bluuebunny/crossref_metadata_2025 huggingface dataset:
Rule-Based Chatbot for Early Self-Depression Indication: A Promising Approach
Authors: Wan Ab.Rahman Wan Nurhayati , Abdul Hamid Nurul Munirah
Published: December 2024

Depression is a prevalent mental health condition worldwide, often characterized by persistent sadness, loss of interest or pleasure, and feelings of worthlessness. Depression is the leading cause of mental health issues worldwide, and it is becoming more severe without self-awareness, early screening, and further medication. Early detection and intervention are critical in mitigating its adverse effects. Leveraging advancements in Artificial Intelligence (AI), particularly in Natural Language Processing (NLP), chatbots have emerged as potential tools for early depression indication. Chatbots are beneficial tools in the mental health domain, such as in assisting mental health risk users. This paper presents the development of a rule-based chatbot aimed at detecting early signs of depression through conversational interactions by screening symptoms of depression. Predefined rules are developed to ensure the assessment can generate reliable results. The rule-based chatbot is developed to assist in depression indication assessment for mental health-risk individuals at an early stage and provide the risky patient with appropriate support and resources. The chatbot assessment has adopted the Depression Anxiety and Stress Scale 21 (DASS21) instrument. Based on the System Usability Scale (SUS) results, the rule-based chatbot has been accepted by all 30 respondents with good acceptance of an average SUS score of 77.2. Thus, the outcome of this chatbot can be utilized as a professional platform to encourage self-disclosure of mental depression indications for users, and it can be beneficial as the initial reference before recommending further action before the earlier help-seeking.
Classification of Defect Photovoltaic Panel Images Using Matrox Imaging Library for Machine Vision Application
Authors: Othman Nur Syahiera , Ramli Suzaimah , Kamarudin Nur Diyana , Mohamad Ahmad Umaer , Ong Ang Teoh
Published: December 2024

The maintenance of large-scale photovoltaic (PV) power plants has long been a challenging task. Currently, monitoring is carried out using electrical performance measurements or image processing, which have limited ability to detect faults, are time-consuming and costly, and cannot pinpoint the defect's precise location quickly. To address these challenges, this research focused on using deep learning techniques to classify defect and non-defect PV panels. The application provided deep learning algorithms capable of image classification in various classifiers. The image dataset was carefully curated and split into training and development datasets during the training model to ensure the highest accuracy for the prediction of the presence or absence of defects on the PV panel. Statistical measures, which are the average accuracy for the training model and average prediction, were employed to evaluate the classification performance of the defect PV panel model. The results demonstrated a remarkable total accuracy of model 99.9% for each class, and prediction results showed that almost 70% of defect PV panels were detected from the testing dataset. Furthermore, a comparative analysis was conducted to benchmark the findings against other algorithms. The practical implications of this research are significant, showcasing the effectiveness of deep learning algorithms and their compatibility with machine vision applications for the classification of defect PV panel images. By leveraging these techniques, solar farm operators can significantly improve maintenance management, thereby enhancing the efficiency and reliability of solar power generation and potentially saving significant costs.
Multimedia-Assisted Elementary School Learning Materials Innovation Using STEAM Learning Approach
Authors: Desyandri - , Agustina Yana , Yeni Indra , Parmadi Bambang
Published: December 2024

Printed materials dominate the teaching materials used in elementary schools in Indonesia. These conditions are backward with the development of the Industrial Revolution 4.0, so it is urgent to research the effectiveness of multimedia-based teaching material using Macromedia Flash Eight application with the learning approach of Science, Technology, Engineering, Art, and Math (STEAM) in Elementary Schools. The research method used is research and development (R&D) with the ADDIE model consisting of Analysis, Design, Development, Implementation, and Evaluation. The data collection instrument uses pre-test and post-test sheets, and an evaluation lift is open to the use of teaching materials for teachers and students. The respondents were eight teachers and 84 elementary school students. The effectiveness of the teaching material is analyzed in two ways: (1) the analysis of learning outcomes (pre-test and post-test) using the N-Gain Test, and (2) the evaluation of the product is based on the results of open-haul analysis, advice, and recommendations. This research and development results show that the pre-test average of 47,14 increased to 84.58 (post-test), while the test score of N-Gain was 71.75%, with the category quite effective. Thus, it can be concluded that Macromedia Flash 8-based teaching materials with STEAM approach to integrated thematic learning in elementary schools are practical and capable of improving student learning outcomes.
Systematic Literature Review: An Early Detection for Schizophrenia Classification Using Machine Learning Algorithms
Authors: Azizi Ainin Sofiya , Kamal Marnisha Mustafa , Azizan Nurzarifah , Zawawi Rohaizaazira Mohd , Zakaria Noor Hidayah , Salamat Mohamad Aizi , Yulherniwati -
Published: December 2024

