bluuebunny/crossref_metadata_2025 huggingface dataset:
Análise da elaboração de jogos para aprendizagem nas aulas de ciências
Authors:   , Safar Lorena Melgaço Ornelas
Published: August 2024

O uso de jogos didáticos tem sido apontado na literatura da área de Ensino de Ciências como estratégia pedagógica alternativa ao ensino tradicional. Este trabalho de mestrado tem por objetivo analisar o processo de construção de jogos por alunos do ensino fundamental, como estratégia de ensino de conteúdos de ciências, apostando na ludicidade e focando no protagonismo estudantil. O projeto consistiu em uma intervenção pedagógica realizada em uma escola pública de Contagem-MG, durante as aulas da disciplina de ciências no ensino fundamental. A pesquisa de cunho qualitativo, investigou o potencial formativo da elaboração de jogos pedagógicos pelos próprios estudantes, a partir das orientações da professora- pesquisadora. Um grupo de 35 estudantes foi convidado a participar das atividades e, após ciência dos procedimentos e assinatura das devidas autorizações (termos de consentimento livre e esclarecido e termo de assentimento), aqueles que tiveram sua participação autorizada jogaram jogos comerciais. Posteriormente, em grupos menores e sob orientação da professora- pesquisadora, desenvolveram jogos baseados em conteúdos da disciplina de ciências. A última etapa consistiu em um grupo focal, em que os participantes expressaram suas percepções sobre a experiência, tendo como ponto de partida um roteiro semiestruturado. Os dados foram constituídos a partir da observação dos encontros, do caderno de anotações da professora- pesquisadora e da gravação em áudio do grupo. Os dados foram tratados a partir da análise de conteúdo de Bardin para responder à questão de pesquisa proposta: a construção de jogos por estudantes do ensino fundamental estimula a aprendizagem de conteúdos conceituais de ciências? Conclui-se que o caráter investigativo das aulas de jogos mostrou que, se o professor organizar previamente regras claras, os jogos podem atuar como catalisadores do processo de ensino e aprendizagem, estimulando e facilitando o desenvolvimento e o conhecimento e a aplicação ativa de conhecimentos científicos, muitas vezes de difícil compreensão para os estudantes. Palavras-chave: Jogos didáticos; Ludicidade; Ensino de Ciências;
Uso de adornos
Authors: Caram Aniceto Samara , Ferreira de Castro Larissa Gabrielle , Corrêa Gevisiez Eduardo , Castro Menezes João Vítor , Zamora Ferreira do Nascimento Liége , Ferreira Cury Rodrigo , Moraes Sampaio da Fonseca Walter Luiz
Published: August 2024

Este artigo traz como objeto de estudo a orientação sobre a não utilização de adornos por acadêmicos de medicina no campo da prática oferecido pela instituição de ensino. A ideia inicial desse estudo partiu da aula de Aprendizagem Baseada em Projetos (PjBL), onde os acadêmicos do primeiro período deveriam desenvolver um produto educacional para orientar os próximos calouros, quanto a biossegurança. O objetivo geral desse estudo é conscientizar os acadêmicos de medicina a não usar adornos no campo de prática. Os objetivos específicos são: descrever as principais  consequências causadas pelo uso de adornos; apresentar um vídeo educacional mostrando a importância do não uso de adornos, elaborado pelos alunos do PjBL. Este estudo foi elaborado em 2 tempos. Para elaboração do texto e do conteúdo do vídeo educacional, utilizou-se  a pesquisa de revisão bibliográfica.  Após a elaboração do conteúdo escrito, partiu-se para a elaboração do material visual. Foram selecionados artigos em português, com lapso temporal de 2019 a 2023, utilizando os descritores infecção hospitalar, equipamento de proteção individual e a palavra chave adornos. Foram encontrados para o descritor equipamento de proteção individual 26 artigos, e, para infecção hospitalar 38 artigos. As escolhas foram feitas após leitura do título e resumo.  A segunda etapa que pertence a elaboração do vídeo educacional,  com público alvo a se atingir. Percebe-se que a quantidade de pessoas que entram na instituição educacional, em sua maioria, são jovens entre 17 a 25 anos (também os mais velhos), com um vídeo curto da plataforma tiktok com a música de fundo “dança da mãozinha”, onde o refrão oferece a possibilidade de acrescentar tópicos de relevância do tema, em flash rápido. A principal problemática do uso de adornos é a microbiota que se mantêm presa a eles, e sua transmissão durante o toque torna-se comum. O uso de esmalte, unhas em gel, dificultam a higienização completa e eficaz das mãos o que também pode contribuir. No ambiente hospitalar, essa transmissão de microorganismos pode desencadear infecções hospitalares. A NR32 tem por finalidade estabelecer e regulamentar as diretrizes básicas para a implementação de medidas de proteção à segurança e à saúde dos trabalhadores dos serviços de saúde, principalmente aqueles que mantêm contato com agentes biológicos .     Por tudo isso, pensa-se sobre a necessidade de ações promotivas e preventivas que ensinam “boas práticas” e assim, o académico consegue de forma consciente, reproduzir condutas que serão primordias para evitar a disseminação de doenças no ambiente de saúde, que além de cumprir na sua vida acadêmica como aluno, irá realizar após formado, e poderá ser um agente transformador no seu ambiente de trabalho.
Cirrose Hepática Alcoólica Descompensada
Authors: Pedrozo Rossetti Ana Luísa , De Oliveira Lopes1 Carina , Silva Arantes Luísa , Vianna Paquelet de Barros Maria Cláudia , Ferreira de Oliveira. Luciana
Published: August 2024

