bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Protectionism: Tren Meningkatnya Kebijakan Proteksionisme Energi di Uni Eropa
Authors: A. Mario Farrasda As  , Nur Isdah Idris
Published: October 2024

This research discusses the impact of EU energy protectionism in the face of global challenges such as the Covid-19 pandemic and the energy crisis due to the Russia-Ukraine conflict. Those two major events reveal the risks of over-dependence on foreign suppliers and the lack of diversification in the EU supply chain. As a solution, the EU has implemented various policies, including RePowerE, Carbon Border Adjustment Mechanism (CBAM), and Green Deal Industrial Plan (GDIP), to reduce dependence on energy imports and increase domestic renewable energy production. Through the analysis of neoliberalism and Game Theory approaches, particularly the Prisoner's Dilemma concept, this article explores the implications of protectionist policies on international trade stability. The analysis shows that while protectionist policies can strengthen the EU's energy independence and domestic security, they also have the potential to trigger international trade tensions and protectionist retaliation from other countries.
Membangun Karakter Bangsa Melalui Pendidikan Pancasila Universitas PGRI Adi Buana Surabaya
Authors: Arjuna Raffi Pradipta  , Mochamad Bahrul Ulum  , Naufal Nur Alfian  , Mohammad Bayhaqie Febby Habibulloh  , Nanda Prima Setyawan  , Yoga Chandra Prianto  , Rizqi Eka Firdyansyah  , Muhammad Aji Pamungkas  , Muhammad Nauval Rizky Alifian  , Robby Suga  , Jea Nur Fitriana  , Suyono Suyono
Published: October 2024

Pancasila education in Indonesia is claimed to be the main foundation for the formation of national character. This education aims to teach basic values which include diversity, justice, unity, democracy and humanity, which are the foundation for the characteristics and morality of the Indonesian nation.This article reviews the importance of Pancasila education in forming national character values. Students are taught to respect differences of opinion, respect human rights, and practice democratic principles in everyday life. This all aims to create citizens who are fair, just and have a democratic culture. Apart from that, Pancasila education also develops a sense of love for the country and humanism. Through this education, students are taught to appreciate Indonesia's cultural and natural riches, and have the enlightenment to contribute to preserving the environment and overcoming social problems among the people.This, Pancasila education is not only about theoretical knowledge, but also about the practice of values in everyday life.
Peran Diaspora Armenia dalam Konflik Nagorno Karabakh Tahun 2020-2022
Authors: Ramadhannil Yusuf  , Hesti Rosdiana
Published: October 2024

The Nagorno-Karabakh conflict from 2020 to 2022 highlights the significant role of the Armenian diaspora in supporting Armenia across various dimensions. The research aims to determine the extent to which the Armenian diaspora's support influences the Armenian government's capacity to handle the conflict. The study utilizes theories of public diplomacy and diaspora engagement, employing a mixed-methods approach that includes qualitative data from secondary data processing such as journals and written results containing data about Armenian Diaspora, official website of the Armenian government, and quantitative data from financial contributions and diplomatic records. Findings indicate that the Armenian diaspora's political lobbying and advocacy efforts have secured significant diplomatic support, while economically providing substantial remittances, investments, and humanitarian aid. Socially, the diaspora has shaped international public opinion through campaigns and cultural activities, and intellectually, it has offered strategic insights enhancing the government's approach to the conflict. Additionally, the mobilization of human resources by the diaspora has provided direct assistance in Armenia. This research offers a comprehensive understanding of the dynamics between the Armenian diaspora and the Armenian government, demonstrating the substantial impact of multidimensional diaspora support on the government's capacity to manage the Nagorno-Karabakh conflict.
Teori Kedaulatan Negara
Authors: David Doresta Wijaya  , Nurul Mubin
Published: October 2024

Sovereignty is simply the highest power. One of the principles of sovereignty means managing domestic affairs without interference from other countries, this is because the state has power. However, the issue of who owns the power is still a polemic to this day. This is because if something is said to be sovereign but can still be subject to other powers, then that is not sovereignty. Therefore, the emergence of theories of sovereignty did not coincide but developed according to the times, followed by the emergence of philosophers who were more critical about sovereignty in the state. Among the theories is the theory of state sovereignty, which means that the highest power is held by the state. However, as has been explained, this theory still has advantages and disadvantages, which means that the state can be subject to many things, but the state can also be subject to other things.
Perubahan Sosial Sistem Kekerabatan dalam Upacara Adat Perkawinan Masyarakat Nias (Studi Kasus Tahapan Fanika Era-Era Mbowo) di Desa Tuhembuasi Kecamatan Sogae’adu Kabupaten Nias
Authors: Fatizaro Gulo  , Masniar H. Sitorus  , Harisan Boni Firmando
Published: October 2024