Schizophrenia is a complex mental health disorder that poses significant challenges in diagnosis and treatment due to its multifaceted symptoms, such as hallucinations, delusions, and cognitive impairments. Early detection is crucial for effective intervention, yet traditional diagnostic methods often fail in precision and scalability. This systematic literature review investigates the application of machine learning (ML) algorithms in the early detection and classification of schizophrenia. By synthesizing findings from 40 primary studies, the review highlights the effectiveness of diverse ML models, including Random Forests, Support Vector Machines (SVM), and advanced deep learning techniques like Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. Key datasets such as clinical records, EEG signals, and neuroimaging data were analyzed to evaluate model performance across metrics like accuracy, precision, and sensitivity. Studies demonstrated that hybrid approaches, integrating multiple data sources and deep learning architectures, achieved classification accuracies exceeding 90%, with notable advancements in early-stage diagnosis. However, the review identifies critical challenges, including data quality issues, biases, and limited external validation, which hinder the widespread clinical application of these models. Through a comparative analysis of ML methods and traditional supervised approaches, the study underscores the transformative potential of ML in enhancing diagnostic accuracy and facilitating personalized treatment plans. Addressing current limitations, such as expanding data diversity and improving model interpretability, is essential for translating these findings into practical healthcare solutions. This research contributes to the growing knowledge in ML-driven diagnostics, advocating for its integration into clinical workflows to optimize schizophrenia management.
The Effects of Imbalanced Datasets on Machine Learning Algorithms in Predicting Student Performance
Authors: Sujon Khaled Mahmud , Hassan Rohayanti , Khairudin Alif Ridzuan , Moi Sim Hiew , Mohd Shafie Muhammad Luqman , Saringat Zainuri , Erianda Aldo
Published: December 2024

Predictive analytics technologies are becoming increasingly popular in higher education institutions. Students' grades are one of the most critical performance indicators educators can use to predict their academic achievement. Academics have developed numerous techniques and machine-learning approaches for predicting student grades over the last several decades. Although much work has been done, a practical model is still lacking, mainly when dealing with imbalanced datasets. This study examines the impact of imbalanced datasets on machine learning models' accuracy and reliability in predicting student performance. This study compares the performance of two popular machine learning algorithms, Logistic Regression and Random Forest, in predicting student grades. Secondly, the study examines the impact of imbalanced datasets on these algorithms' performance metrics and generalization capabilities. Results indicate that the Random Forest (RF) algorithm, with an accuracy of 98%, outperforms Logistic Regression (LR), which achieved 91% accuracy. Furthermore, the performance of both models is significantly impacted by imbalanced datasets. In particular, LR struggles to accurately predict minor classes, while RF also faces difficulties, though to a lesser extent. Addressing class imbalance is crucial, notably affecting model bias and prediction accuracy. This is especially important for higher education institutes aiming to enhance the accuracy of student grade predictions, emphasizing the need for balanced datasets to achieve robust predictive models.
Determinants Generating General Purpose Technologies in Economic Systems: A New Method of Analysis and Economic Implications
Authors: Kargı Bilal , Coccia Mario , Uçkaç Bekir Cihan , Rasyidah -
Published: December 2024

This research proposes using the fishbone diagram, a visualization tool for constructing a comprehensive theoretical framework to analyze the sources of innovation. Traditionally employed to identify causes of specific events, the fishbone diagram is applied innovatively to explore the root causes driving the emergence and evolution of General Purpose Technologies (GPTs). The study identifies critical driving forces such as increased democratization, population growth, demographic shifts, significant investments in research and development (R&D), global leadership aspirations among major powers, competitive socioeconomic environments, and potential threats from adversarial actors. By visually representing these drivers, the fishbone diagram offers insights crucial for technological analysis and foresight, illuminating groundbreaking innovations that drive technological and economic progress. Illustrated through examples from historical GPTs like the steam engine and contemporary technologies such as Information and Communication Technologies (ICTs), this study establishes a foundational framework for developing precise hypotheses about the specific causes and socio-economic impacts of GPTs. The fishbone diagram emerges as a versatile tool adept at systematically analyzing the complex root causes associated with GPTs, facilitating foresight and strategic management of these transformative innovations within society.
Development of A Sensor-Based Tool for Measurement of Sensor-Based Capturing Skills
Authors: Komaini Anton , Kiram Yanuar , Razi Pakhrur , Zakaria Jaffri Bin , Handayani Sri Gusti , Andika Heru
Published: December 2024

This research aims to develop a tool for measuring catching-throwing skills using modern, effective, and efficient sensor technology. This tool is designed to increase accuracy in measuring catch-throwing skills. This type of research uses (R&D). This research involved three experts in their field: an electrical expert, an evaluation and measurement expert, and a physicist. A total of 30 participants participated in testing in a small group of 12 people and a large group of 18 people with an age range of 15-20 years. Testing is carried out with questionnaires and direct tests. The statistical analysis used is r-correlation with the help of the SPSS application. The test results show a high alpha coefficient, confirming that this tool is consistent and reliable in collecting data. Three experts carried out practicality testing: Electrical Experts, Evaluation and Measurement Experts, and Physicists. The results show that this tool is efficient, with practicality levels of 98%, 92%, and 89%, respectively. In addition, an excellent level of effectiveness is demonstrated by expert assessment results, which reach 99%, 89%, and 85%. With this tool, researchers and teachers can evaluate object control skills more efficiently and accurately and assist in collecting more comprehensive data. Overall, this tool for measuring throwing and catching skills provides significant innovation and is expected to support research and education in measuring and developing children's motor skills.
Clustering Analysis of Food Security, Waste and Loss: Malaysia Agricultural Insights
Authors: Chen Sheng Hii Enoch , Lim Siew Mooi , Loo Seng Xian , Yeap Sheng Kit , Tan Ching Yee
Published: December 2024