A doença hepática alcoólica (DHA) constitui-se por uma doença de etiologia alcoólica e apresenta sintomas e limitações de vida progressivas. Paralelamente a isso, a Unidade de Cuidados Paliativos (UCP) caracteriza-se por uma entidade especializada no tratamento de enfermos cuja moléstia seja irreversível e incompatível com a qualidade de vida. Sendo assim, esse trabalho caracteriza-se por um relato de experiência baseado na abordagem paliativa de um paciente cirrótico terminal feita na UCP do Hospital Municipal Dr. Munir Rafful (HMMR), no município de Volta Redonda, Rio de Janeiro, no período de novembro de 2022
A importância dos marcadores biológicos para o diagnóstico precoce e tratamento do câncer de mama
Authors: M. S. Bittencourt Cláudia , Bruno da Costa Felícia , Frascino Nesi Federico , E. S. Bittencourt Mariana
Published: August 2024

Os marcadores tumorais são macromoléculas presentes em tumores, no sangue ou em outros fluidos biológicos, nos quais o aparecimento e/ou alterações em suas concentrações se relacionam com o crescimento de células neoplásicas. Identificar os marcadores que possam retratar o comportamento dos tumores considerados como prognóstico é de extrema relevancia no câncer de mama devido a variabilidade que a progressão clínica da doença pode apresentar. A partir de uma revisão de estudos originais, contemplando os mais importantes fatores genéticos e hormonais em prognóstico, tratamento e prevenção do câncer de mama, como história familiar, nível socioeconômico e marcadores biológicos de tumor, buscamos o objetivo de apresentar uma revisão da literatura nacional e internacional sobre o papel dos marcadores tumorais no manejo clínico de pacientes com câncer de mama, do auxílio no diagnóstico e estadiamento até a avaliação da resposta terapêutica e prognóstica. Evidenciamos a importância dos programas de acompanhamento e rastreio genéticopara a população feminina, em especial aqueles direcionados a mulheres portadoras das mutações nos genes BRCA1, BRCA2 e triplo-negativo, como o pleno funcionamento da Política Nacional de Humanização que aproxima o profissional da saúde ao paciente. Por fim, como utilizar os exames preventivos disponíveis visando a detecção precoce dessa doença, tornando o  tratamento mais eficaz.
Uso indiscriminado de metilfenidato e lisdexanfetamina no meio universitário
Authors: Paschoal de Farias Guilherme , Chiarello Barata de Oliveira Enzo , Boechat Pereira Eduardo , Freitas Rodrigo Cesar Carvalho
Published: August 2024

Este artigo é uma revisão de literatura que examina criticamente o uso indiscriminado de lisdexanfetamina e metilfenidato no ambiente acadêmico, destacando os riscos à saúde e as implicações éticas dessa prática. A revisão explora as evidências disponíveis sobre a eficácia e segurança dessas substâncias quando usadas fora das indicações médicas, bem como os fatores motivacionais que levam os estudantes a recorrerem a essas drogas como auxiliares no processo de aprendizado. A introdução contextualiza a pressão enfrentada pelos estudantes universitários em relação ao alto rendimento acadêmico e apresenta os nootrópicos como uma solução fácil para problemas de concentração, ansiedade e longas horas de estudo. No entanto, destaca-se que a efetividade desses agentes não está completamente determinada e que as drogas psicoestimulantes, como metilfenidato e lisdexanfetamina, utilizadas no tratamento de TDAH e narcolepsia, apresentam efeitos colaterais significativos. A revisão de literatura explora o mecanismo de ação e os efeitos colaterais do metilfenidato e da lisdexanfetamina, destacando seu impacto no sistema nervoso central. Em relação ao metilfenidato, é apresentada sua história, indicações médicas e potencial de abuso. Já a lisdexanfetamina é descrita como uma opção de tratamento para TDAH, com menor ocorrência de efeitos adversos. O uso indiscriminado dessas drogas no meio acadêmico é discutido, abordando as motivações dos estudantes para seu uso, como a busca por melhor desempenho acadêmico, dificuldades de atenção e concentração, influência social e pressão dos colegas. No entanto, ressalta-se que o uso não autorizado desses medicamentos acarreta riscos à saúde, como efeitos colaterais adversos, dependência e problemas cardiovasculares. Os efeitos colaterais desses psicoestimulantes são mencionados, incluindo os sintomas a curto prazo e os efeitos a longo prazo, destacando a dependência e os danos ao organismo. Dados de estudos são apresentados para ilustrar a prevalência do uso de metilfenidato por universitários brasileiros e a forma como esses medicamentos são adquiridos e utilizados sem prescrição médica. Em suma, o artigo busca fornecer uma visão crítica sobre o uso indiscriminado de lisdexanfetamina e metilfenidato no ambiente acadêmico, destacando os riscos à saúde dessa prática.
TARJIMA MUAMMOLARINI YECHISH STRATEGIYALARI
Authors: Fayziyeva Aziza , Sadirova Sitora
Published: August 2024

