bluuebunny/crossref_metadata_2025 huggingface dataset:
A scoping review and bibliometric analysis (ScoRBA) on dengue infection and machine learning research
Authors: Zahiruddin Haikal , Zukarnain Zuriani Ahmad , Wijaya Adi
Published: February 2025

Dengue, a fast-spreading vector-borne infectious disease, requires early prediction and prompt decision-making for effective control. To address this issue, we present a comprehensive scoping review and bibliometric analysis (ScoRBA) that aims to map the current literature landscape, identify main research themes, and offer valuable insights into advancements and challenges in dengue infection and machine learning research. Materials for this analysis consist of scholarly articles related to dengue and machine learning research retrieved from the Scopus database. Our method involves a rigorous literature examination, utilizing keyword co-occurrence analysis. Our study reveals a growing interest in dengue and machine learning research, reflected in an increasing number of publications. Through keyword co-occurrence analysis, we identify four major research themes: Data mining using machine learning for dengue prediction, Deep learning approach for dengue prediction models, Neural network optimization for dengue diagnostic systems, and Climate-driven dengue prediction with IoT & remote sensing. Advancements include substantial improvements in prediction models through machine learning and IoT integration, albeit with identified limitations, necessitating ongoing research and refinement. Our findings hold direct implications for public health professionals, academics, and decision-makers, offering data-driven strategies for dengue outbreak control. The identified research themes act as a roadmap for future investigations, guiding the development of more robust tools for early prediction and decision-making in the battle against dengue. This study contributes to understanding the evolving landscape of dengue research, facilitating informed actions to mitigate the impact of this infectious disease.
Grade Classification of Agarwood Sapwood Using Deep Learning
Authors: Hatta Heliza Rahmania , Nurdiati Sri , Hermadi Irman , Turjaman Maman
Published: February 2025

The agarwood tree (Aquilaria sp.) is a tree that produces agarwood, which is a black resin that has a distinctive fragrant smell. In Indonesia, one that is commonly traded is sapwood agarwood. Agarwood sapwood is black or brownish-black wood obtained from the parts of the agarwood-producing tree containing a strong aromatic mastic. Based on the Indonesian National Standard (SNI) 7631:2018, agarwood sapwood has three classes: Super Double, Super A, and Super B. However, many agarwood farmers need to learn to differentiate and classify the agarwood sapwood classes, and traders exploit this to buy cheap. So, deep learning can be used to classify the agarwood sapwood class. One of the uses of deep learning is in image processing. Image processing is used to help humans recognize or classify objects quickly and precisely and can process many data simultaneously. One of the deep learning algorithms used in image processing is the Convolutional Neural Network (CNN). In this study, it is proposed that the deep learning model used is CNN with batch normalization. The dataset used is 72 agarwood sapwood images with a white background, each consisting of 24 Super A, 24 Super B data, and 24 Super Double data. The dataset is divided into 80% training and 20% testing data. The evaluation results of the proposed method at 100 epochs show an accuracy of 87.5%. The research implications will help agarwood tree farmers differentiate and classify agarwood sapwood so that farmers get the right price from buyers.
Batik Recognition and Classification Using Transfer Learning and MobileNet Approach
Authors: Sastypratiwi Helen , Muhardi Hafiz , Yulianti Yulianti
Published: February 2025

In the vibrant tapestry of Indonesian culture, Batik motifs stand out as a testament to its enduring artistic heritage. Yet, adapting these intricate patterns, particularly the mesmerizing "insang" featuring fish-like forms, presents a unique challenge for modern applications. Limited datasets and the need for efficient mobile solutions create a bottleneck in accurate motif classification. This research boldly tackles this challenge by proposing a groundbreaking approach: marrying the power of MobileNet architecture, specifically designed for mobile devices, with transfer learning techniques. Transfer learning acts as a bridge, leveraging knowledge from a vast dataset to compensate for limited data specific to Batik. This synergy unlocks remarkable accuracy, with our method achieving a stunning 98% classification rate in under a second on mobile devices. The implications of this breakthrough are far-reaching. It safeguards Batik's legacy by enabling its digital preservation and paves the way for its seamless integration into contemporary design. It is predicted that Batik motifs can adorn digital interfaces, enrich user experiences, and inspire innovative fashion trends. This research is a beacon illuminating the path for Batik to evolve and thrive in the digital age. By empowering mobile devices to recognize and interpret these intricate patterns, it aims to unlock many possibilities. Batik's rich history can be woven into the fabric of modern life, enriching our digital landscapes and fostering a deeper appreciation for this cultural gem. This is not merely a technological feat; it is a celebration of tradition, a bridge between generations, and a testament to the enduring power of creativity.
Metaheuristic Optimization in Dynamic Unit Commitment of Power Systems: Current Trends and Future Prospects
Authors: Widayanti Lilis , Afandi Arif Nur , Herwanto Heru Wahyu , Fitria Vivi Aida
Published: February 2025

