oscillation probability function was calculated for two neutrino experiments and was used to verify neutrino detector positions and calculated ∆m2 which is mass difference between oscillating two different neutrinos. From this work, it was understood that detectors are located at positions with the highest probability for detecting neutrino oscillations, and it was also confirmed that neutrino were oscillating from muon neutrinos to electron neutrinos in particle accelerator experiments.
A survey to evaluate mental well being and coping strategies of adolescents during COVID-19 pandemic in Bangalore, India
Authors: Arna Bhattacharya; DR Jigyansa Ipsita Pattnaik , DR Suhas Chandran
Date: 08-03-2021

Background: The COVID-19 pandemic has brought about significant changes in the lifestyle of adolescents. Adolescence is a development stage of high vulnerability that can impact well-being later in life. Mental health plays an important role in one’s quality of life. Understanding coping mechanisms helps make a person safe and resilient from psychological distress. The present study aims to evaluate the mental well-being and coping strategies used by adolescents in India during the COVID-19 pandemic.  Methods: A cross sectional study was conducted in a school in Bangalore, India via an online survey, circulated via the class teacher. Participants included 222 adolescents with ages ranging from 13 to 19. The DASS-21 and Brief COPE scales were used to assess mental well-being and coping mechanisms respectively. The questionnaire concluded with validated general lifestyle related questions. This included inquiring relationships between students and their families, friends, academic performance, social media consumption etc. The data was collected over a period of one month.&nbsp;  Results: In the DASS-21 scoring, 31.9% (n=69), 24.8% (n=55) and&nbsp;5.4% (n=12) received scores indicating extremely severe depression, anxiety and stress respectively. Females were statistically found to be more depressed and anxious than males. Behavioural disengagement and self blame were commonly used coping mechanisms by those who were found to be psychologically distressed.&nbsp;  Conclusions: Psychological distress has been observed in adolescents in varying degrees during the COVID-19 pandemic. This should be addressed in order to prevent further distress.  Keywords: adolescents, covid-19, mental well being, DASS-21, Brief COPE, depression, anxiety, stress
Restaurateur Lockdown Blues  Impact of the COVID-19 Lockdown on the Restaurant Industry in Lucknow, India
Authors: Sukriti Ojha; Kah Ying Choo
Date: 07-01-2021

The COVID-19 pandemic has plunged the Indian restaurant industry into its worst crisis. This research study is a case study analysis on the impact of the COVID-19 lockdown on the restaurant industry in Lucknow, India. Data was gathered through an online survey of Indian respondents residing in Lucknow regarding the changes in their usage of restaurant services (actual and anticipated) before and after the lockdown. Variables compared included: frequency levels of dining out, food delivery, and monthly expenditure on outside food. In addition, the relative importance of three factors- the decline in coronavirus-related deaths, the easing of social distancing measures, and the lifting of mask requirements- on the dining out frequency was analysed. Based on the results, the three variables compared showed statistically significant declines. However, in the case of the three factors influencing dining out frequency, it was discovered that while the decline in deaths did have a statistically significant impact on dining out frequency, none of the factors were considerably important.&nbsp; Taking the results into account, it becomes imperative that restaurants enforce safety guidelines strictly and promote their actions efficiently. Innovative ideas like incorporating bento box services and immunity-boosting dishes may enable restaurants to survive through the crisis.
Comparing the Durability and Strength of Simple Adhesive Recipes and PVA-Based Glues
Authors: Bethany Elliott; Dr. Sara Fox
Date: 07-01-2021