Ushbu maqolaning oʻrganish maqsadi tarjima jarayonida yuzaga keladigan muammolarni aniqlash, ushbu muammolarni hal qilishda samarali yordam beradigan strategiyalarni tanishtirish, tarjima muammolarini batafsil yoritish va ularga kerakli yechim taklif qilish. Kerakli natijalarni qoʻlga kiritishda analitik tavsiflovchi yondashuvlardan foydalanilidi. Soʻrovnoma natijalariga koʻra tarjimonlar quyidagi muammolarga duch kelishadi: tillar oʻrtasidagi Grammatik kategoriyalar, lingvistik, leksik birliklardagi farqlar.
BOSHLANG`ICH SINF OʻQITUVCHILARIDA MUSTAQIL ISHLASH KOMPITENSIYALARINI RIVOJLANTIRISH
Authors: Yuldashev Mengali
Published: August 2024

Boshlangʻich ta'lim sohasida oʻqituvchilarning mustaqil ishlash kompetensiyalari, oʻquvchilarni ma’lum bir fan yoki mavzuga oʻqitishda, oʻzlarining unumli faoliyatlarini tashkil qilish, yangi va kreativ yondashuvlarni qoʻllash, va oʻzlarini oʻquvchilar bilan birgalikda rivojlantirish va ta'lim jarayonini sifatli boshqarishga erishishga yoʻnaltirilgan muhim mavzudir. Ushbu maqola oʻqituvchilarning ma’lum bir maqsad yoki vazifalar uchun oʻzlarini boshqarish, muammolarni hal qilish va yangi yondashuvlarni topish, qoʻllash va rivojlantirish, ma’lumotlarni mustahkamlash va ulashish, tahlil qilish va jamiyat bilan birgalikda ishlash, tajriba almashish va natijalarni hisobga olish qobiliyatlarini oʻz ichiga oladi.
INNOVATSIYA BOSHQARUV ASOSIDA BOSHQARUV XODRLARINI TAYYORLASH SIFATINI OSHIRISh OMILLARI
Authors: Sadullayev Dilmurod
Published: August 2024

Ushbu maqolada Oliy taʼlim muassasalarida boshqarish tamoyillari, metodologik yondashuvlari mohiyatini nazariy asoslari tahlili keltirilgan. Taʼlim muassasasi taʼlim tizimini boshqarishda fan va texnikaning yutuqlaridan toʻliq foydalanishi kerak. Shuning uchun bu davlatni boshqarishda ilmiy tamoyildan foydalanish muhim. Taʼlim tizimining ajralib turadigan xususiyatlaridan biri shundaki, u birinchidan, taʼlim xizmatlarini amalga oshiradigan xizmat koʻrsatuvchi boʻlinma boʻlsa, ikkinchidan, mukofot ishlab chiqaruvchi birlikdir. Shunga asoslanib, taʼlim tizimini boshqarish bu ikki sohani boshqarish qobiliyatini oʻz ichiga olgan keng qamrovli tadqiqot ekanligi yoritilgan.
Movilidad humana, emergencia climática y derechos humanos
Authors: Subía Cabrera Andrea
Published: August 2024

La Revista Justicia (s), de junio de 2024, tiene el agrado de presentar el Volumen 3 Número 1 cuyo monográfico se titula “Movilidad humana, emergencia climática y derechos humanos”, en términos generales los artículos reflexionan la situación de millones de personas desplazadas de su lugar de origen hacia otra ciudades o países por causas ambientales. La emergencia climática producto de la contaminación del planeta incide en la vida de millones de personas, cuyos derechos económicos, sociales, culturales y ambientales se encuentran en riesgo, con énfasis en los grupos más vulnerables.
El enfoque de género como perspectiva teórica en los estudios sobre migración climática en América Latina y el Caribe (siglo XXI)
Authors: Rojas Rendón Daliseth , Valle Franco Alex
Published: August 2024

En este artículo se propuso la idea de abordar el problema de la crisis climática considerando el enfoque de género a través de una investigación documental y de corte cualitativo, con la finalidad de reconocer cómo la migración climática es un nuevo concepto en el marco clasificatorio de las migraciones que envuelve el papel de la mujer dentro de una crisis, reconociendo que la presencia de ella como “migrante climática” conlleva una serie de aristas que deben ser estudiadas de cara a enfrentar los altos niveles de vulnerabilidad que envuelven los desplazamientos humanos del siglo XXI. En este trabajo, se abordó el problema de la crisis climática en relación con las ciencias políticas; se incorporó el análisis ambiental, con el objetivo de analizar la objetivación de la naturaleza, la migración climática desde América Latina y el Caribe y el enfoque de género como perspectiva teórica de investigación actual; con fundamento en un diálogo interdisciplinar que permite aportar elementos para el debate sobre las decisiones que se deben tomar desde el liderazgo político
El sistema constitucional del Ecuador frente a los derechos de las personas en procesos de migración climática
Authors: Toaquiza Díaz Jhony Marcelo
Published: August 2024