This paper discusses various optimization algorithms, a mathematics and computer science method essential to solving challenging real-world problems. The presented real-world scenario centers on a power system with dynamic unit commitment. Power systems involve many variables and constraints that can be changed. Metaheuristic optimization can be an effective method for finding an excellent solution to a problem. Dynamic unit commitment optimization is a critical aspect of power system operation. Dynamic unit commitment discusses determining the operating schedule of generating units and how much their production capacity is at each specific time interval to minimize production costs. This research aims to investigate the current trends and future challenges in applying metaheuristic optimization algorithms to power system problems, using the PRISMA approach to conduct a systematic literature review (SLR). This research starts by formulating research questions: what metaheuristic methods can be employed to tackle dynamic unit commitment challenges in power systems, and how effective are these methods in optimization? We established specific criteria for including and excluding studies, such as choosing articles published in English and concentrating on unit commitment in power systems. Out of the 487 papers discovered from the abstracts, only 14 were chosen for review after an extensive screening process based on complete studies that specifically addressed dynamic unit commitment. The conducted analysis provided insights into the accuracy and efficiency levels attained when using metaheuristic algorithms to solve the dynamic unit commitment problem. The research underscores the pivotal role of metaheuristic optimization in modern energy and power systems, highlighting its significance in tackling diverse challenges associated with enhancing the efficiency and effectiveness of power system utilization. Using metaheuristics in academic research has significantly improved scientific publications, resulting in an average annual increase of 43% in citations. This research's real contribution to the academic field is to provide an alternative reference for approximately 66 ASEAN universities with power system engineering majors.
Identification of Indonesian Traditional Foods Using Machine Learning and Supported by Segmentation Methods
Authors: Rangkuti Abdul Haris , Kerta Johan Muliadi , Mogot Roderik Yohanes , Athala Varyl Hasbi
Published: February 2025

Traditional food is essential in preserving cultural heritage and is a vital part of Indonesian cuisine. In this research, we implement a methodology to identify the traditional Indonesian food using machine learning algorithms supported by various segmentation methods. This research aims to provide an efficient and accurate approach to classifying traditional foods, which can contribute to promoting and preserving Indonesia's culinary heritage. To conduct this research, we conducted experiments on 34 types of conventional Indonesian food originating from various provinces in Indonesia. The analysis of food images involved several segmentation algorithms, including Sobel, Prewitt, Robert, Scharr, and Canny filters. After the segmentation process, we proceeded with feature extraction and classification using traditional machine learning algorithms such as the Random Forest algorithm, Decision Tree, and derivatives of the SVM algorithm. These algorithms aimed to recognize the 34 types of traditional food. After conducting several experiments, we found that Random Forest with Robert's segmentation method was the highest-performance algorithm. It produced extraordinarily accurate results on the test dataset, with an accuracy performance of 85.52%, recall of 84.63%, precision of 83.77%, and an f1 score of 82.49%. Additionally, the best-performing algorithms with execution time averaged less than 1 minute. Another experimental result showed that the Random Forest algorithm with the Canny operator achieved an accuracy of 81.51%, recall of 84.97%, precision of 86.8%, and an f1 score of 85.61% on the test dataset. Furthermore, the Random Forest algorithm with the Sobel operator achieved accuracy results of 78.4%, recall of 65.3%, precision of 62.3%, and an f1 score of 63.71%.  In the SVM algorithms derivative, the Sigmoid SVM combined with the Scharr operator achieved the highest performance in its category across all classification metrics. In conclusion, this research offers valuable insights into classifying traditional Indonesian dishes using traditional machine learning algorithms. Simultaneously, this research aims to promote the appropriate and effective preservation and recognition of traditional Indonesian food.
Involvement of Various Selection Methods for Genetic Algorithms in Determining the Optimal Production Schedule Problem
Authors: Muliono Rizki , Silviana Nukhe Andri , Novita Nanda
Published: February 2025

This research investigates using genetic algorithms (GA) to optimize production scheduling in Medan's shoe industry. The study compares traditional manual and First Come First Serve (FCFS) methods against a GA approach, incorporating selection variations such as Boltzmann, Fitness Uniform Selection Scheme (FUSS), Exponential Rank Selection, and Roulette Wheel Selection. The optimal production order is derived from the chromosome with the highest fitness. Results indicate that GA with FUSS selection significantly reduces production time from 73,630 minutes to 45,650 minutes, achieving a 35% improvement in efficiency. This optimization is attributed to FUSS’s ability to maintain a diverse population, preventing premature convergence and ensuring a broader solution for space exploration. Additionally, it was found that using a smaller population size relative to the number of generations yields better optimization results. The study also demonstrates that while Roulette Wheel Selection shows more variability, it achieves higher optimization over time than FCFS. The practical implications of these findings are substantial for the shoe industry, including faster production cycles, better resource allocation, and an enhanced ability to meet customer demands. These benefits are exemplified by implementing the SISPROMA application, an innovative production scheduling information system that leverages machine learning to optimize scheduling in the manufacturing industry. This study provides valuable insights into applying genetic algorithms for production scheduling, highlighting their potential to enhance operational efficiency and reduce costs. Future research should explore additional optimization techniques and real-world applications to validate and extend these findings, ensuring broader applicability and continuous improvements in manufacturing efficiency.
A Conceptual Framework for Personalized Early Prediction of Asthma Exacerbation Attacks Using Proximal Policy Optimization
Authors: Aliyu Dahiru Adamu , Patah Akhir Emelia Akashah , Osman Nurul Aida , Yahaya Saidu , Adamu Shamsudden , Mamman Hussaini
Published: February 2025