Adhesives are essential components of factory production, for maintaining the stability of large structures, and even for pastimes such as paper-mâché crafts. Therefore, it is imperative that adhesives retain their durability and strength when under pressure. The purpose of this project was to test the tensile strength of several adhesive recipes in order to ultimately create a stronger adhesive. To test the tensile strength of each adhesive, one of the adherends had weights attached and was suspended and the amount of time that the adhesive stayed attached was recorded. After completing the experimental procedures, it was found that the flour/water adhesive, cornstarch adhesive, and the waterproof adhesives performed the best, Elmer’s glue and the Gum Arabic adhesive performed less well than the first three adhesives, and Elmer’s glue with beads did not stay attached. In conclusion, the simple adhesives recipes outperformed Elmer’s glue, most likely because they had better cohesive strength and were able to dry faster. The results of this experiment can aid in the creation of a stronger and more cost-efficient adhesive product. Based on these results, future work will be aimed towards determining the effects of environmental changes like humidity and temperature on the tensile strength.
A survey of Shanghainese dialect: its current situation and future
Authors: Tianao Gui; Yan Zhou
Date: 07-01-2021

Borge Udell, the founder of Wikitongues, questioned ‘Would Cervantes have written the same stories had he been forced to write in a language other than Spanish? Would the music of Beyoncé be the same in a language other than English?’ What he means is that every language carries a unique culture and represents a group of people. All languages and dialects are worth appreciation and preservation. Shanghainese dialect is no exception. As a native Shanghainese citizen, I believe that it is high time that we should be aware of the importance of preserving and inheriting this dialect. To achieve this goal, research about the current situation is indispensable. Therefore, I researched the current situation of Shanghainese and implicated some possible methods to protect this dialect.
Investigating the Ethics of DNA Collection by CODIS
Authors: Tanay Subramanian; Alicia Kerr
Date: 07-01-2021

America's criminal justice system has experienced controversy for decades and it seems as if the Combined DNA Index System (CODIS), an FBI criminal justice database that stores the DNA profiles of millions of Americans, is a major contributor to it. Due to CODIS, an individual’s DNA is collected and permanently stored upon arrest, resulting in major red flags like privacy violations and marginalization. However, there are potential solutions - although each has its drawbacks - to this problem, in order of increasing efficacy: mandating the DNA collection of all Americans to alleviate biases, adopting a solely fingerprint-based system as forensic evidence, and terminating CODIS entirely.
The Synergistic Effects of Rhamnolipids and Antibiotics Against Bacteria
Authors: Ella Shusterman, Abigail Mottahedeh; Merideth McCarthy
Date: 07-01-2021

Antibiotics are used to combat bacterial infections by slowing down and preventing the proliferation of bacteria. Antibiotic resistance is a threat to human health, attributed to its overuse and misuse. Altering the membrane permeability to induce antibiotic uptake may be an effective strategy used against both Gram-positive and Gram-negative infectious bacteria. Rhamnolipids (RLs) are biosurfactants produced by Pseudomonas aeruginosa. RLs surface-active properties operate by creating holes in bacterial cell membranes, increasing target cell permeability; allowing antibiotics to penetrate the cell.&nbsp;  &nbsp;  Rhamnolipids enhance the effect of antibiotics by targeting the intracellular machinery of bacteria. This project tested the susceptibility of bacteria when exposed to antibiotics with and without the addition of RLs, to quantitatively determine if RLs increase antibiotic potency. By analyzing the zones of inhibition data, the results demonstrated that RLs potentiated the antibiotics. Notably, kanamycin coupled with RLs had the most effect inhibiting bacterial growth.&nbsp;  To further assess rhamnolipid biosynthesis, a BLAST search was performed exclusively on two genes, rhlA and rhlB. These genes code for the production of two proteins necessary for rhamnolipids. The search indicated a 48% correlation with putative proteins found in Burkholderia pseudomallei. Therefore, based on the experimental results and the BLAST analysis, further research should be conducted to explore the possible role of using rhamnolipids as antibiotic enhancers. Specifically, future experiments could focus on isolating the putative proteins of B.pseudomallei to genetically modify E.coli. Furthermore, isolated studies analyzing the genes of proteins to determine their role in the pathogenicity of Burkholderia species.
New Meat on the Block: Factors Influencing India’s Gen Z’s Decision to Purchase Plant-based Meat
Authors: Nikita Dhawan; Kah Ying Choo
Date: 07-01-2021