El Estado ecuatoriano, dentro de su ordenamiento jurídico, establece la obligación estatal de ejecutar medidas de prevención y mitigación de los riesgos temporales y permanentes del cambio climático. En la Constitución de la República del Ecuador coexisten un sinnúmero de derechos para que las personas puedan vivir dignamente. Así, en lo referente a los desastres naturales, el Estado es quien debe garantizar que estos derechos también presenten un espectro de protección en relación con la actividad del clima y sus consecuencias. Por tal motivo, es necesario identificar el contenido y alcance de los derechos de las personas o grupos de migrantes climáticos por afectaciones de los acontecimientos de la naturaleza; esto ya que, incluso los instrumentos internacionales de derechos humanos, solo se han preocupado por regular medidas de temor de riesgos naturales. En este sentido, el objetivo de esta investigación fue identificar los derechos de las personas en procesos de migración climática en el sistema constitucional ecuatoriano. Con una metodología cualitativa, nivel de investigación descriptiva, método hermenéutico y técnica de revisión documental, se concluyó que en el Ecuador existen derechos constitucionales amparados por el principio de igualdad formal y material, bajo los criterios indicados por la jurisprudencia de la Corte Constitucional. No obstante, con la proliferación de los desastres naturales, es necesaria una norma sustantiva y adjetiva para amparar a las personas afectadas por el cambio climático hacia la vida digna.
La protección de los derechos humanos en la Comunidad Andina: evolución y nuevos retos
Authors: Sanmartin Sagbay Shilda
Published: August 2024

La Comunidad Andina (CAN), caracterizada por una diversidad étnica, cultural y geográﬁca, nació de los esfuerzos por fortalecer la integración regional y potenciar el comercio internacional. Con el objetivo principal de desarrollo para sus países miembros, fue imperativo iniciar con el debate sobre los derechos de los y las ciudadanas andinas. De esta forma, el presente artículo tuvo como objetivo analizar la evolución y nuevos retos de la protección de los derechos humanos en la CAN. Para esto, se utilizó un enfoque cualitativo, aplicando los métodos histórico-lógico e inductivo-deductivo. Se destacó que la CAN, a pesar de ser un bloque comercial, ha venido normando aspectos sociales. Es así como la CAN cuenta con un instrumento jurídico para la protección de los derechos humanos: la Carta Andina para la Promoción y Protección de los Derechos Humanos (CAPPDH), misma que necesita transversalizar el enfoque de género y no limitar los derechos de las mujeres en un único apartado. Entre los retos que la integración andina debe afrontar están la crisis climática, las desigualdades, la violencia de género, la brecha digital y las crisis políticas. Desafíos que se deben abordar con urgencia en la actualización y reforma de la CAPPDH, que debía ser revisada cada cuatro años, pero que desde hace más de veinte años no se lo ha hecho.
Respuesta de la sociedad civil ante la movilidad forzada: el caso de la Casa de Acogida Temporal San Antonio de Pichincha de la Fundación Nuestros Jóvenes
Authors: Ribadeneira Sarmiento Mónica Elizabeth , Betancourt Meneses Saarhy Viviana , Tejero Cuero Kevin Alexander , Caisaluisa Guasgua Jefferson
Published: August 2024

La Fundación Nuestros Jóvenes (FNJ) nació en 1998 como organización no gubernamental dedicada a mejorar las condiciones de vida de poblaciones vulnerables. En 2018, para atender a la población en movilidad forzada, abrió una casa de acogida temporal, alrededor de la cual articuló otros proyectos para garantizar una intervención integral. Desde entonces, implementó un programa humanitario que incluye la atención de menores de edad, la promoción de una adecuada nutrición de las familias, varias opciones para la integración socioeconómica y los servicios de un centro integral de prevención y atención de violencia basada en género que operaba 3 años antes. Para elaborar este artículo, se efectuó un análisis documental de todas las iniciativas de la FNJ y se veriﬁcó información a través de entrevistas a sus personeros. El artículo presenta los resultados del programa humanitario de la FNJ, así como importantes lecciones aprendidas al atender a población en movilidad forzada y trabajar por sus derechos humanos y su inclusión social y económica. Su objetivo principal fue difundir el trabajo, favorecer su réplica y escalamiento, y convocar a la sociedad civil a incrementar su solidaridad y colaboración con la población vulnerable. Se concluye que, aunque hasta el momento la gestión de la FNJ se ha ﬁnanciado mayoritariamente con recursos propios es imperativo contar con líneas sostenibles de asistencia técnica y ﬁnanciera estatales y externas que apoyen las labores de organizaciones de la sociedad civil, así como políticas públicas que faciliten sus tareas, especialmente porque se enfocan en poblaciones vulnerables como aquella en movilidad humana.
N.A. Semashko on the management of preventive measures to preserve and improve the health of citizens (to the 150th anniversary of his birth)
Authors: Tregubov Valerij N.
Published: August 2024

