bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of an educational Program on improving nurses’ knowledge regarding Apgar score in Akre city
Authors: Othman Shevan Younis , Mosa Mohammed Haydar
Published: October 2024

Background: Newborns are tested shortly after birth to get their Apgar score. This assessment evaluates an infant’s cardiac function, muscle tone, and other essential characteristics to establish whether additional investigations or actions that can be considered as emergency procedures are needed.      
Objectives: To assess the impact of the educational program in enhancing the knowledge of Apgar scores among nurses.      
Methodology: A cross-sectional interventional study was conducted with the selected nurses at the General Hospital and the Pediatric and Maternity Hospital in Akre City in order to evaluate the effectiveness of the educational program for enhancing the knowledge of the Apgar score. Eighty nurse nurses, who made up the entire study population during the study period, made up the sample size. Participants were asked to complete a questionnaire, specially designed for the research, indicating their overall satisfaction. In the data analysis, a statistical package for social sciences (SPSS) was used to analyze the results.                                                                                  
Results: This current study found out that, the overall mean knowledge degrees of the nurses rose 30 days after the program had been initiated; the enhancement is statistically significant.         
Conclusion: A thorough training program significantly increased the nurses' understanding of the Apgar score
Assessment of Troponin Levels as a Biomarker of Myocardial Injury in Patients with Fatal Covid-19 for the Period 2020 to 2022: A Literature Review
Authors: Al_Joubouri Zainab Tawfeeq , Shamran Shaymaa Galeel , Jabbar Rehab Mazi , Ajeena Entesar Gh.
Published: October 2024

Background: COVID-19 initially described at the end of 2019. COVID-19 is caused by an uncommon ‎coronavirus infection. Since then, it has been spreading rapidly and has caused a global pandemic, infecting more than 29 million people and causing more than ‎‎900,000 deaths as of September 15, 2020. In most cases this disease mainly affects the respiratory ‎system and can cause a syndrome called acute respiratory distress, leading to acute ‎respiratory failure. However, COVID-19 causes other systemic ‎indications, such as myocardial injury, coagulopathy, and cytokine storm. Myocardial injury patients were determined by elevated troponin levels by large number of COVID-19 patients, ranging from ''7.2% to 36%''. COVID-19 patients may experience myocardial injury due to other complications such as ‎arrhythmias, heart failure, or even sudden cardiac arrest, as well, COVID-19 is a complex disease that can cause severe respiratory ‎failure. Understanding these complications is crucial for ‎managing the disease ‎and developing effective treatment.     
Aim: This review research aims to assess the roles of troponin in COVID-19 patients at a higher risk of ‎myocardial injury, as well as shed light on the most significant research articles conducted in this ‎field of regard area between 2020 and 2022.
Methods and Materials: This review outlined the latest scientific research for the period from 2020 to ‎‎2022 ‎associated with the involvement of cardiac injury in the population of COVID-19 ‎‎patients by focusing on the use of troponin levels as a vital ‎indication. Additionally, it is starting from ‎encountered patients with COVID-19, as well as it‎‏ is ‏‎related to the increased risk of ‎death data and it had a crucial role in the identification of COVID-19 with a high risk of hypoxia in the blood. At that point, it was going through the evidence regarding COVID-19 and ‎cardiovascular biomarkers, such as troponin articles recognized using the electronic ‎search, as performed via PubMed, Embase, and Google Scholar Database through a ‎comprehensive search conducted by combining key terms for instance; “biomarkers”, ’’myocarditis”, “COVID-19”, “troponin”. English-language articles were screened for ‎relevance and a full review of publications for the important studies was conducted, ‎including additional publications identified from individual article ‎reference lists.                                                                       
Conclusion: Cardiac troponin (cTn) is the most reliable test for detecting heart disease, particularly myocardial injury. Elevated levels of troponin (both cTnI and cTnT) are a critical risk factor for severe myocardial injury and hospitalizations, especially for COVID-19 patients who face a higher risk of adverse events. Therefore, measuring cTn levels is critical to monitor the progression of heart disease and effectively manage patients'
The Double-Edged Sword of Social Media on Mental Health: A Review of Current Research
Authors: Hanine Ismail , Douk Kamal , Amara Yahya , Mouhadi Khalid , Kadiri Mohamed
Published: October 2024

Social media has undeniably become an integral part of modern life, offering numerous benefits such as connection, information dissemination, and entertainment. However, its impact on mental health has been a subject of growing concern. While excessive use of social media has been linked to negative mental health outcomes, particularly depression, it can also be harnessed as a valuable tool for therapeutic interventions, especially within the framework of self-expression, seeking help and belonging to therapeutic communities. This brief review of current research, shed the light on the positive and negative aspects of this trend.
Renal Function Alterations Following Contrast Media Exposure: A Clinical Analysis
Authors: Mazumder Dr. Mohammad Mahbub Alam , Haque Dr. A.H.M. Aslam-Ul- , Hossain Dr. Mohammad Rezaul
Published: October 2024