The title of this research emphasizes social changes in the kinship system in the traditional marriage ceremony of the Nias community (case study of the fanika stages of the mbowo era) in Tuhembuasi Village, Sogae'adu District, Nias Regency. The aim of this research is: To find out/describe social changes in the kinship system in the traditional marriage ceremony of the Nias community (case study of the fanika stages of the mbowo era) in Tuhembuasi Village, Sogae'adu District, Nias Regency. In this research, the method used is a descriptive qualitative approach. The results of the research show that the causes of changes in the Fanika stages of the Mbowo era in the Nias tribe community in Tuhembuasi Village, Sogae'adu District, Nias Regency are: (1) parents nowadays are very busy so they don't have time to talk about or teach about customs. and the culture of the Nias people to their children; (2) because the implementation of the Fanika stages in the Mbowo era took a lot of time, up to 3 to 4 hours, so people also felt bored because the time was too long, so the implementation of this stage was often postponed; (3) many people currently have very little experience of Nias culture so that the implementation of its customs as they are is important to remember but is not implemented; (4) migrate, marry with other tribes, so that the celebration does not reflect Nias culture.
Comparative Analysis of Imputation Methods for Enhancing Predictive Accuracy in Data Models
Authors: Zamri Nurul Aqilah , Jaya M. Izham , Irawati Indrarini Dyah , Rassem Taha H. , Rasyidah - , Kasim Shahreen
Published: October 2024

The presence of missing values within datasets can introduce a detrimental bias, significantly impeding the predictive algorithm's ability to discern patterns and accurately execute prediction. This paper aims to elucidate the intricacies of data imputation methods, providing a more profound understanding of prevalent imputation methods, including list-wise deletion (IGN), mean imputation (AVG), K-Nearest Neighbors (KNN), MissForest (MF), and Predictive Mean Matching (PMM). The dataset employed in this study consists of financial data about S&P 500 companies in the Compustat North America database. The training and validation dataset encompasses 1973 instances, consisting of data during the fourth quarter of 2009, the first quarter of 2010, and the third quarter of 2014. Within this set, 457 missing values were identified and imputed. The test dataset comprises 197 randomly selected instances from the fourth quarter of 2014, equivalent to ten percent of the total instances in the training dataset. The evaluation findings prominently position the dataset derived from MF imputation as the leading performer among all the imputed datasets. The insights derived from this study are intended to assist practitioners in making informed choices when selecting the most suitable data imputation method, particularly in the context of predictive modeling tasks.
Deep Learning Models for Dental Conditions Classification Using Intraoral Images
Authors: Makarim Ahmad Fauzi , Karlita Tita , Sigit Riyanto , Bayu Dewantara Bima Sena , Brahmanta Arya
Published: October 2024

This paper presents the digitalization of dentistry medical records to support the dentist in the patient examination process. A dentist uses manual input to fill out the evaluation form by drawing and labeling each patient’s tooth condition based on their observations. Consequently, it takes too long to finish only one examination. For time efficiency, using AI-based digitalization technology can be a promising solution. To address the problem, we made and compared several classification models to recognize human dental conditions to help doctors analyze patient teeth. We apply the YOLOv5, MobileNet V2, and IONet (proposed CNN model) as deep learning models to recognize the five common human dental conditions: normal, filling, caries, gangrene radix, and impaction. We tested the ability of YOLO classification as an object detection model and compared it with classification models. We used a dataset of 3.708 intraoral dental images generated by various augmentation methods from 1.767 original images. We collected and annotated the dataset with the help of dentists. Furthermore, the dataset is divided into three parts: 90% of the total dataset is used as training and validation data, then divided again into 80% training data and 20% validation data. 10% of the total dataset will be used as testing data to compare classification performance. Based on our experiments, YOLOv5, as an object detection model, can classify dental conditions in humans better than the classification model. YOLOv5 produces an 82% accuracy testing value and performs better than the classification model. MobileNet V2 and IONet only get 80% and 70% testing accuracy. Although statistically, there is not much of a difference between the test accuracy values for YOLOv5 and MobileNet v2, the speed in classifying dental objects using YOLOv5 is more efficient, considering that YOLOv5 is an object detection model. There are still challenges with the deep learning technique used in this research, but these can be addressed in further development. A more complex model and the enlargement of more data, ensuring it is varied and balanced, can be used to address the limitations.
Design of Tools for Visualizing Thermodynamic Concepts in Steam Power Plant Trainer Processes with Web-Based Exploratory Data Analysis (EDA)
Authors: Karudin Arwizet , Leni Desmarita , Lapisa Remon , Kusuma Yuda Perdana , Abbas Muhammad Rabiu
Published: October 2024

