bluuebunny/crossref_metadata_2025 huggingface dataset:
CLASSIFYING THE SUPERVISED MACHINE LEARNING AND COMPARING THE PERFORMANCES OF THE ALGORITHMS
Authors:   Research Scholar, Department of Computer Science and Engineering, Jashore University of Science and Technology., Nath Mohalder Rathindra , Alam Hossain Md. ,   Professor, Department of Computer Science and Engineering, Jashore University of Science and Technology., Hossain Nazmul ,   Assistant Professor, Department of Computer Science and Engineering, Jashore University of Science and Technology.
Published: February 2024

Supervised Learning (SL), also recognized as SML, means Supervised Machine Learning. Its a subclass of AI (Artificial Intelligence) and Machine Learning (ML). Its defined by the conduct of entitled datasets for training algorithms that predict outcomes precisely or classify data. The input dataset is faded into the supervised Machine Learning model, which synthesizes its weights until the model has been fitted properly, which happens as a segment of the cross-validation process. Supervised learning machine assists organizations in solving different kinds of real-world problems. SML is searching for algorithms that externally outfitted the instances to produce common hypotheses, preparing predictions for future cases.The supervised Machine Learning (SML) classifications are frequently completed tasks by effective intelligent systems. This paper discusses different categories of Supervised Machine Learning classification technology, compares different categories of supervised learning algorithms and identifies the best effective classification algorithm based on some instances, data set and variables or features. This paper discusses eight different types of SML algorithms. Those were envisaging: Artificial Neural Network (ANN), Bayesian Networks, K-nearest Neighbor (KNN), Random Forest, Decision Tree (DT), Linear Regression, Support Vector Machine (SVM), and Logistic Regression.These eight algorithms develop in the python language. Using a sample dataset for every algorithm and justify the algorithm performance. Here, justify the algorithms based on three different outcomes: throughput, response time, and accuracy. The supervised learning method depends on pre-defined parameters. The performance metric has an important role in identifying the ability and capacity of any kind of machine learning algorithm. The outcomes show that Decision Tree is the best prediction performance in this paper and gives the best accuracy, response time and throughput. The next accurate algorithms in SML algorithms are Logistic Regression and SVM after the DT algorithm.
MODEL AGREEMENT FOR AGRICULTURAL LAND PRODUCT SHARING BASED ON CUSTOMARY LAW AND LAW NO. 2 OF 1960 CONCERNING PROFIT SHARING AGREEMENTS(CASE STUDY OF PROFIT SHARING ON MARO AGRICULTURAL LAND IN WEST LAMPUNG REGENCY)
Authors: Ayuhandika Ninik , a Hamzah , Sumarja FX
Published: February 2024

Agricultural land production sharing agreements are agreements that have permanent legal force as regulated in Law Number 2 of 1960 which specifically regulates production sharing agreements. These agreements originate from customary law in Indonesia. The profit sharing agreement implemented in GihamSukamaju Village, Sekincau District, West Lampung Regency has always been done verbally based on trust and agreement. The cultivator and land owner together determine the terms and conditions of the agreement, including rights and obligations. Profits obtained from the use of the land will be distributed according to mutually agreed terms. The aim of this research is to identify and analyze production sharing agreements (Maro) for agricultural land in GihamSukamaju Village, Sekincau District, West Lampung Regency. The research method uses normative-empirical law and a case approach. The results of this research are that the production sharing agreement (maro) for agricultural land in GihamSukamaju Village, Sekincau District, West Lampung Regency is still based on hereditary customs and on the basis of mutual trust. Maro or agricultural land production sharing agreement, divides the results of agricultural land according to the agreement between the owner/controller of the land and the cultivator. After deducting cultivation costs, the results are shared between the cultivator and the land owner/controller.
USING SOCIAL SCIENCE RESEARCH TO FORM PEDAGOGICAL PRACTICES: EVIDENCE-BASED TEACHING STRATEGIES
Authors:   Ph.D. in Education Sciences, Associate Professor at Ovidius University of Constanta, Teacher Training Department., Badoi Hammami Mona
Published: February 2024

The modern trend in the field of education is to increase the active participation of learners during their learning process and to achieve this goal, it was necessary to seek the help of social sciences, especially since many of the fluctuations that occur in the individuals educational path are caused by external changes, such as those social and others. Discussing the evidence-based education tool through the social perspective is important in demonstrating more effective methods for its application, which results in the learners achieving more effective and beneficial learning outcomes inthe long term. Evidence-based teaching is essentially using instructional strategies and procedures that have been proven successful through social science and pedagogical research.It is easier for teachers to make decisions when creating instructional strategies to achieve better outcomes for learners given social and educational events when they incorporate effective teaching techniques backed by unequivocal scientific evidence.To gain a deeper understanding of how learners access education and discover the most effective teaching strategies, content design incorporates social science research and evidence-based learning by presenting different educational strategies, such as active learning, cooperative learning, and problem-based learning, in addition to the flipped learning strategy, technology integration, differentiated teaching, formative assessment, and classroom management from the perspective of evidence-based learning.These technologies have the potential to enable educators to create dynamic learning spaces that meet the unique needs of their students and enhance their academic and personal career advancement. Ultimately, these evidence-based practices are crucial in preparing learners for success in the digital age.
A STUDY TO ASSESS THE ETHICAL CHALLENGES FACED BY THE NURSES POSTED IN COVID CARE UNIT IN SELECTED HOSPITAL OF JAMMU AND KASHMIR
Authors:   Tutor IUST J&K., Khurshid Junaid , Zubair Zahid ,   Tutor Govt. AMT School Srinagar.
Published: February 2024

