bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Depression, Anxiety And Stress In Undergraduate And Postgraduate Medical Students
Authors: Iftikhar Nadia , Tanwir Khaliq
Published: May 2024

Objective: To determine the frequency of depression, anxiety, and stress among medical students and to compare between undergraduate and postgraduate students.
Study Design: Comparative cross-sectional study.
Place and Duration of Study: Pak Emirates Military Hospital Rawalpindi, Public Sector Medical College, Pakistan Jul to Dec 2019.
Methodology: A study was carried out on 200 medical students. One hundred undergraduates from all five years and 100 postgraduates/residents from varying specialities were asked to complete DASS 21(depression, anxiety, and stress score 21).
Results: Out of 200 students who completed the questionnaire, 116(58%) were depressed. Among the postgraduates, females were more likely to be depressed (p=0.029). 135(67.5%) students suffered from anxiety. Undergraduates were statistically more likely to suffer from anxiety (p=0.011). 101(50.5%) students were stressed. Overall, females were more stressed than male students (0.012). Among postgraduates, females were more likely to be stressed than males (p=0.013). Marital status does not appear to have any effect on depression, anxiety, and stress. 25(12.5%) students had suicidal ideation.
Conclusion: Depression, anxiety and stress are present in over half of our medical students, both undergraduates and postgraduates/residents. We need to address this in our hospitals and medical schools by providing easily accessible counselling facilities and psychologists to help them.
Paediatric Patients-Based Case-Control Analysis: The Association Between Serum Vitamin D Levels And Febrile Seizures
Authors: Nasir Farhina , Shakoor Ibrahim , Iqbal Syed Arif , Masood Shaheen , Farrukh Riffat , Naseer Amber
Published: May 2024

Objective: To determine the association between serum vitamin D levels and febrile seizures in the paediatric patients.
Study Design: Case-Control Study.
Place and Duration of Study: Abbasi Shaheed Hospital, Karachi Pakistan, from Mar 2020 to Mar 2021.
Methodology: The study included all pyrexia paediatric patients, both with and without febrile seizures, as cases and controls. Children aged below six months or older than 60 months, with a previous history of afebrile seizures, diagnosed with central nervous system infection, dehydration, or electrolyte disturbance, were excluded from the study. Serum vitamin D levels and other demographic data were documented.
Results: The study included 86 cases and controls. The mean age of cases was 28.07±16.47, and the controls were 26.38±15.72 months. The rate of vitamin D insufficiency was three times more likely in cases compared to controls, i.e. [OR, 95% CI: 3.95 (2.084—7.489)] with p=0.0001.
Conclusion: Vitamin D deficiency is substantially more likely in the case than in the control group. As a result, children with febrile seizures should have their serum vitamin D levels tested.
Cephalometric Differences In Male And Female Characteristics of Facial Soft Tissue Thickness In Various Orthodontic Malocclusions
Authors: Adnan Nasira , Amin Erum , Nawaz Ramsha , Ijaz Muska , Shah Tooba Ishtiaq , Janjua Tehreem
Published: May 2024

Objective: To compare the mean facial soft tissue thickness between males and females in different malocclusion groups.
Study Design: Cross-Sectional Study.
Place and Duration of Study: Armed Forces Institute of Dentistry, Rawalpindi Pakistan, from Jan 2020 to Jan 2021.
Methodology: Cephalometric radiographs of 230 patients were used to measure soft tissue thickness at seven landmarks: the glabella, subnasal region, labrale superius, labrale inferius, sulcus labrale superius, labiomentalis, and soft tissue chin.
Results: Of 230 patients, 39% were of Class I, 21% of Class II/1, 26% of Class II/2 and 13% of Class III. The gender ratio was the same in all skeletal classes. The mean age of 230 patients was 18.36±2.29 years. The mean ANB angle and UI were 4.02±3.22 and 25.95±8.86. The mean ANB angle and UI significantly differed between skeletal classes. In contrast, the mean age of patients of different skeletal classes was not significantly different, with a p-value of 0.433. The mean FSTT measured from subnasal area (A-NS), sulcus labrale superius (RR-SLS), labrale superius (J-LS), labrale inferius (I-Li) and chin (Pg-Pg1) was significantly different between skeletal classes (p value <0.001).
Conclusion: The facial soft tissue thickness was thicker in class III. The FST measured through the labrale superius (J-LS) of male patients was thicker than that of female patients in all skeletal class patients.
Association of Vernal Keratoconjunctivitis (VKC) with Keratoconus in Patients Presenting to Ophthalmology Clinics of Rawal Institute of Health Sciences, Pakistan
Authors: Zehra Maham , Anwar Mohd Shakaib , Yousafzai Erum , Ain Qura-Tul- , Akhter Waseem , Rana Afia Matloob
Published: May 2024

Objective: To establish an association of vernal keratoconjunctivitis with keratoconus.
Study Design: cross-sectional study.
Place and Duration of Study: Department of Ophthalmology, Rawal Institute of Health Sciences, Rawalpindi Pakistanv from Dec 2019 to Feb 2020.
Methodology: Patients with an age less than 16 years and a history of VKC were included. Ulcers or scars, systemic connective tissues, and blue sclera were excluded. Follow-up after two weeks and later three months was conducted. Individuals with K readings of less than 45 diopters were considered normal.
Results: Among the 135 individuals enrolled in the study, more males 95(70%) than women 40(30%) were observed. The study also showed more individuals from age groups 1-10 years of age 107(79%). After three months, biomicroscopic findings and corneal topography (Oculus Pentacam HR) revealed that 20 individuals (14.8%) developed keratoconus (p˂0.001). The disease severity, periodicity, and eye rubbing lead to the development of keratoconus.
Conclusion: Pediatric keratoconus deteriorates faster than adults, and the management differs for various reasons, such as faster progression and advanced stage of disease at the time of diagnosis. It burdens society as it influences children's quality of life and development. Hence, predisposing conditions such as Vernal keratoconjunctivitis need early diagnosis, recognition of progression, and appropriate intervention to prevent vision-threatening conditions such as keratoconus.
Goolge Earth Engine-based Rainfall-Runoff Modelling for Hydrological Assessment in Rasulpur River Basin
Authors: Das Goutam Kumar
Published: May 2024