Introduction: Contrast-Induced Nephropathy (CIN) typically occurs within 24 to 72 hours after contrast media exposure, potentially leading to serious complications. The purpose of the study was to clinically analyze renal function changes following contrast media exposure and explore strategies for prevention and management. Aim of the study: The aim of the study was to clinically analyze renal function alterations following contrast media exposure. Methods: This prospective observational study included 140 patients who underwent imaging procedures with contrast media at the Department of Nephrology, Colonel Maleque Medical College, Manikganj, Bangladesh, from January 1, 2019, to December 31, 2023. Patients aged 18 years and above, with no pre-existing severe renal impairment, were included. Data on serum creatinine, risk factors such as diabetes and hypertension, and renal function outcomes were collected and analyzed using SPSS version 22.0. Result: The majority of patients (42.86%) were aged 57–61 years, with 64.29% being male. Post-contrast serum creatinine were less than 80 µmol/L in 50.00% of patients and 14.29% developed contrast-induced nephropathy (CIN). Diabetes mellitus was significantly more prevalent among CIN patients, occurring in 60.00% compared to 19.16% in non-CIN patients. Among those with CIN, 65% achieved renal function recovery within 7 days. Conclusion: Exposure to contrast media can significantly alter renal function. Incidence of contrast-induced nephropathy was 14.29%. Higher risk in patients with pre-existing conditions and favorable short-term recovery, though some may experience persistent renal dysfunction.
How does integration of comprehensive sexuality education in schools shape sexuality decisions among adolescents in Zambia?: A community based participatory research driven realist evaluation study protocol
Authors: Zulu Joseph Mumba , Goicolea Isabel , Chavula Paul , Mulubwa Chama , Michelo Charles , Musonda Patrick , Matafwali Beatrice , Hurtig Anna-Karin
Published: October 2024

Introduction: Many adolescents in low- and middle-income countries face challenges related to sexual and reproductive health and rights, which are exacerbated by gender inequalities. One approach to address these issues is the integration of Comprehensive Sexuality Education (CSE) in schools. However, the process of effectively implementing CSE in these settings is often suboptimal. There is a significant lack of research exploring the specific conditions and methods that effectively lead to enhanced knowledge and improved decision-making in sexuality and gender equality among adolescents through CSE. This realist evaluation protocol will address this gap by exploring how the nature and pattern through which CSE is provided has a) changed adolescents’ knowledge regarding sexuality and gender relations and b) shaped adolescents’ capacity to make positive decisions.
Methods: This study uses a multiple-case design, combining realist evaluation with participatory action research methods to explore Comprehensive Sexuality Education (CSE) integration across multiple levels in Eastern province—from provincial to community levels. Data collection will occur in phases, utilizing interviews, photovoice, drawings, reviews, and observations. The study involves several key steps: 1) identifying challenges to CSE integration, 2) creating an initial theory or action plan that explains how CSE promotes positive decisions among adolescents about sexuality, 3) testing this theory through case studies, and 4) refining the theory and formulating recommendations to improve future CSE integration. Additionally, the study will document informal, contextual, and horizontal factors (ICAMO configurations) that influence the integration of CSE at the school level and affect adolescents' understanding and decision-making regarding sexuality and gender relations.
Discussion: This study will contribute to the development of strategies for effectively facilitating the integration process of similar programmes within the school system. The study will further contribute to methodological development in participatory research driven realist evaluation.
РОЛЬ АГРОХИМИЧЕСКИХ СВОЙСТВ ЧЕРНОЗЕМА ВЫЩЕЛОЧЕННОГО В УСТОЙЧИВОСТИ К ЗАГРЯЗНЕНИЮ ТЯЖЕЛЫМИ МЕТАЛЛАМИ
Authors: Захарова О.А. , Садовая И.И.
Published: October 2024

Аннотация. Проблема и цель. Тяжелые металлы (ТМ) являются цитоплазматическими ядами, влияющими на количество урожая и качество продукции, ухудшающими продуктивность земель. Цель исследований – анализ агрохимических свойств чернозема выщелоченного в устойчивости к загрязнению тяжелыми металлами при внесении органического удобрения на основе отходов животноводства. Методология. Методика исследований общепринятая. Анализы выполнялись при участии к.т.н., в.н.с. ВНИИГиМ К.Н. Евсенкина. Обработка результатов исследований с использованием программы Statistika 10. Результаты. Урожай овса выше среднего по Рязанской области и по хозяйству на 34 и 36% соответственно, рНКCl соответствовал градации близкие к нейтральным. Общее количество катионов 32 мг∙экв/100 г почвы. По сумме поглощенных оснований почва вошла в группировку очень высокая. Чернозем выщелоченный обладает буферностью, в составе его поглощенных катионов преобладают Са2+ и Мg2+, их содержание выросло до 38 мг∙экв/100 г почвы. Общая численность целлюлозоразрушающей микрофлоры увеличилась с 277 тыс.КОЕ/г до 322 тыс.КОЕ/г. Концентрации Zn, Cd, Pb соответствовали уровню градации по шкале экологического нормирования по подвижным формам как умеренно-опасные, а по концентрации Cu - повышенно-опасные. По шкале частных оценок буферности к ТМ по содержанию гумуса почва находилась в интервале, равному 3,5 баллам, физической глине – 8 баллам, полуторным оксидам – 4 баллам, рН – 10 баллам с учетом поправочного коэффициента. Буферность почвы по отношению к ТМ составила 25,5 баллов, то есть была ниже градации повышенная (от 31 до 40 баллов), что, в общем, соответствовало показателям небогатой почвы. Интегральная оценка загрязнения (ИОЗ) зерна ТМ составила 3,29, что свидетельствовало 1-ому уровню загрязнения. Заключение. Содержание ТМ в почве соответствовало уровню градации по шкале экологического нормирования как умеренно-опасные, кроме Cu - повышенно-опасные.
Enhancing Risk Management in Cloud Security Using Machine Learning: An Indian Enterprise Case Study
Authors: Dr. Pooja Singh
Published: October 2024