Asthma, a chronic respiratory ailment affecting millions worldwide, presents significant challenges due to the unpredictable nature of exacerbation episodes. Existing methodologies struggle to accurately predict exacerbations individually, particularly across diverse patient demographics. This paper introduces an innovative conceptual framework for the early prediction of asthma exacerbations, leveraging advanced reinforcement learning (RL) techniques, specifically proximal policy optimization, along with patient-specific data and environmental factors. The primary goal is to revolutionize asthma management by providing customized predictions and tailored reward mechanisms that enable proactive interventions and optimize resource allocation. The framework comprises critical components such as patient profiling through a mobile application, trigger identification, a RL-based predictive model, an early warning mechanism, and a personalized reward scheme. Data for patient profiling is gathered through a mobile application, which includes medical history, demographics, symptoms, and triggers. Profiling forms the foundation for the prediction model, enabling it to identify subtle patterns and anticipate exacerbation events more accurately and efficiently. The significant contributions of this research include offering a novel approach by incorporating custom reward functions to enhance learning across heterogeneous patient populations, tailoring interventions to unique triggers and symptom presentations, and addressing challenges associated with patient diversity. By addressing the limitations of existing methodologies and offering a comprehensive solution, this research promises significant improvements in asthma care and healthcare delivery, paving the way for future advancements in personalized medicine and predictive healthcare systems.
Batiknet: Batik Classification-based Management Application for Inexperienced User
Authors: Putra Muhammad Taufik Dwi , Pradana Hilmil , Munawir Munawir , Pradeka Deden , Yuniarti Ana Rahma , Sadik Jafar , Andhika R Muhammad
Published: February 2025

Batik has significantly contributed to the Indonesian economy, is diverse, and is spread throughout cities. Currently, batik patterns are very diverse and spread from Sabang to Merauke. Each batik pattern holds distinct meanings, philosophies of life, and ancestral heritage and reflects the region where it was crafted. We introduce a new batik dataset containing five patterns: Kawung, Megamendung, Parang, Sekarjagad, and Truntum. The Convolutional Neural Network (CNN) method is an effective Deep Learning method for extracting image information. CNNs have become the state of the art for various image processing tasks, such as classification, segmentation, and object recognition. This study used several state-of-the-art architectures, including Xception, ResNet50V2, MobileNetV2, and DenseNet169. However, we chose EfficientNetV2 as the primary feature extractor due to its superior performance. Our results show that EfficientNetV2 outperformed other architectures in training, validation, and testing accuracy, making it the best choice for classifying batik patterns. The training process resulted in an accuracy of 98% for training, 97% for validation, and 96% for testing. To ensure the accessibility and practical application of this research, we developed a user-friendly, web-based interface with a RESTful API, making the tool accessible to a broader audience. The application is named "BatikNet," a name chosen to reflect the blend of traditional batik culture ("Batik") with neural network technology ("Net"). This research contributes a valuable dataset and a practical tool for future studies and applications in batik pattern recognition and supports the preservation and understanding of Indonesian cultural heritage
Harmonizing Emotion and Sound: A Novel Framework for Procedural Sound Generation Based on Emotional Dynamics
Authors: Hariyady Hariyady , Ag Ibrahim Ag Asri , Teo Jason , Md Ajis Ahmad Fuzi , Ahmad Azhana , Md Yassin Fouziah , Salimun Carolyn , Weng Ng Giap
Published: February 2025