Thermodynamics is considered one of the most complex and challenging subjects for many students. This is primarily due to comprehending abstract concepts such as entropy, enthalpy, and energy flow, which involve complex mathematical equations and are rarely accompanied by tangible visualizations. This research aims to design, develop, and test a data-based visualization tool for thermodynamics testing results. This study collected and processed data from thermodynamics testing and simulations, such as the mini-steam power plant trainer used as a teaching aid in thermodynamics education, as the foundation for designing a data-based visualization tool for thermodynamics concepts. The visualization tool was created using the Python programming language integrated with the web-based Streamlit framework. The designed visualization tool encompasses various features, including automated data reporting, visualization of variable correlations using correlation heatmaps, Sankey diagrams for visualizing energy flow, and the capability to predict electrical output using machine learning integrated with three different machine learning algorithms. The visualization tool was evaluated by thermodynamics experts using a Likert scale. Based on the results obtained, the experts gave an average score of 4 in the information accuracy aspect in the good category. This shows that the information displayed in this visualization tool is by thermodynamics learning at Padang State University. In the visualization aspect, experts gave an average score of 4.25, which is in the Good and Very Good range. In alignment with the education aspect, experts gave an average score of 3.75, which is close to the good category. This shows that this aspect is considered suitable for studying thermodynamics, although shortcomings still need to be corrected. Experts gave a relatively high assessment of the Ease-of-Use aspect, with an average score of 4.5, with a range of Good and Very Good. This enables students to better understand complex patterns, cause-and-effect relationships, and parameter changes within thermodynamics concepts.
A Review on Deep Learning Approaches and Optimization Techniques For Political Security Threat Prediction
Authors: Zaabar Liyana Safra , Mat Razali Noor Afiza , Ishak Khairul Khalil , Abdullah Nor Asiakin , Wook Muslihah
Published: October 2024

In an era of complex geopolitical dynamics and evolving security threats, the accurate prediction and proactive management of political security risks are imperative. This article provides a comprehensive review of the application of deep learning methodologies and optimization techniques to enhance political security threat prediction. Beginning with analyzing the dynamic landscape of political security threats, the paper emphasizes the necessity for adaptive, data-driven predictive tools. It then delves into the fundamentals of deep learning, elucidating core principles, notable architectural frameworks, and their diverse applications across domains. Expanding upon this foundation, the study evaluates the suitability of deep learning models for addressing the multifaceted challenges associated with political security threat prediction. To maximize the utility of these models, the article explores optimization techniques encompassing hyperparameter tuning, transfer learning, and ensemble strategies, assessing their effectiveness in fine-tuning predictions and bolstering the resilience of threat prediction systems. This review involved the utilization of four journal databases: IEEE, Science Direct, Association for Computing Machinery (ACM), and SpringerLink. We analyzed and examined 39 articles, paying close attention to the different patterns and techniques found within the chosen research framework. Through a critical synthesis of existing research, this review offers insights into the strengths, limitations, and future directions of deep learning-based political security threat prediction, contributing to the ongoing discourse on leveraging artificial intelligence for safeguarding global stability and security.
The Analysis Factors Influencing the Implementation of Digital Social Entrepreneurship Application in Learning Engineering Education Using Structural Equation Modelling
Authors: Ganefri - , Nordin Norazah Mohd , Yulastri Asmar , Hidayat Hendra
Published: October 2024

A big part of being an entrepreneur is keeping up with modern technological advancements. However, many factors can lead to the ambition to launch an online company. Digital social entrepreneurship methodology examines the effects of college students' entrepreneurial mindset, smartphone usage habits, and Locus of Control on their digital business intentions. This research is fundamental because it provides information to universities that they can use to evaluate their plans for a digital-based entrepreneurship learning model that will help them provide a good education. This study involved 428 respondents, and the data obtained from the respondents were examined using the application of structural equation modeling with a survey approach for this research, which looks at a small portion of the community and collects data through questionnaires. The primary data was examined using SmartPLS 4.0 software and structural equation modeling. This study found that having an entrepreneurial mindset, smartphone use, and locus of control exerts a substantial and meaningful impact on one's aspiration to become a digital entrepreneur. We wanted to find out how college students' thinking about being an entrepreneur affects their desire to become a digital entrepreneur, using smartphone usage habits and locus of control as influencing factors. To make someone who wants to become an entrepreneur, this research needs to measure Digital Entrepreneurial Intention appropriately in students who take Entrepreneurship courses.
Transliterating Javanese Script Images to Roman Script using Convolutional Neural Network with Transfer Learning
Authors: Naufal Mohammad Farid , Siswantoro Joko , Soebroto Juan Timothy
Published: October 2024

The Javanese script holds immense cultural significance within Indonesia despite its diminishing usage in contemporary contexts. Its presence remains notable in specific regions of Java and remains integral to many historical documents and texts. Consequently, there is an urgent need for a transliteration system adept at converting Javanese script into contemporary scripts like Roman or Indonesian, thereby contributing to preserving Java's linguistic and cultural legacy. However, reading or transliterating Javanese script can be time-consuming, especially for longer texts, presenting considerable challenges for non-native readers. This study aims to develop an effective transliteration system for converting Javanese script into Roman script. This system addresses the pressing need to preserve Java's linguistic and cultural heritage by facilitating the readability and accessibility of Javanese script, especially for non-native readers. This study introduces an Optical Character Recognition (OCR) system tailored to identify Javanese script characters and transcribe them into Roman characters, explicitly focusing on fundamental nglegena and sandhangan swara characters. Individual characters are isolated by leveraging horizontal and vertical projection techniques, facilitating subsequent classification using a Convolutional Neural Network (CNN) employing transfer learning methodologies. The system's achievement of an impressive average similarity score of 90.78% is noteworthy, with the Xception architecture demonstrating superior efficiency in transliteration tasks. Implementing such a system harbors significant promise in safeguarding the Javanese script and enhancing its accessibility to a broader audience. This research contributes substantially to preserving and propagating Indonesia's rich cultural and linguistic heritage amidst the digital age.
A Semiotic Approach to Translating between Arabic and English
Authors: Almanna Ali , Farghal Mohammed
Published: October 2024

