bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Natural Dyes on the Qualitative and Quantitative Parameters of Bivoltine Silkworm Breeds under Sub-Tropical Conditions of Poonch District, Jammu and Kashmir
Authors: Bukhari Rubia , Ahmed Mukhtar, , Sharma Arti , Gull Azad
Published: October 2024

The study on Influence of Natural Dyes on the qualitative and quantitative parameters of Bivoltine Silkworm Breeds under Sub-tropical Conditions of Poonch District, UT Jammu and Kashmir,” was conducted during the spring of 2022 at the PG, Department of Sericulture, Poonch Campus, University of Jammu. The study examined the effects of feeding bivoltine silkworm breeds CSR16 and CSR27 with two concentrations (50% and 100%) of natural dyes: madder (Rubia cardifolia) and indigo blue (Indigofera tinctoria). A comprehensive evaluation of both qualitative and quantitative parameters was undertaken, including fecundity, hatching %, larval duration, weight of 10 mature larvae, survival rate, mortality %, pupation % and cocoon quality parameters. The results indicated significant enhancements in fecundity, hatching % and cocoon yield for silkworms treated with both dyes at 100% concentration (T2). Specifically, CSR16 and CSR27 exhibited the highest values for larval weight, cocoon weight, pupation rate and shell ratio % in T2 treatments. The findings suggest that feeding silkworms natural dyes, particularly at higher concentrations, significantly improved the economic parameters of both breeds. While the cocoons produced were intrinsically coloured without compromising commercial parameters, the colour intensity was lighter than anticipated. This implies that introducing dyed mulberry leaves during the 1st instar stage may yield more favourable results. Overall, the study demonstrates that madder and indigo dyes are suitable for producing coloured silk, offering potential for large-scale applications in sustainable silk production.
Resistance of Chickpea (Cicer arietinum L.) Varieties to Gram Pod Borer (Helicoverpa armigera) in a Controlled Environment
Authors: Singh Lal Bahadur , Jaiswal Ajay Kumar , Bawane Atul Suresh , Singh Shubham
Published: October 2024

The research was conducted within the controlled environment of the net house at the Faculty of Agriculture Science and Technology, AKS University, Satna (M.P.), during the Rabi season of 2023-24. Eight diverse chickpea (Cicer arietinum L.) genotypes, viz. JG-63, JG-130, L-2, JG-14, RAJ-128, Narendran-2, Annagiri and RVG-202, were systematically screened to evaluate their resistance to the gram pod borer (Helicoverpa armigera) under protected conditions. The study was meticulously designed using a Completely Randomized Design (CRD) with three replications to ensure robust statistical analysis. Throughout the critical vegetative, flowering and maturity stages, the larval population density of H. armigera was rigorously monitored across all genotypes at regular intervals. The comprehensive data analysis revealed that genotypes RAJ-128 and RVG-202 demonstrated superior resistance, exhibiting the lowest mean larval density of 0.25 and 0.29 larvae per 0.5 m², respectively, indicating their potential for integrated pest management in chickpea cultivation.
Effect of Incorporating Hibiscus sabdariffa Seed Flour (Red Variety) on Zootechnical Performance of Broilers Chickens Cobb500 Strain
Authors: Parfait Kouadio Kouakou , Soronikpoho Soro , Kouhana Soro , Yéo Doffére , Réné Soro Yadé
Published: October 2024

The aim of this study was to evaluate effects of incorporating red Hibiscus sabdariffa seed meal into the feed ration on the growth performance, carcass characteristics and economic margins of broiler chickens in Côte d'Ivoire. To achieve this, 237 broiler chicks of the Cobb500 strain, two (2) weeks old, were divided into three (3) lots of 79 birds each. lot 1 was fed with ration that did not contain Hibiscus sabdariffa red variety (HSR0) seed meal. Lots 2 and 3 were fed respectively by ration HSR 2% and HSR 4% by which contain 2 % and 4 % of Hibiscus sabdariffa seed meal respectively. The results showed that the inclusion of Hibiscus sabdariffa seeds significantly reduced food consumption in subjects fed HSR 2 and HSR 4 compared with ration  HSR 0 (control). It varied from 38.71 ± 1.26 g/d to 161 ± 5.08 g/d for lot 2 and from 37.85 ± 1.16 g/d to 148 ± 6.08 g/d for lot 3 compared with 39.8±1.3 g/dr to 172 ± 7.2 g/d for lot 1. On  other hand, the subjects in lot 2 achieved better growth performance than the other lots. They recorded an average weight of 2,334±208.6 g compared with 2,213 ± 170.78 g and 1,958 ± 182.57 g for lots 1 and 3 respectively. Over the 4-week period, the highest mortality rate was observed in lot 1, at 10.13 %. No negative effect was observed on the carcass yield of chickens fed Hibiscus sabdariffa meal. In economic terms, incorporation reduced the production cost of broilers. In conclusion Hibiscus sabdariffa seeds can therefore be incorporated up to 2% into chicken rations without causing any significant loss in chicken weight. Studies need to be carried out to improve the organoleptic quality of Hibiscus sabdariffa seeds.
Synergistic Effect of Organic Inputs on the Morphophysiological Traits of Sweet Basil (Ocimum basilicum L.)
Authors: Muruganandam C. , S Dharanidharan
Published: October 2024