The hydrological assessment of surface rainfall-runoff is crucial for effective water resource management and flood risk mitigation. Using the SCS-CN method, this study combined remote sensing GIS, and Google Earth Engine (GEE) methods to give an occupied hydrological assessment. GEE facilitated the processing of large-scale environmental data and facilitated large details of run-off properties, land used dynamics, and rainfall patterns. Following the study, there was an overall rise in runoff with rainfall for the years 2019 to 2022. For watersheds I, II, and III, the AMC results were 71.220, 74.990, and 33.330 for normal condition (CNII), dry condition (CNI), 50.965, 55.739, 17.353, and wet condition (CNIII), 85.056, 87.336, and 53.485, respectively. From 2019 to 2021, the average annual rainfall, volume of run-off, and run-off co-efficient are 10040.371 mm, 7728.371 mm3, and 0.764 mm respectively. The annual rainfall-run-off ratio is significantly increased in the years 2019 and 2021, but in 2022, are decreased. There is a strong relationship between total rainfall and run-off in the contain, with a correlation coefficient (r) value is 0.99. The Rasulpur River basin's hydrological behaviour was able to be accurately and recently assessed thanks to the use of high-resolution, real-time satellite data and it is a valuable tool for informed decision-making and the development of sustainable water resource management strategies.
Comparative Study of the Implementation of Accounting Conservatism in a Country: United Kingdom, Australia, Malaysia and Indonesia
Authors: Moh EKo Saputro
Published: May 2024

Artikel ini berfokus pada eksplorasi determinan yang dapat mempengaruhi tingkat konservatisme akuntansi, dan bagaimana suatu negara merespons hal tersebut. Negara yang kami jadikan sampel meliputi: Inggris, Australia, Malaysia, dan Indonesia. Kami menjelaskan beberaapa determinan yang paling sering digunakan pada penelitian-penelitian sebelumnya. Beberapa determinan tersebut yaitu financial distress dan laverage, Krisis financial, gender CEO, earnings timeliness, board composition, Independensi Dewan, dan Governance Mechanism. Kami menemukan bahwa tingkat konservatisme akuntansi di beberapa negara juga beragam. Hal ini disebabkan oleh perbedaan dari masing-masing keadaan negara. seperti halnya Malaysia dan Indonesia, yang sempat terpengaruh tingkat konservatisme nya karena adanya krisis keuangan Asia. Di sisi lain, Inggris dianggap sebagai salah satu negara dengan tingkat konservatisme yang tinggi di Eropa (Lara dan Mora:2004).
Pengaruh Karakteristik Individu, Lingkungan Kerja dan Kepuasan Kerja Terhadap Kinerja Pegawai Dinas Budaya dan Pariwisata Kabupaten Rembang
Authors: Nabilah Nur Rosyiqoh  , Dian Anita Sari
Published: May 2024

Penelitian ini bertujuan untuk mengetahui pengaruh karakteristik individu, lingkungan kerja dan kepuasan kerja terhadap kinerja pegawai Dinas Budaya dan Pariwisata Kabupaten Rembang. Populasi yang digunakan yaitu pegawai Dinas Budaya dan Pariwisata Kabupaten Rembang. Model pengambilan sampel yang digunakan yaitu total sampling. Teknik pengumpulan data dalam penelitian ini menggunakan metode survei dengan cara menyebar kuesioner pada 35 pegawai. Data yang digunakan adalah data primer, teknik analisis data yang digunakan dalam penelitian ini yaitu analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa: 1) karakteristik individu berpengaruh positif signifikan terhadap kinerja pegawai, 2) lingkungan kerja berpengaruh positif tidak signifikan terhadap kinerja pegawai dan 3) kepuasan kerja berpengaruh negatif tidak signifikan terhadap kinerja pegawai. Nilai adjusted R square adalah 0,895 artinya variabel independen pada model penelitian ini dapat menjelaskan variabel dependen sebesar 89,5% sedangkan 10,5% dijelaskan oleh faktor lain diluar model penelitian ini.
Pengaruh Self Assessment System Terhadap Penghindaran Pajak Dengan Religiusitas Intrinsik Sebagai Pemoderasi
Authors: Maulia Regita Belananda
Published: May 2024

The importance of this research was due to the greater dependence on the government budget (APBN) sourced from taxes. Tax avoidance is an action that has a negative effect on state revenues became a major concern for most countries to mitigate. This study aimed to evaluate the moderating role of intrinsic religiosity on the effect of the self assessment system as a taxpayer toward tax evasion. Evaluation of factors that can minimize tax avoidance, such as religiosity, is expected to provide important information for the tax authorities to optimize tax revenue. The purposive sampling method was used to select a sample of taxpayers. The research data and hypothesis were analyzed and tested using moderated regression analysis (MRA). The results of this study indicate that the self assessment system has a negative effect on tax evasion, and this study failed to support intrinsic religiosity as a moderating variable toward tax evasion.
Mgr. Keila Ledezma: ¨Las instituciones públicas, privadas y ONG´s deben crear más incubadoras de empresas que acompañen a las mujeres emprendedoras hasta que demuestren independencia en su emprendimiento¨
Authors: Aguilar Gutiérrez Diana
Published: May 2024