The present work proposes a novel framework for emotion-driven procedural sound generation, termed SONEEG. The framework merges emotional recognition with dynamic sound synthesis to enhance user schooling in interactive digital environments. The framework uses physiological and emotional data to generate emotion-adaptive sound, leveraging datasets like DREAMER and EMOPIA. The primary innovation of this framework is the ability to capture emotions dynamically since we can map them onto a circumplex model of valence and arousal for precise classification. The framework adopts a Transformer-based architecture to synthesize associated sound sequences conditioned on the emotional information. In addition, the framework incorporates a procedural audio generation module employing machine learning approaches: granular and wavetable synthesis and physical modeling to generate adaptive and personalized soundscapes. A user study with 64 subjects evaluated the framework through subjective ratings of sound quality and emotional fidelity. Analysis revealed differences among samples in sound quality, with some samples getting consistently high scores and some getting mixed reviews. While the emotion recognition model reached 70.3% overall accuracy, it performed better at distinguishing between high-arousal emotions but struggled to distinguish between emotions of similar arousal. This framework can be utilized in different fields such as healthcare, education, entertainment, and marketing; real-time emotion recognition can be applied to deliver personalized adaptive experiences. This step includes acquiring multimodal emotion recognition in the future and utilizing physiological data to understand people's emotions better.
Building Historical Narratives: The Development of Virtual Reality Learning Media for Exploring Historical Sources Bung Hatta's Birthplace
Authors: Ofianto Ofianto , Ningsih Tri Zahra , Mulyani Fini Fajri , Putri Suci Kurnia
Published: February 2025

The shortcomings in the history of education, constrained by conventional teaching approaches, inadequate utilization of historical sites, and logistical hurdles, diminish student engagement and comprehension. This study aims to develop a virtual reality (VR) learning medium around Bung Hatta's birth house, aiming to enhance students' historical understanding through captivating and immersive experiences. We adapted the Borg and Gall development model into four phases: preliminary study, strategic planning, development, and validation. We utilized 360-degree pictures in conjunction with extensive historical data regarding Bung Hatta's birthplace, integrating these elements into an immersive virtual reality environment. We used expert validation to guarantee material accuracy, subsequently doing practical testing with history educators and students to evaluate usability and overall effectiveness. The findings revealed a practicality score of 87%, highlighting the substantial influence of VR media on enhancing student motivation and understanding of historical material. This technology facilitates the virtual investigation of significant historical locations, effectively surmounting geographical and financial barriers and enhancing accessibility, engagement, and the relevance of history for learners. This method enhances critical thinking and deepens appreciation of national heritage while offering a strong framework for incorporating VR into educational curricula. Further research must examine the long-term impacts of VR on various learning outcomes and its relevance across the educational curriculum. Moreover, integrating VR technology in diverse historical disciplines may augment its effectiveness and applicability in education. Virtual reality techniques improve students' understanding of history while strengthening 21st-century skills such as critical thinking and creativity
Implementation of Virtual Reality Moot Court for Simulation and Procedural Law Learning of the Constitutional Court
Authors: Hidayah Nur Putri , Wicaksono Galih Wasis , Perdana Muhammad Ilham , Faiz Ahmad , Cholidah -
Published: February 2025

The limited space for moot court simulations in law learning is one of the main obstacles. In the Constitutional Court's judicial practice, no faculty has a Moot courtroom identical to the actual courtroom. Every law student must be able to practice trial to improve their argumentation, advocacy, legal reasoning, and other problem-solving skills. This research aims to build and develop a Virtual Reality (VR) Moot Court that can be used as a Moot Court in the trial of the Constitutional Court. VR Moot Court is a means of practicum in the constitutional procedure law course. This research was carried out through scenario preparation and system design stages, followed by 3D asset optimization, user interaction design, multi-user design, and testing. This research utilizes Unity to build 3D assets and Spatial.io as a VR platform. For more immersive use, users can use VR headsets such as Oculus. However, VR Moot Court can also be accessed via smartphone or PC for broader use. The development of VR Moot Court is quite complex, requiring the optimization of assets used across various devices. This study optimizes poly, texture, material, and lighting. The results of VR Moot Court development in this study tested the system's functionality and measured the optimization results. The results of system optimization tests have shown a decrease in GPU and CPU usage. Meanwhile, the results of the functionality and user satisfaction tests also show that VR Moot Court, in addition to taking course learning outcomes in the constitutional court's procedural law course, this system is also relevant to the actual Constitutional Court courtroom. This research in the future requires the development of a type of moot courtroom for other kinds of courts.
Application of Artificial Intelligence in Detecting SQL Injection Attacks
Authors: Augustine Nwabudike , Md. Sultan Abu Bakar , Osman Mohd Hafeez , Sharif Khaironi Yatim
Published: February 2025

SQL injection attacks rank among the most significant threats to data security. While AI and machine learning have advanced considerably, their application in cybersecurity remains relatively undeveloped. This work mainly aims to solve the IT-related challenge of insufficient knowledge bases and tools for security practitioners to monitor and mitigate SQL Injection attacks with AI/ML techniques. The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored; these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions; specific algorithms have demonstrated success rates of up to 80% in detecting SQL injections. Despite this promising performance, around 75% of survey participants acknowledged a decrease in harmful content, with a similar number highlighting increased efficiency in their roles as security researchers or incident responders. Nevertheless, the tool’s adoption among cybersecurity professionals remains under 30%. This underscores a gap between the capabilities these technologies offer and their current level of adoption among professionals. This will help lay the groundwork for future work in identifying the best solutions and providing potential approaches to incorporating AI/ML into cybersecurity frameworks. The implications of this study indicate that adopting robust defenses against SQL injection and other cyber threats could increase many folds if we continue to research and implement AI ML. technologies.
A Systematic Literature Review on Characteristics Influencing Software Reliability
Authors: Subramanium Lehka , Hassan Saadah , Osman Mohd. Hafeez , Zulzalil Hazura
Published: February 2025