The present investigation was conducted from 2023 in Chengam, Tiruvannamalai district. The objective was to evaluate the impact of various organic treatments on the growth and yield characteristics of sweet basil (Ocimum basilicum L.). The experiment was carried out is Randomized Block Design with ten treatments and replication thrice. Among the ten different treatments applied, the combination of FYM @ 25 t ha⁻1 + VC @ 2.5 t ha⁻1 + Seaweed extract @ 2% (T9) consistently outperformed other treatments. This treatment significantly enhanced growth characteristics viz., plant height (35.01, 60.33, 86.71 and 110.34 cm), number of leaves plant-1(291.34, 540.56, 850.41 and 1010.66), leaf area (482.33, 1673.20, 3581.23 and 4468.67 cm²) and leaf area index (0.65, 1.33, 2.32 and 3.23), number of primary branches plant-1 (21.45, 25.37, 32.17 and 39.46) and secondary branches plant-1 (64.72, 76.45, 96.56 and 109.34), plant spread (north -south) (25.32, 33.39, 40.26 and 50.38 cm), plant spread (East- west) (40.56, 55.89, 65.47 and 71.45 cm), at 30, 60, 90 and 120 DAT. The findings indicate that the integration of organic inputs of treatment, T9 (FYM @ 25 t ha⁻1 + VC @ 2.5 t ha⁻1 + Seaweed extract @ 2%) is highly effective in optimizing the growth of sweet basil.
Ethnotaxonomy and Ethnobotanical Studies of Honey and Resinous Plants in the Tchamba Prefecture in Togo
Authors: Gabriel Belei Essotolom , Mawussi Koudegnan Comlan , Galé Ekoue Akouété , Martin Gangue Minlipe , Kouami Kokou
Published: October 2024

Natural plant products have gained increasing attention, but climate change and human activities have led to the degradation of ecosystems and loss of biodiversity. This study aims to contribute to the preservation of local knowledge related to the classification and use of honey-producing and resinous plants in the Tchamba prefecture, Togo. Ethnotaxonomic and ethnobotanical data were collected through semi-directed interview and focus groups in the four localities, involving 92 respondents. A total of 96 plants of beekeeping were identified, classified into 88 genera, 33 families, and 22 orders, with 16 ethnotaxonomic criteria used for classification. The most common criteria were "plant use" and "plant habit". The study highlights the rich local knowledge of plant uses for food, medicine, and rituals, emphasizing the importance of conserving both biodiversity and cultural heritage. These findings contribute to understanding how indigenous knowledge can support conservation and sustainable use of plant resources.
Rainfall Patterns and Groundwater Dynamics: Implications for Soil and Water Conservation in Kodihalli Sub-Watershed, Haveri District, Karnataka, India
Authors: M V Manjunatha , S B Manjunatha , Malappanavar Nagaraj , Hebbara Manjunatha , V B Kuligod , M S Shirahatti , F H Mehaboobatabasum , Hiremath Jyoti
Published: October 2024

The Kodihalli sub-watershed (4D4D2f) is lies between 14028’23.68”-14034’20.103” North latitudes and 75026’49.224”-75031’44.208” East longitudes and covers an area of about 4398.83 ha. with an average annual rainfall of 783.0 mm (2014-2021). The maximum rainfall of 439.0 mm is received from June to September, 226.0 mm from October to early December and the remaining 118.0 mm is received during the rest of the year. The number of rainy days (>2.5 mm) varied from 13-24 days per year. On an average, the number of rainy-day events likely to produce runoff (20 to 30 mm) are about 2 to 8 rainy days per year with moderate variation across the years. The Actual Evapotranspiration (AET) over the years 2014 - 2021 in the Kodihalli sub-watershed varied from 383.0 to 770.0 mm. During 2014 - 2021, the average annual AET (621.0 mm) was less than the average rainfall (783.0 mm). The average AET/P ratio between 2014-2021 was about 0.79 which is less than the sustainable limit of about 0.80. The soils of watershed viz., sandy clay loam (IR 10 mm/hr) and sandy clay (IR 14 mm/hr) resulted in more infiltration rate than clay (2 mm/hr) and clay loam soils (7 mm/hr). Soil infiltration during a rainstorm is closely related to a number of factors such as the intensity and kinetic energy of the rainfall, soil surface conditions and soil properties such as those related to aggregate stability.  For effective soil and water conservation, maximum area of about 3769 ha (85.7%) requires graded bunding and 267 ha (6.06%) area requires contour bunding.
A Pentahelix Model Approach: Creating Vilage Innovation Perception in Sokaraja Village Banyumas
Authors: Kharismasyah Alfato Yusnar , Anggara Ali Akbar , Dewandaru Rhis Ogie , Aryoko Yudhistira Pradhipta
Published: October 2024