This paper explores the application of machine learning (ML) techniques in improving risk management for cloud security in Indian enterprises. As Indian companies migrate to cloud infrastructures, they face new security challenges. The study presents various ML models such as Decision Trees, Random Forest, and Support Vector Machines (SVM) applied to cloud security systems to mitigate risks like unauthorized access, data breaches, and Distributed Denial of Service (DDoS) attacks. Case studies from major Indian industries are analyzed to showcase the effectiveness of these models in real-time risk detection and mitigation. The paper also discusses challenges such as data privacy, scalability, and compliance with Indian cyber laws.
Adversarial Machine Learning in Indian Cybersecurity: Threats and Mitigation Strategies
Authors: Dr. Rahul Kumar
Published: October 2024

With the rise of machine learning (ML) in cybersecurity, adversarial attacks targeting ML models pose new challenges to Indian enterprises. This paper explores the vulnerabilities of machine learning models to adversarial attacks, particularly in critical Indian sectors such as finance, healthcare, and government. The study reviews attack vectors such as evasion, poisoning, and inference attacks, and suggests robust mitigation strategies like adversarial training, gradient masking, and defense distillation. Case studies from Indian organizations implementing adversarial-resistant ML models are analyzed to demonstrate real-world applications and effectiveness.
Machine Learning for Risk Compliance Automation in India’s Financial Sector
Authors: Dr. Amitabh Sharma
Published: October 2024

The automation of risk compliance through machine learning (ML) has become essential for Indian financial institutions to ensure adherence to regulatory standards. This paper explores the use of ML algorithms such as Decision Trees, Random Forest, and Support Vector Machines (SVM) to automate the process of risk compliance. The study evaluates how these algorithms can analyze large volumes of financial data to detect compliance violations, fraud, and money laundering activities. The research also examines the role of AI in enhancing transparency and reducing operational costs in the Indian financial sector.
Deep Learning Approaches to Cloud Security in the Indian Retail Sector
Authors: Dr. Raghavendra Rao
Published: October 2024

Cloud security in India's retail sector has become a significant concern as the industry adopts cloud-based solutions for data management and customer engagement. This paper examines how deep learning techniques such as Convolutional Neural Networks (CNN) and Autoencoders can be applied to detect anomalies and mitigate cyber threats in cloud-based retail environments. The study focuses on identifying and addressing security vulnerabilities such as data breaches, insider threats, and account takeovers. By presenting case studies from leading Indian retail companies, the paper highlights the potential of deep learning to enhance security and operational efficiency in cloud infrastructures.
AI-Powered Credit Scoring Models: Transforming Financial Inclusion in Rural India
Authors: Dr. Priyanka Gupta
Published: October 2024

This paper discusses the role of AI in enhancing financial inclusion in rural India by implementing AI-powered credit scoring models. Traditional credit scoring systems are often inaccessible to rural populations due to a lack of financial history. AI models, particularly machine learning algorithms such as Random Forest, Gradient Boosting, and Neural Networks, offer alternative methods to assess creditworthiness by analyzing non-traditional data sources such as mobile usage, social media activity, and transaction histories. The study examines the effectiveness of AI-driven credit scoring systems implemented by Indian fintech companies, focusing on their impact in improving access to credit for small-scale farmers and rural entrepreneurs. The paper also addresses the ethical implications, including privacy concerns, algorithmic bias, and the need for regulatory frameworks to govern AI-based credit scoring systems. By highlighting case studies from rural India, the paper demonstrates how AI can be a game changer in bridging the financial inclusion gap and contributing to India's economic growth.
Advancements in Cloud Security: Leveraging Machine Learning for Threat Detection
Authors: Dr. Samuel Green
Published: October 2024

Cloud security is becoming increasingly vital as organizations migrate their data and services to cloud infrastructures. This paper investigates the integration of machine learning (ML) algorithms into cloud security frameworks to improve threat detection and mitigate security risks. With the advent of complex, distributed cloud environments, traditional security mechanisms often fail to detect sophisticated attacks such as Distributed Denial of Service (DDoS), Advanced Persistent Threats (APTs), and zero-day vulnerabilities. Machine learning models, including supervised, unsupervised, and reinforcement learning, offer new methodologies to detect and respond to security anomalies. The study explores how ML techniques, such as anomaly detection, classification, and clustering, can be applied to large-scale cloud data to identify malicious behaviors in real time. By employing neural networks and decision trees, cloud-based systems can learn from historical attack patterns to improve detection accuracy. The paper presents a comparative analysis of ML models used in threat detection, including Random Forest, Support Vector Machines (SVM), and Convolutional Neural Networks (CNN), demonstrating their effectiveness in enhancing cloud security postures. Moreover, it delves into the challenges of implementing ML in cloud environments, including data privacy, the risk of adversarial attacks on ML models, and the need for real-time processing of large datasets. The paper also proposes a hybrid framework that combines ML-based threat detection with traditional security measures like firewalls and intrusion detection systems (IDS). Future directions for improving ML-driven cloud security are discussed, particularly in the context of emerging technologies like edge computing and the Internet of Things (IoT).
Deep Learning Models for Cybersecurity: A Comparative Analysis of CNN and RNN Architectures
Authors: Dr. John Smith
Published: October 2024