Entrevista: 
Keila Ledezma es una destacada emprendedora boliviana formada en España, consultora, docente y mentora de varios emprendimientos, actualmente tiene cuatro emprendimientos, entre ellos destaca VOAMEL, una marca de cosméticos comprometida con la economía circular que usa huesos de frutas para evitar residuos. Este emprendimiento de cosmética surgió por la necesidad de usar productos libres de químicos a raíz de una enfermedad que hubo en su casa
Restoration of the Debacle Faced Scheme - ‘Make in India’
Authors: Felix Caleb Mervin , Kumar A.C. Kiran
Published: May 2024

Initially, Covid-19 outbreak drew the progressive economy towards regression, but later with India being seen as a prime investment destination over China exacerbating the current scenario, there is a comeback of the failed campaign ‘Make In India’ to light, with global pharmaceuticals companies eyeing on India. Therefore there emerges a need for Make In India to be catering not just the pharmaceutical companies, but it is the right time to cater to other companies, as well, in various sectors to look at India as a profitable destination.
A Study on HR Analytical Tools and Techniques
Authors: Dr. Chitralekha Kumar Vidya Nayak, Dr. Shankar Chaudhary,
Published: May 2024

HR Analytics simplifies data collection, interpretation, measurement, and forecasting in organizations by combining statistical techniques for data collection, interpretation, measurement, and forecasting. It aims to enhance the utilization of data analytics in HR management actions, specifically in relation to tools and techniques with reference to employee attrition. Recent literature has reported that implementation of HR analytics helps in identifying employee attrition patterns, hiring timelines, productivity costs, and the impact of learning and development on performance. While the study suggests that a modern, innovative, and competitive workplace is being driven by performance expectations, which is why HR analytics is becoming more and more important in firms, it will also examine the advantages and challenges of HR analytics. This is a theoretical paper, and the purpose of this paper is to study the literature available on HR analytics tools and types of HR analytic techniques. The study is done based on secondary data from published research papers, journals, blogs, and websites from the period of 2017-2023.
AI-Powered Strategies for Talent Management Optimization
Authors: Dr. Borugadda Subbaiah Dr Sundarapandiyan Natarajan, Dr. Korapu Sattibabu, , M. Rajalakshmi Dr. D. Paul Dhinakaran, J. Rashmi Kumar,
Published: May 2024

In today's dynamic and competitive business landscape, effective talent management is paramount for organizational success. This paper explores the integration of artificial intelligence (AI) technologies into talent management practices to optimize recruitment, development, and retention processes. Through a comprehensive review of existing literature and case studies, we elucidate various AI-powered strategies for talent management optimization. These strategies encompass AI-driven recruitment, predictive analytics for talent acquisition, personalized learning and development initiatives, AI-enhanced performance management and feedback systems, retention strategies, succession planning, and diversity and inclusion initiatives. By harnessing AI capabilities, organizations can enhance decision-making, improve efficiency, mitigate bias, and foster a more inclusive and agile workforce. The implications of AI adoption in talent management are discussed, highlighting opportunities for innovation and potential challenges to address. Ultimately, this paper provides insights for HR professionals, business leaders, and researchers into leveraging AI for strategic talent management optimization in the digital age.
Ai-Driven Solutions for Supply Chain Management
Authors: Dr. Nagaraju Ellaturu Vandana. M, Naveena M, , M. Rajalakshmi Dr. T. Lavanya Kumari, Dr. Shweta Bambuwala,
Published: May 2024

In today's dynamic business environment, the efficient management of the supply chain is crucial for companies to stay competitive. Traditional methods often struggle to cope with the complexities and uncertainties inherent in modern supply chains. However, the integration of artificial intelligence (AI) is revolutionizing supply chain management by offering advanced tools and techniques to optimize various processes. This abstract explores the transformative impact of AI-driven solutions on supply chain management. It highlights key applications of AI, including demand forecasting, inventory optimization, supply chain planning, predictive maintenance, route optimization, supplier relationship management, warehouse automation, and blockchain integration. These AI-powered solutions enable companies to enhance efficiency, visibility, and decision-making capabilities throughout the supply chain. By leveraging AI algorithms to analyse vast amounts of data and extract valuable insights, companies can make more accurate demand forecasts, optimize inventory levels, and dynamically adjust supply chain plans in response to changing market conditions. Furthermore, AI-driven predictive maintenance and route optimization algorithms help minimize downtime, reduce transportation costs, and improve overall operational efficiency. Additionally, AI facilitates better supplier relationship management by identifying risks, opportunities, and areas for improvement in supplier relationships. Warehouse automation technologies powered by AI enhance throughput, reduce labor costs, and minimize errors in warehouse operations. Moreover, the integration of AI and blockchain technology ensures greater transparency, traceability, and security across the supply chain. Overall, the adoption of AI-driven solutions is reshaping supply chain management, enabling companies to achieve higher levels of efficiency, resilience, and competitiveness in today's rapidly evolving business landscape.
The Moravian Church in the Aftermath of World War I: Global Connections and Internal Disjunctions
Authors: Jensz Felicity
Published: May 2024

At the end of July 1919, members of the American, Continental, and British Provinces of the Moravian Church came together for the first time in five years to discuss the state of the church’s missions after the end of World War I. The preceding years had resulted in problems in terms of finances, administration, and labor as well as put into question the future of many mission fields. Nationalistic tensions ran high between members of the church, and there was a real concern that the worldwide Moravian Unity would be dissolved. That it did not was in part due to the sustained efforts of many members of the administrative bodies of the church who discussed how to resolve these tensions in various internal, international, and ecumenical settings. Through examining the reports from various missionary conferences in the aftermath of World War I, this article postulates that the structure of the Moravian Church allowed for the reconfiguration of the mission stations to fulfill external political, economic, and social expectations. The structure, however, also limited the work of the Continental Province of the church and created artificial distance between the Provinces.
Hormone replacement therapy and the incidence and prevalence of breast cancer: an integrative review
Authors: Feitosa Amanda , Chambó Lívia , Silva Marcela , Tasso Mariana , Abib Maria Fernanda , Masi Paula , Teruel Sofia , Oliveira Vitoria , Chagas Eduardo , Doca Heloísa
Published: May 2024