The development of village innovation has become unsustainable, and the financial support provided by the government each year has become less effective in driving innovation. This study aims to identify the factors influencing village innovation development from the community’s perspective. The research was conducted in Sokaraja Village, Banyumas Regency, where two sub-tofu business group were selected: Tofu business group A, which has village assets, and Tofu business group B, which does not. Data was collected through a survey of 60 respondents, 30 from each tofu business group, chosen in collaboration with the village administration. The survey, conducted between January to May 2024, explored community perceptions using the Pentahelix model, which encompasses the roles of social institutions, government programs, market support, innovation sources, and communication media, across 22 indicators. Data was analyzed descriptively using Importance Performance Analysis (IPA). Although all aspects of the Pentahelix model play a vital role in fostering village innovation, several indicators still require performance improvement. Strengthening village-owned enterprises and empowering local economic institutions is crucial to enhancing innovation efforts, with the support of the village community and assistance from external stakeholders.
House Rental Finding System Using Laravel, Vue.Js, And PHP Machine Learning Library
Authors: Rana Mohammad Shohel , Omar Saleh Ibne , Pranta Md. Fahim Muntashir
Published: October 2024

The use of technology in all parts of our lives has greatly increased in recent years, nowadays, people tend to search for everything online before they make decisions. However, looking for rental houses online is not common in Bangladesh, it is not because people do not want to, but because there are not many online platforms focusing on residential rentals. For the mentioned reason we developed a house rental finding web application using Laravel, Vue.js, and PHP-ML library. Laravel handles the backend whereas Vue.js manages the frontend, we utilized PHP Machine Learning Library’s Linear Regression and K-Nearest Neighbours (KNN) algorithm to build a machine learning model for the search system. The goal is to make it easier to find rental properties. Our system gives personalized suggestions based on user inputs, like location, rental price, property size, and the number of rooms and bathrooms. Our application aims to make searching for rental houses a better experience and more efficient
Devika AI: An Open-Source Revolution In AI-Powered Code Generation
Authors: Sowjanya Anuku
Published: October 2024

Devika AI is an innovative open-source platform designed to revolutionize software development through AIpowered code generation. Leveraging advanced natural language processing (NLP), machine learning algorithms, and a modular architecture, Devika AI translates high-level human instructions into executable code across multiple programming languages. This paper presents a comprehensive overview of Devika AI's architecture, methodologies, and functionalities. We discuss its ability to improve developer productivity, reduce coding errors, and facilitate collaborative development. Experimental results demonstrate Devika AI's effectiveness in various coding tasks, highlighting its potential as a free and accessible alternative to proprietary AI coding assistants. The implications of Devika AI's adoption on the future of software development are also explored
Recognition Of Digits From EEG Signals: An Innovative Approach
Authors: Jha Subodh Kumar , Bedre Sushil , Jaiswal Pratik , Yannawar Pravin , Gaikwad Ashok
Published: October 2024

Communicating with computers through thought has been a remarkable achievement in recent years. This was made possible by the use of Electroencephalography (EEG). Brain-computer interface (BCI) relies heavily on Electroencephalography (EEG) signals for communication between humans and computers. With the advent of deep learning, many studies recently applied these techniques to EEG data to perform various tasks like emotion recognition, motor imagery classification, sleep analysis, and many more. This study proposes a methodological combination of EEG signal processing techniques and SVM models for the classification of digit. Also, it explores DCT and LDA techniques for feature extraction and selection. As a result, the proposed classification pipeline achieves comparable performance with the existing methods.
Comprehensive Survey On Generative AI, Plethora Of Applications And Impacts
Authors: A M Vandana Pranavi , Cholli Dr. Nagaraj G
Published: October 2024

The primary objective for the AI subfield of "generative artificial intelligence" is to develop systems that may produce new, novel and creative content including text, photos, audio, music, and movies. These models are able to generate fresh content that nearly mimics realistic content created by humans by utilizing deep learning techniques. These models of Gen AI have gained significant importance in research and have plethora of applications in wide varieties of fields. The impact of GenAI is not just on abled but also on disabled communities who are sometimes unnoticed. This survey provides a thorough overview of general artificial intelligence (GenAI), its applications, the cutting edge models at the moment, its effects on the disabled groups, and its challenges going forward with the future aspects
Plant Leaf Disease Detection System using Machine Learning and Deep Learning: A Survey
Authors: Sharma Mr. Abhishek , Bansal Mr. Rohit
Published: October 2024

Plant diseases are becoming more common, which is a serious threat to profitability of agriculture worldwide and requires the creation of reliable and efficient disease detection technologies. This work uses machine learning (ML) and deep learning (DL) approaches to give an extensive assessment of previous research on plant leaf disease identification. We examine and evaluate the many approaches used in the last several research, emphasizing the advantages, disadvantages, and useful uses of each. The study covers both sophisticated deep learning designs, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), as well as more conventional machine learning techniques, such support vector machines (SVM) and decision trees. According to our research, plant leaf diseases can be more accurately identified and classified using deep learning techniques, especially CNNs, when applied to a variety of crop categories. The study also looks at the field’s obstacles and promising directions, highlighting the use of multifaceted approaches and real-time illness monitoring systems.
The Use Of Language That Creates Intent In Riddles Consequential From Social Variation In Tanzania
Authors: Mwangosi Gerephace
Published: October 2024