Cybersecurity has increasingly turned to deep learning models to address the growing complexity of cyber threats. This paper provides a comparative analysis of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in detecting various types of cyber attacks, including malware, phishing, and network intrusions. The research examines how CNNs, traditionally used in image processing, can be adapted for network traffic analysis, while RNNs are leveraged for sequence data in detecting attack patterns over time. The paper discusses the performance of these models in terms of accuracy, detection speed, and false-positive rates. It also explores the training requirements for each architecture and the datasets used to benchmark their performance. The potential for hybrid models that combine CNN and RNN elements to enhance cybersecurity is also discussed, along with the challenges posed by adversarial attacks on deep learning systems. The paper concludes with recommendations for deploying these models in real-world cybersecurity applications.
Machine Learning for Predictive Healthcare: Early Diagnosis of Diabetic Retinopathy in India
Authors: Dr. Priya Nair
Published: October 2024

Diabetic retinopathy (DR) is a leading cause of blindness in India, and early detection can significantly reduce its impact. This paper proposes a machine learning-based predictive model for the early diagnosis of DR using retinal imaging. The study evaluates various machine learning algorithms, including Support Vector Machines (SVM), Random Forest, and Convolutional Neural Networks (CNN), to develop a reliable classification model. Using a dataset from leading Indian hospitals, the paper demonstrates the effectiveness of these models in detecting DR at its early stages. The challenges in data collection, such as the need for high-quality retinal images and the lack of accessible diagnostic tools in rural areas, are also discussed.
Deep Learning Models for Cybersecurity in Indian Enterprises: A Comparative Study
Authors: Dr. Ravi Malhotra
Published: October 2024

Indian enterprises are becoming prime targets for cyberattacks, highlighting the need for robust cybersecurity systems. This paper provides a comparative analysis of deep learning models, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), for detecting cyber threats in Indian businesses. The research focuses on identifying advanced threats such as ransomware, phishing, and insider threats by leveraging large-scale enterprise data. By comparing the performance of CNN and LSTM models, the paper highlights their respective strengths in real-time threat detection and sequence data processing. The paper also discusses the practical challenges of implementing deep learning systems in Indian organizations.
Cloud Security in Indian FinTech: A Machine Learning Approach to Risk Mitigation
Authors: Dr. Ravi Malhotra
Published: October 2024

As India's FinTech sector grows, so do the security challenges associated with cloud-based financial services. This paper investigates how machine learning algorithms can be utilized to enhance cloud security in Indian FinTech companies. The study evaluates the performance of various ML models, such as Random Forest and Gradient Boosting, in detecting security threats like identity theft, account takeover, and payment fraud. The research highlights the need for real-time threat detection systems that comply with Indian regulatory frameworks, such as the Payment and Settlement Systems Act. Case studies of prominent Indian FinTech companies that have implemented ML-based security systems are also presented.
Deep Learning for Indian Language Processing: A Focus on Speech Recognition Systems
Authors: Dr. Ashish Ranjan
Published: October 2024

India's linguistic diversity poses unique challenges for the development of AI-powered speech recognition systems. This paper presents a deep learning-based approach to develop robust speech recognition systems for Indian languages. The research evaluates models like Recurrent Neural Networks (RNN) and Transformer architectures to enhance the accuracy of speech-to-text conversion in languages such as Hindi, Tamil, Bengali, and Marathi. By using datasets from regional linguistic repositories, the study showcases the challenges of dialect variation, pronunciation differences, and lack of annotated data. The paper also discusses the socio-economic benefits of speech recognition technologies in India, particularly in areas like education, healthcare, and governance.
La Disputa por el Estado de México
Authors: Johansson Mondragón Steven Iván
Published: October 2024

El trabajo busca determinar, a partir del análisis comparativo de las plataformas electorales redactadas por los partidos políticos para las elecciones de gobernador del Estado de México de 2023, si el discurso morenista es sustancialmente distinto al del resto de los partidos mexicanos. Se pone a prueba, a través de las herramientas que ofrece la lexicometría, la hipótesis de que, a semejanza de lo que ocurre en las plataformas federales, no hay, a nivel subnacional, una oposición significativa entre el discurso de Morena y el de los demás partidos, lo cual no implica que no haya una serie de temas que generen controversia. Se llega a la conclusión de que sí existen diferencias significativas, pero que éstas se deben en lo fundamental al alcance de las plataformas, nacional en el caso de Morena, local en el caso de los demás partidos.
O CORPO DA TRABALHADORA E A “IGUALDADE DE OPORTUNIDADES” NO CAPITALISMO
Authors: LYRA LIMA FÉLIX TATIANA
Published: October 2024

O presente texto tem como fio condutor, primeiramente, a captura do modus operandi do capital para explorar o corpo do trabalhador, em que a contraposição cabeça e mãos encontra seu coroamento na exploração do corpo da trabalhadora de procedência negra. No segundo momento, observa-se como a ideologia da “igualdade de oportunidades” tenta obliterar a constituição duma efetiva igualdade substancial entre os gêneros no interior de um sistema hierarquicamente estruturado para controlar ubiquamente a força de trabalho. Desse modo, busca-se entender como a opressão à mulher penetrou o seu corpo mediante um complexo de mediações ideológicas regulamentadas na perspectiva de aprofundar a apropriação do tempo de trabalho excedente. Para analisar o processo de reificação que inscreve a subjetividade e a corporeidade feminina no modo de produção capitalista, recorrer-se-á aos empréstimos teóricos oferecidos por Heleieth Saffioti (1976), Karl Marx (1985) e István Mészáros (2011).
TRABALHADORAS DOMÉSTICAS NEGRAS E A PANDEMIA DA COVID-19 NO BRASIL
Authors: Silva Joelcio Jackson Lima , Felix Thayná da Silva
Published: October 2024