Statement of the problem: A Study to assess the Ethical challenges faced by the nurses posted in COVID care unit in selected hospital of Jammu and Kashmir Background of the study: COVID-19 infection is a noval disease that infects and kills a substantial number of people every day around the world. Corona Virus Disease 2019 (COVID 19) pandemic has provided a significant challenge to global health care systems. Health care providers, particularly nurses, are dedicated to serving society, and the greatest difficulty they face today is curing and caring for COVID 19 patients.. Aim of the study: To assess the ethical challenges faced by the nurses posted in COVID care unit in selected hospital of Jammu and Kashmir Material and Method: Quantitative research approach and Descriptive research design was used to assess the ethical challenges faced by the nurses working in COVID care unit. Sixty staff nurses who were posted in COVID care unit in DRDO hospital, Jammu and Kashmir were selected using Convenient sampling technique. A Structured rating scale were used to assess the ethical challenges faced by the staff nurses posted at COVID hospital. Results: The result showed that 7.7% strongly agreed on facing ethical challenges, 44.6% agreed, 32.3% were not sure and 15.4% were somewhat not agreed on facing ethical challenges during duty in COVID care unit. Conclusion: According to the studys findings, the majority of staff nurses agreed to face ethical concerns while working in the COVID care unit. Staff nurses should be thoroughly trained to reduce or prevent such issues. They should receive backing from management and administration. This study also suggests that staff nurses should seek support from their families, friends, and society.
THE TAX SYSTEM AND ITS IMPACT ON SUSTAINABLE DEVELOPMENT IN MOROCCO
Authors:   Mohammed V University, Rabat., Rhorfi Abdelkhalek El , Ouafa Filali ,   Souissi Faculty of Legal, Economic and Social Sciences.
Published: February 2024

The study examines the interrelationship between the Moroccan tax system and sustainable development, exploring how tax policies can influence economic, social and environmental sustainability in the country. Focusing on the implications and effects of taxes, tax incentives and environmental taxation measures, the analysis assesses their impact on economic growth, social equity and environmental protection. By highlighting the challenges and opportunities, this research aims to inform strategies to optimise the tax system for sustainable development in Morocco.
EFFECT OF ASHGOURD JUICE ON ANTHROPOMETRIC AND BIOCHEMICAL VARIABLES AMONG HEALTHY VOLUNTEERS - A COHORT STUDY
Authors:   PG Scholar, Department of Diet and Nutrition, SDM College of Naturopathy and Yogic Sciences, Ujire, D.K, Karnataka 574240, Affiliated to Rajiv Gandhi University of Health and Sciences, Bangalore, Karnataka, India., Krishna Thanmaye , Shetty Prashanth ,   SDM College of Naturopathy and Yogic Sciences Affiliated to Rajiv Gandhi University of Health and Sciences, Bangalore, Karnataka, India., B. Shetty Geetha ,   SDM College of Naturopathy and Yogic Sciences, Ujire, D.K, Karnataka 574240, Affiliated to Rajiv Gandhi University of Health and Sciences, Bangalore, Karnataka, India.
Published: February 2024

Background & Objective: Ash gourd has antioxidant, anti-inflammatory, analgesic, antiasthmatic, diuretic, nephroprotective, antidiabetic, hypolipidemic, and antimicrobial effects. Flavonoids, glycosides, saccharides, proteins, carotenes, Î²-sitosterol were the main components. Chemical analysis showed that the main sugars in the Benincasa hispida peels were galactose, glucose, xylose, and sorbose and the edible portion contains 96.3% moisture,0.12% acidity, and 0.5% minerals. The mineral content in ash gourd follows the order: Na>Ca>Fe>Zn>K>Mn, which are important for maintaining homeostatic balance. Drinking ash gourd juice also aids in weight loss. Hence the present study is to evaluate the effect of ash gourd on anthropometric and biochemical variables of healthy individuals. Methods: In this study, 60 subjects were advised to drink 200ml of ash gourd juice for 4 days in a week. Baseline data for Anthropometric measurement, Biochemical variables, and Depression Anxiety Stress Score, were taken before the study and after 3 months of the study. Data was analyzed using appropriate statistical tests. Results: The result showed significant impact of ash gourd juice on anthropometric variables. There was reduction in weight, BMI, waist-hip ratio, Triceps-SKF, and Subscapular-SKF measures. On analysis, Total cholesterol, Triglyceride, LDL cholesterol, HDL cholesterol, Urine pH and NLR showed significant reduction p < 0.05. A significant change in DASS21 adds value to psychological well-being. There was no change in Lymphocytes, Neutrophils, and VLDL cholesterol parameters. Conclusion: There was significant impact of ash gourd juice on parameters like Anthropometry height, weight, waist circumference, hip circumference, BMI, skinfold thickness and biochemical variables, Total cholesterol, Triglyceride, LDL cholesterol, HDL cholesterol, Urine pH and NLR. The result of the DASS21 questionnaire in the study shows evidence to enhance mental health and well-being. Hence, Ash gourd juice may be beneficial in metabolic disorders and inflammatory conditions.
YELLOW LIGHT THE NEXT TECHNOLOGY FOR SMART WATCHES
Authors: Dharwadkar Rashmi
Published: February 2024