Reliability, as a non-functional requirement, is a crucial aspect that refers to the system's ability to perform its intended functions consistently and without failure over an extended period. It is essential in designing and implementing software systems, as it affects software quality. Maintaining software reliability is a significant challenge, as it is directly impacted by factors such as the complexity of the software design, the amount of code, and the measures taken to secure the system from unauthorized use. There are significant growing appeals for predicting reliability to account for risks. Research on reliability risk assessment has a long tradition; unfortunately, comprehensible reliability characteristics are still vague when determining potential risks. Clearly defining, prioritizing, and addressing reliability characteristics is essential for delivering reliable, high-quality software that meets user needs and business goals. The ignorance and lack of comprehensive reliability characteristics have evolved into inaccurate risk assessment, triggering malfunctions in the operational environment. Comprehensive characteristics are key elements to predict and estimate software reliability. The reliability characteristics could determine the precise objective of reliability efforts. This systematic literature review aims to identify the key characteristics influencing software reliability, the potential risks associated with these characteristics, and the metrics used to measure and assess them. Thirty-one research articles related to research questions have been reviewed. The findings indicate that comprehensive reliability characteristics could identify, classify, and prioritize potential risks, improving current metrics. It can be concluded that the accurate potential reliability risk can demonstrate the consequence of failure.
Impact of Teachers’ Critical Thinking Skills on Students’ Academic Performance: Basis for an Upskilling Program
Authors:   Emilio Aguinaldo College, Jing Lu
Published: February 2025

This study investigates the impact of physical education (PE) instructors’ critical thinking skills on students’ learning in a business college in Wuhan, China. The research examined critical thinking across three dimensions: evaluating information, creative thinking, and problem-solving. Utilizing a descriptive design, data were collected through a validated questionnaire distributed to student respondents. The findings revealed that PE instructors demonstrate a high level of critical thinking. Key indicators, such as identifying new information, and applying PE skills to solve real-world problems, highlighted the instructors’ capabilities. However, challenges were noted in distinguishing factual information from inferences and exploring alternative data interpretations. The study emphasizes the need for targeted upskilling program to further enhance the PE instructors’ critical thinking skills, fostering improved educational outcomes and aligning with contemporary pedagogical demands. The results contribute to the broader discourse on integrating critical thinking into educational practices in China.
Hypercoagubility: An Updated Overview for Healthcare Providers
Authors: Jaafari Abdullah Siddiq Ahmed , Alajmi Khaled Hadi Ali , Althabaity Ahmed Misfer , Salem Khalid Shayim Alsharari , Alhargan Mohammed Saleh , Alotaibi Hissah Faihan Ayad , Almutairi Najla Alhumaidi , Alanazi Samar Mnwer , Almutairi Fayez Nukhaylan , Alazmi Abdullah Hamdan Khidhr , Alotaibi Mamdoh Abdullah
Published: February 2025

Background: Hypercoagulability, or thrombophilia, is a pathological state characterized by an increased tendency for blood clot formation, leading to conditions such as venous thromboembolism (VTE), arterial thrombosis, and thromboembolism. This condition arises from a disruption in the balance between pro-coagulant and anticoagulant factors, influenced by both inherited and acquired risk factors. The understanding of hypercoagulability has evolved significantly since the early 20th century, with key discoveries such as antiphospholipid syndrome, factor V Leiden mutation, and deficiencies in proteins C and S contributing to improved diagnosis and management. Aim: This article aims to provide healthcare providers with an updated overview of hypercoagulability, including its etiology, epidemiology, pathophysiology, diagnostic approaches, and management strategies, to enhance the prevention and treatment of thrombotic disorders. Methods: The review synthesizes current literature on hypercoagulability, focusing on the interplay between genetic and environmental factors, the role of Virchow’s triad in thrombosis, and the clinical significance of various thrombophilic disorders. Diagnostic tools, risk assessment models, and treatment options, including anticoagulation therapy, are discussed in detail. Results: Hypercoagulability disorders are influenced by both inherited mutations (e.g., factor V Leiden, prothrombin G20210A) and acquired conditions (e.g., malignancy, inflammation, pregnancy). Thrombosis risk is further modulated by factors such as age, lifestyle, and comorbidities. Diagnostic approaches include thrombophilia screening and risk stratification tools, while management involves anticoagulation therapy tailored to individual patient risk profiles. Conclusion: Hypercoagulability is a multifactorial condition requiring a comprehensive understanding of its underlying causes and risk factors. Early diagnosis, risk stratification, and personalized treatment are essential to reduce morbidity and mortality associated with thrombotic disorders. Future research should focus on novel therapies and improved risk prediction models
Synthesis on the Impact of Land Cover Conversion towards Water Quantity and Quality
Authors: Sudjatmiko Henny , Bisri Muhammad , Limantara Lily Montarcih , Roebijoso Jack
Published: February 2025