On September 21, 2024, the medical community celebrates the 150th anniversary of the birth of Nikolai Aleksandrovich Semashko, an outstanding manager of Russian healthcare, a scientist and teacher in the field of social hygiene. The results of his work in creating a new healthcare system in difficult conditions, one of the main principles of which is prevention, is highly appreciated by the World Health Organization and is known all over the world.
To study the main directions of the prevention of various diseases over the first half of the twentieth century, there were analyzed the scientific works of N.A. Semashko, located in the electronic scientific libraries eLibrary, CyberLeninka, Scopus, Web of Science, the Central Scientific Medical Library, and the Russian State Library.
N.A. Semashko considered prevention a priority in the activities of not only health professionals, but also other state and public organizations, as well as the citizens themselves in maintaining and strengthening their health. For its implementation, he recommended using various approaches, including improving the activities of sanitary organizations and medical institutions, developing dispensaries, the district principle of work, involving sanitary inspectors in joint activities with doctors and conducting health education of the population.
Conclusions. Justified by N.A. Semashko in scientific works and the main directions of preventive medicine implemented in practice contributed to the elimination of epidemics, a decrease in the level of morbidity and mortality of the population, and therefore this experience should be taken into account and used in modern conditions.
Informal economy in Tunisia
Authors: Hedhli Mayssa  , Hadhek Zouhaier
Published: August 2024

Informality has been a phenomenon that has existed in Tunisia for a long time; it expanded with the Tunisian revolution. The relationship between informal economy and GDP varies in only one direction, that is to say only informality has a negative effect on growth...The expansion of the informal sector comes back to the problem of economic freedom, Tunisia is among the least economically free countries also the political institutional framework such as the problem of government efficiency, the high level of corruption and political instability are among the explanatory variables of informality.
The Role of Digital Influencers as Opinion Leaders in Strategic Marketing Communication among Boutique Owners in Nairobi, CBD, Kenya
Authors: Okong’o Lydia , Mberia Hellen , Syallow Maureen
Published: August 2024

Purpose: The objectives for the study was to establish the role of digital influencers as opinion leaders in strategic marketing communications.
Methodology: A descriptive research design was used. The population of study was boutique owners in Nairobi CBD, from which a sample were drawn. The sampling technique was purposive sampling based on the respondent’s special characteristics necessary for the study. Questionnaires containing both open and closed ended were used as the research instruments for the study. The data collected was then processed and analyzed using SPSS software or Advanced Excel. Data was presented inform of tables.
Findings: The results indicated that descriptive statistics were used to evaluate the relationship between the roles of digital influencers as opinion leaders in strategic marketing. Respondents indicated that digital influencers were extremely influential as opinion leaders in strategic marketing. The inferential results further indicate that there was a positive relationship between the role of digital influencers as opinion leaders and strategic marketing however the relationship was found not significant (β= 0.03, P-value 0,051> 0.005).
Unique Contribution to Theory, Practice and Policy: The study was anchored on elaboration likelihood model theory. The study recommends formulation policies regulating social media platforms so as to ensure more accountability and credibility of the information shared in those platforms.
An Assessment of YouTube Educational Video Quality Through Machine Learning
Authors: Weng John
Published: August 2024

This paper presents a machine learning-based approach to assessing the quality of educational videos on YouTube. With the growing number of educational videos available on the platform, verifying efficacy and credibility has become increasingly important. To address this issue, we propose a framework that allows for automated evaluation of video content based on analytic parameters provided by the YouTube Data API. We look at features such as view count, comment polarity, channel subscriber count, like/dislike ratio, and comment count to capture various dimensions of video quality and engagement. We introduce our target variable as the "Educational Quality Score" (EQS), which measures a video's impact on education using the RACED model - Relevance, Accuracy, Clarity, Engagement, and Depth. Our method offers educators and content creators a tool to enhance their selection of quality educational YouTube videos.
Bridging the Gender-Based Financial Literacy Gap: An In-Depth Examination of Contributing Factors and Policy Recommendations for Equitable Financial Empowerment
Authors: Huang Sarabeth , Kosnik Tom
Published: August 2024

Financial literacy is a critical life skill for individuals to make informed decisions about their investments or personal finances. However, studies have revealed a gender-based financial literacy gap, with women having lower levels of financial knowledge than men. While there is a general consensus that women have lower rates of financial literacy, there is less literature discussing the possible causes of this gap. Through interviews with experts and researchers in the financial literacy field, I seek to uncover the factors that influence financial literacy outcomes for men and women in America, and what can be done to counter the gender-based disparities in financial literacy rates. I concluded that a major factor of financial literacy is confidence in their ability to learn and handle personal finance. The best way to resolve this is by mandating financial education.
Unveiling the Impact of Key Determinants on Microloan Allocation Using Machine Learning
Authors: Ali Sheraz
Published: August 2024

Microfinance initiatives have emerged as crucial tools in poverty alleviation, particularly in developing countries.  These initiatives extend small loans to underserved populations and marginalized communities, as a means to improve their financial standing.  This research leverages machine learning models to analyze a large microfinance initiative and find the key variables that drive micro-loan allocation. By conducting an in-depth feature analysis of a comprehensive microloan dataset, we aimed to pinpoint key variables that impact the allocation and size of microloans. Our study finds that the repayment period, lender networks, and the geographic location of borrowers significantly influence the loan allocation and size. The insights from our study can provide strategic guidance to microfinance programs in their loan allocation decisions.  More specifically, lending decisions can be targeted more effectively to maximize impact of microfinance programs. In addition, this research also demonstrates the application of machine learning models in the realm of microfinance.
The Applications of Machine Learning to Probability of Students Continuing to College
Authors: Chen Nathan
Published: August 2024