Light emitting diodes (LED) are often found in wearable smart electronic devices, such as smart watches, health care monitoring system etc. These are utilized for photoplethysmography (PPG) to monitor a variety of physical health factors. Wearable health monitoring systems have been developed as an outcome of the growth of sensor-based process to deliver real-time feedback information to promote health. This technique has the potential to help with symptom checking and treatment in sophisticated diseases, such as pain management.
KNOWLEDGE, ATTITUDE AND PRACTICES TOWARDS STANDARDS OF WORKING IN A PERIPHERAL INSTITUTE THROUGH APPLICATION OF ISQUA (INTERNATIONAL SOCIETY FOR QUALITY IN HEALTHCARE) ACCREDITED NQAS (NATIONAL QUALITY ASSURANCE STANDARDS) GUIDELINES
Authors:   MD SPM.Medical Officer CHC Nagam., Khurshied Wani Ermeen , Mansoor Suhail ,   MD Medicine. Medical Officer CHC Nagam., Roohi Iqbal Malik ,   BMO Block Nagam, Budgam., Jehangir Majid ,   Doctor at SKIMS.
Published: February 2024

Objective: To study change in knowledge, attitude and practices of healthcare employees through implementation of quality standards for a period of one year. Inclusion criteria: All healthcare employees including doctors and paramedics who were supposed to be posted at our hospital for next two years. Exclusion criteria: Employees with impending transfer to other institutions. Methodology: A cross sectional study was carried out after implementation of quality standard (NQAS) National quality assurance standards. The study was carried out for one year from January 2023 to December 2023.Our sample size was N=70.( 20 doctors and 50 paramedics). Data was taken from all sections using NQAS indicators and questioniires PSS (Patient satisfaction survey), ESS (Employee satisfaction survey). Data was analysed using SPSS-29. Results:The data was analyzed in terms of knowledge, attitude and practices of health staff in pre and post application of NQAS standards. There was a significant improvement in knowledge ,attitude and practices of healthcare employees post NQAS . our sample size was 70 ,including 50 paramedics and 20 doctors (N=70). Results showed significant changes in knowledge ,attitude and practices of employees through implementation of quality standards in a peripheral care hospital as shown in tables 1a to 7c in discussion part. Conclusion: Study results showed significant statistical changes in knowledge attitude and practices through implementation of quality standards at a peripheral institute and highlights the need to implement same standards in other hospitals. Declaration : This was an observational study carried out at our hospital Since NQAS is a new concept in INDIA ,it is a pure research work with no external aid or funding as is evident from the literature regarding quality parameters in peripheral health institutions. This work has not been published previously in any journal.
COMPARATIVE ASSESSMENT OF MACHINE LEARNING MODELS IN RICE CROP STAGE CLASSIFICATION
Authors:   Assistant Professor, L.D. College of Engineering, Ahmedabad, Gujarat, India., Solanki Shital
Published: February 2024

The effective classification of rice crops plays a crucial role in optimizing agricultural management and enhancing yield forecasts. In this paper, we explored the efficacy of various machine learning (ML) techniques in advancing the classification of rice crops. Four machine learning classification algorithms, namely k-nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forests (RF), Decision Trees (DT), and XG Boost, are assessed using a dataset comprising rice crop images and environmental parameters. The studys findings reveal that XG Boost significantly outperforms other models, achieving an impressive accuracy of 96.78%, along with high precision and F1-Score. The Support Vector Machine also demonstrates strong performance with an accuracy of 93.83%. These findings emphasize the potential of ML in advancing agricultural practices and decision-making, highlighting the role of precision agriculture in food security.
A COMPREHENSIVE REVIEW ON CYBERBULLYING PREVENTION
Authors:   Associate Professor, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India., L. Rajesh , V.S Ajay ,   B.E. Students, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India., Biradar Basannagouda ,   B.E. Students, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India., V.H Bhanav ,   B.E. Students, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India., Ahmed Parwez ,   B.E. Students, Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India.
Published: February 2024

The rise of cyberbullying in the digital age necessitates innovative approaches for prevention and intervention. This project proposes a probabilistic framework for Cyber Bullying Prevention utilizing machine learning techniques, support Vector Machines (SVM) and NaÃ¯ve Bayes classifiers, in particular, are the focus.. The objective is to develop a robust system capable of identifying and mitigating instances of cyberbullying in online environments. The proposed model integrates advanced natural language processing and sentiment analysis to effectively analyze textual content and contextual cues within digital communications. By employing SVM and NaÃ¯ve Bayes algorithms, the system aims to discern patterns indicative of cyberbullying behavior, achieving a probabilistic assessment of the likelihood of such occurrences. Through a training dataset enriched with diverse cyberbullying instances, the model learns to generalize its understanding and adapt to evolving online communication dynamics. The project further explores feature engineering and optimization techniques to enhance the classifiers performance. The ultimate goal is to provide a proactive and accurate cyberbullying prevention tool that empowers users, platform administrators, and law enforcement agencies to intervene and mitigate the impact of cyberbullying effectively. This research contributes to the broader discourse on utilizing machine learning in social contexts, emphasizing the importance of collaborative efforts to create a safer digital space for all users.
An alternative class of models to position social network groups in latent spaces
Authors: Nolau Izabel , Ferreira Gustavo
Published: February 2024