As the world population grows rapidly nowadays, the demand for food has come to rise. The escalating demand for food has caused substantial wastage and loss, which not only hampers food security efforts but also aggravates greenhouse gas (GHG) emissions, intensifying the environmental crisis. Among numerous countries, Malaysia, with its diverse agricultural profile, emerges as a good fit for our case study. This study chooses the clustering technique to examine food sector data in Malaysia and investigate the link between the clustering results on food data and the data on GHG emissions. This case study aims to find crops depending on their production efficiency, underline those that match major waste, and estimate their contribution to greenhouse gas emissions. Three clustering techniques, Gaussian Mixture Modelling (GMM), Birch, and Density Peak clustering, are applied in the Production and Supply Utilisation Accounts (SUA) datasets, help to identify and cluster crops based on their similar traits to acquire uncovered patterns between the food sector and environmental issues. Using cutting-edge clustering algorithms and visualization tools, this study investigated in-depth the complex interactions among food production, waste, and greenhouse gas emissions in Malaysia. By addressing food production efficiency and waste reduction, the outcome will be a cascade of benefits that not only improve food security but also help to lessen negative environmental effects. This study illuminates the multifaceted dynamics of food production, waste, and environmental impact, offering valuable insights and pathways toward a more sustainable future for Malaysia and potentially other nations.
Comparative Analysis of Machine Learning Algorithms for Cross-Site Scripting (XSS) Attack Detection
Authors: Hamzah Khairatun Hisan , Osman Mohd Zamri , Anthony Tumusiime , Ismail Mohd Arfian , Abdullah Zubaile , Alanda Alde
Published: December 2024

Cross-Site Scripting (XSS) attacks pose a significant cybersecurity threat by exploiting vulnerabilities in web applications to inject malicious scripts, enabling unauthorized access and execution of malicious code. Traditional XSS detection systems often struggle to identify increasingly complex XSS payloads. To address this issue, this research evaluated the efficacy of Machine Learning algorithms in detecting XSS threats within online web applications. The study conducts a comprehensive comparative analysis of XSS attack detection using four prominent Machine Learning algorithms, which consist of Extreme Gradient Boosting (XGBoost), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). This research utilizes a comparative methodology to assess the selected Machine Learning algorithms by analyzing their performance metrics, including confusion matrix, 10-fold cross-validation, and assessment of training time to thoroughly evaluate the models. By exploring dataset characteristics and evaluating the performance metrics of each selected algorithm, the study determined the most robust Machine Learning solution for XSS detection. Results indicate that Random Forest is the top performer, achieving 99.93% accuracy and balanced metrics across all criteria evaluated. These findings will significantly enhance web application security by providing reliable defenses against evolving XSS threats.
Vulnerability Liquefaction Mapping in Padang City Based on Cloud Computing Using Optical Satellite Imagery Data
Authors: Razi Pakhrur , Putri Amalia , Sri Sumantyo Josaphat Tetuko , Akmam -
Published: December 2024

Liquefaction is a significant geological hazard in earthquake-prone locations like Padang City, Indonesia. The phenomenon happens when saturated soil loses strength owing to seismic shaking, resulting in substantial infrastructure damage. Accurate identification of sensitive locations is critical to catastrophe mitigation. This study aims to map water distribution using optical satellite data and estimate its importance as a crucial element in determining liquefaction vulnerability. The Normalized Difference Water Index (NDWI) was used to assess water and vegetation indexes, taking advantage of its sensitivity to water content in varied land surfaces. We recommended using the NIR (near-infrared) and SWIR (short wave infrared) bands with 832.8 nm and 2202.4 nm, respectively, which are sensitive to soil water content. High-resolution satellite data were used to create NDWI maps, highlighting locations with high water saturation. These findings were combined with geological and seismic data to identify liquefaction-prone zones. The study found that locations with high water content, as measured by NDWI, are highly associated with greater liquefaction susceptibility. The findings highlight the importance of water distribution in determining soil behavior during seismic occurrences. This study highlights the value of NDWI as a low-cost and efficient tool for measuring liquefaction vulnerability at the regional level. The technique offers insights into Padang City's urban planning, catastrophe risk reduction, and community preparedness. By identifying high-risk zones, the study aids in making informed decisions to reduce the impact of future earthquakes. Most of the water content change occurred along the coastal line and in the low-lying areas of Koto Tanggah and North Padang sub-districts. The model can be used in other places with similar geological challenges, providing a scalable solution for liquefaction risk assessment.
Exploring Key Factors Influencing Blockchain Adoption in E-Government: Pilot Study
Authors: Falih Raed , Abdullah Salfarina , Y Jusoh Yusmadi , Abdullah Rusli , C PA Noraini , Kadhim Dheyaa J , Altawaiha Iyad
Published: December 2024