The objective of this study was to carry out an integrative review an integrative review to analyze the incidence and prevalence of breast cancer after hormone replacement therapy. This integrative review followed several steps, including identifying the topic, structuring the research question using the PICO strategy, defining inclusion criteria, selecting articles, evaluating and analyzing selected studies, interpreting the results and presenting the review. The use of hormone replacement therapy (HRT) is linked to a significantly increased risk of breast cancer, especially with combination therapy. The risk increases with time of use and persists after discontinuation. Although some studies have found a significant risk, estrogen-only therapy carries a lower risk, particularly for long-term use. Hormone replacement therapy, especially the combined formulation of estrogen and progestogen, is associated with a significant increase in the risk of breast cancer, persisting after discontinuation. The estrogen-only formulation has a lower risk. The duration of HRT and body mass index (BMI) also influence the risk.
Criptococose sistêmica atípica em felinos causada por Cryptococcus gattii VGII
Authors: Alberti Taina dos Santos , Marcolongo-Pereira Clairton , Venancio Fabiano da Rosa , Zamboni Rosimeri , Bermann Carolina dos Santos , Schild Ana Lucia , Pereira Daniela Isabel Brayer , Ianiski Lara Baccarin , Botton Sônia de Avila , Sallis Eliza Simone Viégas
Published: May 2024

Criptococose é uma micose sistêmica, subaguda a crônica causada por fungos do gênero Cryptococcus spp. A infecção ocorre principalmente por via aerógena, através da inalação de leveduras presentes no ambiente, podendo causar quadros respiratórios ou se disseminar por via hematógena para outros tecidos. O objetivo do presente trabalho foi descrever dois casos de criptococose sistêmica com diferentes apresentações clínico-patológicas em felinos. Dois felinos foram encaminhados para necropsia no Laboratório Regional de Diagnóstico (LRD) da Universidade Federal de Pelotas (UFPel). Um dos animais (felino 1) apresentava histórico de linfadenomegalia generalizada e o outro (felino 2) de emagrecimento e anisocoria. O felino 1 foi tratado durante 3 anos, porém apresentava recidivas e morreu após piora acentuada no último ano. O felino 2 foi eutanasiado pois o animal apresentou alterações comportamentais e convulsões. Na necropsia do felino 1 havia nodulações pardo-acinzentadas, homogêneas, de aspecto gelatinoso na região cervical e o pulmão apresentava-se armado e firme, com placas cinzentas, brilhantes, multifocais a coalescente em toda a superfície pleural. No felino 2 havia um nódulo bem delimitado branco-acinzentado no lobo caudal direito do pulmão e áreas cinzentas, irregulares e friáveis no encéfalo. Amostras de tecido, de ambos os casos, foram coletadas para exame anatomopatológico e cultura micológica. No exame histopatológico observou-se no pulmão, encéfalo e linfonodos do felino 1 áreas de necrose, com estruturas esféricas a ovais, de 2 a 10 µm de diâmetro, circundadas por halo claro (semelhantes a bolhas de sabão), compatíveis com leveduras e infiltrado inflamatório de macrófagos e neutrófilos. Também foram observadas células fúngicas no fígado, baço e rins. No encéfalo e pulmão do felino 2 foram observadas as mesmas lesões, porém no pulmão estas eram mais discretas. No exame micológico dos dois casos houve isolamento de Criptococcus gatti. O diagnóstico de criptococose em felinos pode ser realizado através do exame histopatológico e colorações especiais, baseando-se nas características histoquímicas típicas do agente, inclusive nos casos em que não ocorre lesão em plano nasal.
Protótipo para automatizar o processo de aparafusamento em movimento nas tampas traseiras de televisores fazendo uso da técnica do conveyor tracking
Authors: Feitoza Weidson de Oliveira , Glória Darío da Silva , Nascimento Carlos Wagner Alves , Gouvêa Nelson Alexandre , Moura Ricardo da Silva , Périco Alexandre de Magalhães , Sodré Anderson Bentes , Lima Ângela Timótia Pereira , Gomes Caio César de Araújo , Leão Juliana Marques , Lira Renato Souza de
Published: May 2024

O presente artigo tem como objetivo abordar a automatização do processo de aparafusamento da tampa traseira de televisores. Atualmente, essa tarefa é realizada manualmente, o que resulta em produção lenta, esforço repetitivo e concentração intensa por parte dos operadores. A solução proposta envolve o desenvolvimento de um protótipo que utiliza a técnica do conveyor tracking para automatizar o aparafusamento em movimento. Durante o desenvolvimento do projeto, foram enfrentados diversos desafios, como: controle preciso do torque para garantir que os parafusos sejam apertados com a força correta, implementação de um sistema de visão para utilizar câmeras para identificar os pontos de aparafusamento, sincronização com diferentes modelos na esteira para adaptar o sistema para lidar com diferentes tipos de televisores, alimentação automática dos parafusos para assegurar que os parafusos sejam fornecidos de forma contínua, atendimento aos tempos atuais da linha (Takt Time) para manter o ritmo de produção adequado e confirmação do aparafusamento em cada ponto do produto para verificar se todos os parafusos foram corretamente apertados. A metodologia utilizada no desenvolvimento do módulo de aparafusamento abrangeu as seguintes etapas: especificação de requisitos e planejamento que tem como finalidade identificação das funcionalidades do protótipo e planejamento das atividades, o projeto mecânico que permitiu a criação de desenhos 3D e 2D do módulo de aparafusamento, o projeto de automação responsável pela elaboração de uma lista de materiais ou itens comerciais e o projeto de software etapa responsável pela programação da automação do módulo, incluindo a lógica de controle e comunicação com outros sistemas. A implementação bem-sucedida desse projeto resultará em diversos benefícios para a linha de produção, incluindo o aumento da produtividade, a redução da fadiga dos operadores e o aprimoramento da qualidade do produto. Em resumo, a pesquisa científica não apenas aprimora processos industriais, mas também enriquece a sociedade e fortalece a base de conhecimento acadêmico.
A EMBALAGEM E SEU DESIGN ALÉM DE SEU PAPEL PRIMORDIAL ATUANDO COMO FERRAMENTA DE COMUNICAÇÃO E DE MARKETING
Authors: Silva Renato Emanuel Gomes da , Mantoan Alyne
Published: May 2024