This article has examined how the aspect of language use creates intent in the riddles arising from social change in Tanzania. The primary data used in the analysis, discussion and presented in this article were found in the library by the method of careful reading. The target selection technique was used to find selected riddles by referring to the specific objective of the article aimed at investigating how the use of language creates intent in riddles resulting from social change. A review of the documents used to verify the primary data was obtained through electronic and library methods. The results of the study are presented in a descriptive manner. The analysis and discussion of the data presented was guided by the theory of New Historism. The results of the study show that there is a specific relationship between the elements of language in building the objectives that are linked to the changes that occur in society. The use of language elements has focused on the issue of context, time and the needs of society in designing a language that depicts the real situation in society. Also, the selected genre has given us a Figurative language that it is a solid link in building the foundations for understanding cultural change and the development of science and technology as an important tool in designing the mission and language of riddles that review those changes. This article recommends that more research be done to examine the role of riddles arising from social change in building sustainable foundations to maintain and strengthen traditional ideologies and philosophies in this country.
Advancing Photorealism Enhancement Using Convolutional Neural Networks (CNNs)
Authors: Shaikh Dr. (Mrs.) N.F. , Wagh Dr. (Mrs.) S.K. , Singh Devesh Sandeep
Published: October 2024

Photorealism has been the defining goal of computer graphics for half a century. A look at even the most sophisticated real-time games will quickly reveal that photorealism has not been achieved. An ineffable difference in the appearance of simulation and reality remains. In recent years, a complementary set of techniques has been developed in computer vision and machine learning. These techniques, based on deep learning, convolutional networks, and adversarial training, bypass physical modeling of geometric layout, material appearance, and light transport. Instead, images are synthesized by convolutional networks trained on large datasets. These techniques have been used to synthesize representative images from a given domain to convert semantic label maps to photographic images and to attempt to bridge the appearance gap between synthetic and real images. The images are enhanced by a convolutional network that leverages intermediate representations produced by conventional rendering pipelines. The network is trained via a novel adversarial objective, which provides strong supervision at multiple perceptual levels.
Advanced Fraud Threats And Detection In Browser, Android, And Ios Environments
Authors: George Jeffrie Joshua Lazarus
Published: October 2024

As digital technologies evolve, so do the methods employed by cybercriminals to exploit vulnerabilities within browser and mobile environments. This paper explores advanced fraud threats such as VPN detection evasion, browser spoofing, mobile device factory resets, jailbroken phones, user-initiated app cloning, and Android emulators and tampering. We discuss how these threats are misused and outline advanced detection techniques to mitigate risks. The paper emphasizes the importance of implementing robust security measures to protect against sophisticated fraud tactics in browser, Android, and iOS platforms.
Text Detection And Recognition: A Review
Authors: CSE Manish Kushwaha
Published: October 2024

This paper identifies and compares different stages in the process of text detection and recognition and analyses different approaches used for text extraction from color images. Two commonly used methods for this problem are stepwise methods and integrated methods, whereas this task is further divided into text detection and localization, classification, segmentation and text recognition. Important approaches used to undergo these stages and their corresponding advantages, disadvantages and applications are presented in this paper. Various text related applications for imagery are also presented over here. This review performs comparative analysis of fundamental processes in this field.
Artificial Intelligence And Its Implications In Health Care: A Textual Analysis
Authors: Mathur Vivaan
Published: October 2024

This all-inclusive research paper plunges into the transformative nature of artificial intelligence (AI) in healthcare, emphasizing its ability to change patient care and administrative activities. The investigation examines systematically how AI technologies are creating major improvements towards patients’ outcomes and enhanced operational efficiency within the healthcare systems. From diagnostics to personalized treatment plans and administrative tasks, AI is being integrated using sophisticated algorithms in numerous aspects of healthcare delivery. One major focus is improving diagnostic accuracy. AI-backed diagnostic tools such as image recognition software as well as predictive models have outperformed traditional methods in medical condition identification and diagnosis. For instance, artificial intelligence algorithms show exceptional skills in analysing medical images resulting to earlier detection as well as accurate diagnoses of diseases like cancer, cardiovascular conditions among others neurological disorders. These enhancements not only allow for timely intervention but they significantly reduce instances where diagnosis goes wrong hence enhancing patient prognosis while reducing health costs drastically. The ability to customize personalized therapy is yet another essential aspect of AI in healthcare. With such information as genetic data, medical records and lifestyle factors, and other patient information, AI systems can develop individualized treatment plans. It is for this reason that personalization of treatments enhances their efficiency while reducing the risk of any adverse effects as well as ensuring patients’ adherence to prescribed therapies. Besides, it is important to note that AI-driven predictive models are helpful in identifying individuals with a higher probability of developing specific conditions thereby allowing interventions aimed at preventing diseases and bettering overall population health. AI has also transformed administrative tasks within hospitals besides its clinical applications. For example, AI driven automation is now used to streamline scheduling of appointments or billing processes or even storage of patient records which are normally considered routine administrative works. In addition, through these means there is reduced burden on administrative duties for healthcare workers who continue to perform them with increased precision and timeliness. The net effect is that time and resources can be redirected towards more direct patient care thus improving service quality across the board’s entire system
Gender Dynamics In Organ Donation And Transplantation: An Analysis Of Donor And Recipient Trends
Authors: Kaur Nimrit
Published: October 2024