E-government systems face numerous challenges, including trust, privacy, transparency, security, traceability, and service delays. Blockchain technology holds promise for revolutionizing these systems by addressing their long-standing vulnerabilities. Despite the acknowledged potential of blockchain in enhancing e-government systems via improved security and transparency, empirical research on the factors influencing its adoption within government remains scarce. This pilot study addresses this gap by constructing and validating a theoretical model and a corresponding questionnaire. The development of the model and questionnaire followed a four-step methodology. Initially, potential influencing factors were identified and collected. These factors were then filtered and categorized into four main groups: Technological Specific Factors (TSFs), Organizational Specific Factors (OSFs), Individual Specific Factors (ISFs), and Environmental Specific Factors (ESFs). The Analytic Hierarchy Process (AHP) was applied to rank these factors based on their relative importance. The fifteen top-ranked factors were then used to construct the model and develop the questionnaire. Finally, Structural Equation Modelling (SEM) was utilized to assess the reliability and validity of the constructs. The SEM results confirmed the reliability and validity of all model constructs, including the items. Based on these findings, a validated questionnaire has been formulated for future research. This questionnaire is designed to gather data to test hypotheses and identify statistically significant factors that influence the adoption of blockchain technology in e-government.
Efficacy Study of Selected Maize (Zea mays L.) Genotypes Against the Asian Corn Borer, Ostrinia furnacalis (Guenée)
Authors:   College of Agriculture, Sultan Kudarat State University, Lutayan, Sultan Kudarat, Philippines, Marfori Yoryncita ,   Institute of Crop Science, University of the Philippines Los Baños, College 4031, Laguna, Philippines, Caasi-Lit Merdelyn ,   Institute of Plant Breeding, University of the Philippines Los Baños, College 4031, Laguna, Philippines, Laude Tonette ,   Institute of Crop Science, University of the Philippines Los Baños, College 4031, Laguna, Philippines
Published: December 2024

Laboratory and screen house studies were conducted to assess the efficacy of selected twenty-six maize varieties against Asian corn borer (ACB), Ostrinia furnacalis (Guenée). Hierarchical tree based on resistance parameters clearly revealed that the twenty-six maize varieties are best classified into three groups, viz. resistant, intermediate, and susceptible. In laboratory test, the varieties RCS2, RCS4, RCS5, 'IPB Var13', Bt2, Bt3, and Bt4 were consistently identified as highly resistant. Further examinations in stalk feeding assay showed that the resistant varieties had sharp decline in larval survival (LS) on the 2nd to the 5th day of larval feeding in stalk tissue. On the other hand, the susceptible varieties showed high LS across the 5-day feeding duration. This research highlighted that resistant maize varieties were mainly attacked below the ear nodes and internodes, with the most frequent observation on the 8th node below the ear node but had zero attack on the crucial ear node. Meanwhile, both the intermediate and the susceptible varieties were attacked on the ear node, with the feeding attacks distributed throughout the whole plant. This research provided further evidence that ACB resistance is available in Philippine native maize varieties. These experiments corroborate with previous results that transgenic maize expressing the Cry1Ab protein is lethal to ACB larvae. High resistance observed from the non-Bt 'IPB Var13' suggests that natural resistance is present. This research have presented that Bt varieties (Bt2, Bt3, Bt4) together with RCS2, RCS4 and 'IPB Var13' were the consistently resistant varieties in both laboratory and screen house assays. The plant resistance indices used in this study can effectively screen different varieties of maize in the Philippines. Further experimentations would be needed to determine the mechanism involved in the resistance and susceptibility of maize varieties infested with ACB.
Epinasty Accompanies Potassium Nitrate-Induced Flower Bud Break in 'Carabao' Mango [RESEARCH NOTE]
Authors:   Assistant Professor, College of Agriculture and Related Sciences, University of Southeastern Philippines, Tagum City, Philippines, Besas Ulysses , Protacio Calixto ,   Professor, Institute of Crop Science, College of Agriculture and Food Science, University of the Philippines Los Baños, Laguna, Philippines
Published: December 2024

The hypothesis that potassium nitrate application promotes epinasty in ‘Carabao’ mango through increased ethylene production was investigated. The degree of drooping, apical primordium growth as affected by shoot ethylene and levels after potassium nitrate spraying were monitored. Evidence presented established for the first time in ‘Carabao’ mango that epinasty occurred just before flower emergence, coinciding with visible bud break, and extended up to 18 days, marking floral anthesis. The possible reasons could be the higher levels of ethylene at 0.31% and earlier increase of ethylene in the shoot apex at 4 hours and apical primordium growth. Increased ethylene levels at 0.21% were observed 2 hours from spraying of potassium nitrate, peaking between 4 to 5 hours both in the leaves and shoot apex and eventually declined at 0.11% thereafter while apical primordium growth started three days from potassium nitrate spray which the emerging buds pushes the side of the apex causing partial bending of apical leaves.
An Analysis Of English 9th Grade Turkish Efl Coursebook For High School According To Critical Thinking And Problem Solving In 21st Century Principles
Authors: Küçük Gülhan
Published: December 2024

This study looks at how critical thinking and problem-solving abilities can be developed using Uplift Coursebook, a Ministry of National Education English Course textbook intended for English language instruction (ELT) at the ninth grade level. The study is to look into how course materials assist these abilities in a setting where problem-solving and critical thinking are becoming more and more crucial in reading skills. The document analysis method, which is a qualitative research method, was used in the process of finding and analyzing the values in the book.A checklist for reading skills that was based on the Facione Model was used to conduct the analysis. Critical thinking and problem-solving abilities were assessed in relation to the coursebook's objectives, exercises, and provided materials. The coursebook's capacity to promote student participation and its student-centered approach were also taken into consideration.Results indicate that the coursebook has a great deal of promise for fostering critical thinking and problem-solving abilities. It is said, meanwhile, that certain areas still need work and that putting the suggested tactics into practice can assist support these skills more successfully.As a conclusion, this study offers a foundation for comprehending the function of Grade 9 ELT coursebooks in fostering critical thinking and problem-solving abilities as well as pinpointing areas in which these abilities may be strengthened.
Veredicto, instrucciones y sentencia: algunos aspectos relevantes
Authors: Ramírez Ortiz José Luis
Published: December 2024