There have been increasing concerns regarding the meat industry due to its negative influence on the environment, such as freshwater pollution, biodiversity loss, and increased methane emissions. These concerns have sparked the public’s interest in plant-based meat, the demand for which is expected to reach USD 27.5 billion by 2025. This study evaluated the factors influencing the decision of India’s Gen Z (aged 15-25) to purchase plant-based meat by conducting an online survey using a mixed method research approach. Among the eight different factors examined, the study found environmental consciousness as one of the highest-rated factors in all the three categories of respondents—combined (vegetarians and non-vegetarians), vegetarians, and non-vegetarians—in influencing their decision to purchase plant-based meat. This finding mirrors the growing environmental awareness of Gen Z globally. Health/safety was another top-rated factor for all three groups, possibly due to the increasing concern of zoonotic diseases, such as COVID-19. Conversely, price, convenience, and food curiosity were the least influential, highlighting the Indian market's unique characteristics. As a significant majority of young Indian adults live with their parents, plant-based companies targeting Gen Zs need to consider India’s family-oriented culture and the parents’ dominant role in determining meal choices at home. While companies could incorporate plant-based meat products into traditional food and well-known dishes to appeal to parents, companies can also target the more independent Gen Zs by emphasizing plant-based meat as a sustainable alternative to traditional meat. Additional nuanced marketing strategies for vegetarians and non-vegetarians have also been discussed in this paper.
The Effects of Image Augmentation on Efficiency of a Convolutional Neural Network of a Self-Driving Car
Authors: Kiaan Upamanyu; Indukala P.R.
Date: 07-01-2021

The objective of this paper was to study the effectiveness of image augmentation techniques in training a Convolutional Neural Network (CNN) of a self-driving car and identify the most suitable form of image augmentation technique, using the Udacity Car Simulator. Firstly, a dataset of augmented and non-augmented images from a training track, consisting of left-, right-, and front-facing views from the car cameras was created. Various image augmentation techniques were used: zoom, brightness, pan, flip, random (augments the image by arbitrarily choosing a technique from the previous four), and no augmentation. Secondly, training datasets consisting of the aforementioned images and a log of car turning angles, throttle, and brake were built. The final training datasets were then used with NVIDIA training method to train different CNN. The different trained networks generated steering commands from the front-facing camera of the simulation and test track had no effect on the generalization of the CNN. Lastly, different trained networks were used on the test track of Udacity Car Simulator to calculate the following variables: distance travelled, and number of crashes made by the car. After these values were acquired, an efficiency analysis was performed. The results suggested augmentation of training data is a crucial factor when it comes to the process of generalizing a model to perform tasks. Random augmentations performed the best, but a combination of flip and brightness augmentations performed equally efficiently.
Vaping and Adolescents’ Characteristics: Implications for Prevention and Intervention
Authors: Ava Chae; Janet Stark
Date: 07-01-2021

Vaping in the United States has increased in the past decade especially among teens and young adults, causing a rise in public concern for their health. What is relatively scarce in the previous research and the current discussion is the question about what groups of adolescents may be more vulnerable to vaping. This research investigates this very issue by analyzing the associations between vaping use and adolescents’ individual characteristics using a national survey of drug use among U.S. adolescents (“Monitoring the Future: A Continuing Study of American Youth (12th-Grade Survey), 2018”). The findings for logistic regression show that students who struggle with academics and skip school are more vulnerable to vaping than other students. In addition, there is a greater chance of vaping with those students going out more often than others. The amount of money students earn from a job and other work may also be increasing the chance for vaping. The findings can be valuable elements in designing a program of effective prevention and intervention of vaping in the U.S.
How does the pH of a solvent influence the solubility of turmeric in it?
Authors: Miyu Bansal; Uma Sivakumar
Date: 07-01-2021