Drawing on Arabic authentic excerpts that feature key semiotic signs in English translation, this paper shows how challenging it is for translators to capture the communicative value of such signs. The discussion shows that signs have two important components: iconic and indexical. In a few cases in which a happy coincidence may exist in the language pair, the translator can relay both components and, optimally, capture the semiotics of the sign. However, in most contexts, he/she needs to search for other translation procedures. These may include formal equivalents that follow source language norms, functional equivalents that embrace target language iconicity, ideational equivalents that only capture the sign’s indexical import, or a combination of two procedures. In any case, the translator should pay utmost attention to the interpretant of the semiotic sign in its relevant context because the same sign may have to be rendered differently.
Collectivism-Based Travel Culture as the Antecedents of Travel FOMO And Intention to Travel Responsibly
Authors: Harahap Dian E. , Arief Mts. , Furinto Asnan , Anggraeni Adilla
Published: October 2024

As collectivists, Indonesians tend to travel with friends and family. The destination is usually inspired by social media content which then will increase fear-of-missing-out anxiety (FOMO) for traveling because it generates travel intention. A previous study claimed that collectivist culture has a strong correlation with FOMO behavior. This research analyzes the role of collectivism-based travel culture as the antecedent of travel FOMO on Indonesian domestic tourists. High travel intention may lead to high profits for tourism businesses, but the sustainability of the natural habitat of the natural tourism destinations is no less important. Tourists must also increase their intention to travel responsibly when visiting natural destinations to protect nature. This study employed an empirical quantitative research method with 340 sample data of Indonesian domestic tourists. The analysis of statistical data analysis is provided from PLS-SEM. This research is limited to collectivist behavioral observation of Indonesian domestic tourists to natural tourism destinations. Future studies can be conducted on different cultural dimensions and tourism market segmentation. The analysis showed that the collectivism-based travel culture of Indonesian tourists had positive influences on both travel FOMO and intention to travel responsibly individually, but will bring damage if combined.
Harnessing AI for Next-Generation Financial Fraud Detection: A Data-Driven Revolution
Authors: Ismaeil Mohamed Kamal Aldin
Published: October 2024

Artificial Intelligence in Financial Fraud Detection: A Comprehensive Approach to Enhancing Financial Security
The rise of artificial intelligence (AI) offers an opportunity to significantly strengthen financial security by combating financial fraud, which has become increasingly complex and widespread. Traditional detection methods are often insufficient in identifying and preventing fraudulent activities, prompting a shift towards AI-based solutions. This study explores the application of AI, particularly machine learning algorithms, in improving the accuracy and efficiency of fraud detection. By analyzing large financial datasets, AI can detect anomalies that may indicate fraudulent behavior more effectively than traditional approaches. This research adopts a two-phase methodology. The first phase involves a thorough review of existing financial fraud detection methods, comparing traditional techniques with AI-based models to identify gaps. Various machine learning approaches, including supervised, unsupervised, and deep learning algorithms, are reviewed for their effectiveness in detecting fraud. The second phase involves developing and testing an AI model to identify fraudulent patterns within transactional data. The model uses machine learning algorithms to process vast datasets and detect deviations from typical financial behaviors, flagging potentially fraudulent activities. The expected results indicate that AI systems can outperform traditional fraud detection methods by significantly reducing false positives and improving the detection rate of genuine fraud. This reduction in false positives is vital for financial institutions, as it reduces unnecessary investigations and saves valuable resources. Additionally, enhanced fraud detection protects both institutions and consumers from financial losses.The findings of this study aim to provide financial institutions with practical insights into the implementation of AI-driven fraud detection systems. Furthermore, the research highlights the need for continuous refinement of AI models to adapt to the evolving nature of financial fraud. By leveraging AI technologies, financial institutions can revolutionize their approach to fraud detection, making financial systems more secure and responsive to emerging threats.
Complex Evidence Theory for Multisource Data Fusion
Authors: Xiao Fuyuan , Wen Junhao , Pedrycz Witold , Aritsugi Masayoshi
Published: October 2024