En el presente trabajo se abordan algunos de los problemas prácticos que plantea la secuencia "instrucciones-veredicto-sentencia" en el procedimiento ante el Tribunal del Jurado, y se pone de relieve cómo esas tres instancias constituyen una unidad, un todo que puede integrarse de modo armónico si se parte de una comprensión del jurado como una institución al servicio de la garantía de la presunción de inocencia. Además, se aporta, como anexo, instrucciones de deliberación y votación para los jurados.
Design of Energy-Efficient CMOS Circuits for AI Applications
Authors: Karaosmanoğlu Mehmet Fuat
Published: December 2024

The design of energy-efficient CMOS circuits has become a critical area of research, driven by the escalating demand for artificial intelligence (AI) applications that require immense computational power. This study investigates advanced techniques for optimizing CMOS (Complementary Metal-Oxide-Semiconductor) circuit architectures to enhance energy efficiency without compromising performance. Key areas of focus include reducing dynamic and static power consumption through innovative transistor-level designs, clock-gating strategies, and the integration of advanced materials. Additionally, the research explores the potential of hybrid architectures combining CMOS with emerging technologies like memristors and neuromorphic circuits. By addressing power constraints in AI hardware, the study aims to contribute to the development of scalable, sustainable computing systems for machine learning, neural networks, and edge AI devices. The findings have broad implications for the future of AI hardware, offering solutions that balance computational demands with energy sustainability.
Памяти заслуженного профессора Московской духовной академии Бориса Александровича Нелюбова (15.11.1930 — 12.07.2024)
Authors: И.Э. Кечкин
Published: December 2024

Статья посвящена памяти ревностного труженика церковной науки и заслуженного профессора Московских духовных школ, доктора богословия Бориса Александровича Нелюбова, скончавшегося в 2024 г. в день памяти св. первоверховных апостолов Петра и Павла. Почти вся жизнь профессора была связана с Академией у Троицы. Его многочисленные труды, посвященные исследованию традиции дохалкидонских церквей, еще будут глубоко изучены. Цель настоящей статьи заключается в попытке описать основные этапы жизни и научной деятельности Б. А. Нелюбова в Московской академии. Главными источниками для статьи послужили архивные материалы. В приложении приводится избранная библиография трудов профессора Нелюбова.

The article is dedicated to the memory of Boris Alexandrovich Nelyubov, an enthusiastic worker of church science and honored professor of Moscow theological schools, doctor of theology, who passed away in 2024 on the day of the holy apostles Peter and Paul. Nearly his entire life was connected with the Trinity Academy, and his works on the study of the traditions of pre-chalcedonian churches will continue to be deeply studied. The purpose of this article is to attempt to describe the main stages of the life and scientific activities of B.A. Nelyubov at the Moscow academy. The main sources for this article were archival materials, and the appendix includes a selected list of works by Professor Nelyubov.
Penerapan Terapi Relaksasi Otot Progresif Terhadap Kecemasan Pasien Pre Operasi Sectio Caesarea Di RS Bhayangkara Polda Lampung Tahun 2024
Authors: Herlina Leni , Wijayanto Wisnu Probo , Amirudin Ikhwan
Published: December 2024

Pendahuluan: Kecemasan muncul pada pasien pre operasi caesar karena takut akan rasa sakit, perubahan fisik, dan ketakutan akan kematian pasca operasi. Dalam situasi ini, perawat berperan penting dalam perawatan pasien yang terdiagnosis gangguan kecemasan untuk  mengurangi atau mengatasi keluhan tersebut. Salah satu teknik untuk mengurangi kecemasan adalah terapi  relaksasi otot progresif.
Tujuan: mengukur tingkat kecemasan sebelum dan sesudah  intervensi serta efektivitas  intervensi menggunakan teknik relaksasi otot progresif. Tes tersebut dilakukan di RS Bhayangkara Polda Lampung.
Metode: Kegiatan ini menggunakan metode deskriptif dengan pendekatan studi kasus. Data disajikan dalam format naratif, dengan pernyataan verbal dari subjek studi kasus sebagai data pendukung.
Hasil:  Hasil Studi menemukan bahwa setelah dua hari pelatihan relaksasi otot progresif yang berlangsung selama 5 hingga 20 menit  sekali  sehari, pasien mengatakan kecemasan mereka telah menurun ke kisaran tidak cemas. Dapat disimpulkan bahwa penggunaan terapi relaksasi otot progresif mungkin efektif dalam menurunkan kecemasan pada pasien menjelang operasi caesar.
Simpulan: Para peneliti menyarankan agar rumah sakit  memberikan informasi dan mengajari pasien cara mengatasi ketakutan mereka terhadap operasi dengan memanfaatkan terapi relaksasi otot progresif sebagai alternatif dalam mengurangi ketakutan mereka terhadap operasi caesar.
SUV FONDI YERLARI MONITORINGINI YURITISHNING AHAMIYATI VA VAZIFALARI
Authors: Jo‘rayev Akbar
Published: December 2024

В данной статье описаны значение и задачи мониторинга на землях водного фонда, направления мониторинга и методы мониторинга
Quantifying and Mitigating Greenhouse Gas Emissions in Egg-Laying Hen Farming: A Path Towards Carbon Neutrality
Authors: Ubolsook Putthadee , Khamfong Krissana , Boonmak Aphirak , Podong Chattanong , Jansanthea Pongthep , Kongnun Weerapon , Aimyuak Yasintinee
Published: December 2024