Organ donation and transplantation represent critical components of modern medicine, offering life-saving solutions for individuals with organ failure. Despite advancements in medical practices, significant gender disparities exist within these processes, where women disproportionately contribute as donors while men are predominantly recipients. This study integrates an in-depth statistical analysis of data from major registries like the United Network for Organ Sharing (UNOS) and the Organ Procurement and Transplantation Network (OPTN), utilizing chi-square tests, logistic regression, multivariate analysis, and stratified sampling to elucidate these trends. By combining quantitative data with socio-cultural theories, this research aims to uncover the multifaceted causes behind these gender-based discrepancies, revealing that social conditioning, altruistic behaviour, and systemic biases in medical practices play crucial roles. The results indicate statistically significant correlations between gender and donor/recipient status, suggesting that both traditional gender roles and healthcare biases need to be addressed to create a more equitable organ donation system. The study concludes by proposing policy reforms and advocacy strategies to foster gender neutrality in organ transplantation, ultimately promoting a fairer healthcare paradigm.
Early Warning Strategy And Fault Diagnosis Strategy Of Electric Vehicle Charge And Discharge Based On Artificial Intelligence
Authors: . Kabir
Published: October 2024

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Competitiveness, Competitive Intelligence, And Strategic Positioning: An Integrated Approach For Organizational Success
Authors: Dantas Robson Gualberto , Silva Valdilene G. Machado , Gomes José Vitor Lemes , Vieira Maria Augusta De Assis , Amaral Joubert Caetano
Published: October 2024

In an era marked by rapid globalization and digital transformation, businesses face unprecedented challenges. Understanding and integrating key concepts such as competitiveness, competitive intelligence, and strategic positioning has become essential for organizations aiming to maintain a sustainable competitive edge. This article explores how these three strategic elements interact to create synergy, enabling organizations to identify opportunities, anticipate threats, and develop strategies that drive long-term success. By analyzing foundational theories from notable authors like Porter, Prahalad, Hamel, and Mintzberg, and using real-world examples, this study highlights the importance of a holistic approach in strategic management. The findings suggest that companies capable of harmonizing these concepts are better positioned to innovate, adapt, and thrive in the competitive business landscape
Esportes Coletivos E Desenvolvimento Social: O Impacto Do Trabalho Em Equipe Na Formação De Competências Sociais E Físicas
Authors: Rufino João Luiz , Silva Pablo Rodrigo De Oliveira , Maurício Alex Aryel Ribas
Published: October 2024

Os esportes coletivos têm se destacado como uma ferramenta essencial para o desenvolvimento social e físico de indivíduos, em especial entre crianças e jovens. A prática regular desses esportes envolve o trabalho em equipe, uma característica que contribui significativamente para o desenvolvimento de competências sociais como a comunicação, cooperação, resolução de conflitos e responsabilidade coletiva. Essas habilidades, adquiridas no contexto esportivo, são facilmente transferíveis para outros aspectos da vida, como o ambiente escolar, familiar e profissional. Além das competências sociais, os esportes coletivos promovem o desenvolvimento de habilidades físicas que são fundamentais para a saúde, prevenindo doenças e melhorando o bem-estar geral dos praticantes (SMITH, 2019; JOHNSON, 2020). Este artigo analisa o impacto dos esportes coletivos na formação dessas competências a partir de uma revisão de literatura recente e estudos de caso conduzidos em contextos escolares e comunitários. Estudos apontam que a participação em esportes coletivos não apenas melhora o desempenho físico dos indivíduos, mas também fortalece o senso de comunidade e promove a inclusão social, especialmente em áreas de vulnerabilidade (LEE, 2021). A metodologia utilizada inclui uma abordagem qualitativa, baseada em entrevistas semiestruturadas e análise documental de programas de incentivo ao esporte em diversas regiões do Brasil. Essa análise busca entender como os esportes coletivos podem servir como um meio eficaz para a construção de uma sociedade mais igualitária, inclusiva e saudável. Os resultados sugerem que os esportes coletivos são uma poderosa ferramenta de desenvolvimento social, proporcionando aos participantes a oportunidade de interagir com seus pares, superar desafios coletivos e desenvolver um senso de pertencimento. Além disso, os esportes contribuem para a saúde física, melhorando a resistência, a força e a coordenação motora dos praticantes, o que, por sua vez, reflete em uma melhor qualidade de vida (GREEN, 2021). A discussão enfatiza a necessidade de políticas públicas que garantam o acesso aos esportes coletivos em todas as esferas da sociedade, com um foco especial em contextos educacionais e em comunidades de baixa renda. A promoção dos esportes coletivos pode ser uma estratégia fundamental para o desenvolvimento equilibrado de habilidades sociais e físicas, beneficiando tanto os indivíduos quanto a comunidade como um todo. Concluímos que o investimento em programas de esportes coletivos deve ser ampliado como parte de uma estratégia mais ampla de desenvolvimento social e promoção da saúde
Novas Tecnologias No Diagnóstico Precoce De Doenças Cardiovasculares: O Papel Da Inteligência Artificial E Da Telemedicina
Authors: Aragão Felipe Matheus Sant’Anna , Aragão Iapunira Catarina Sant’Anna , Reis Francisco Prado , Aragão José Aderval
Published: October 2024

