ikatkov/journal-of-student-research-hs-articles huggingface dataset:
Artificial Intelligence Assisted Mobility Device Development
Authors: Shivali Upadhyay; Jothsna Kethar
Date: 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.&nbsp;  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
Authors: Wenshi Zhao; Blake
Date: 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?
Authors: Linxiang Sheng; Chyng Sun
Date: 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
Authors: Mahek Dugar; Vinodh Madhavan
Date: 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. &nbsp;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
Authors: Falak Chhatre, Sudhanva Deshpande , Sidhant Malik , Grace Yan ; Suresh Subramaniam
Date: 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
Authors: Chandni Kumar; Tom McClelland
Date: 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
Authors: Michael Li
Date: 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?
Authors: Emma Zhang
Date: 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
Authors: Wanqing Gao; Dr. Nagel , Paul Ashton
Date: 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
Authors: Brandon Bao; Reto Asmis
Date: 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
Authors: Kyle Wang; Sajeth Dinakaran
Date: 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.&nbsp; 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
Authors: Dhriti Shah; Jothsna Kethar
Date: 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.&nbsp;
Associations Between Biofuel Production and Sustainable Development Goals 2, 6, 7, 13, and 15
Authors: Alicja Mazurkiewicz; Ceyhun Elgin
Date: 05-31-2023

Total biofuel demand in areas like transport and energy is set to grow by almost 30% annually to reach 50 billion gallons by 2026. Biofuels' association with sustainable development has been a subject of discussion among researchers and policymakers. Even the most robust studies on this topic examine only a small number of sustainable development indicators across a limited number of countries. This study analyzes whether biofuel production could advance, impede, or have no association with targets of Sustainable Development Goals (SDG) 2, 6, 7, 13, and 15, which relate to biofuel production on a global scale. Correlations between ethanol, biodiesel, and total biofuel production datasets and 23 indicators of the selected targets in 34 of the world's largest biofuel-producing countries for 2009–2019 were compiled and analyzed in the context of the existing literature. Findings suggest that biofuel production has varying associations with SDG targets.
Investigating convergence and divergence of sequences
Authors: Jayan Gandhi; Hayk Sedrakayan
Date: 05-31-2023

Convergence and divergence questions and limit of sequences appear in many different levels of mathematics including high school calculus and college-level research topics. In this paper, we are providing different approaches and techniques to deal with limit of sequences, convergence, and divergence. We also consider several applications and different examples to explain how these techniques can be used.
Population Dynamics of Intertidal Resident Species during a Reduction in Asian Shore Crab Population
Authors: Ryan Fernandez; Alejandro Victoria
Date: 05-31-2023

Hemigrapsus sanguineus (Asian shore crab), which is native to coastal estuarine habitats along the east coast of Asia, have overtaken a wide range of the coast in the northeastern region of the United States. Intertidal population densities of Hemigrapsus sanguineus, Cancer irroratus (Atlantic rock crab), Littorina littorea (Common periwinkle), and Modiolus demissus (Atlantic Ribbed Mussel), among others, were measured at three sample sites from 8/2/22 to 11/14/22 using quadrat sampling techniques. A period of removal was enacted solely upon Sample site #1 from 9/28/22 to 11/2/22 to cause a reduction in the Asian shore crab population. During the period of removal, no statistically significant changes in Asian shore crab demographics (Carapace size/sex ratios) would be observed (p = 0.181 for carapace size changes). There would however be an 8% decrease in Asian shore crab population density within Sample site #1, comparative to a 1% increase at Sample site 2. Rock crab population density at Sample site #1 would increase by a relatively drastic 31%, whereas the Rock crab population would experience only a 7% increase at Sample site #2. The Shannon-Weiner diversity index was used to derive the effective number of species (ENS). There would be a drastic difference in change of ENS following the removal period at Sample site #1 (increase of 0.248 ENS), and the change of ENS at Sample site #2 (decrease of 0.024 ENS), suggesting the reduction in Asian Shore Crab population played a role in increased population diversity of intertidal resident species.
Utilizing Machine Learning to Predict the Number of Bikes in an Area
Authors: Tavishi Bansal; Guillermo Goldsztein
Date: 05-31-2023

Machine learning is a type of Artificial Intelligence that uses data to make predictions and improve the accuracy of its outcomes. In this article, the problem discussed is classified as supervised learning and the technique utilized is Logistic Regression. After a description detailing what supervised learning and logistic regression are, using a data set to develop a model which predicts the number of bikes a rental bike company should provide based on certain conditions is discussed. The accuracy of this model is also communicated and the challenges and how the final estimations were reached are covered.
Exploring the Acculturation Strategies Among First Generation and Second Generation  Indian Immigrants residing in the United States of America
Authors: Arjun Arya
Date: 05-31-2023