This study presents a comprehensive framework for assessing and mitigating greenhouse gas (GHG) emissions in commercial egg-laying hen farming in Uttaradit Province, with the aim of achieving carbon neutrality within the poultry sector. Employing a detailed life cycle assessment (LCA) over a 450-day production period, this research identifies key sources of emissions, with feed consumption identified as the largest contributor, followed by water use and energy demands. To address these emissions, the study explores several innovative strategies: transitioning to solar photovoltaic systems for lighting and water pumping, shifting from diesel to biodiesel for fuel, and optimizing feed compositions. Additionally, advanced manure management practices are proposed to reduce methane and nitrous oxide emissions. Collectively, these interventions could significantly diminish the emissions associated with hen farming operations, thereby advancing environmental sustainability. This work not only provides actionable insights for poultry farms seeking to lower their emissions but also offers a scalable and adaptable model with broader implications for sustainable practices across the agricultural sector. The findings underscore the importance of renewable energy integration, feed optimization, and efficient waste management in mitigating the environmental impact of agriculture, thereby informing both policy and practice in the pursuit of carbon-neutral food production.
Assessing the effectiveness of curriculum implementation across global educational systems
Authors: Alvarado Joevie , Galigao Regina
Published: December 2024

This study investigates the effectiveness of curriculum implementation across selected countries in Asia, Europe, North America, and South America, focusing on how educational frameworks are applied in classrooms to enhance learning outcomes. Using a qualitative comparative research design and a systematic literature review, this research identifies patterns and challenges in curriculum implementation worldwide, emphasizing content knowledge, pedagogical skills, and teaching methods. Findings reveal that successful implementation requires coherence between policy and practice, as well as access to resources and continuous professional development. In developing regions, challenges such as inadequate infrastructure and teacher training hinder effective curriculum delivery, whereas in developed countries, evolving standards and technological integration create additional pressures. The study highlights distinct approaches across continents: Asia’s focus on STEM and innovation, Europe’s balanced emphasis on foundational and advanced skills, North America’s critical thinking and social development frameworks, and South America’s commitment to inclusivity and practical education. These insights underscore the importance of context-specific strategies and a global recognition of critical thinking, problem-solving, and collaborative learning as core competencies. This comparative analysis provides valuable recommendations for educators and policymakers to address disparities, enhance implementation quality, and foster equitable access to quality education globally.
Sistemas de acueducto
Authors: Lizcano Caro José A. , Medina Daza Rubén Javier , González Pérez Mario Guadalupe
Published: December 2024

Existe convergencia generalizada en torno a que factores como la suficiencia financiera y el uso racional del presupuesto público se relacionan fuertemente con la proyección de la demanda futura del servicio de acueducto que prestan las empresas proveedoras. Los costos de producción y las tasas de descuento pueden originar escenarios complejos que podrían comprometer la disponibilidad hídrica para la población.La regulación universal para el sector de los servicios públicos domiciliarios se determina a través de las variables macro de costos presentes e inversiones futuras, determinadas por las proyecciones de la demanda en horizontes de largo plazo. Ello es fundamental en el subsector del agua potable o agua entubada (Centro de Naciones Unidas para los Asentamientos Humanos, 1996, p. 543). Las predicciones de consumo que se vayan a suministrar, partiendo de consumos históricos y coberturas nominales y reales, son función determinante no controlable para tasar la tarifa en distintos tiempos comparables a valores presentes. Como ejemplo, en Bogotá el horizonte de la demanda se ha proyectado a cerca de 45 años (Lizcano, 2011, p. 60). La eficiencia y la suficiencia financiera y presupuestal de la prestación del servicio de acueducto depende en gran medida de la precisión de las mediciones (micro y macro) y proyecciones llevadas a cabo para determinados entornos de mercado. La suficiencia financiera se centra en proyecciones de costos y tasas de descuento que remuneren las inversiones a corto, mediano y largo plazo. Tales inversiones se perfilan para expansión, reposición y rehabilitación (Comisión de Regulación de Agua Potable y Saneamiento Básico [CRA], 2004). Para responder a estas exigencias y analizar y corregir las distorsiones socioeconómicas regionales se plantea la creación de un modelo para regular el sector de agua potable en escenarios de equilibrio inestable que considere criterios de solidaridad y priorice inversiones ecoambientales. Con este fin se plantearon dos posibles herramientas de pronóstico para el periodo 2006-2040 teniendo a Bogotá como modelo: la primera, redes neurales, y la segunda, series de tiempo (Lizcano, 2018, p. 170). De estas herramientas solo la segunda arrojó resultados validables, encontrando, entre otras cosas, que los estratos 1 y 2 muestran incrementos en la demanda, mientras que los estratos 3, 4, 5, 6 y el sector comercial tienden a decrecer en su consumo.
The Use of the Detective Genre in 19th-Century English Prose
Authors: Sadiqzade Zarifa
Published: December 2024

The detective genre in 19th-century English literature emerged as a response to the social, cultural, and legal transformations of the Victorian era. Rooted in urbanization, the rise of crime, and advancements in legal systems, the genre offered both entertainment and moral reflection for its readers. Key figures such as Charles Dickens, Wilkie Collins, and Arthur Conan Doyle played pivotal roles in shaping the genre, introducing enduring archetypes and innovative narrative structures. Detective fiction not only captivated audiences with its intricate plots and logical deductions but also reinforced societal values by exploring themes of justice and morality. This study examines the genre's foundational characteristics, its influence on Victorian readers, and its enduring legacy in modern literature and culture.
Implikasi dan Strategi Teori Elastisitas Permintaan dalam Ekonomi Manajerial
Authors: Ayi Nurpadilah Ayi Nurpadilah , Hasan Dina Nurmala , Fauziah Hesti , Octaviani Lidiyana Tasya , amelia Fannisya , Suriyanti
Published: December 2024