Turmeric is a culinary spice used in many meals particularly in traditional Indian cuisine. Turmeric has a bright orange colour that is due to the presence of curcumin within it. Because of it’s bright colour, it is important to be able to easily remove turmeric stains from clothing. In my research I attempted to find the ideal conditions for removing turmeric stains and found that no investigation had been made into the impact the pH of the cleaning agent on its effectiveness.  In this investigation the solubility of turmeric in 5 different solutions was found using colorimetry. Colorimetry is a scientific technique that is used to determine the concentration of coloured solutions by the application of the Beer-Lambert law. This method allowed the solubility of turmeric to be determined, in a range of different solvents with good accuracy and precision. The experimental results showed that turmeric was more soluble in solutions with higher pH levels as the solubility in 0.2M sodium hydroxide was 17.6mg/mL and in pure ethanol was 10.1mg/mL, while the solubility in hydrochloric acid was only 0.034mg/mL.  Ultimately, this investigation shows that turmeric is more soluble in basic solutions and hence basic solvents are more effective removers of turmeric stains. A claim which was shown to be true by washing turmeric stained clothes with the solvents and comparing the cleaned clothes. This investigation also shows that turmeric could be used as a pH indicator as it has a different colour in different pH solutions.
The McGurk Effect In Relation to Musicians' Abilities
Authors: Claire Luo, Olivia Yeroushalmi; Alan Schorn
Date: 07-01-2021

The original study of the McGurk Effect, a perceptual phenomenon caused by contradictory audiovisual stimuli fusing together to create the illusion of a third sound, was carried out by psychologists McGurk and MacDonald in 1976. The results of early experiments displayed that observers used both auditory and visual signals while being spoken to, auditory signals being the sound waves entering their ears, and visual signals being how the speaker moved his face while pronouncing a word. When conflicting signals are given, a third sound is perceived, as the brain is disoriented from the different signals. The idea that musicians have superior audiovisual cortexes have led some to speculate if musicians are as susceptible to the McGurk Effect as non-musicians. To research the susceptibility of musicians to the McGurk Effect, the experiment conducted included a total of 40 subjects, 20 musicians and 20 non-musicians. The subjects were played a control video of a speaker saying “ga” and were then presented with four audiovisually incongruent videos, all containing a speaker mouthing the word “ga” with the audio recording of the speaker saying “ba” dubbed on. Two main 2x2 Chi Square tests and fifteen secondary 2x2 Chi Squares tests were run in total. The two main tests, which compared the amount of McGurk interpretations to either audio or visual interpretations, both produced a p-value of &lt;.0005. Upon further research, 25.7% of musicians reported a McGurk interpretation, as opposed to 52.2% of non-musicians, which implied that musicians are less susceptible to the McGurk effect.
The Effects of Cosmic and Ultraviolet Rays on Yeast and Seeds
Authors: Samara Steinfeld, Caroline Brustoloni, Dat Bui, Emma Chothani, Caitlin Harhai, Joseph Harrington, Amrit Kaluri, Anna Klein, Duncan LaDuke, Sein Lee, Adam Miller, Tyler Rose, William Serrano, Jason Stentz; Dr. Michael Gullo, Vince Scalzo
Date: 07-01-2021

Cosmic and ultraviolet rays are pervasive and often difficult to avoid, for atmospheric pollution has caused an increase in harmful radiation reaching the Earth's surface due to the rapid depletion of the ozone layer. Because the deterioration of the ozone layer is a recent phenomenon, it is important to understand the rays’ effects on the DNA of organisms. It is also an area of interest in the field of astrobiology as humans begin to consider the possibility of long-term exposure of crops to these types of radiation in prolonged space travel. The Bioballoon project, described in this paper, was a payload for a weather balloon built to expose samples of yeast and seeds to cosmic and ultraviolet rays in the middle to upper stratosphere. After plating the yeast and planting the seeds, it was found that although cosmic and UV radiation appeared to induce mutations in yeast genes, they do not produce significant phenotypic differences in plants.