Identifying key nodes, estimating the probability of connection between them, and distinguishing latent groups are some of the main objectives of social network analysis. In this paper, we propose a class of blockmodels to model stochastic equivalence and visualize groups in an unobservable space. In this setting, the proposed method is based on two approaches: latent distances and latent dissimilarities at the group level. The projection proposed in the paper is performed without needing to project individuals, unlike the main approaches in the literature. Our approach can be used in undirected or directed graphs and is flexible enough to cluster and quantify between and withingroup tie probabilities in social networks. The effectiveness of the methodology in representing groups in latent spaces was analyzed under artificial datasets and in a case study.
Previsao de Vazão com Séries Temporais Nebulosas para Bacias do Sistema Interligado Nacional
Authors: Alves Tiago da Rocha , Silva Júnior Ivo Chaves , Honório Leonardo
Published: February 2024

This study proposes a comparative analysis between the Soil Moisture Accounting Procedure (SMAP/ONS) and the fuzzy time series technique for water flow forecasting in Brazilian hydroelectric power generation systems. The reservoir crisis of 2021, caused by the worst drought since 1931, which affected the country’s energy sector and increased energy tariffs, served as a warning of the importance of water resource planning and management and how it is essential for electricity generation in Brazil. The SMAP/ONS model, currently used by the Brazilian National Electric System Operator (ONS), calculates water flow based on evapotranspiration and precipitation. In contrast, the fuzzy time series technique is a machine learning-based approach that uses fuzzy logic to handle uncertain data. Results show that the fuzzy time series technique presented competitive performance in most assessed cases.
Plataforma Baseada em Sistema Neuro-nebuloso para Auílio do Psicólogo no Diagnóstico de Transtornos do Neurodesenvolvimento
Authors: Montel Ben-Hur , Figueiredo Angela , Pires Danúbia , Pires Bruna , Rocha Filho Orlando
Published: February 2024

Este artigo apresenta o desenvolvimento de uma plataforma baseada em sistema de identificação neuro-nebuloso para auxiliar psicólogos no diagnóstico de transtornos do neurodesenvolvimento. A metodologia utilizada consiste em um sistema de inferência neuro-nebuloso adaptativo modelado por dados obtidos por intermédio de um profissional psicólogo. Esses dados correspondem a questões avaliadas presentes em um questionário para análise dos níveis de desenvolvimento emocional e funcional. Para a modelagem das regras, dados de entrada foram simulados e avaliados por um psicólogo. Esse conjunto de dados foi utilizado para determinar os parâmetros de saída da regra nebulosa através de um algoritmo de descida de gradiente. Para o teste do modelo, um conjunto de dados foi gerado, e a resposta do sistema foi comparada com o parecer informado pelo psicólogo. Para simplificar a aplicação, uma interface gráfica foi desenvolvida com o objetivo de realizar a comunicação entre o profissional e o sistema neuro-nebuloso. Após a etapa de validação, é observado o potencial de aplicação dessa metodologia para o diagnóstico de transtornos do neurodesenvolvimento. Além disso, a inclusão do parecer do profissional psicólogo na modelagem das regras fortalece a confiabilidade e a precisão do sistema, tornando-o uma ferramenta valiosa para auxiliar no diagnóstico desses transtornos.
Detecção de Ataques DDoS com Base em Métricas de Tráfego usando Redes Convolucionais
Authors: Freitas Junior Antonio Alcir , Lima Filho Francisco , Brito Júnior Agostinho , Silveira Luiz Felipe
Published: February 2024

Este trabalho propõe o uso de uma Rede Neural Convolucional para detectar ataques de negação de serviço distribuído usando métricas de tráfego amostrado em ativos de rede. O treinamento da rede proposta é baseado em imagens formadas a partir das métricas consideradas. Após o treinamento, a rede utiliza imagens formadas a partir do fluxo de rede amostrado para diferenciar o tráfego normal do tráfego anômalo em um curto período de tempo. Dado que o tamanho das imagens criadas pela abordagem proposta é pequeno, a rede convolucional é capaz de operar com eficiência, fornecendo respostas rápidas e bem-sucedidas para os testes realizados, sendo competitiva quando comparada com trabalhos semelhantes na literatura.
Interdisciplinary integration of land use and drainage planning for urban adaptation under the climate change scenario
Authors: Liao Chin-Hsien , Huang Cheng-Chia
Published: February 2024