Artikel ini akan membahas faktor-faktor yang mempengaruhi elastisitas permintaan, metode pengukurannya, serta implikasi dan strategi yang dapat diterapkan oleh perusahaan berdasarkan konsep ini. Faktor utama yang memengaruhi elastisitas permintaan di antaranya adalah ketersediaan barang substitusi, proporsi pendapatan yang dihabiskan untuk barang tersebut, serta jangka waktu yang diberikan untuk merespons perubahan harga. Semakin banyak alternatif yang tersedia bagi konsumen, semakin elastis permintaan suatu barang. Pemahaman mendalam tentang elastisitas permintaan memungkinkan perusahaan membuat keputusan harga lebih cerdas. Dengan mempertimbangkan faktor-faktor yang mempengaruhi elastisitas dan menganalisis kondisi pasar, perusahaan dapat memaksimalkan pendapatan dan pangsa pasar. Analisis elastisitas ini membantu mengidentifikasi segmen pasar yang responsif terhadap perubahan harga untuk mengembangkan strategi pemasaran efektif. Selain harga, kualitas produk, citra merek, dan layanan pelanggan juga mempengaruhi permintaan. Mengintegrasikan faktor ini dalam keputusan harga membantu perusahaan tetap kompetitif dan adaptif
Dampak Pemberitaan Fajar Cirebon Dalam Pendidikan Politik Tinjauan Undang-Undang Nomor 40 Tahun 1999 Tentang Pers
Authors: Hafizd Jefik , Abdul Hakim Fadlih , Rana Mohamad
Published: December 2024

Menghadapi pemilihan umum 2024 perlu adanya suatu edukasi politik untuk memberikan pencerahan kepada masyarakat guna memberikan pilihan yang rasional terhadap para calon yang bertanding di pemilu 2024 sehingga melahirkan sosok pemimpin yang kompeten. Salah satu yang terlibat dalam memberikan sosialisasi politik melalui andil dari media massa. Namun pada realita yang terjadi di masyarakat masih saja termakan berita hoaks dan juga terjerumus praktik pemilu yang kotor. Penelitian ini bertujuan untuk mengkaji dampak dari pemberitaan Surat Kabar Fajar Cirebon dalam pendidikan politik pada Pemilu 2024 di Kota Cirebon serta mengkaji dampak dari Undang-Undang Nomor 40 Tahun 1999 tentang Pers terhadap pemberitaan media massa dalam menyediakan informasi pendidikan politik. Penelitian ini menggunakan metode yuridis empiris melalui pendekatan penelitian studi kasus. Data yang dihimpun melalui cara wawancara, observasi, dokumentasi kemudian dianalisis melalui metode analisis deskriptif. Dapat diketahui hasil kajian ini bahwa dampak pemberitaan Fajar Cirebon dalam pendidikan politik pada pemilu 2024 di Kota Cirebon yakni, dapat berdampak sebagai pembentuk opini publik dengan menyediakan wadah bagi calon yudikatif atau calon legislatif untuk menuangkan gagasannya melalui berbagai platform yang tersedia di Fajar Cirebon. Selain itu, media massa berdampak sebagai penyeimbang dan pengawas pemilu. Kemudian terkait dampak UU Pers terhadap pemberitaan media massa dalam menyediakan informasi pendidikan politik dapat memberi manfaat yang dirasakan masyarakat seperti akses informasi politik yang mudah dan tingkat akurasi kebenarannya terjamin, media massa bisa hadir untuk memberi rujukan terhadap isu yang bertebaran. Serta terkait memproduksi informasi media massa akan lebih leluasa karena kebebasannya dijamin oleh negara.
Pergeseran Wewenang Perum Perhutani KPH Malang Dalam Pengelolaan Cagar Budaya (Studi Kasus: Candi Sumberawan, Singosari)
Authors: Santoso Rizki Andi , Siatiman Reinhard Valent , Amirulazka Naufal Itsnain , Mustaqim Muhammad Azhar Shiroth
Published: December 2024