Segundo Eldesouky e Mesias (2014), as embalagens bem desenhadas podem criar valor de comunicação. Atualmente, devido à enorme concorrência existente em todas as áreas, a embalagem ganhou destaque e importância no composto de marketing e na identificação para o consumidor, sob o domínio dos indícios que ela proporciona. O objetivo desta pesquisa é avaliar a embalagem e seu design além de seu papel primordial atuando como ferramenta de comunicação e de marketing. Trata-se de uma pesquisa exploratória com enfoque quantitativo, cujos dados foram coletados em um survey, baseado em uma escala do tipo Likert (1976). Foram aplicados 150 questionários a Professores Universitários da Cidade de São Paulo, contendo 10 assertivas. O levantamento dos resultados foi realizado por meio de Análise Fatorial e Modelagem de Equações Estruturais por Mínimos Quadrados Ponderados, MEE-PLS. O software utilizado para o tratamento de dados foi o IBM SPSS 18.0. O modelo de mensuração e o modelo estrutural foram desenvolvidos utilizando o software SmartPLS 3.0. A validade discriminante teve sua verificação pelo critério de Fornell-Larcker, por meio do qual apresentou validez discriminante em todos os três construtos propostos. O bootstrapping, processo que testa a significância do modelo, foi realizado em ambos os casos, inicial e final e apresentou significância nas estatísticas t, ao nível de 95% de confiança. As análises conduzidas a partir da utilização do modelo elaborado, em estado inicial e final, mostram que, apesar da falta de assertivas para avaliar de forma mais ampla a significância do mesmo, a confiabilidade (confiabilidade composta) e a significância estatística (bootstrapping) do mesmo, mostraram a validade do questionário e do método empregado, mostrando que, de fato, a composição e a funcionalidade afetam na percepção visual de uma embalagem, ou seja, esta torna-se uma forma de comunicação.
From Non-Invasive to Invasive Diagnosis in Pleural Tuberculosis: Case Series and Literature Review
Authors:   Department of General Surgery, ISSSTE General Hospital, Aguascalientes, Mexico, Nieves Arellano A , Gutiérrez Vargas HC ,   Department of Internal Medicine, ISSSTE General Hospital, Aguascalientes, Mexico, Rodríguez González JS ,   Department of Medicine, Autonomous University of Aguascalientes, Mexico, Montano Hernández PA ,   Department of Pathology, ISSSTE General Hospital, Aguascalientes, Mexico, Ortiz Pérez JDC ,   Department of Surgical Oncology, ISSSTE General Hospital, Aguascalientes, Mexico, Díaz JM ,   Department of Microbiology and Immunology, University of Western Ontario, Canada, Ponce Campos Silvia Denise ,   Department of Pneumology, ISSSTE General Hospital, Aguascalientes, Mexico
Published: May 2024

Introduction: Tuberculosis (TB) in Mexico is considered an endemic public health problem. Infection in adults is caused 95% of the time by Mycobacterium tuberculosis (Mtb). Although non-invasive diagnostic techniques are the first choice, the diagnostic yield of these techniques does not always allow definitive diagnosis, so sometimes, surgical biopsy is necessary. Objective: To describe two cases of pleural TB with a difficult diagnosis in which non-invasive diagnostic tests were inconclusive. Conclusion: In the presence of pleural or pulmonary nodules or tumors, we should consider TB as a differential diagnosis, as well as in those patients whose clinical suspicion is high and non-invasive methods have not been diagnostic. Therefore, the surgical approach is still an option for these patients.
Evaluation of plant diversity and soil quality under plantations raised in surface mined areas
Authors: Verma R. , Kapoor K. , Subramani S. , Rawat Ranjeet
Published: May 2024

Studies to evaluate the changes in plant diversity and chemical properties of soil under the plantations of Cupressus torulosa D. Don and Robinia pseud-acacia Linn. raised on mine overburden areas near Paonta Sahib in Sirmour District of Himachal Pradesh were carried out during August, 2000. The number of ground flora species as recorded under Cupressus torulosa and Robinia pseud-acacia plantations were 30 m-2 and 42 m-2 respectively. On the basis of Importance Value Index (IVI), Oplismenus compositus and Eupatorium adenophorum were found to be the dominant herbs under Cupressus torulosa and Robinia pseud-acacia plantation respectively. In general, distribution of most of ground flora species was contiguous. Index of dominance was lower and index of diversity was higher for ground flora under plantations as compared to the exposed mine overburden area. The ground flora under Robinia pseud-acacia has highest diversity index (4.223). The index of dissimilarity between plantations and exposed mine overburden area was high indicate remarkable degree of dissimilarity in ground flora species. However, there was plenty of similarity between two plantations as far as ground flora under them was concerned. Soil under plantations revealed better fertility status in comparison to exposed mine overburden area.
Improving Arabic Spam classification in social media using hyperparameters tuning and Particle Swarm Optimization
Authors:   Department of Curricula and Teaching Methods, College of Education, King Faisal University, P.O. Box: 400 Al-Ahsa, 31982, Saudi Arabia; Faculty of Specific Education, Minia university, Egypt, Amr Amr ,   Department of Mathematics and Statistics, College of Science, King Faisal University, P.O. Box: 400 Al-Ahsa, 31982, Saudi Arabia; Department of Computer Science, Faculty of Science, Minia University, P.O. Box:91519, Minia, Egypt,   Department of Computer Science, Faculty of Science, Minia University, P.O. Box:91519, Minia, Egypt, Eliwa Entesar H. Ibraheem , Omar Ahmed
Published: May 2024