The majority of Indians living in the US came to the US during the Y2K scare close to 2000 and were first-generation immigrants who faced a very different culture than they had in India. Many people had different strategies to adapt to the newness of American Culture. This paper aims to explore and understand the similarities and differences in the acculturation strategies used by&nbsp; how first-generation parents, specifically mothers and second-generation immigrants i.e. their adolescent children. A total sample of 30 respondents reading in Bay Area (15= mothers, 15= adolescents) was taken using convenience sampling. The adolescent acculturation strategies were measured by the Bicultural Involvement Questionnaire (BIQ) (Szapocznik, Scopetta, Kurtines, &amp; Aranalde, 1978), and adult acculturation strategies were measured by the Likert scale. This questionnaire, based on a scale of 1-5, measures biculturalism and lack thereof, as well as cultural involvement and lack thereof. To analyze, a Mann-Whitney U test was carried out. Children adapted to the new American culture, whereas mothers mainly stayed with Indian culture, and children were more culturally involved than their mothers. This implies that children on the whole used their mother’s strategies about halfway through when they began to incorporate American culture into their life.
Clinical Pathology of Breast Cancer: Staging and Biomarkers
Authors: Adithi Jonnagadla
Date: 05-31-2023

Based on recent statistics, one in every eight women will be diagnosed with breast cancer in their life. Breast cancer is classified into a staging system that ranges from zero to four, which is determined by several factors. In the staging system, the clinical pathology taken and tested by the healthcare professional plays a key role in determining the gravity of the patient's case. Biomarkers provide insight into the carcinogenic cells in the person's body, such as the Estrogen receptor (ER), human epidermal growth factor (HER2), and the progesterone receptor which are discussed in this paper. Each of these biomarkers communicates a specific attribute about the tumor cells and signifies the severity and the extent of the breast cancer. Based on this research, it was proven that there is not a direct correlation, but a slight correlation between the biomarkers found in the cells with the relative stage the patient has. Studies have shown a link between cells testing HER2 positive with high-grade tumors, unfavorable prognosis, lymph node collusion, high mortality rates, and higher rates of recurrence in patients which signify a stage three or four cancer. Studies also suggested that patients who test ER positive, PR negative, and HER2 negative are more likely to have early-stage invasive breast cancer, which alludes to stage one or two clinically. A definite conclusion was not able to be obtained as more research must be conducted, however, general trends were discovered between stages and biomarkers.
Using Machine Learning to Forecast Progression from Cognitively Normal to Alzheimer's Disease
Authors: Ann Song
Date: 05-31-2023

Alzheimer's Disease (AD) affects approximately 50 million individuals worldwide and is estimated to rise to 152 million by 2050. There is currently no treatment for AD that halts the progression from cognitively normal (CN) and/or mild cognitive impairment (MCI) to AD. The ability to predict disease progression will allow for early treatment. While Machine Learning (ML) has been successful in diagnosing the cognitive state, further improvement is necessary for predicting progression. In this study, Random Forest and Bagging Decision Tree Recursive Feature Elimination (RFE) was utilized to ascertain the cognitive state and forecast progression. Clinical diagnoses, demographics, and post-processed PET and MRI scans used in this study were obtained from the Open Access Series of Imaging Studies (OASIS). The findings suggest that aging and lower levels of education are associated with higher risk. The study found that ML using post-processed MRI and PET scans, particularly RFE ML, is effective in diagnosing cognitive states with 90% accuracy. It can predict progression from CN to MCI or AD with 85% accuracy, which is significantly higher than the average reported in literature. Patients with progression from CN to AD were distinguished by elevated amyloid deposition, hippocampus and amygdala atrophy, left accumbens atrophy, thinning of the left hemisphere temporal, and enlarged inferior lateral ventricles. The study demonstrated that RFE ML is effective in diagnosing and predicting the progression of AD. Future studies will concentrate on identifying the specific regions of amyloid plaque that have the most significant impact on cognitive state and progression.  &nbsp;
Heading Towards Accountability: An Analysis of the Efficacy of Concussion Protocol
Authors: Lucy Rudolph
Date: 05-31-2023

The objective of this study was to evaluate the success of concussion protocols and accommodations, focusing on what factors were most influential. The approach will be a qualitative one, involving the use of open-ended questions and interviews to extract subjective responses. This approach was taken to encourage authentic answers and data. It concludes with an analysis of the data which reveals that while academic accommodations are beneficial, concussion protocols are not.