Candi Sumberawan adalah salah satu cagar budaya di Kabupaten Malang. Terletak di tengah hutan pinus, candi ini dikelola oleh Perum Perhutani KPH Malang. Sebagai cagar budaya, sudah semestinya candi ini dikelola oleh Dinas Pariwisata dan Kebudayaan Kabupaten Malang. Namun, status quo menunjukkan sebaliknya, terdapat tumpang tindih kewenangan antara Perum Perhutani KPH Malang dan Disparbud Kabupaten Malang. Regulasi pengelolaan cagar budaya di Kabupaten Malang telah diatur dalam Peraturan Bupati Nomor 49 Tahun 2016 tentang Kedudukan, Susunan, Organisasi, Tugas dan Fungsi, Serta Tata Kerja Dinas Pariwisata dan Kebudayaan Kabupaten Malang. Dalam Perbup tersebut, diatur kewenangan Disparbud Kabupaten Malang untuk menjalankan fungsi pengelolaan cagar budaya. Tujuan penelitian ini adalah mengetahui kewenangan Perum Perhutani KPH Malang, Disparbud Kabupaten Malang, dan mengetahui perbandingan kewenangan kedua lembaga tersebut dalam mengelola cagar budaya, serta menganalisis pergeseran fungsi Perum Perhutani KPH Malang melalui regulasi a quo. Metode penelitian yang digunakan adalah yuridis normatif dengan bahan analisis berupa bahan hukum primer, sekunder, dan bahan hukum tersier. Bahan hukum primer yang digunakan adalah regulasi yang mengatur tentang kewenangan pengelolaan cagar budaya. Kemudian, bahan hukum sekunder yang digunakan adalah buku, jurnal, artikel, hasil penelitian sebelumnya, dan pendapat ahli. Hasil penelitian menunjukkan bahwa terdapat pergeseran fungsi dan kewenangan dalam pengelolaan Candi Sumberawan. Pergeseran tersebut ditunjukkan dengan dikelolanya Candi Sumberawan oleh Perum Perhutani KPH Malang, padahal secara yuridis sebagai cagar budaya seharusnya Candi tersebut dikelola Disparbud Kabupaten Malang. Oleh sebab itu, diperlukan adanya harmonisasi peraturan terkait kewenangan dalam pengelolaan Candi Sumberawan antara Perum Perhutani KPH Malang dengan Dinas Pariwisata dan Kebudayaan Kabupaten Malang.
ANÁLISE DAS PRÁTICAS DE DESCARTE DE MATERIAIS BIOLÓGICOS EM LABORATÓRIOS
Authors: Silva Jheniffer Danielle Carvalho , Maia Janini Tatiani Lima Souza , Scremin Marlete , Oliveira Valdira Vieira de , Oliveira Elizete Pereira , Abrahão Neto Alexi , Gomes Rafael Fernandes , Alves Maysa Souza Ferreira , Pereira Laura Katherine Lopes , Pimenta Joice Fernanda Costa Quadros , Dias Leydiane Martins Souza , Antunes Junior Geraldo Batista , Fonseca Jonathan Ribeiro , Santana Flavia Ferreira , Monteiro Marivone de Oliveira , Nere Juliane Costa
Published: December 2024

Introduction: The correct disposal of biological materials is important for the health of the whole population, thus avoiding soil contamination and preventing accidents with sharp-perforated materials. The Agência Nacional de Vigilância Sanitária – (ANVISA) has established rules for an appropriate disposal of the biological waste  such as incineration, grounding and radiation.  These rules are applied to laboratories, hospitals, clinics, doctors' offices and other health facilities. Objective: To analyze the disposal of biological waste by the laboratories of the city of Montes Claros, Minas Gerais. Methodology: A field study that presents a quantitative, descriptive and cross-sectional analysis with a population of four clinical analysis laboratories and a company responsible for the final waste disposal. Questionnaires were applied for a better analysis of the data.  Results: The results indicate that the laboratories participating in the research are aware of ANVISA standards and they are concerned about their collaborators and the population, making sure that they are not putting them at risk. Conclusion: The training of professionals is necessary to avoid accidents with perforating materials.
MARKETING E COMUNICAÇÃO INCLUSIVA: O PODER DA LÍNGUA DE SINAIS NA TRANSFORMAÇÃO DE MERCADOS E SOCIEDADES
Authors: Coelho  Ayna Rodrigues
Published: December 2024

Imagine um mundo onde a comunicação é uma barreira para milhões de pessoas. Um mundo onde a surdez impede a participação plena em todos os âmbitos da vida. Essa realidade, infelizmente, ainda persiste, marginalizando indivíduos surdos e limitando suas oportunidades. Mas existe uma ferramenta poderosa que pode transformar essa realidade: a Língua de Sinais. 

A Língua de Sinais, um sistema de comunicação visual complexo e rico, representa muito mais do que um simples meio de comunicação. É a identidade cultural, a expressão individual e o idioma de uma comunidade que por muito tempo foi silenciada pela falta de acessibilidade. Reconhecer a Língua de Sinais como um direito fundamental significa abrir portas para a participação dos indivíduos surdos em todos os aspectos da vida. 

De acordo com relatos da comunidade surda, “o reconhecimento da Libras é de extrema importância, mas ainda há uma falta de metodologia adaptada para surdos, como a necessidade de recursos tecnológicos visuais, como a lousa digital, para facilitar o aprendizado.” 

Esse depoimento ilustra a necessidade urgente de ações concretas para melhorar a inclusão. O artigo aborda os benefícios da implementação da Língua de Sinais, tanto no contexto social quanto no profissional. Investigaremos como a inclusão dessa ferramenta impacta positivamente a comunicação, o acesso à informação e o mercado de trabalho, além dos desafios enfrentados pelas empresas e instituições em relação à acessibilidade para pessoas surdas. 

O artigo aborda os benefícios da implementação da língua de sinais, tanto no contexto social quanto no profissional. Investigaremos como a inclusão dessa ferramenta impacta positivamente a comunicação, o acesso à informação e o mercado de trabalho e os desafios enfrentados pelas empresas e instituições em relação à acessibilidade para pessoas surdas, analisando as barreiras existentes e as estratégias para superá-las. Com base em dados estatísticos, estudos de caso e pesquisas relevantes, este artigo visa contribuir para a construção de uma sociedade mais justa e inclusiva, onde a língua de sinais seja reconhecida como um direito fundamental, abrindo portas para a participação de indivíduos surdos e promovendo um ambiente social e profissional mais rico e diverso.