Online social networks continue to evolve, serving a variety of purposes, such as sharing educational content, chatting, making friends and followers, sharing news, and playing online games. However, the widespread flow of unwanted messages poses significant problems, including reducing online user interaction time, extremist views, reducing the quality of information, especially in the educational field. The use of coordinated automated accounts or robots on social networking sites is a common tactic for spreading unwanted messages, rumors, fake news, and false testimonies for mass communication or targeted users. Since users (especially in the educational field) receive many messages through social media, they often fail to recognize the content of unwanted messages, which may contain harmful links, malicious programs, fake accounts, false reports, and misleading opinions. Therefore, it is vital to regulate and classify disturbing texts to enhance the security of social media. This study focuses on building an Arabic disturbing message dataset extracted from Twitter, which consists of 14,250 tweets. Our proposed methodology includes applying new tag identification technology to collected tweets. Then, we use prevailing machine learning algorithms to build a model for classifying disturbing messages in Arabic, using effective parameter tuning methods to obtain the most suitable parameters for each algorithm. In addition, we use particle swarm optimization to identify the most relevant features to improve the classification performance. The results indicate a clear improvement in the classification performance from 0.9822 to 0.98875, with a 50% reduction in the feature set. Our study focuses on Arabic spam messages, classifying spam messages, tuning effective parameters, and selecting features as key areas of investigation.
Lung nodule growth measurement and prediction using Multi scale - 3 D- UNet segmentation and shape variance analysis
Authors:   Research Scholar, Vel Tech Rangarajan Dr Sagunthala RD Institute of Science and Technology, India, Sathyamoorthy Sathyamoorthy ,   Associate Professor, Vel Tech Rangarajan Dr Sagunthala RD Institute of Science and Technology, India, S. Ravikumar.
Published: May 2024

In this work, a statistical model is constructed to forecast the possibility of lung nodules that may grow in the future. This study segments all potential lung nodule candidates using the Multi-scale 3D UNet (M-3D-UNet) method. 34 patients' CT scan series yielded an average of approximately 600 nodule candidates larger than 3 mm, which were then segmented. After removing the arteries, non-nodules and 3D shape variation analysis, 34 actual nodules remained. On actual nodules, the nodule growth Rate (NGR) was calculated in terms of 3D-volume change. Three of the 34 actual nodules had RNG values greater than one, indicating that they were malignant. Compactness, Tissue deficit, Tissue excess, Isotropic Factor and Edge gradient were used to develop the nodule growth predictive measure.
Fusing Deep Learning Techniques for Intrusion Detection in Smart Grids
Authors:   Department of Computer Science and Engineering ,Karunya Institute of Technology and Sciences, R. R. ,   Department of Computer Science and Engineering ,Rajiv Gandhi College of Engineering, Anna University,   Department of Computer Science and Engineering ,Karunya Institute of Technology and Sciences,   Department of Computer Science and Engineering ,Karunya Institute of Technology and Sciences, P. Sindhu. , Sundar G. Naveen , Venkatesan R.
Published: May 2024

Smart grids, pivotal in modern energy distribution, confront a mounting cybersecurity threat landscape due to their increased connectivity. This study introduces a novel hybrid deep learning approach designed for robust intrusion detection, addressing the imperative to fortify the security of these critical infrastructures. Renamed as Intrusion Detection for Smart Grid Using a Hybrid Deep Learning Approach, the study amalgamates Conv1D for spatial feature extraction, MaxPooling1D for dimensionality reduction, and GRU for modeling temporal dependencies. The research leverages the Edge-IIoTset Cyber Security Dataset, encompassing diverse layers of emerging technologies within smart grids and facilitating a nuanced understanding of intrusion patterns. Over 10 types of IoT devices and 14 attack categories contribute to the dataset's richness, enhancing the model's training and evaluation. The proposed hybrid model's architecture is detailed, emphasizing the synergy of convolutional and recurrent neural networks in addressing complex intrusion scenarios. This research not only contributes to the evolving field of intrusion detection in smart grids but also sets the stage for creating adaptive security systems. The convergence of a hybrid deep learning approach with a comprehensive cyber security dataset marks a significant stride towards fortifying smart grids against evolving cybersecurity threats. The proposed model achieves 98.20 percentage.
Intuitionistic Possibility Fermatean Fuzzy Soft Sets
Authors:   Department of Mathematics, Faculty of Science and Technology, Jadara University, Irbid 21110, Jordan, Areen Areen ,   Department of Mathematics, Faculty of Science and Technology, Jadara University, Irbid 21110, Jordan,   Department of Mathematics, Faculty of Science and Technology, Jadara University, Irbid 21110, Jordan,   Department of Mathematics, Faculty of Science and Technology, Jadara University, Irbid 21110, Jordan,   Department of Mathematics, Faculty of Science and Technology, Jadara University, Irbid 21110, Jordan, .. Areen Al , .. Hamzeh , .. Belal , Almarashdeh Rawan
Published: May 2024