The challenge posed by urbanization often revolves around effectively integrating land use and comprehensive drainage planning. The empirical results of urban layout on stormwater management are summarized into two major categories: (1) decrease of runoff volume and (2) decrease of peak flows. Interdisciplinary incorporation of urban design and hydraulic engineering should be employed for reducing upstream runoff volumes and a regional downstream detention system to mitigate peak flow releases. This study proposes a framework that combines the distribution of flow loading and the control of flow releases to formulate the adaptation strategy by synthesizing land use and comprehensive drainage planning. The study leverages environmental and land use data to investigate Dapu township, Taiwan. The presented paper designs a detention and low-impact development (LID) method based on relative land use layout. It identifies the relationships between land use and master drainage planning (MDP) in watershed areas. It contributes to an integrated framework for the urban planners' flood mitigation adaptation strategy. Most importantly, it provides insights into MDP practices under slight, medium, and even climate change scenarios.
Quantifying water loss in leaky micro-dam reservoir through water balance analysis and high-resolution water level data modeling
Authors: Berhane Gebremedhin , Walraevens Kristine
Published: February 2024

This study aimed to assess the runoff, recharge, and response of a shallow aquifer to leakage from the Arato micro-dam reservoir (MDR). The assessment was conducted using the Soil Conservation Service Curve Number (SCS-CN), soil moisture balance (SMB), and diver (automatic data logger) measurements in both the MDR and a shallow hand-dug well. Recharge was estimated using the chloride mass balance (CMB) and water table fluctuation (WTF) methods. The results revealed that the annual runoff from the catchment was 48.8 mm, which accounted for approximately 0.71 million m3. The yearly groundwater recharge was estimated to be 104, 92.8, and 100 mm using the SMB, CMB, and WTF methods, respectively. Furthermore, the water balance model of the Arato MDR indicated a leakage rate of 13.2 mm/day. It is noteworthy that the estimated leakage exceeded the seepage initially anticipated during the project's design phase (9,965 m3/year). This research project highlights the significance of utilizing local climatic and physical data from the specific watershed under investigation when planning reservoirs and other water resources. It also underscores the importance of conducting thorough site investigations to accurately quantify hydraulic conductivity for leakage estimation purposes.
Spatio-temporal patterns of groundwater level changes in southwestern Indian Punjab
Authors: Dhaloiya Arvind , Singh J. P.
Published: February 2024

The study aimed to assess the dynamic behavior of groundwater levels in the southwestern districts of Indian Punjab, focusing on the spatial and temporal distribution of waterlogged and overexploited areas before and after the monsoon season. The study utilized groundwater level data spanning 48 years (1973 -2020), using GIS to map groundwater levels and visualize fluctuations throughout the study area. The findings revealed significant variations in groundwater levels within the southwestern district of Punjab during different seasons. The maximum waterlogged areas were found to be 97,350 ha (1973, Faridkot), 56,080 ha (1981, Ferozepur), 21,730 ha (1991, Sri Muktsar Sahib), 52,790 ha (2000, Sri Muktsar Sahib), 6,760 ha (2010, Sri Muktsar Sahib), and 2,910 ha (2020, Fazilka). However, the waterlogged and potential waterlogging area observed in Fazilka district covered about one-third (32.52%) of the district during 2020. The study identified that 45% of the study area faced the risk of overexploitation, 46% was considered safe, and 9% was either waterlogged or at risk of waterlogging. Over the 48 years, the study demonstrated the dynamic nature of waterlogged areas in the southwestern districts of Punjab, including Ferozepur to Fazilka via Faridkot and Sri Muktsar Sahib districts.
Research Progress of TCM Therapy for Rotator Cuff Injury
Authors: Zhang Xianquan , Zhou Guanghui , Gu Zhuoxu , Luo Minghui , Liang Guihong
Published: February 2024

Background::

Rotator cuff injury is a common orthopedic disease with high morbidity,
which is one of the most important reasons for shoulder pain and limited movement. With the
development of more research, the Traditional Chinese Medicine(TCM) therapy for rotator cuff
injury is increasingly rich, and has achieved a good curative effect.

Method::

TCM has certain characteristics and advantages, which may become the main development
trend of the treatment. By consulting the relevant literature on TCM therapy for rotator cuff
injury in recent years, we found that commonly used TCM therapy include Chinese herbal therapy,
Chinese herbal compounds.

Result::

External treatment of Chinese herbal therapy, Acupuncture therapy, Floating needle therapy, Massage therapy, and others, which make a great clinical effect.

Conclusion::

This paper summarizes and analyzes the common TCM therapy of the rotator cuff
injury, to provide new ideas for the selection of clinical treatment options.
Valeriana jatamansi: Bioactive Compounds and their Medicinal Uses
Authors: Maurya Antim K. , Agnihotri Vijai K.
Published: February 2024

Valeriana jatamansi is a reputed perennial medicinal herb distributed throughout the world, where it is used in cytotoxicity, neuronal problems, insomnia, leishmania and acetylcho-linesterase inhibitor, antioxidant, antiviral and α-glucosidase inhibition activities. This review de-scribes the current state of chemical characterization of isolated metabolites, which are well ac-cepted for the treatment of various ailments in the indigenous system of medicine. This compre-hensive review covers previously published research articles and reviews up to 2023 with an em-phasis on the structural characterization of isolated bioactive compounds using different analyti-cal techniques. Furthermore, the present review also focuses on the detailed medicinal and phar-macological properties of isolated compounds from this threatened herb.
Effect of in vitro Digestion on the Bioaccessibility of Polyphenols and Potential Prebiotic Properties of Potato Peel
Authors: Mall Urvashi P. , Patel Vinayak H.
Published: February 2024

Background:

Potato peel is a byproduct of the potato processing industry and a potential
source of functional ingredients such as dietary fiber, polyphenols, and prebiotics. However,
the bioaccessibility of polyphenols and antioxidants during in vitro digestion and prebiotic potential
after in vitro digestion of potato peel flour has not been reported.