We attempt to use machine learning to predict whether or not a student will end up going to college. The data that is provided are statistics such as whether their parents went to college, whether they live in a rural or urban area, and the students’ interest level of actually going to college. The main object of this project was to apply machine learning to accurately predict whether a student would continue to college. How this can be useful in the world is that based on certain statistics, a student can see if they are more likely to pursue college or if they are more likely to not continue to college. The conclusions were that the model had been trained to predict pretty accurately.
Deep Learning for Neurodevelopmental Disorder Diagnosis: Leveraging Retinal Images with Self-supervised Learning
Authors: Kim Beom , Kim Hwan , Min Sojung
Published: August 2024

Neurodevelopmental disorders like autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have posed substantial challenges to the cognitive, social, and emotional development of children. Early and precise diagnosis of ASD and ADHD  holds significant importance in facilitating timely interventions and support, ultimately enhancing outcomes for individuals affected by these conditions. Conventional diagnostic approaches for these disorders have depended on behavioral assessments, clinical observations, and structured interviews, which are labor-intensive and susceptible to subjective judgments made by healthcare professionals. In this research paper, we proposed a deep learning-based system for diagnosing neurodevelopmental disorders. The proposed system utilizes retinal images as input and generates disorder predictions. We introduce a novel self-supervised learning approach to attain superior accuracy outcomes. We demonstrated that the proposed system achieves state-of-the-art accuracy on large-scale retinal image datasets with extensive experimental results.
CardioXNet: Representation Learning for Accurate Cardiovascular Disease Diagnosis from X-ray Images
Authors: Hwang Jiwon , Klingebiel Jesse
Published: August 2024

Cardiovascular Disease (CVD) is a prevalent, incurable condition affecting the heart and blood vessels. Due to its significant impact on mortality in the United States, there is a pressing need for enhanced risk stratification methods. Coronary Artery Calcium Score (CACS), reliant on CT scans,  is most commonly employed as a risk stratification method but suffers from limitations, including accessibility and early detection challenges. To address the problem, this research study proposes a representation learning-based CVD diagnosis framework utilizing X-ray images, offering expedited and earlier detection, as well as improved accessibility. This system comprises two distinct stages: representation learning to extract CVD-related features and transfer learning to train a CVD classifier. Representation learning enhances the quality of extracted features, thereby leading to more precise results in the subsequent CVD diagnosis network. Comprehensive experiments and training validate the efficacy of the proposed method, demonstrating its superiority over the existing methods. These promising results suggest the potential utility of X-rays as a valuable biomarker for diagnosing CVD disease.
Advancing the Diagnosis of Acute Lymphoblastic Leukemia with Hybrid Neural Networks
Authors: Somu Meghana , Ramanathan Anika , Luitel Karma
Published: August 2024

Acute Lymphoblastic Leukemia (ALL) is a malignancy of B or T lymphoblasts characterized by the uncontrolled replication of abnormal cells in the blood. The difficulty in diagnosing ALL arises from its visual similarity with other cells (HEM) in the blood, and misdiagnosis rates are high with other diseases. Thus, we seek an alternate solution to help medical professionals with the diagnosis of ALL. Recent solutions have utilized hybrid models that have delivered better performance than prior models, so we utilize a hybrid architecture unused for ALL detection. Our proposed architecture consists of EfficientNetB0 as our feature extractor and XGBoost classifier for its gradient boosting framework to perform a binary classification between ALL and HEM cells. The model maintains an accuracy of 85% when diagnosing ALL, proving the effectiveness of a data-driven approach for diagnosis. In the future, our model could be trained with other ALL datasets in order to become more versatile. Our work can assist doctors in providing an accurate and efficient diagnosis of leukemia, allowing for early intervention of the disease.
AntiBloom: A Novel Deep Learning-Powered Device to Predict Harmful Algal Blooms
Authors: Bhattacharyya Neel , Wankhede Jay , Kingman Zachary
Published: August 2024

Harmful Algal Blooms (HABs) affect biosystems, leading to Unusual Marine Mortality Events (UMEs). Predicting algal bloom events can be costly and challenging. In this study, we developed a method for predicting algal blooms using an Artificial Neural Network (ANN) with Keras and Sklearn. We also designed a buoy that can collect real-time data on wind speed, UV index, pH, water temperature, and salinity to calculate real-time predictions of algal bloom. With a low cost of $150, the buoy was equipped with imaging and notification capabilities using Amazon Web Services (AWS), enabling relevant parties to be informed of harmful conditions. The ANN was trained using data from the National Centers for Environmental Information, which provided water quality data sets for Lake Erie. The model demonstrated 96.34% accuracy in predicting elevated levels of chlorophyll-a, a common marker for detecting algae. The buoy and its algorithm significantly improve over current methods of detecting elevated chlorophyll-a levels, affirming their potential to be mass-produced and usable by local authorities.
Using Artificial Intelligence for Stock Price Prediction and Profitable Trading
Authors: Bradley Logan , Droisis Odysseas
Published: August 2024