Este artigo tem como objetivo evidenciar a exposição das trabalhadoras domésticas negras à morte, em específico durante a Pandemia da Covid-19 no Brasil. Tem-se abordagem qualitativa e baseada em pesquisas documental e bibliográfica, afrorreferenciada em intelectuais negras. De modo geral, a partir de Gonzalez (2020), discute-se sobre a posição das mulheres negras na sociedade brasileira pós-abolição em relação as divisões do trabalho. Apresenta-se as vulnerabilidades da população negra brasileira, por último reflete-se sobre as reivindicações da categoria das trabalhadoras domésticas por uma quarentena remunerada, em contraponto a tendência que houve em afirmar todo trabalho doméstico como serviço essencial. Parte-se da interseccionalidade, enquanto sensibilidade analítica que dá instrumentalidade teórico-metodológica para compreender a imbricação estrutural entre capitalismo, racismo e cisheteropatriarcado, consequentemente instrumentalizando a compreensão sobre o processo de vulnerabilização e exposição à morte ao qual as trabalhadoras domésticas negras estão historicamente submetidas, pois representam um dos principais alvos da matriz colonial moderna.
ESTADO NEOLIBERAL E A CONSTITUIÇÃO DE UMA CIDADANIA PRECÁRIA PARA PESSOAS TRANS
Authors: De Oliveira Gregorio Andressa
Published: October 2024

O presente artigo apresenta resultados parciais da dissertação de mestrado intitulada: “O SUS em transição? Os Ambulatórios TT e o direito à saúde para a população trans”, vinculada ao Programa de Pós-Graduação em Serviço Social da Universidade Federal do Rio Grande do Norte. Avaliamos como crucial para uma análise a respeito de políticas públicas para a população trans, as considerações a respeito das formulações sobre o Estado e a articulação com os elementos conjunturais do contexto brasileiro, marcado pela ascensão de uma nova direita, do fortalecimento do neoconservadorismo e dos ataques aos direitos da população trans. Desse modo, o artigo tem como objetivo elaborar uma breve síntese sobre a relação entre Estado neoliberal e suas implicações na realidade da população trans brasileira, no que diz respeito aos direitos e a cidadania.  Para esse estudo realizamos uma revisão de literatura que, ao longo do texto, se apresenta inicialmente a partir da caracterização dos fundamentos do pensamento neoliberal com ênfase no debate sobre o Estado, em seguida abordamos o processo de constituição de uma cidadania precária para a população trans e por fim, analisamos os rebatimentos do neoconservadorismo e ascensão da nova direita na corrosão dos direitos para esse público. Evidenciamos, ao longo do trabalho, que a conformação do Estado neoliberal e o próprio processo de formação social do Brasil relegaram a determinados segmentos da sociedade, dentre eles a população trans, a uma condição de cidadania precária.
IMPROVING SPEAKING THROUGH INSIDE AND OUTSIDE CIRCLE STRATEGY
Authors: Ni Putu Yuliastuti  , Dewa Gede Agung Gana Kumara  , Ni Wayan Krismayani
Published: October 2024

This research used a classroom action research design conducted at SMPN 2 Ubud, Bali. The pre-test results showed that students needed help with fluency, comprehensiveness, and grammar speaking skills. In addition, this research aimed to determine whether seventh-grade students' speaking skills could be improved by implementing the Inside and Outside Circle strategy. The research was carried out in two cycles, with two sessions. Tests and questionnaires served as the research instruments. Fifty-eight were the results of the pre-test, while 69 and 79 were the post-test I and II findings. After that, the data was examined by contrasting the pre-test and post-test results, which led to a notable increase in the individuals' mean scores. Questionnaires were distributed as supplementary data after the previous cycle. The individuals' positive reactions to the strategy's implementation were evident from the questionnaire's results. According to the results of the research instrument, the inside and outside circle strategy can improve students' speaking abilities.
MUSEUM SUBAK: MENJAGA IDENTITAS BUDAYA AGRARIS DI TENGAH GEMPURAN ALIH FUNGSI LAHAN PERTANIAN DI BALI
Authors: Ida Bagus Brata  , Lianda Dewi Sartika
Published: October 2024

Museum sejatinya dapat diposisikan sebagai konstruksi identitas lokal dan nasional. Dalam perannya menjaga warisan sejarah lokal dan nasional, museum subak dapat menjadi lembaga otentifikasi identitas lokal dan nasional di masa silam dan sekaligus memproyeksikannya ke masa depan. Kajian ini bertujuan untuk mengetahui dan mendeskripsikan sejauh mana museum subak dapat dijadikan wahana untuk menjaga identitas budaya agraris di tengah maraknya alih fungsi lahan pertanian di Bali. Data dikumpulkan melalui observasi, wawancara, dan studi dokumen yang selanjutnya diolah secara deskriptif kualitatif. Hasil penelitian menunjukkan: subak sebagai warisan budaya petani Bali yang bernilai luhur penting dilestarikan. Membangun kesadaran masa lalu bukan hanya bertujuan mempertahankan nilai-nilai lama, namun disertai pembinaan untuk mengembangkan terhadap unsur-unsur yang tidak sesuai lagi dengan tuntutan masa kini maupun masa depan agar dapat disesuaikan dengan kebutuhan. Upaya-upaya yang dapat dilakukan untuk memertahankan subak agar tetap eksis dalam mengantisipasi perkembangan global, seperti melalui wadah koordinasi antar subak dalam praktik pertanian di lapangan, terutama untuk menghindari timbulnya konflik karena air, koordinasi berkenaan dengan pola tanam, mendorong subak agar dapat berkembang menjadi suatu lembaga yang berorientasi agribisnis untuk meningkatkan pendapatan petani sangat penting dilakukan. Mengadakan program pendidikan, pelatihan, dan penyuluhan untuk meningkatkan sumber daya manusia anggota subak, khususnya pimpinan-pimpinan subak. Serta yang tidak kalah pentingnya adalah adanya kebijakan yang melibatkan petani untuk dapat mencegah atau setidaknya dapat mengurangi percepatan alih fungsi lahan.
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE JIGSAW UNTUK MENINGKATKAN HASIL BELAJAR PESERTA DIDIK SMP DWIJENDRA DENPASAR
Authors: Welhelmince Umbu Pati  , Desak Nyoman Budiningsih  , I Made Diarta
Published: October 2024