Data fusion is a prevalent technique for assembling imperfect raw data coming from multiple sources to capture reliable and accurate information. Dempster–Shafer evidence theory is one of useful methodologies in the fusion of uncertain multisource information. The existing literature lacks a thorough and comprehensive review of the recent advances of Dempster– Shafer evidence theory for data fusion. Therefore, the state of the art has to be surveyed to gain insight into how Dempster–Shafer evidence theory is beneficial for data fusion and how it evolved over time. In this paper, we first provide a comprehensive review of data fusion methods based on Dempster–Shafer evidence theory and its extensions, collectively referred to as classical evidence theory, from three aspects of uncertainty modeling, fusion, and decision making. Next, we study and explore complex evidence theory for data fusion in both closed world and open world contexts that benefits from the frame of complex plane modelling. We then present classical and complex evidence theory framework-based multisource data fusion algorithms, which are applied to pattern classification to compare and demonstrate their applicabilities. The research results indicate that the complex evidence theory framework can enhance the capabilities of uncertainty modeling and reasoning by generating constructive interference through the fusion of appropriate complex basic belief assignment functions modeled by complex numbers. Through analysis and comparison, we finally propose several challenges and identify open future research directions in evidence theorybased data fusion.
Unlocking the Future of Biotechnology: The Transformative Potential of CRISPR and Emerging Gene-Editing Technologies
Authors: Liv Buse
Published: October 2024

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and gene editing technologies are revolutionising biotechnology with great potential in the fields of healthcare, agriculture and synthetic biology. CRISPR's sensitivity and adaptability allow targeted modifications of DNA, offering the potential to treat genetic disorders such as sickle cell anaemia, cystic fibrosis and muscular dystrophy. In agriculture, it promises to increase crop resilience and reduce dependence on pesticides. Next-generation CRISPR technologies, such as base and master editing, provide even greater specificity by minimising off-target effects and allowing more precise gene modifications. These advances could potentially eliminate inherited diseases by enabling the repair of single nucleotide mutations. The integration of artificial intelligence and machine learning is also expected to enhance personalised medicine by optimising gene editing strategies. Despite these breakthroughs, ethical and regulatory concerns arise, particularly with regard to germline editing and its impact on human genetic development. There are also concerns about ecological risks from genetically modified organisms. A strong ethical framework will be necessary to balance innovation with safety and equity. As CRISPR technology continues to evolve, multidisciplinary collaboration will be critical in addressing these challenges while maximising its benefits.
Materials and Processing Methods for Aerospace Engineering
Authors: Gürsoy Derin
Published: October 2024

Over the years there has been tremendous development in aerospace engineering. The designs, materials, technologies, and everything that are utilized while creating an aircraft have evolved, and they continue to evolve today with the developments in a variety of fields from nanotechnology to material science. Aerospace engineering related to space started in the late 50s, with the start of the “Space Race” between the U.S.S.R. and the USA. In 1957, U.S.S.R. sent the very first spacecraft to Space, Sputnik 1. Following the space race, Yuri Gagarin traveled to space in Vostok 1, establishing himself to be the first person in space. Afterwards, Neil Armstrong traveled to the Moon and there have been a huge amount of journeys to space. The technology evolved according to these journeys, focusing on how to improve and make them more sustainable. The materials, overall structure, and geometry all evolved leading to today’s technological advancements. Nasa and SpaceX are now the leading companies in aerospace engineering. The technology and conditions have over the years improved so much that now Blue Origin is considering civilian space travel.
Advanced AI and Augmented Reality (AR) Integration in Medical and Surgical Practice
Authors: Liv Buse
Published: October 2024

The future of artificial intelligence (AI) in diagnosing rare genetic disorders is poised to transform precision medicine by accelerating the identification of conditions that are often difficult to diagnose. Rare genetic disorders, which affect millions of people worldwide, typically involve complex symptoms and lengthy diagnostic processes. AI's ability to process vast amounts of genomic, phenotypic, and clinical data positions it as a game-changer in this field. By detecting subtle patterns and correlations in large datasets, machine learning algorithms can deliver diagnoses faster and more accurately than traditional methods. AI-powered tools are proving valuable in whole genome and exome sequencing, automating the identification of pathogenic variants linked to rare diseases. By integrating clinical and phenotypic data, these systems can offer personalized insights, reduce diagnostic delays and improve genetic counseling and treatment development. However, the use of AI in rare disease diagnosis poses challenges, such as the need for diverse datasets to train algorithms and concerns over data privacy and equal access. Ensuring that AI tools are validated in diverse populations and effectively integrated into healthcare systems is crucial to their success. This summary will focus on the potential of AI to improve diagnostic accuracy, personalize treatments, and improve the management of rare diseases.
Suplementação de probióticos na modulação intestinal em indivíduos disbióticos com depressão: uma revisão integrativa
Authors: Soares Pereira Lima Rodrigo , S C D Sobreira Lôhara , Carvalho Oliveira Danilo , Campos de Oliveira Adolfo Marcito , de Sousa Sá Odara Maria
Published: October 2024