Investing in the stock market is generally considered a safe and reliable way to protect and grow your savings over the long term. However, stock investments are risky and investing in the wrong companies can lead to financial loss. This research paper aims to see how the emerging field of Artificial Intelligence (AI) can be used to predict a stock’s future movement and capitalize on it by anticipating the movement and automatically buying or selling the stock, in an attempt to safely generate profit while minimizing risk. In this paper, a Multi-Layer Perceptron regressor model was trained to predict a stock’s future price using the stock’s previous prices, two industry competitors’ previous stock prices, and previous daily crude oil prices. The model was evaluated based on its average accuracy to the actual price in percent, and it was found that the model had an average 1.7% error on AAPL (Apple Inc) stock. An automated trading bot was then created and used the model’s daily output to perform a simulated backtest, where it was given a simulated $100,000 portfolio. Its performance was measured in multiple different trading scenarios. It was found that the model can reliably outperform stocks in fairly flat or downward market conditions and still profit on upward-moving stocks, but can still end up failing to profit if the underlying stock it was given drops in price significantly over the testing period.
Low-cost, manual centrifuge for separation of particles from water
Authors: Lavichant Matthew , Wahi Rajeev
Published: August 2024

Water separation is a critical process with far-reaching implications for the environment, public health, and various industries. Traditional water filtration methods are often limited to commercial use, posing challenges for individuals lacking access to clean water, or the equipment to separate particles suspended in water. In this study, we developed a spinning device for water separation through centrifugal and rotation force. Our goal was to create a device that could provide a low-cost alternative for removing contaminants from water. During the testing, we found that the device had a theoretical efficiency of 67% and longer separation times consistently produced significantly lower absorbance values in the visible range, indicating more effective particle removal. A computational model was also used to simulate the movement of particles under the influence of rotational forces, and showed that the smallest particle in this experiment (microplastics) can be theoretically moved by the rotational forces. This study underscores the promise of a manually powered spinning toy as an innovative and efficient tool for water separation and contaminant removal, holding the potential to address global water quality challenges.
Chitosan Aerogels as an Alternative to Desalination
Authors: Kim Roy , Jarquín Carlos , Han Xiao
Published: August 2024

Water scarcity is an emerging problem in the world. Despite water covering 71% of the Earth, up to two billion people lack access to clean water globally. Conventional desalination methods are readily available, but consume large amounts of energy; consequently, they are substantially more expensive than naturally sourced freshwater. Aerogels are an emerging material that poses as a potential alternative to conventional desalination methods. This material is lightweight, porous, and has low density, allowing it to exhibit exceptional absorption qualities. This study explores the use of chitosan aerogels as an alternative to desalination.
Factors Influencing the Relationship Between Gender and Depression
Authors: Chavez Gonzalez Emily
Published: August 2024

Depression is one of the most common mental health disorders that affect both mental and physical well-being. Like other mental health conditions, various factors influence the prevalence of depression. One such factor is gender. Based on a review of academic articles discussing gender roles in mental health disorders like depression, this research paper addresses the various factors contributing to depression in men and women concerning the influence of gender roles. When it comes to depression, women tend to suffer higher depressive symptoms than men because of temperament, cognitive vulnerability, puberty, national wealth, gender equity, education, masculinity norms, and socioeconomic factors. However, men and women tend to be affected by different specific factors. Men are more susceptible to job-related activities while women tend to be affected by societal pressure. Some suggestions to address depression among men and women include implementing youth groups in schools specifically to address gender issues, promoting healthier masculine roles that include emotional sharing, coping strategies, and cooperation, and encouraging a more balanced work life.
Imitation Learning as a Tool for Modeling Cooperative Agent Games
Authors: Alladi Nikhil , Showalter Sam
Published: August 2024

The modern day sees constant application of team-level cooperation, and game theory offers a way to model these tasks in a way that provides applicable results. We created a game using Python 3 that had 3 or more agents from one team surround an agent from another team to consume them, with the end goal of consuming the other team. These agents were then trained in a centralized training, decentralized execution schema to mimic an expert’s behavior using imitation learning. Agents trained under this imitation learning schema performed significantly better than agents who followed a random policy, and as more training was supplied to the agents to learn off of, the agents performed better compared to other lesser trained teams.
Examining Investment Companies’ ESG Data to Determine Investment Efficiency
Authors: Inegol Arda , Talay Berk
Published: August 2024

Environment, Social, and Governance (ESG) investing is a crucial topic in modern society. Every day, new government regulations and incentives fuel sustainable investing by requiring robust corporate ESG disclosures. As companies become more aware of their societal and environmental impacts, investment companies such as Blackrock and Vanguard also learn to reshape their capital allocation decisions to benefit their customers. In this paper, we examine the S&P 500 equity holdings of some of these significant asset managers with a specific focus on the ESG scores of the companies they invest in. Through the compiled data, we see that the ESG scores of asset managers are ultimately very similar. Additionally, we derive that asset managers tend to base their decisions on several other factors, including the expected returns, as most investors also demand profit. As the ESG investing landscape continues to evolve, we determine that investors approaching their investments in an ESG-conscious manner may prefer to make their investments based on their independent analysis until the birth of more ESG-conscious investing strategies.
USING LITHIUM BASED MEDICATIONS TO INCREASE GRAY MATTER VOLUME IN DEPRESSED ADOLESCENTS
Authors: Elton Chloe , Gilyard Kristen
Published: August 2024