As doenças cardiovasculares (DCVs) representam um grande desafio de saúde pública, sendo responsáveis por 31% de todas as mortes globais, de acordo com a Organização Mundial da Saúde (2021). A mortalidade associada a essas condições sublinha a necessidade urgente de inovações no diagnóstico precoce e na gestão clínica, a fim de prevenir complicações graves e salvar vidas. Nos últimos anos, o avanço das tecnologias emergentes, como a Inteligência Artificial (IA) e a telemedicina, tem transformado o panorama do diagnóstico de DCVs, promovendo uma revolução no campo da cardiologia. A IA, em particular, se destaca por sua capacidade de processar grandes volumes de dados clínicos de forma rápida e precisa, permitindo a identificação de padrões complexos que podem passar despercebidos em métodos tradicionais. Ao analisar exames de imagem, como ecocardiogramas e tomografias, a IA tem demonstrado melhorar significativamente a acurácia diagnóstica, o que possibilita a detecção precoce de doenças cardiovasculares. Além disso, essa tecnologia oferece uma abordagem personalizada, ajustando o tratamento de acordo com as características individuais de cada paciente, levando em consideração fatores genéticos e comportamentais (BROWN et al., 2021). Por outro lado, a telemedicina tem permitido o monitoramento remoto de pacientes, especialmente aqueles com risco elevado de eventos cardiovasculares. Essa tecnologia facilita a coleta contínua de dados clínicos, como pressão arterial e frequência cardíaca, que podem ser transmitidos aos médicos em tempo real, promovendo uma intervenção rápida em caso de anomalias. A telemedicina também tem o potencial de reduzir a necessidade de consultas presenciais, o que facilita o acompanhamento de pacientes em áreas remotas ou com dificuldades de acesso aos serviços de saúde (JOHNSON et al., 2022). Essas tecnologias emergentes não apenas otimizam o diagnóstico e o tratamento, mas também têm o potencial de reduzir custos ao diminuir hospitalizações desnecessárias e promover uma gestão mais eficiente dos recursos de saúde. No entanto, existem desafios a serem superados para garantir sua adoção generalizada. A acessibilidade ainda é uma questão crítica, uma vez que muitos países de baixa e média renda enfrentam barreiras para implementar essas tecnologias. Além disso, a capacitação dos profissionais de saúde é essencial para garantir o uso adequado dessas ferramentas, permitindo que seu potencial seja plenamente realizado (KIM et al., 2021). A IA e a telemedicina oferecem uma oportunidade sem precedentes para transformar a cardiologia, proporcionando diagnósticos mais precisos e acessíveis, mas sua implementação requer soluções para questões de custo, infraestrutura e treinamento
Impact of Bank-Specific Factors on Capital Adequacy in the Nigerian Banking Sector: An Empirical Analysis
Authors: Olu Akinuli, Bankole , Clement Adedayo, Olawale , Elizabeth Popoola, Olukemi , S. Remi-Esan, Sumbo
Published: October 2024

The study investigates the divergence between the capital adequacy of banks in Nigeria and the Bank for International Settlements' (BIS) global standards for bank capital adequacy. It specifically examines the factors affecting capital adequacy in Nigerian banks. The main objective is to evaluate how specific factors impact capital adequacy within this context. Data spanning from 2012 to 2022 from the Central Bank of Nigeria's Statistical Bulletin was collected for 13 selected deposit money banks in Nigeria. Econometric methods were employed to analyse this data. The findings indicate that asset quality and return on equity (ROE) adversely affect the capital adequacy of Nigerian deposit money banks during the study period. Conversely, bank liquidity, bank size, management efficiency, non-performing loans, and return on assets positively influence bank capital adequacy in Nigeria. It is recommended that particular attention be given to bank liquidity and bank size, as these factors significantly enhance the capital adequacy of Nigerian banks within the reviewed of period
Livelihood, Poverty and Multiple Deprivation among Tribals in Odisha
Authors: Pothal Dr. Siba Prasad
Published: October 2024

The present study seeks to examine the livelihood pattern, incidence of poverty and multiple deprivation among the tribal communities or Scheduled Tribes (STs) of Odisha by using secondary data collected from the various rounds of the National Sample Survey (NSS), Census of India reports, District Level Household and Facility Survey (DLFS) reports, etc. It evaluates the contributions of the different sources of livelihood on level of living, quality of life and economic well-being of the tribals. Methodologically, the study employs the Foster, Greer and Thorbecke (FGT) class of poverty measures to examine the incidence and magnitude of poverty among the tribals. It finds a strong relationship between livelihood pattern and poverty among them. Though there has been a decline in the incidence of poverty (head count ratio) among the tribals over a period of time, the rate of decline has been slower among the tribal communities than the other social classes. The tribals are confronted with low levels of income and higher levels of poverty due to their subsistence level of livelihood. Most of them are engaged in low-paid works, and suffer from chronic poverty and multiple deprivation. Finally, the study concludes with suggestions on how potential policy options can improve the livelihood condition of the tribals and redress the problem of heavy incidence of poverty among them.
Fintech And Financial Inclusion: Case Studies From The United States
Authors: Malani Rohan
Published: October 2024