Introdução: Os probióticos intestinais desempenham um papel importante na comunicação bidirecional entre o intestino e o cérebro. A disbiose intestinal é caracterizada por alterações na atividade e na distribuição da microbiota intestinal, com predomínio de bactérias patogênicas sobre as benéficas. Esse desequilíbrio resulta no aumento da permeabilidade intestinal e na diminuição da seletividade na absorção de toxinas, bactérias, proteínas ou peptídeos, contribuindo para a inflamação local e sistêmica. Embora as interações entre cérebro, intestino e microbioma sejam multifatoriais e ainda não completamente esclarecidas, o sistema vagal atua como um canal de comunicação entre a microbiota e o cérebro. Objetivo: Avaliar estudos recentes sobre a suplementação de probióticos na modulação intestinal em pacientes disbióticos com depressão. Métodos: Foi realizada uma revisão integrativa da literatura, com levantamento bibliográfico efetuado no mês de janeiro de 2020 nas bases de dados eletrônicas Biblioteca Virtual em Saúde (BVS) e PubMed. Após a aplicação dos filtros, foram selecionados 30 artigos, dos quais 25 foram excluídos conforme os critérios de exclusão: leitura de título, resumo e artigo na íntegra. Resultados: Os estudos sugerem que a suplementação de probióticos apresentam impacto positivo na modulação da microbiota intestinal, com resultados promissores para reduzir os sintomas depressivos. Além disso, os psicobióticos, uma classe de probióticos que produz substâncias neuroativas, também mostraram benefícios significativos na modulação do sistema regulador e na resposta ao estresse. Conclusão: A utilização de probióticos em indivíduos disbióticos com depressão parece ser uma estratégia eficaz na redução dos sintomas depressivos. Palavras-chave: Probiótico; microbiota; disbiose e depressão.
Cultivo de frutas e hortaliças em cemitérios: uma inusitada prática observada em municípios do interior baiano
Authors: Santos de Jesus Rosângela , Dantas Soares Micheli , dos Santos Andrade Thaise , Cavalcante Viana Ana Carolina , Queiroz Conserva Vitoriano Anarah Suellen , Pinheiro Helen , da Silva Bandeira Ana Ligia , Ricarte Guedes Maria
Published: October 2024

Objetivo: discutir a prática do plantio de hortaliças e frutíferas no interior e ao redor de cemitérios, correlacionando este aspecto com os possíveis riscos para a saúde da população. Métodos: Foram avaliados 47 cemitérios de 13 municípios do interior da Bahia, através de visitas aos cemitérios observou-se a ocorrência do cultivo de vegetais para alimentação, qual tipo de alimento estava sendo cultivado e a localização dos cultivares em relação aos jazigos, além da identificação de potenciais perigos de contaminação, sendo registrado por meio fotográfico tais situações. Resultados: 29,79% (n=14) apresentavam cultivo de frutas/hortaliças no interior do cemitério, enquanto ao redor ou muito próximo do cemitério foi encontrado o percentual de 72,34% (n=34). As principais frutas e hortaliças cultivadas no interior e ao redor do cemitério foram: manga, caju, banana, coco, mamão, mandioca, laranja, tomate, abóbora, cenoura, beterraba, jiló, repolho, pimentão, milho, limão, goiaba, graviola, quiabo, jaca, fruto do conde, amêndoa, pitanga e mandioca. Alimentos que não pertencem ao grupo alimentar de frutas e hortaliças também foram observados nos cemitérios, como a existência de uma colmeia e de galinhas chocando ovos no interior de sepulturas. Conclusão: há necessidade de monitoramento do solo e lençol freático do cemitério, a fim de evitar/corrigir/minimizar o impacto ambiental decorrente dos sepultamentos de cadáveres. É necessário a realização de ações da gestão municipal para a descontinuidade desta prática, assim como a proposição de ações seguras, duradouras e sustentáveis para o desenvolvimento econômico das pessoas envolvidas nesse processo. Palavras-chave: Cemitérios; alimentação; saúde pública.
Effect of physical activity in children and adolescents with metabolic syndrome: a systematic review
Authors: de Souza Mendes Paula , Gomes Pascoal Andreza , Pessoa de Souza Lainara , Mori Bruno
Published: October 2024

Introduction: evidence demonstrates that regular physical exercise has beneficial effects in the prevention and treatment of high blood pressure, insulin resistance, diabetes, dyslipidemia and obesity in the population. Objective: To evaluate the impact of physical activity on children and adolescents with metabolic syndrome. Methods: Data surveys. Medline (Pubmed), Cochrane Library, LILACS/VHL. Study selection. Cross-sectional studies (2008-2022) that evaluated the ability of physical training to reduce at least one of the following outcomes: HDL-C; triglycerides; HOMA-IR, Fasting Glucose, systolic blood pressure (SBP); diastolic blood pressure (DBP), Body Mass Index (BMI); 2) Intervention (modality, intervention period, weekly session and duration, weekly frequency, intensity, number of sets and repetitions); in children and adolescents classified as having metabolic syndrome. Data extraction and analysis. Two independent reviewers extracted the data and assessed the quality of the included studies. The differences (physical training group minus control group) in the evaluated results were analyzed using (mean values and standard deviation of pre- and post-intervention, and difference between means). Results. Of the 1,961 articles retrieved, 03 studies were included. This review showed that the practice of physical activity, in general, was associated with a reduction in HDL-C levels (before 44.21 mg/dL (± 9.6), after 42.13 mg/dL (± 7. 76), but was associated with reductions in TG levels (before 113.87 mg/dL after 87.53 mg/dL (26.34). AND HOMA (before 2.54 mg/dL after 2.61 mg /dL) Fasting glucose (before 79.86 mg/dL (±9.22) after 82.43 mg/dL (±8.31). Physical activity is associated with reduced HDL-C levels. Conclusion: seems likely that physical training can play an important role in preventing or delaying metabolic syndrome. We emphasize the need for future intervention studies that investigate the effects of physical activity with greater methodological quality. Keywords: Children; adolescent; physical activity; metabolic syndrome.
PHÁT HUY ĐỘNG LỰC DÂN CHỦ TRONG CÁCH MẠNG THEO TƯ TƯỞNG HỒ CHÍ MINH
Authors: TS. NGUYỄN THỊ PHƯƠNG NAM
Published: October 2024