Objective:

The study was designed to assess the bioaccessibility of polyphenols and the prebiotic
potential of potato peel flour.

Methods:

In this study, the changes in polyphenol content and antioxidant capacity during different
phases of in vitro digestion, including salivary, gastric and intestinal phases were studied.
Additionally, an investigation was conducted to evaluate the prebiotic properties of potato peel
flour by in vitro fermentation with Lactobacillus acidophilus.

Results:

The findings revealed a significant increase in the recovery index for total phenolic content
during both gastric (106.90%) and intestinal (102.71%) digestive phases. Furthermore, polyphenols
in potato peel flour exhibited high residual intestinal digestibility index values (>90%).
The antioxidant capacity increased by >50% during various phases of in vitro digestion. Regarding
prebiotic properties, potato peel flour significantly increased L. acidophilus counts and promoted
the production of short-chain fatty acids, specifically propionate and butyrate.

Conclusion:

This study suggests that potato peel flour has the potential to serve as a functional
ingredient or nutraceutical that can enhance health and may help in reducing environmental
problems.
Metabolic Reprogramming in Gliocyte Post-cerebral Ischemia/
Reperfusion: From Pathophysiology to Therapeutic Potential
Authors: Gong Lipeng , Liang Junjie , Xie Letian , Zhang Zhanwei , Mei Zhigang , Zhang Wenli
Published: February 2024

Ischemic stroke is a leading cause of disability and death worldwide. However, the clinical
efficacy of recanalization therapy as a preferred option is significantly hindered by reperfusion injury.
The transformation between different phenotypes of gliocytes is closely associated with cerebral ischemia/
reperfusion injury (CI/RI). Moreover, gliocyte polarization induces metabolic reprogramming,
which refers to the shift in gliocyte phenotype and the overall transformation of the metabolic network
to compensate for energy demand and building block requirements during CI/RI caused by hypoxia,
energy deficiency, and oxidative stress. Within microglia, the pro-inflammatory phenotype exhibits
upregulated glycolysis, pentose phosphate pathway, fatty acid synthesis, and glutamine synthesis,
whereas the anti-inflammatory phenotype demonstrates enhanced mitochondrial oxidative phosphorylation
and fatty acid oxidation. Reactive astrocytes display increased glycolysis but impaired glycogenolysis
and reduced glutamate uptake after CI/RI. There is mounting evidence suggesting that
manipulation of energy metabolism homeostasis can induce microglial cells and astrocytes to switch
from neurotoxic to neuroprotective phenotypes. A comprehensive understanding of underlying mechanisms
and manipulation strategies targeting metabolic pathways could potentially enable gliocytes to
be reprogrammed toward beneficial functions while opening new therapeutic avenues for CI/RI treatment.
This review provides an overview of current insights into metabolic reprogramming mechanisms
in microglia and astrocytes within the pathophysiological context of CI/RI, along with potential
pharmacological targets. Herein, we emphasize the potential of metabolic reprogramming of gliocytes
as a therapeutic target for CI/RI and aim to offer a novel perspective in the treatment of CI/RI.
Model concepts to support the improvement of students' skills in learning tasks
Authors: Jeumpa Kemala , Harahap Rumila
Published: February 2024

This article aims to design a concept model that can support learning to improve students' ability in learning tasks to deal with problems that exist in the real world. Based on KKNI (Indonesian National Qualification Framework), there are six tasks in learning, namely routine tasks, critical book reports, critical journal reports, idea engineering (scientific or creative writing), mini research, and projects. Therefore, the learning process must be able to increase student learning motivation. In addition, it must also develop their competencies and skills to think critically, have high creativity, be able to work together in teams, be disciplined, be responsible, and be able to create frameworks and solve problems in life and the environment. Therefore, it is necessary to develop a learning model that is in accordance with these objectives. In this case, it is a learning model designed to encourage students to learn and practice, so that they are skilled in responding to problems based on their experience in learning. The approach in this development research was carried out using the ADDIE model. The design concept of this development model is done by combining a project-based learning model with six tasks based on KKNI (Indonesian National Qualification Framework). The results of the design concept of this development model consist of seven syntax stages, namely: material explanation, material review and formulation of problem formulation, study and review of book and journal literature, idea engineering (scientific or creative writing), mini research, project design and implementation, and presentation and evaluation.
Employability skills and self-perception of diploma 3 graduates in the world of work
Authors: Febriana Rina , Hanafi Ivan , Kandriasari Annis , Nuryanto Apri , Soeprijanto Soeprijanto , Muksin Muksin , Ching Su Jo , Mamat Abu Bakar
Published: February 2024