Throughout several decades, the top name among companies that have accepted online payment transactions is a multinational financial technology company PayPal, situated in the United States that was founded in 1998. Internet payments gained traction and expanded globally over time. This research examines how financial technology, or FinTech, is changing financial accessibility in the US. It also analyzes how these advancements, together with innovations in blockchain and cryptocurrency technology have changed the way that financial services are accessed through case studies of well-known websites like PayPal, Venmo, and Robinhood. These technological advancements have promoted financial transaction transparency, democratized investing opportunities, and expedited payment systems. Furthermore, the research emphasizes how Splitwise and similar platforms facilitate shared spending management, which in turn encourages economic inclusion and gives people more ability to engage in the financial ecosystem. The paper offers insights into how FinTech is changing the financial services industry, improving accessibility and supporting larger financial inclusion goals in the US by examining some case studies.
The Impact Of Cashless Payments On Smes’ Financial Performance In Mount Lebanon
Authors: Masri Nadia Al , Khawaja Danie
Published: October 2024

Cashless payments are one of the innovations playing a significant role in business strategy. However, in Lebanon, the economic and financial crisis has forced SMEs to primarily use cash as a mode of payment, leading to numerous issues affecting their financial performance. To overcome these challenges, companies are seeking to adopt cashless payments outside the banking sector to better control their finances and adapt to rapid technological advancements. This study aims to examine the impact of cashless payments on the financial performance of SMEs in Mount Lebanon, highlighting the factors affecting the adoption of this payment method. A survey was conducted with the leaders of 183 SMEs in the region, and the results of multiple regression analysis, carried out using SPSS software, confirmed the significant impact of electronic payments on the financial performance of SMEs in the region. Specifically, mobile money and E-transfer have a significant positive relationship with financial performance. Furthermore, the study identified that competition, risks, and ease of use are the behavioral intention factors that affect the adoption of cashless payments. Consequently, leaders must adjust their strategy by integrating cashless payments to improve their financial performance.
Innovative Financial Products And Services For Underserved Communities
Authors: Enudi Ogechi
Published: October 2024

This paper provides an in-depth exploration of innovative financial products designed to meet the unique needs of underserved populations in the United States. It systematically examines how Community Development Financial Institutions (CDFIs) and Minority Depository Institutions (MDIs) are important in the delivery of these specialized financial services. By focusing on microloans, credit-building loans, and affordable housing financing, the paper elucidates the transformative potential of these financial products in enhancing financial inclusion and increasing economic empowerment within marginalized communities. The analysis shows how microloans facilitate entrepreneurship and poverty alleviation while credit-building loans serve as a tool for establishing and improving credit histories. It addresses innovative financing models for affordable housing by illustrating their impact on community stability and development. The role of CDFIs and MDIs is examined to reveal their unique contributions and challenges in providing accessible financial services to underserved groups. The paper explores implementation strategies and policy recommendations, emphasizing the need for a comprehensive approach that leverages technology, ensures strong partnerships with government and nonprofit entities, and addresses regulatory barriers. It entails the importance of measuring the impact of financial inclusion initiatives to ensure their effectiveness and sustainability. The paper calls for concerted action from policymakers, financial institutions, and community organizations to collaborate in advancing financial inclusion efforts. By harnessing the insights and strategies outlined, stakeholders can enhance the reach and effectiveness of financial products, ultimately driving economic growth and opportunity for all
Theoretical Underpinnings Of Gender, Finance And Development: A Critical Review
Authors: R Dr. Remyakrishnan.
Published: October 2024

Economies around the world have recorded tremendous advancement in their journey towards access to finance dimension of financial inclusion over these years. But women who constitute around fifty percent of the world population still lag much behind their counterparts in achieving the higher goals of financial inclusion particularly the usage of financial products and services. A persistent gender gap of 6% is visible while analyzing the Global Financial Inclusion Database (Global Findex,2021) data. The gender gap in financial access and usage aggravates economic inequity and underlines women's economic subservience. For instance, lack of accessibility to property and assets constraints women’s ability to pledge collateral such as land or livestock to obtain credit from formal financial institutions. The participation of women in the economic activities is far below their potential due to many socio-economic and cultural barriers. A deep-rooted historical reading of the gender dynamics evolved in the development discourse is vital for the policy makers to frame strategies to address such issues. The study investigates the interrelated roles of gender, finance, and development from a theoretical standpoint. A comprehensive review regarding the paradigm shifts happened in the domain of gender and development comprising of WID approach, WAD approach and GAD approach is also presented.
Economic Indicators And Stock Market Performance: An Analysis Of GDP, Unemployment Rates, And Inflation
Authors: Jain Krisha
Published: October 2024