Hồ Chí minh chỉ ra rằng, đổi xã hội cũ thành xã hội mới, giải phóng dân tộc, giải phóng giai cấp và giải phóng con người muốn đi tới thành công ngoài xác định mục tiêu đúng đắn, có chính đảng chân chính lãnh đạo, được sự ủng hộ của nhân dân, thì cần có phương pháp khoa học, cách mạng, phù hợp và đặc biệt Đảng lãnh đạo phải huy động và phát huy được các loại động lực, trong đó có động lực dân chủ. Đó chính là phát huy dân chủ, đảm bảo quyền làm chủ của nhân dân để phát triển sức dân, giải phóng mọi tiềm năng to lớn của nhân dân để thúc đẩy cách mạng đi tới thắng lợi.
Local Tax Optimization Strategy In Jambi City: A Literature Review
Authors: Ervina Nella , Tan Syamsurijal , Junaidi Junaidi , Achmad Erni
Published: October 2024

This scientific paper seeks to evaluate the ability of local taxation as a source of income, the level of tax participation and the efficiency of the tax collection mechanism in Jambi City budget 2018-2022. The analytical methodology used in this research includes descriptive and qualitative approaches. Descriptive analysis incorporates computational methods that are illustrated in the form of numerical data, tabulations, and graphical representations. In the meantime, the qualitative aspects include conducting intense interviews that are analyzed using SWOT. Based on the findings from the analysis of local tax effectiveness covering from 2011 to 2023, it reveals that the efficiency of local taxation shows variability in different years. Based on existing literature and comparisons between studies that have been conducted, tax optimization can be carried out in Jambi City in line with the principle of fiscal decentralization in regional autonomy by enforcing regulations to ensure the creation of sustainable development and economic growth. Some of the things that can be done are increasing tax compliance, digitalization and simplifying the tax structure. This discussion produces input to the Jambi City Government to explore the potential of local revenue, which influences the growth of Regional Own-Source Revenue (PAD). Therefore, optimal development can lead to positive outcomes for the community, such as the economic growth of people in Jambi City and the optimization of tax revenue.
Changes In People's Consumption Patterns In The Digital Era: A Study On The Millennial Generation
Authors: Lesmana Teguh
Published: October 2024

The millennial generation, born between the early 1980s and early 2000s, grew up in the era of digital technology that affects their consumption patterns. This study uses a qualitative approach with case study design, collecting data through in-depth interviews, case studies, and participatory observations, which are analyzed thematically. The results show that millennials prefer online shopping through e-commerce platforms, influenced by social media and influencers, and prioritizing experience over goods ownership. They are also sensitive to social and environmental values in choosing products. The use of mobile apps for transactions and product reviews is very dominant, although challenges related to data privacy and information reliability are major concerns. This research reveals the need for content-based marketing strategies, product and service customization, and increased transparency and data security to build consumer trust. These findings provide in-depth insights into the consumption dynamics of millennials in the digital era, offering guidance for companies to develop more adaptive and innovative strategies in the face of evolving consumption trends.
STAD Cooperative Model with Audio Visual Media Assistance as an Effort to Improve Elementary Madrasah Students' Learning Achievement: A Classroom Action Research
Authors: Listiana
Published: October 2024

This study aims to improve student learning achievement by using the STAD type cooperative learning model assisted by audio-visual media. This study is a classroom action research with four stages, namely planning, action, observation and reflection. The subjects of this study were elementary school students. Data were collected using observation and test techniques. The data obtained were analyzed using descriptive statistical techniques. The results of the study indicate that the STAD type cooperative learning model assisted by audio-visual can improve student learning achievement. Therefore, this audio-visual media-assisted cooperative model can be used as an alternative in overcoming the low learning achievement of elementary school students.
Case Report: Conjunctivitis in Children
Authors: Kaherma Sari  , Thalia Shalsabillah
Published: October 2024