This study aims to determine the world's perception of Diploma 3 graduates regarding work skills. The research used a questionnaire survey method on Diploma 3 graduates who had worked for 2-5 years. Measurement of work aspects includes individual qualities, basic skills, interpersonal skills, thinking skills, resource management, systems and technology, and information skills. The instrument's validity in each aspect ranges from 0.416 to 0.683, with a reliability of 0.882. The research technique used simple random sampling with 109 respondents in this study. The results of the study stated that the self-perception of graduates are (1) an individual quality score of 85.5 with a very high interpretation; (2) basic skills get a score of 81.8 with a high interpretation; (3) an interpersonal score of 84.8 with a very high interpretation; (4) thinking skills get a score of 83.1 with a very high interpretation; (5) resource management obtained a score of 88.6 with a very high interpretation; (6) systems and technology got a score of 92.4 with a very high interpretation, and (7) information skills got a score of 85.1 with a very high interpretation. Thus, the average worldwide employment of Diploma 3 graduates is 85.9, with a high interpretation. This finding implies that the higher graduates' employability skills, the higher their self-perception at work.
Application of Augmented Reality (AR) in vocational education: A systematic literature review
Authors: Supriyanto Supriyanto , Joshua Quienera , Abdullah Ade Gafar , Tettehfio Emmanuel Obobi , Ramdani Sulaeman Deni
Published: February 2024

Augmented Reality (AR) is a technology that combines two-dimensional and or three-dimensional virtual objects into a real environment and then projects these virtual objects in reality in real time. Through this AR technology, users can see virtual objects added to the real world with contextual information. In education, AR has been widely used to complement the standard curriculum. Text, graphics, video, and audio can be superimposed into the student's real-time environment. This article aims to examine how the application and impact of the use of AR in vocational education. The Systematic Literature Review (SLR) method is used to identify, study, evaluate, and interpret Augmented Reality in vocational education. Research data were identified using the SLR method with the help of the PRISMA 2020 form. Article collection was carried out on the Science Direct database. There were as many as 454 articles. After being selected using inclusion and exclusion criteria, the data used were 14 articles. The study results reveal that AR is applied in learning as an innovative learning medium, a new approach to learning to improve students' understanding of knowledge and skills and provide a concrete learning experience. The integration of AR in education has the impact of increasing students' understanding and learning experience, promoting positive attitudes, making the learning process fun and interesting, and learning efficiency
Implementation of BMC-based teaching and learning factory model in increasing student competencies in leather creative skills concentration and imitation in vocational school
Authors: Sutianah Cucu , Nurhutami Meita Annisa , Yamin Alfian Azhar
Published: February 2024

Learning in vocational education must be carried out with collaboration between educators, vocational schools, curriculum alignment, and learning in factories as miniature industries stakeholders to achieve assessment in the form of real assessment so that the achievement of learning objectives follows the needs of students and the world of work. Assessment in the form of assessment must be measured in real terms, with religious, character, moral, and cultural education values and work competencies following community expectations. The objectives to be achieved through this research are to produce a learning program that can improve student competence in Vocational High School (VHS), including identifying the current condition of learning implementation, obtaining learning planning findings, obtaining learning implementation findings, obtaining findings regarding the assessment of learning outcomes, identifying supporting and inhibiting factors, knowing students' perceptions of the implementation of the BMC-based teaching and learning factory model in improving student competence in the concentration of leather and imitation craft design and production expertise in  VHS. With the implementation of a learning system using a block system as a teaching and learning factory, the implementation of learning must stimulate students to be more active in improving social skills, emotional skills, spiritual skills, scientific skills, mental skills, kinesthetic skills, as well as entrepreneurial skills, work ethics and safety, and work safety and the environment, which in turn can improve the competence and entrepreneurial character of students, following the vision and mission of the education unit.
Smart learning model in technical and vocational education training with webcast technology
Authors: Huda Yasdinul , Jaya Putra , Tasrif Elfi , Elmi Hafiz
Published: February 2024

This research aims to develop an e-learning strategy for the industrial revolution 4.0 era by developing an innovative and adaptable TVET learning model using Webcast technology. This approach highlights the blended learning model developed as a smart learning model featuring a balance between synchronous and asynchronous learning using webcast technology. Research and development method is used in this approach.  The model design is done by literature study and focus group discussion with experts and academicians. The model effectiveness trial results were measured with an experimental design (using the one-group pretest-posttest and posttest-only method with nonequivalent groups). The results of developing a smart learning model of TVET webcast technology describe: (1) How the learning rules are used; (2) How to connect with webcasting technology; and (3) What are the stages and steps of the webcasting-based smart learning model? The proposed model approach allows for simultaneous learning interactions in synchronous and asynchronous classes in various locations, thus triggering student engagement in learning activities and enhancing different learning styles, ways of thinking, and problem-solving skills.
Essential competences contribution of the S2-PTE course in Universitas Negeri Yogyakarta to work competence
Authors: Taruno Djoko Laras Budiyo , Djatmiko Istanto Wahyu , Hadi Samsul , Yuniarti Nurhening
Published: February 2024