In this study, we introduce a new concept by making Possibility Fermatean fuzzy soft sets into a more general concept, namely Intuitionistic Possibility Fermatean fuzzy soft sets. We present examples of the application of this theory to a decision-making problem. From a theoretical point of view, we review the basic properties of this model and define the operations essential to its framework. Comprehensive definitions of complement, union, and intersection, as well as AND and OR operations are meticulously presented. As a transition from theory to practical application within this innovative context, we present an algorithm for solving decision-making problems, contributing to the practical implementation of this extended concept. This research aims to improve our understanding of the intuitionistic possibility of Fermatean fuzzy soft sets and to bridge the gap between theoretical advances and their real-world utility in decision-making problems.
Boosting Financial Fraud Detection Using Parameter Tuned Ensemble Machine Learning Model
Authors:   Higher Colleges of Technology, United Arab Emirates, Atassi Reem , Zikriyoev Aziz ,   Tashkent state University of economics, Uzbekistan, Turayev Nurbek ,   Tashkent state University of economics, Uzbekistan, Botırovna Sagdullayeva Gulnora ,   Tashkent state University of economics, Uzbekistan
Published: May 2024

Fraud detection in the financial industry is a challenging area as financial transactions gradually shift to digital platforms. More and more businesses such as the financial industry are operationalizing their services online as the usage of the internet is growing exponentially. Accordingly, financial fraud can increase in number and forms worldwide leading to remarkable financial losses that make financial fraud a main challenge. Threats such as irregular attacks and unauthorized access must be identified through a financial fraud detection system. Over the past few years, data mining and machine learning (ML) approaches have been widely used to address these issues. However, this technique has yet to be enhanced in terms of speed computation, identifying unknown attack patterns, and dealing with big data. This study presents Financial Fraud Detection using the Parameter Tuned Ensemble Machine Learning (FFD-PTEML) method. The FFD-PTEML incorporates multiple advanced components, such as z-score normalization for feature scaling and ensemble classification employing Artificial Neural Networks (ANN), Multilayer Perceptron (MLP), and Radial Basis Function (RBF) networks. The use of z-score normalization ensures uniformity in feature distribution, improving the effectiveness and interpretability of the fraud detection technique. Furthermore, the ensemble classification model combines the strength of different neural network architectures to enhance the detection performance and resilience to complicated fraud patterns. FFD-PTEML demonstrates better performance than the classical technique through extensive experimentation on real-time financial datasets, exhibiting high sensitivity and specificity in fraudulent activity detection.
Development of an Approach for Image Forgery Detection Using Machine Learning Algorithms
Authors:   Ministry of Education, General Directorate of  Dhi Qar  Education, Dhi Qar, Iraq, Ahmed Ahmed
Published: May 2024

Digital picture fraud detection is an increasing societal necessity due to the importance of verified images. The detection of picture copying, splicing, retouching, and re-sampling forgeries is included. In the absence of digital signatures or watermarks, passive picture authentication may serve as an alternative to active authentication. Passive techniques, every so often recognized as blind techniques, could take place without preceding knowledge of the picture or its reference. Identifying counterfeiting picture or tampering was a research field for long a period of time, triggered via the Internet, online platforms, social messaging platforms, and extensive digital image usage. The rate of failure could be a key factor for examining the alteration of picture or forgery, among other existing methods. The research applies almost six common algorithms related to machine learning in order to extract features from Lightweight, Spatial Exploitation, and Residual deep learning models on benchmark datasets MICC-F220, Columbia, and CoMoFoD. The models of incorporated deep learning could consist of AlexNet, GoogleNet, VGG16, VGG19, SqueezeNet, MobileNetV2, ShuffleNet, ResNet-18, ResNet-50, and ResNet-101 for spatial exploitation. Fine-tuning is applied to the top three deep learning models, optimizing hyperparameters centered on indicators of performance for every single benchmark dataset. Tweaked SqueezeNet, MobileNetV2, and ShuffleNet deep learning models with SGDM Optimizer and SVM classifier yielded the best results for MICC-F220 dataset. Fine-tuned VGG19, MobileNetV2, and ResNet-50 deep learning models with SGDM Optimizer and SVM v classifier yielded the best results for Columbia dataset. In CoMoFoD dataset, fine-tuned AlexNet, MobileNetV2, and ShuffleNet deep learning models with SGDM Optimizer and SVM classifier yielded the best results. The proposed approach, utilizing machine learning algorithms and deep learning features, enhanced forgery detection and reduced false positives. Results were validated on benchmark image forgery datasets and compared to current methods.
Peran Pengembangan Kepribadian Guru Sebagai Pembentuk Karakter Siswa Pada Tingkat Sekolah Dasar
Authors: Maslinda Rizky , Herachwati Nuri , Nadia Fiona Niska Dinda
Published: May 2024

Keakraban psikologis antara guru dan siswa merupakan unsur penting dalam proses pembelajaran di sekolah dasar. Karakter dan kepribadian guru yang matang, kuat dan unik dapat menjadi teladan dan inspirasi bagi siswa. Hubungan yang berkualitas antara guru dan siswa hanya dapat terjalin jika didukung oleh karakter guru yang baik. Kepribadian merupakan keseluruhan kualitas sikap dan perilaku serta merupakan prasyarat utama bagi terselenggaranya proses belajar mengajar secara optimal. Definisi kepribadian yang dibicarakan para ahli menunjukkan bahwa kepribadian bersifat dinamis, berkaitan dengan sistem psikofisiologis, dan menentukan tindakan, pikiran, dan sifat seseorang. Kepribadian juga dapat digambarkan sebagai kualitas pribadi yang diungkapkan melalui pola perilaku yang konsisten terhadap lingkungan. Harga diri seorang guru merupakan unsur terpenting dalam kepribadiannya dalam mencapai keberhasilan profesional. Oleh karena itu, guru harus mampu mengenalinya dan mengembangkannya secara sehat.
Motivasi Berprestasi, Motivasi Kekuasaan dan Motivasi Afiliasi serta Pengaruhnya terhadap Prestasi Kerja Karyawan
Authors: Waruwu Fotuho
Published: May 2024