Pembelajaran yang berkualitas dan menyenangkan di sekolah merupakan suatu proses yang sangat penting untuk menciptakan suasana nyaman dalam menjalankan kegiatan pembelajaran bersama peserta didik. Tujuan penelitian ini adalah untuk mengetahui pengaruh dari model pembelajaran Kooperatif tipe Jigsaw terhadap hasil belajar peserta didik di SMP Dwijendra Denpasar. Jenis penelitian adalah kuantitatif dengan metode eksperimen semu (quasi eksperimental). Rancangan penelitian Control Group Pretest and Posttest Design. Penelitian ini dilakukan di SMP Dwijendra Denpasar dan dilaksanakan pada 16 Aptil-3 Mei Tahun ajaran 2023/2024. Sampel di pilih  secara acak (random cluster).  Didapatkan sebagai sampel kelas eksperimen yaitu  peserta didik di kelas VIII D dan peserta didik kelas VIII B sebagai kelas kontrol. Hasil penelitian berdasarkan uji  independent sample test,  didapatkan nilai sangat signifikan sebesar 0,001**(0,001 < 0,01), ini berarti bahwa pembelajaran tipe kooperatif tipe Jigsaw berpengaruh terhadap peningkatan hasil belajar peserta didik, dimana Ho ditolak dan Ha diterima, hal ini membuktikan bahwa model pembelajaran kooperatif tipe Jigsaw mampu meningkatkan hasil belajar peserta didik. Dilihat dari nilai mean atau rata-rata dari pembelajaran kelas kontrol bernilai 62,7705 dan lebih kecil dibandingkan dengan nilai dari kelas eksperimen yaitu sebesar 69,9300. Berdasarkan hasil ini menunjukkan bukti bahwa rata-rata nilai hasil belajar pada kelas eksperimen memiliki peningkatan yang lebih baik  dibanding pada kelas kontrol, sehingga dapat dinyatakan bahwa penerapan model pembelajaran kooperatif tipe Jigsaw dapat meningkatkan hasil belajar peserta didik.
Epidemiology and risk factors for healthcare-associated maternal peripartum infections in Ukraine: results a multicenter study
Authors: Salmanov Aidyn G. , Artyomenko Volodymyr V. , Shchedrov Andrii O. , Prishchepa Andrii P. , Padchenko Anastasia S. , Korniyenko Svitlana M. , Kovalyshyn Orusia A. , Zarichanska Khrystyna V. , Nastradina Nataliia M. , Kokhanov Igor V.
Published: October 2024

Aim: To estimate the frequency of different types of healthcare-associated maternal peripartum infections and their risk factors among women in Ukraine.
Materials and Methods: Multicenter prospective cohort study was conducted in nine regional perinatal centers of Ukraine between January 1, 2021, to December 31, 2023. The criteria for specific healthcare-associated maternal peripartum infections (endometritis, episiotomy infection, and maternal sepsis) site were adapted from the CDC/NHSN case definitions. Surveillance was performed during the hospitalization period and up to 30 days after hospital discharge.
Results: A total of 3600 deliveries by the vaginal route were performed during the study period, 600 (16.7%) maternal peripartum infections were observed. Of all maternal peripartum infection cases, 79.7% were detected after hospital discharge. The most common maternal peripartum infections include endometritis (54.8%), episiotomy infections (34.4%), and maternal sepsis (10.8%). According to the multivariate logistic regression analysis, the body mass index >25, placenta previa, premature rupture of membrane, prolonged rupture of membranes, manual removal of the placenta, multiple vaginal examinations, bacterial vaginosis, aerobic vaginitis, gestational diabetes mellitus, and anemia during pregnancy were independent risk factors for maternal peripartum infections.
Conclusions: Results this study suggest a high prevalence of healthcare-associated maternal peripartum infections in Ukraine. Several factors have been associated with increased risk of maternal peripartum infections, including pre-existing maternal conditions, placenta previa, prolonged rupture of membranes, and spontaneous or provider-initiated conditions during labour and childbirth.
Youth’s internet dependence forming factors as a global public health problem
Authors: Okhrimenko Ivan М. , Okhrimenko Svitlana S. , Marchuk Alla V. , Kudinov Vadym A. , Pakrysh Oleksandr Ye. , Tyurina Valentyna O. , Liakhova Nataliia
Published: October 2024

Aim: The aim is to study the main factors of youth’s Internet dependence formation.
Materials and Methods: We conducted psychodiagnostic examination of students in the National Academy of Internal Affairs. The research involved 154 students: full-time students aged 18-25 (n = 78) and part-time students aged 26-35 (n = 76).
Results: The degree of prevalence of various types of Internet dependence among young people was determined. It was determined that the problem of Internet dependence requires consideration of socio-demographic, socio-psychological, individual, and psychological, as well as organizational factors.
Conclusions: It was found that the number of Internet-dependent people among youth is currently growing rapidly. The most favorable individual-typological properties of a personality for the development of Internet dependence are introversion, anxiety, sensitivity, and aggressiveness. Internet dependence is a type of social dependence. An Internet-dependent individual suffers from the inability to maintain harmonious interpersonal contacts and resolve personal issues that are distorted by the virtual environment. Deviations from normal behavior in society change the peaceful way of life and affect public health.
Music therapy and psychotherapy – complementarity or antagonism in the treatment of patients with mental disorders
Authors: Witusik Andrzej , Mosiołek Anna , Pietras Tadeusz
Published: October 2024