This research paper delves into the intricate relationship between three fundamental economic indicators—Gross Domestic Product (GDP), unemployment rates, and inflation—and their consequential effects on stock market performance. The primary objective of this study is to elucidate how variations in these indicators influence investor behavior and, subsequently, stock market trends. The research employs a dual methodological approach: quantitative analysis of historical economic and stock market data, and qualitative examination through case studies of notable economic events. This research looks back in history for a pattern and correlation of the stock market's moves in relation to changes in various economic indicators. For instance, it probes how changes in the GDP growth rate have their effect on investor confidence and, in turn, stock market valuation. It also looks at how fluctuations in the rate of unemployment lead to variations in market performance, as this generally indicates economic health and spending on the part of consumers. It also tends to focus on the relationship between inflation and return in the stock market, given influences on interest rates and corporate profits as a result of inflationary pressures. Besides data analysis, the study also makes use of case studies of vital periods in economies, such as the financial crisis of 2008 and the COVID-19 pandemic, to develop context and enrich the understanding of how these indicators interact within an extreme economic scenario. Such case studies bring understanding into the way investor sentiment and stock market performance respond to changes in GDP, unemployment, and inflation in real-world scenarios. These findings from this research indicate complex interdependencies between the series of economic indicators and stock market performance. For example, strong GDP growth is perceived in general to be associated with favorable stock market performance, whereas high inflation and increasing unemployment may soften or even exert negative effects. The study also emphasizes the role of investor sentiment and market psychology in amplifying or dampening the impacts of these economic indicators. In sum, this paper contributes to an integrated understanding of how GDP, unemployment rate, and inflation interact in shaping dynamics in the performance of the stock market. It thus provides an avenue through which both investors and policymakers, and economists who want to navigate or predict market movements in light of economic trends, draw useful guidance. The underlined idea herein is that instead of looking at separate economic parameters, it will be more relevant for any research work if several factors are considered together for better analytical reasoning on stock market performance.
Capital Structure And Earnings Per Share: An Empirical Analysis Of Selected Companies Listed On The Nigerian Exchange Group
Authors: Phd Ihenyen, J. Confidence , Buseri Tonye , Phd Nera Ebenezer Mansi
Published: October 2024

Focussing on the moderating influence of company size, this study analyses the implication of capital structure on earnings per share (EPS) for a subset of businesses listed on the Nigeria Exchange Group. The research examines data from fifteen publicly listed food and drink firms over a certain time frame using a random effects model. According to the results, some parts of the capital structure, like LDTA and EQTA, significantly boost earnings per share (EPS), while others, like TPTA, have the opposite effect. Including company size as a moderating variable significantly improves the model's explanatory power. The modified R-squared value goes up from 7.5% to 55.8%. Firm-specific features heavily influence capital structure decisions and their influence on financial viability. Firm size should be a major aspect in financing decisions, according to the report, since larger organisations are better able to optimise their capital structure to boost profitability. Corporate managers, lawmakers, and investors can benefit from the study's new findings, which add to the current literature by demonstrating how business size affects the correlation between capital structure and profitability
How Does The Proliferation Of E-Commerce Influence Consumer Expenditure Patterns, And What Factors Contribute To The Effectiveness Of E-Commerce Strategies In Stimulating Consumer Spending In The Digital Age
Authors: . .
Published: October 2024

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How Do Macroeconomic Indicators (E.G., GDP Growth, Unemployment Rates, Interest Rates) Influence Stock Market Returns And Volatility In Emerging Vs. Developed Markets
Authors: Arora Vivaan
Published: October 2024

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The Effect Of Non-Performing Loans On The Financial Performance Of Commercial Banks In Ghana
Authors: Atisu Jerome Christopher , Mensah Nicholas , Alipoe Stanley Agbenya , Rahman Saaka Abbul-
Published: October 2024

Non-performing loans (NPLs) are considered financial pollution as a result of their high risk and effect on the profitability and liquidity of banks. The study examines the effect of non-performing loans on the financial performance of commercial banks in Ghana. The study is guided by the following research objectives: examining the level of NPLs of commercial banks in Ghana, examining the relationship between loan-to-deposit ratio and profitability and determining the relationship between NPLs and the financial performance of selected commercial banks. The data for this study was obtained from financial institutions from 2010 to 2021. The NPL rate shows some volatility but generally decreases from 2010 to 2014. It reached its lowest point in 2014 at 11.3%. However, from 2015 to 2017, there was a notable increase in the NPL rate, with a peak of 21.59% in 2017. The findings show that non-performing loans have a positive and significant relationship with ROA. The finding indicates a positive and significant relationship between loan deposit ratios. The study recommends the need to implement strong risk management practices to identify and mitigate potential credit risks proactively. This includes monitoring and early detection of deteriorating loan accounts, regular portfolio reviews, and stress testing. By identifying high-risk loans early, banks can take timely actions to mitigate potential losses and prevent loans from becoming non-performing. Also, management has to invest in training and development programs for loan officers and credit staff. Ensure they have the necessary skills and knowledge to accurately assess creditworthiness, detect warning signs, and effectively handle loan monitoring and collections.