Conjunctivitis is an inflammation of the conjunctiva, the mucous membrane covering the back of the eyelids and the eyeball, which can be acute or chronic. This condition is characterized by conjunctival hyperemia, edema, and discharge. Causes of conjunctivitis include bacteria, chlamydia, allergies, viruses, and systemic diseases. The incidence of conjunctivitis varies by age, sex, and season. Although slightly more common in women in emergency departments, the seasonal pattern of conjunctivitis is consistent across regions. Allergic conjunctivitis, which affects 15-40% of the population, is most common in the spring and summer. Bacterial conjunctivitis is most common from December to April. Acute bacterial conjunctivitis is generally self-limited, with symptoms lasting 1-3 days if treated appropriately, but can last 10-14 days if left untreated. Staphylococcal and gonococcal conjunctivitis can lead to chronic complications or serious problems such as corneal perforation. Viral conjunctivitis usually gets worse in 4-5 days and resolves in 1-2 weeks. Complications are rare but can include corneal problems and life-threatening conditions such as meningitis or sepsis.
Historiography of the study of theatrical and decorative art in the theatrical culture of Transcarpathia in the 20th – first quarter of the 21st century
Authors: Sadovenko Svitlana , Zaitsev Oleg
Published: October 2024

The purpose of the study is to review and systematise the source base of research on theatrical and decorative art, to consider the dynamics of the latter in the theatrical culture of Transcarpathia in the 20th and first quarter of the 21st century. The research methodology is based on the cultural-historical method. The article reveals for the first time the historiography of cultural studies of theatrical and decorative art, summarises, systematises and periodises sources that deepen the understanding of theatrical and decorative art of the theatrical culture of Transcarpathia in the period of the 20th – first quarter of the 21st century in the cultural dimension, outlines the state of scientific development of the topic; reviews publications on theatrical and decorative art, the work of scenography figures and their artistic achievements. The scientific works that study the theatrical culture of the region in the 20th and first quarter of the 21st century are analysed and its influence on the formation of the region’s scenic art is determined. The analysis of the historiography of theatrical and decorative art of the 20th – first quarter of the 21st century shows that the main problems faced by a modern researcher of this topic are the lack of a source base dedicated to the theatrical and decorative art of Transcarpathia of this period and the absence of its periodisation. Modern cultural studies and other researchers studying this issue can only rely on literary publications and other general sources, till april 2024 there is a lack of research on Transcarpathian theater and set design. The results of the study can be used in the preparation of generalised works on the history and theory of culture, the history of theater in Transcarpathia, as well as in the preparation of scientific seminars, lectures, advanced training courses
Lived Experiences of School Heads in School-Based Management (SBM) Implementation
Authors: Sta. Ana Brian Paul
Published: October 2024

This study explored the lived experiences of school heads in SBM implementation using Collaizi’s phenomenological approach with transcribed semi-structured face-to-face interviews among nine participants who were school heads in the Schools Division of Siargao. Selected through the snowball sampling technique, these participants graciously shared their lived experiences, including the challenges and best practices through SBM implementation. This study was anchored on RA 9155: Governance of Basic Education Act of 2001 and DepEd Order No. 1, s. of 2003 (Implementing Rules and Regulations of Republic Act 9155) as supporting legislative works. Moreover, this study was also in line with Pluralism, Social Cognitive, and Functionalism Theories. Six emergent themes were derived from the study: (1) unified support from stakeholders; (2) pressure; (3) community linkages; (4) transparency and responsibility; (5) challenging journey; and (6) development. The emergent themes comprehensively explained an understanding of the participants’ thoughts about SBM, the perceived challenges and opportunities, best practices, and achievements in collaboration with the internal and external stakeholders. To ensure the aim of this study, it was crucial to develop meaningful programs as recommendations for enhancing quality assurance, particularly within the realm of school-based management across the entire division. Moreover, empowerment not only among internal but also external stakeholders must be established, in order to keep empowering communities and foster unity in diversity for the benefit of enhanced SBM implementation in schools.
MARIA MADALENA: TRAÇOS DA FORMAÇÃO DA MENINA QUE SE FEZ PROFESSORA
Authors: Muniz Tamiris Alves , Santos Yara Magalhães dos
Published: October 2024

O presente artigo apresenta resultados de pesquisa sobre história de vida e formação de professores no estado de Goiás, tendo como recorte, a cidade de Goiandira-GO, onde entrevistamos a professora Maria Madalena Barbosa Vigário. A pesquisa buscou compreender os processos de formação da professora escolhida, considerando que esta análise aponta para compreensão de outras trajetórias de professores de Goiás. O método de pesquisa ancora-se nos referenciais da história de vida. A metodologia de história de vida faz parte das abordagens biográficas nas pesquisas qualitativas e permite um acesso ao que é vivido subjetivamente, aos significados e representações que o sujeito constrói, assim como à sua relação com o contexto macrossocial e a forma como a experiência vivida vai sendo revisitada pelo sujeito. Assim, estabelecemos também uma discussão sobre memória e identidade. A pesquisa teve como campo problemático a investigação das relações entre a história de vida da referida professora e sua formação ao longo da vida. Os resultados da pesquisa apontaram que a formação e atuação profissional da referida professora está muito associada aos processos de aprendizagem ao longo da vida, não restritos à formação formal institucionalizada, tais como experiências pessoais e a própria atuação profissional. Formação esta associada ao contexto social e aos significados que nossa entrevistada criou para o seu fazer. Uma construção que ajuda a pensar a formação e atuação docente em seu tempo e espaço, e concorre para a reflexão desta formação e atuação nos dias atuais.