Aim: The aim of the paper was to compare the principles of music therapy and psychotherapy, pointing out numerous similarities and differences between these two techniques.
Materials and Methods: Resistance is observed, as well as the phenomenon of transference and countertransference. In either method, the therapist is a covered therapeutic mirror for the patient/client. Music therapy, unlike psychotherapy, works almost exclusively on emotions and on the symbolic layer of expression of personality. In the case of music therapy, the verbal layer plays a less significant role than in the case of psychotherapy. The clinical effectiveness of music therapy has been studied much less than that of psychotherapeutic methods. In both psychotherapy and music therapy, there is a phenomenon of transference, countertransference and resistance.
Conclusions: Psychotherapy and music therapy are complementary methods in the treatment of mental and behavioral disorders.
Analisis Unsur Antropologis dalam Cerita Rakyat La Raji dan La Dija Sangga
Authors: Nuraeni  , Najamudin  , Rusmin Nurjadin
Published: October 2024

Penelitian ini bertujuan untuk menganalisis unsur antropologi yang terdapat dalam cerita rakyat La Raji dan La Dija Sangga karya Yuni Indriati. Permasalahan dalam penelitian ini dipecahkan dengan menggunakan pendekatan antropologi sastra. Konsep antropologis yang sesuai dengan masalah dalam penelitian ini adalah tujuh unsur kebudayaan yang dikemukakan oleh Koenjaraningrat. Teknik analisis data dilakukan dengan cara memaparkan secara deskriptif melalui komponen reduksi data, penyajian data dan penarikan kesimpulan.Hasil penelitian menunjukkan bahwa data unsur antropologi ada 6 aspek yaitu  (1) Peralatan Kehidupan Manusia ditemukan tiga jenis yakni tempat perlindungan diri, alat untuk mencukupi kebutuhan hidup, dan kebutuhan pangan, (2) Mata Pencaharian ditemukan dua jenis yakni berburu dan bercocok tanam, (3) Sistem Kemasyarakatan ditemukan dua jenis yakni kekerabatan dan organisasi sosial, (4) Sistem Bahasa ditemukan dua jenis yakni bahasa Indonesia dan bahasa Bima, (5) Sistem Pengetahuan ada dua jenis yakni pengobatan dan menjala ikan, (6) Sistem Religi ditemukan tiga jenis yakni kepercayaan pada dewa, nenek sihir dan api jelmaan.
Judi dan Masyarakat Bawah dalam Cerpen “Gorengan di Tepian Perempatan”: Kajian Sosiologi Sastra
Authors: Sugiarto Septian Rifki
Published: October 2024

Judi menjadi salah satu persoalan yang digambarkan dalam karya sastra. Dalam cerpen “Gorengan di Tepian Perempatan” karya Uri Pradanasari judi digambarkan dilakukan oleh seorang kakek tua yang bekerja sebagai pengamen dan merupakan bagian dari golongan masyarakat bawah. Penelitian ini membahas fenomena judi dan kaitannya dengan masyarakat bawah, serta dampak yang ditimbulkan.  Penelitian ini termasuk penelitian kepustakaan dengan menggunakan pendekatan sosiologi sastra. Pengumpulan data dilakukan dengan pencatatan dan teknik analisis datanya menggunakan analisis interpretasi. Hasil penelitian ini menunjukkan bahwa judi digambarkan memiliki kedekatan dengan masyarakat bawah lantaran sebagai pelampiasan atas masalah yang dialami dan sebagai cara untuk mendapatkan uang. Meskipun demikian, dampak negatif yang diakibatkan oleh judi sangat beragam dan luas. Judi menyebabkan krisis finansial sehingga kebutuhan dasar seperti makanan tidak dapat tercukupi.  Selain itu, judi juga berdampak buruk terhadap kesehatan dan dapat merusak hubungan sosial.
Development of Rice Threshing Machine Based Quality Function Deployment Approach – A Case Study
Authors:   Department of Mechanical Engineering, Universitas Riau, Pekanbaru, Indonesia, Susilawati Anita , Roni Guido ,   Department of Mechanical Engineering Alumnus, Universitas Riau, Pekanbaru, Indonesia, Yohanes Yohanes ,   Department of Mechanical Engineering, Universitas Riau, Pekanbaru, Indonesia, Anuar Kaspul ,   Department of Mechanical Engineering, Universitas Riau, Pekanbaru, Indonesia, Fatiya Fatiya ,   Researcher in Mechanical and Construction Engineering, California, US
Published: October 2024