This research intends to establish a policy on watershed management based on the land use recommendation and an analysis of land cover conversion to per-urban location towards water quality and discharge which many sub-watersheds in Indonesia are in critical condition due to the frequent event of flooding, drought, and landslide. It is further worsened by the changes of land cover in the watershed that causes to increase in surface runoff which also affects the water quality in the watershed. Watershed condition can be restored by management if the correct implementation and regulation is effective. Out of 458 watersheds in Indonesia, 60 of them were very critical, 222 were critical, and the remaining 176 were in endangered condition. One of the critical watersheds is Ciliwung watershed. Furthermore, public participation is a key in managing watershed. The methodology consists of collecting the primary data as a benchmark for simulation by using SWAT; the regression model is used for covering the water quality while the water discharge analysis is performed through hydrological simulation. Then socio-economic survey is conducted to evaluate public willingness and capacity to participate in the watershed management. The result of simulation shows that sediment and nitrate is positively affected by water discharge while phosphate is negatively affected by it. The conversion of forest into agriculture significantly increases the nitrate and sediment production in while phosphate is not really affected. Meanwhile, in the watershed overall, surface runoff, nitrate, and phosphate are increasing drastically. The result of survey shows that most people that are living in the watershed do not have the funding or yard to participate in the watershed management. This result is a recommendation which reduces the agriculture land use by 10% and allocating it for water management.
APPLICATION OF LOCAL IDENTITY TO DEVELOP PACKAGING FOR MARKETING COMPETITION FOR COMMUNITY PRODUCTS: A CASE STUDY OF BAN CHIANG KHROM RICE COMMUNITY ENTERPRISE PRODUCTS
Authors: Yoowattana Pattaravis
Published: February 2025

This article aims to provide guidelines for using marketing principles to integrate with knowledge of art and design to create strategies for commercial benefits for community enterprise products. In this article, we will present Ban Chiang Krom rice products. Udon Thani Province This is a product that was originally not unique and different from other community enterprise products. But later on, there was a research study to use graphic arts principles for design combined with modeling for marketing strategies to develop such products to be different. Create uniqueness by applying local identity and marketing by focusing on the appearance of packaging that is unique to the region. The study found that the importance of “Novelty” will lead to positive consumer attitudes and purchasing behavior. This knowledge may be applied to other community enterprise products.
THE INFLUENCE OF DIGITAL SOCIAL MEDIA AFFECTING TO PURCHASE ONLINE MERCHANDISE VIA ELECTRONIC COMMERCE
Authors: Kaewkhuntee Boonthai , Tunvaravuttichai Supakorn
Published: February 2025

It is required for the business sector to study the Influence of Digital Social Media affecting. The decision to purchase online merchandise via electronic commerce, consisting of digital marketing factors and advertising media for respond to the consumer needs and develop sales channels to be affective for business success. The purpose of this research was to explore 1) opinion levels on digital marketing factors and advertising media and 2) influence of digital social media affecting decision to purchase online merchandise through the electronic commerce marketplace. The research was a qualitative study undertaken through the sampling group consisting of 400 internet users reserving and making their orders the merchandise via online system in 2022. The convenience sampling and data collection of the target group were carried out through online questionnaires placed on the Google form website in the social network whereas the content analysis was applied for data analysis. The results of the research found that 1) the majority of the samples were 211 males at the age of 31 – 40 years with single status, bachelor’s degrees education, state-enterprises/government officials occupation who gain a monthly income over 25001 Baht 2) In the view of digital social media the results represented that the overall opinion at the highest level and 3) Considering the purchase decision it was found that the overall opinions were at the highest levels, respectively the results of this research can be further utilized for development of digital social media strategies to be in accordance with current purchase behavior of companies and applied for marketing planning and selecting of marketing tools in order to be in line with the target and also increasing competitiveness in due course.
Investigating the Relationship of Financial Hardships with Postpartum Depression in Maternal Health of Pakistani Women: A Cross-Cultural Study
Authors: Afridi Hajra Sajjad , Bint-E-Zahid Hira , Solehria Tabassum Faiz
Published: February 2025