In this paper, the correlation between gray matter and depression will be presented and speculations on the effectiveness of anti-depression treatments will be made. Over time, the gray matter volume in a depressed individual will continue to decrease unless the mental illness is treated. The effectiveness of treatments varies but in terms of halting the decrease of gray matter volume or increasing gray matter volume, medications containing lithium have proven to be the most effective. While an increase in gray matter volume has the potential to increase one's mood some tradeoffs come with taking antidepressants of any sort. Lithium appears to be the most effective component of medications that increase gray matter volume, but it is crucial to examine potential side effects as well as entirely different medications that target different areas of the brain.
Addressing the Issue of Musical Education through Gamified Tuning Analysis
Authors: Kang Adelle , Fan Jeffrey , Battulga Aminjin , Choi Hyunwook
Published: August 2024

Technologies are rapidly evolving, and they are impacting human lives profoundly. And this also applies to the music industry, especially musical instrument training. There is the traditional option of receiving private expensive lessons including how to accurately tune your own instrument from a music teacher. However, it is not always viable for a teacher to be present, let alone the high cost. Furthermore, musical instrument training could overall be enhanced through a more technical approach without being constrained by the cost and human resources. With this goal in mind, we Noteblasters decided to investigate whether technology can address and resolve this common problem facing any musically inclined instrument players. Our Noteblast app is designed to detect pitches and give real-time feedback to the musicians on whether the correct note is being played or not. Through our multiple versions of prototypes, we were able to test our Noteblast app’s functionalities such as the tuner, providing real-time accurate feedback on the user’s playing, creating an easy and convenient tuning experience. The data shows aforementioned musical tuning problems can be resolved significantly more with a technology integrated device, which is our app.
Merging Technology and Tradition: A Comparative and Unique Insight into Organic Farm Internships in New Zealand and China
Authors: Zhang Shuyi
Published: August 2024

Internship plays a crucial part in preparing a student to deal with all kinds of challenges in one’s professional life (Rastegari Henneberry, S., & Radmehr, R. 2020). It promotes the skills of an individual through experimentation in learning. The importance of theoretical learning cannot be underrated, yet a healthy balance between theory and practice polishes the individual to become a competitive person in the respective field. The skill enhancement even becomes more important for an agriculture student as agri-business is the matter of producing food, raw materials, and even more than 50% of revenue for a country. Agricultural practices in organic farming, coupled with theoretical knowledge, serve as a link between institutions of higher learning and agricultural producers (Ermatovich, Y. S. 2021). Thus, it is crucial to give students real-world experience, especially in the agricultural sector, to avoid any major blunders (Ermatovich, Y. S. 2021).
Analysis of Artificial Neural Networks on Predicting Dementia
Authors: Potula Tanish , Custar Ian
Published: August 2024

Dementia, a chronic neurological disorder characterized by memory loss and impaired cognitive ability, has affected tens of millions of people globally and projections estimate this number to rise in the coming decade. Despite its widespread impact, dementia remains one of many diseases with no true cure or definitive method of diagnosis. This study aims to explore the question of how artificial neural networks can be used to predict dementia. Analyzing current research on neural networks for disease diagnosis highlights a notable gap, known as the "black box conundrum," indicating the challenge of tracing steps leading to a given output. Another gap in the literature is the absence of comparative data on factors influencing successful neural network algorithms. Conducting a comprehensive cross-continental comparative analysis across North America, Asia, and Europe, and utilizing an experimental design with the UCI ML Repository’s Parkinson’s Database, this study specifically aims to fill the identified gaps. The findings reveal key elements for successful neural networks: a data sample exceeding 100, clinically intelligible data values, and a backpropagation model. In the experimental phase, a comparison between a backpropagation model and logistic regression, paired with Shapley value analysis, elucidated a 94.87% accuracy for the former, surpassing the latter's 92.3%. These findings extend beyond dementia, providing valuable insights for neural network applications in all healthcare settings. Future research endeavors should focus on refining and optimizing neural networks with the ultimate goal of achieving 100% accuracy and maximized efficiency.
Artificial-to-Real Domain Adaptation for Lunar Landscape Semantic Segmentation
Authors: Seo Jeonghyeon , Yang Donghyuk
Published: August 2024

From Apollo 11 to India’s Chandrayaan-3, humans have put a vast amount of effort into exploring the moon. While analysis on the lunar surface provides valuable information for humans, costly and risk-taking problems of lunar exploration resulted in such scant amount of data accessible to the lunar landscape to this day. Nonetheless, study on lunar landscape remains pivotal for probing resources, detecting hazards, and studies on moon evolution. In addition, analysis on the lunar surface is the ground for future development on the moon as a potential site of resources, identifying safe landing sites, and further civilization. In this study, I propose a machine learning-based lunar landscape image semantic segmentation system. Given lunar landscape images, the proposed method outputs semantic segmentation maps that separate different types of objects such as the ground, sky, and rocks. These segmented objects potentially provide valuable insights for guiding autonomous investigation rovers. The proposed method is trained on a synthetic lunar landscape dataset and evaluated on both synthetic and real lunar landscape samples. Through comprehensive experiments, it is demonstrated that the proposed method exhibits domain adaptation capabilities, achieving state-of-the-art performance on real lunar landscape images.