Threshing rice is an important stage in agriculture, especially in rice production. The aim this paper is to develop designs for multi-functional rice threshing machines using the Quality Function Deployment (QFD) approach. The case study was conducted on farmers in a village in Indonesia. Based on observations and survey results conducted with farmers, there was a problem with the rice threshing machine being used less than optimally, so that the time and cost of harvesting became greater. The research was carried out by collecting data by distributing questionnaires directly to 15 respondents. In this research, validity and reliability testing was carried out. The result was in the form of design development, the weight of the rice threshing machine was obtained at 35 kg, which was lighter than previously machine used by farmers. More, the development for new one was resistant to rust and has a fan that functions to separate the rice grains from the grain. Priority of technical characteristics based on weight and dual function of the tool. The dual function of the tool was to thresh and separate the rice with sides and empty ones. Furthermore, the development of rice threshing machine can tailored to the consumers needs.
Combination of Qur'anic Murrotal and Deep Breath Relaxation Against Post Sectio Caesarea (Sc) Pain Changes
Authors: Kustin Kustin , Nurdiana Didin
Published: October 2024

Sectio Caesarea (SC) surgical procedure will have an impact on damage at the tissue level to the nerves that cause postoperative wounds in the incision area which results in pain. Non-pharmacological complementary therapies may be an option that can be done by nurses to manage the pain of SC postoperative patients. The purpose of this study is to determine the effect of the combination of Qur'an Murotal therapy and deep breath relaxation on the pain of post-SC patients at Jember Clinic Hospital in 2023. The design of this study was a pre-experiment with the one group pretest-posttest method. The research sample was 45 respondents with accidental sampling technique. The Visual Analog Scale (VAS) is used to measure pain. Bivariate analysis using parametric paired t-test. Result of this study was the average score of postoperative SC patients before the intervention of a combination of Qur'anic Murotal therapy and breath relaxation was 6.76. The average score of pain levels in SC postoperative patients after a combination intervention of Qur'anic Murotal therapy and breath relaxation was 4.73. The paired t-test results obtained a value of p = 0.000 which means Ha is accepted which means there is an effect of combination therapy of Murotal Qur'an therapy and deep breath relaxation on the pain of post-SC patients at Jember Clinic Hospital.
The Relationship of Oxygen Saturation With Malaise In Diabetes Mellitus Patients in Jember
Authors: Pranata Andi Eka , Jannah Nikmatul , Sukowati Umi
Published: October 2024

Introduction: Diabetes mellitus causes sugar in the blood to not be brought into cells and causeshyperglycemia. Excessive levels of sugar in the blood can disrupt the work of blood cells whichwill release oxygen so that oxygen in the blood becomes reduced which causes hypoxia inperipheral tissues. Glucosuria causes the body to lose calories, causing a decrease in metabolicenergy and malaise. This study aimed to analyze the relationship of oxygen saturation withmalaise in diabetes mellitus patients. Methods: The design used in this research is a cross-sectional approach. The population of DM patients at hospital on average in the last 3 monthswas 160 patients. The sample in this study was 50 respondents. This study used a samplingtechnique of no-probability sampling with the Quota sampling method. Data collection in thisstudy used oximetry and the DSS questionnaire. The data analysis technique used is theSpearman test. Results: This study showed that most of the oxygen saturation experiencedmoderate hypoxemia as many as 20 people and the category of acute malaise was 1 person (2%),subacute malaise was 16 people (32%), and chronic malaise was 33 people (66%). Based on theresults of the Rank Spearman statistical test, it is known that there is a relationship betweenoxygen saturation and malaise in diabetes mellitus patients (p-value 0.000 α < 0.05).Conclusion: There is a relationship between oxygen saturation and malaise in Diabetes Mellituspatients. The health care system can implement the comprehensive strategy to solve problemrelated to diabetes mellitus patient.
Hubungan Inisiasi Menyusui Dini dengan Keberhasilan Pemberian ASI Ekslusif pada Bayi
Authors: Masluroh  , Anita Nur
Published: October 2024

Salah satu indikator untuk menilai derajat kesehatan masyarakat adalah dengan menilai Angka Kematian Bayi (AKB). Menurunkan AKB merupakan salah satu kebijakan pemerintah Indonesia dalam mencapai MDGs (Melinium  Development Goals). Menurut The World Factbook tahun 2014, dari jumlah total 224 negara, Afghanistan merupakan negara yang memiliki AKB tertinggi yakni sebesar 117.23/1,000 kelahiran hidup. Monaco merupakan negara yang memiliki  jumlah AKB terendah yakni sebesar 1.81/1,000 kelahiran hidup, sedangkan Indonesia saat ini menduduki peringkat ke-71 dengan jumlah AKB sebesar 25/1,000 kelahiran hidup (CIA, 2014). Untuk mengetahui hubungan IMD dengan keberhasilan pemberian ASI Eksklusif pada bayi di Mitra Keluarga Bekasi Periode Mei 2018. Metode  penelitian yang digunakan adalah analitik. Populasi dalam penelitian ini adalah seluruh ibu yang mempunyai bayi yang berkunjung di Poliklinik anak Mitra Keluarga Bekasi pada bulan Mei 2017 dengan jumlah sampel sebanyak 80 orang. Dari analisis univariat didapatkan sebagian besar responden tidak memberikan ASI eksklusif 62,5% dan memiliki riwayat IMD 60%.  Analisis bivariat menunjukkan adanya hubungan yang bermakna antara riwayat IMD dengan keberhasilan pemberian ASI eksklusif.
Reseña histórica de la creación de un hospital referencial en el norte del Perú
Authors: Ballón-Manrique Benigno
Published: October 2024

We describe the main events that enabled the construction and equipment of the Lambayeque Regional Hospital, an institution dependent on the Ministry of Health at level III-1, located in the city of Chiclayo in Northern Peru. The creation of this Referral Hospital has allowed for the optimization of health care for the inhabitants of northeastern Peru. The construction process of this hospital should serve as a model to be replicated in our country, where there is a significant gap in hospital infrastructure that needs to be addressed.