The aim of this study is to investigate the impact of financial hardships on postpartum depression among Pakistani women. In Pakistan, many women face postpartum depression during and after their pregnancies once or twice but receive very little care in hospitals and homes, which is alarming. Many women are not financially stable, and that's why they don't go for postpartum therapy. In fact, many women face financial hardships during pregnancies, and this issue leads to postpartum depression as well. This was a quantitative, descriptive, correlational research design. For this study, more than 150 females were requested to fill out the questionnaires via online and face-to-face meetings and finally received 103 (from Peshawar, Islamabad, and Lahore) complete responses, so the retrieving rate was 68.7%. The results of the current study stated that the relationship between financial hardships and postpartum depression in maternal health is positive and significant. This study is of great theoretical significance from the Pakistani perspective and of practical significance because it will help medical health practitioners design policies to reduce the financial hardships for women to improve their health during maternity.
Uwagi wstępne
Authors: Dobroński Adam
Published: February 2025

Z zadowoleniem przyjąłem propozycję zredagowania ostrołęckiego „Zeszytu Naukowego", poświęconego tym razem dziejom regionu w latach 1918-1939. To miły obowiązek dla członka Ostrołęckiego Towarzystwa Naukowego, rodaka z Ostrowi Mazowieckiej. Nie owe sentymenty są w tym przypadku jednak najważniejsze, lecz pilna potrzeba rozwinięcia badań historycznych i popularyzacji ich wyników. Temu celowi służą również konferencje organizowane przez OTN, we współpracy z innymi instytucjami i placówkami Ostrołęckiego. Odbyliśmy takowe w 70 rocznicę odzyskania niepodległości przez II Rzeczpospolitą oraz w 50 rocznicę wybuchu II wojny światowej. I właśnie materiał z obu spotkań naukowych, przerobiony i uzupełniony, stanowi podstawę tego tomiku. Wierzę, że okaże się bardzo przydatny, między innymi w pracy z młodzieżą szkolną. Czekamy na opinie, by uwagi wykorzystać przy tworzeniu następnych historycznych pozycji OTN.
 
Skan artykułu udostępniony z zasobów prowadzonego przez Muzeum Historii Polski repozytorium BazHum.
Odzyskani niepodległości przez Polskę w 1918 roku w świadomości ostrołęckich maturzystów
Authors: Pajka Stanisław
Published: February 2025

Od pamiętnego 1918 roku minęło 70 lat. W ciągu tego czasu różnie interpretowano okoliczności i przyczyny odzyskania przez Polskę niepodległości. Jak jawi się ten fakt z tej odległej perspektywy w świadomości maturzystów? Próba odpowiedzi na to właśnie pytanie stanowiła główny cel podjętego badania i jednocześnie wyznaczała jego problematykę. Choć podjęte badania miały na celu ukazanie także elementów orientacji w zakresie interesującej nas problematyki, to główną uwagę skupiono na świadomości. Terminem tym określam przekonania, idee, wizje, postawy psychiczne maturzystów 1 dotyczące tego historycznego wydarzenia. Rozpatrywano je nie tylko z punktu widzenia zgodności lub braku zgodności z wiedzą historyczną, ile z punktu widzenia źródła kształtowania tych przekonań (szkoła, rodzina) oraz ich ideowotwórczego oddziaływania na świadomość historyczną.
 
Skan artykułu udostępniony z zasobów prowadzonego przez Muzeum Historii Polski repozytorium BazHum.
Wojna obronna Polski w 1939 roku w świadomości uczniów (wyniki sondażu)
Authors: Pajka Stanisław
Published: February 2025

W poniższych rozważaniach chcemy ukazać, mówiąc najogólniej, jak widzi pewne aspekty wojny obronnej młodzież szkolna. W badaniach tych, opartych na ankiecie anonimowej, chodziło o rozpoznanie kilku — moim zdaniem — ważniejszych kwestii, a mianowicie:
— znajomość największych bitew Września
— samoocena uczniów co do stopnia orientacji na temat wojny obronnej Polski w 1939 roku,
— źródła orientacji na temat tej wojny,
— pogląd na możliwość wygrania tej wojny,
— obraz Niemców w świadomości uczniów,
— państwa najbardziej zagrażające pokojowi światowemu w ocenie młodzieży,
— postawy wobec zachowań ludności cywilnej i żołnierzy w czasie wojny obronnej 1939 roku.
Klon – kartka z historii. Walka o polską szkołę w gminie Rozogi w okresie międzywojennym
Authors: Nowotka Marek
Published: February 2025