This study aims to determine the essential competencies contribution of each vocational course and engineering course in the curriculum to the competence needs of education, training, and engineering work in the electrical power competencies. The research was carried out using a goal-oriented evaluation approach. The object of this research is to the essential competencies of the electrical engineering education Master Program's courses at Universitas Negeri Yogyakarta, including engineering and vocational education courses. Data collection used a questionnaire, then analyzed descriptively. Furthermore, it was presented in the form of categorical data and graphs. The research results show that each essential competence contributes 70.0% to electrical education and training jobs. Referring to the Indonesian National Work Competency Standards, each essential competency contributes more than 66.7%. Thus it can be concluded that the essential competencies of the electrical engineering education Master Program's courses in Universitas Negeri Yogyakarta have contributed to the electricity sector jobs.
Development and validation of a self-assessment-based instrument to measure elementary school students’ attitudes in online learning
Authors: Setiawan Ari , Cendana Wiputra , Ayres Mark , Yuldashev Azim Abdurakhmanovich , Setyawati Sri Panca
Published: February 2024

Online learning during the COVID-19 pandemic makes it difficult for teachers to assess student learning attitudes. Limited availability of instruments to measure attitudes of students when they are engaged in online learning leads to difficulty of teachers to conduct appropriate assessments on that measure. The current study, therefore, mainly was intended to produce a self-assessment-based instrument that is feasible to use to measure students’ attitudes in online learning. In order to produce such instrument, we used developmental research method by following steps in the instrument design that is proposed by McCoach, Gable, and Madura. Furthermore, in order to provide feasibility of our instrument, we provided evidence of content validity through experts’ judgment data as well as evidence of construct validity with confirmatory factor analysis (CFA) and reliability estimation with Cronbach’s α through a limited trial and an expanded trial using response data of sixth graders of elementary school engaged in online learning. Our study has produced a self-assessment-based instrument that uses a summated rating scale and is composed of six components (i.e., honest, disciplined, responsible, polite, caring, and self-confident) and 24 items that have demonstrated evidence of content validity, stable factor structure, and high reliability estimates.
Smartphone application for assessing teacher performance
Authors: Marlianawati Hesty , Suranto Suranto , Kartowagiran Badrun
Published: February 2024

This work seeks to design a smartphone application for assessing teacher performance utilizing a 4D development model modified with the Mardapi instrument development model of (1) define (defining); (2) design (deciding instrument requirements, determi­ning application media specifications, creating flowcharts, and creating storyboards); (3) develop (assemble instruments, code, execute tests, evaluate test results, and interpret measurement findings); and (4) disseminate (spread). Proof of the application’s viability was established through product testing with 26 principals acting as application users and evaluations by material and media specialists. The content validity of the acquired results was evaluated using the Aiken method, and the construct validity was evaluated using PLS (Partial Least Squares) analysis because the sample size does not have to be large, in accordance with this study where the number of samples is not so large. Using Cronbach’s alpha to evaluate the reliability. The results demonstrated that the built application was “possible,” as proven by the existing instruments in the valid and trustworthy application. This is proven by the fact that the content validity test utilizing the Aiken method yielded good validity results, with a mean score of 0.80 for material experts and 0.75 for media experts. The construct validity test using PLS (Partial Least Squares) yielded positive results for validity. The estimation of reliability using Cronbach’s alpha yields positive findings. Therefore, it can be concluded that the developed application for teacher performance evaluation possesses the features of a valid and trustworthy assessment instrument.
The development of measurement instruments of Sharia students’ perceptions about Khilafah
Authors: Subando Joko , Wibowo Muhammad Kurniawan Budi , Farkhani Farkhani
Published: February 2024

This study aims to develop an instrument to measure Sharia students’ perception of the Khilafah. The research applied the ADDIE development research approach. The activity began with reviewing Taqiyuddin An-Nabhani’s books and articles about Khilafah to get the instrument construct (analysis). The next stage was to compile the grid and assemble the instrument items (design). The items of the assembled instrument were then assessed by 11 experts (development). The validated Instruments were then carried out with limi­ted and expanded trials. The limited trial was conducted on 26 students at Universitas Islam Negeri (UIN) Salatiga, and the expanded trial was conducted on 227 Sharia stu­dents from Institut Islam Mamba’ul ‘Ulum (IIM) Surakarta, UIN Raden Mas Said, and UIN Salatiga. The experimental data were analyzed with CFA. The results indicate that the instrument construct consisted of seven aspects of measurement encompassing the essence, the function, the establishment, the power and sovereignty, the form of state and government, the Khilafah government system, and the constitution for non-Muslims. The measurement model meets eight model fit criteria, including AGFI = 0.84 ( 0.8), chi-square/df = 1.459 ( 2), RMR = 0.054 (≤ 0.1), SRMR = 0.056 (≤ 0.1), RMSEA = 0.045 ( 0.08), NFI = 0.95 (≥ 0.9), NNFI = 0.98 (≥ 0.9), CFI = 0.98 (≥ 0.9), IFI = 0.98 (≥ 0.9). The instrument also has a good guarantee of validity and reliability. This is indicated by the loading factor value of each indicator above 0.4 and the composite reliability value of 0.95 ( 0.7) so that the instrument can be used for further measure­ments.