Prestasi kerja merupakan suatu pencapaian yang melebihi dari hasil kerja yang diharapkan oleh perusahaan. Semua perusahaan ataupun organisasi perlu memiliki sumber daya manusia yang berprestasi agar tujuan perusahaan dapat terwujud dan perusahaan dapat berkembang. Salah satu faktor yang dapat meningkatkan prestasi kerja adalah motivasi. Penelitian ini bertujuan untuk mengetahui pengaruh motivasi berprestasi, motivasi kekuasaan dan motivasi afiliasi terhadap prestasi kerja pada PT Sumber Alfaria Trijaya Tbk (Cabang Bandung 1), objek dalam penelitian ini adalah PT Sumber Alfaria Trijaya Tbk. Variabel independen dalam penelitian ini adalah motivasi berprestasi, motivasi kekuasaan dan motivasi afiliasi, serta variabel dependen pada penelitian ini adalah prestasi kerja. Jenis penelitian yang digunakan adalah causal explanatory dan metode yang digunakan adalah kuantitatif, dengan jumlah sampel sebanyak 31 karyawan. Teknik analisa data yang digunakan adalah Regresi Linear Berganda dengan alat bantu software komputer SPSS 22.0 for windows. Berdasarkan hasil penelitian, secara keseluruhan nilai perhitungan yang diperoleh melalui regresi linear berganda bahwa tingkat motivasi kerja yang dimiliki PT Sumber Alfaria Trijaya Tbk. berpengaruh positif dengan kategori sangat kuat terhadap prestasi kerja.
Kelayakan Buku Ajar Mata Kuliah Pembelajaran Sepakbola
Authors: Firdana Muhammad Yuda , Pamungkas Hari , Nidomuddin Muhammad , Pradipta Anangga Widya , Kurniawan Rubbi
Published: May 2024

Mata kuliah pembelajaran sepakbola merupakan mata kuliah teori dan praktik dengan cakupan materi yang kompleks sehingga memerlukan sumber belajar. Salah satu sumber belajar yang dapat digunakan dalam pembelajaran mata kuliah pembelajaran sepakbola yaitu buku ajar. Penelitian ini bertujuan untuk mengukur kelayakan buku ajar mata kuliah pembelajaran sepakbola ditinjau dari ahli materi dan ahli media. Penelitian ini menggunakan metode penelitian deskriptif kuantitatif. Subjek penelitian yaitu ahli materi dan ahli media. Tempat Pelaksanaan penelitian di Universitas Insan Budi Utomo. Instrumen yang digunakan berupa  angket  untuk  mengetahui  kelayakan  buku  ajar  berdasarkan ahli materi dan ahli media. Perolehan skor kelayakan ahli materi yaitu sebesar 48 dari skor maksimal 52 dengan persentase 92%. Perolehan skor ahli media sebesar 178 dari skor maksimal 188 dengan persentase 94%. Berdasarkan perolehan skor kelayakan ahli materi dan ahli media, buku ajar mata kuliah belajar dan pembelajaran dinyatakan valid dan dapat digunakan.
Analisis Faktor-Faktor Yang Mempengaruhi Minat Mahasiswa dalam Melakukan Investasi Pada Galeri Investasi Nahdlatul Ulama Sidoarjo
Authors: Kartikasari Maharani , Muzakki Kafidin
Published: May 2024

Investasi adalah sebuah terminologi yang erat hubungannya dengan bidang keuangan dan ekonomi dimana investasi merupakan tindakan mengorbankan konsumsi saat ini, yang melibatkan uang untuk mendapatkan hasil atau keuntungan di masa depan. Namun saat ini masih rendahnya minat berinvestasi terutama di kalangan mahasiswa. Penelitian ini dilakukan bertujuan untuk mengetahui pengaruh faktor sikap, norma subjektif, presepsi kontrol prilaku dan presepsi risiko terhadap minat berinvestasi mahasiswa fakultas ekonomi universitas nahdlatul ulama Sidoarjo. Jenis penelitian ini adalah penelitian kuantitatif dengan pendekatan asosiatif. Populasi dalam penelitian ini berjumlah 101 mahasiswa. Penelitian ini mengunakan teknik Purposive sampling dengan adanya kriteria. Jumlah sampel yang sudah memenuhi kriteria sebanyak 97 responden. Teknik pengumpulan data yang dilakukan melalui penyebaran kuesioner melalui google form pada mahasiswa fakultas ekonomi angkatan 2020-2022. Teknik analisis data yang digunakan adalah regresi linier berganda dengan bantuan program SPSS versi 24.0. Hasil penelitian ini menyatakan bahwa faktor sikap, norma subjektif, presepsi kontrol prilaku dan presepsi risiko secara simultan berpengaruh positif terhadap minat berinvestasi mahasiswa fakultas ekonomi universitas nahdlatul ulama sidoarjo. Adanya variable sikap tidak berpengaruh terhadap minat berinvestasi mahasiswa fakultas ekonomi universitas nahdlatul ulama Sidoarjo. Namun variabel norma subjektif, prespesi kontrol prilaku dan presepsi risiko berpengaruh positif terhadap minat berinvestasi mahasiswa fakultas ekonomu universitas nahdlatul ulama Sidoarjo.