Gmina Rozogi, leżąca w północnej części województwa ostrołęckiego obejmuje w zdecydowanej większości tereny mazurskie, które wróciły do Polski dopiero w 1945 r. Jednak i w okresie „rozłąki" z ziemiami ojczystymi znane są liczne wzajemne kontakty tych ziem. Wystarczy wymienić poparcie ludności mazurskiej dla powstania styczniowego i to w różnej formie — od dostaw broni i żywności po ukrywanie powstańców i udział w „partiach" czyli oddziałach powstańczych. Ale jest również inny fragment historii, w którym ludność tych terenów potwierdziła swoją polskość. Jest to okres walki o język polski, o polską szkołę w okresie międzywojennym.
Disseminated neuroinfection caused by Rhinocladiella mackenziei in a patient with Systemic Lupus Erythematosus: Case report and review of literature
Authors:   Khoula Hospital, Medical Microbiology Department, Muscat Oman, Al-Kindi Nawal , Al Wahsh Humaid A. ,   Royal Hospital, Rheumatology, Department of Medicine, Muscat, Oman, Kallow Zainab ,   Royal Hospital, Rheumatology, Department of Medicine, Muscat, Oman, Al-Hajri Alia ,   Royal Hospital, Radiology Department, Muscat, Oman, Al-Busaidi Ibrahim , Khamis Faryal ,   Royal Hospital, Adult Infectious Diseases, Department of Medicine, Muscat, Oman, Al-Jahdhami Habib. , van der Lee Hein ,   Center of Expertise for Mycology, Radboud University Medical Center/Canisius Wilhelmina Hospital, Nijmegen, The Netherlands, Delma Fatima Zohra , Al-Housni Saif ,   Natural & Medical Sciences Research Centre, University of Nizwa, Nizwa, Oman, Nasser Al-Saqri Suad ,   Natural & Medical Sciences Research Centre, University of Nizwa, Nizwa, Oman, de Hoog G. Sybren , Al-Rawahi Ahmed ,   Natural & Medical Sciences Research Centre, University of Nizwa, Nizwa, Oman, Al-Harrasi Ahmed , Al-Hatmi Abdullah M.S.
Published: February 2025

Rhinocladiella mackenziei is a dematiaceous fungus that has been reported as the cause of fatal cases of brain abscess exclusively in the Middle East. Although it is rare, the mortality rate in both immunocompetent and immunocompromised individuals is 100%. We report a case of R. mackenziei brain abscess in a young immunocompromised patient. Despite receiving a combined antifungal therapy that included the newer triazole isavuconazole intravenously, as well as liposomal amphotericin B, voriconazole, and terbinafine the patient died. We examine the literature on the relationship between SLE in immunocompetent patients and brain infections caused by R. mackenziei. According to available information, SLE and other autoimmune illnesses may increase the risk of developing a fungal infection
Women taking the lead: Inspiring female philanthropy in annual giving
Authors: Morden Hilary
Published: February 2025

This paper focuses on inspired leadership from women philanthropists in an Annual Giving context by covering a case study on a volunteer-led fundraising initiative that raised CAD$130,000 in 12 months from female donors. It shows how McGill University supported the volunteers and highlights the roles of the Annual Giving, Alumni Engagement, Communications and Major Giving teams. This paper also covers some important lessons learnt and explores how such initiatives have been successful in other Advancement teams of all sizes.
From campus to community: Amplifying alumni pride and engagement through the University of Sydney’s Alumni Festival
Authors: May Kate , Herbert Anna , Bellingham Scott
Published: February 2025

The University of Sydney’s Alumni Festival represents a transformative approach to their alumni engagement, driven by a strategic vision to reignite alumni pride and foster deeper connections. Spearheaded by a dedicated team of advancement professionals, the festival was conceived in response to challenges such as a significant number of ‘lost alumni’ and disengagement among the 30–49 age group. The festival aimed to create a vibrant, inclusive event that resonated with diverse alumni demographics. Key strategies included leveraging Sydney’s cultural affinity for festivals, securing broad institutional support and designing unique, interactive experiences. The festival featured exclusive tours, family-friendly activities and nostalgic events, all tailored to re-engage alumni. A comprehensive marketing campaign, emphasising inclusivity and leveraging internal partnerships, successfully raised awareness and drove participation. The inaugural festival exceeded expectations, achieving high registration numbers, reconnecting with lost alumni and fostering a renewed sense of community. Post-event surveys indicated strong alumni satisfaction and a desire for future participation. This paper analyses how festival’s success underscores the importance of innovative, data-driven approaches to alumni engagement and sets a new standard for future initiatives.
From uprising to uplifting: When volunteer leadership has gone astray
Authors: Ditchcreek Julie , Maenza Amanda , Warner Kristin
Published: February 2025

Volunteers are the lifeblood of many higher education institutions, whose limited staff and financial resources could use additional support to meet institutional needs. However, when volunteers stray from their original intentions, drastic changes need to be made to keep them from ultimately hurting an institution. This paper outlines a six-step pathway to turn volunteer uprising into an uplifting, meaningful and valuable experience for staff and volunteers. The process involves identifying overarching problems, deciding on the purpose of a volunteer group, having tough conversations with internal and external constituents, preparing proper documentation for future groups, launching the new group, and honing the power of your successful volunteers. Once completed and properly maintained, volunteer groups can be a resource to the staff and institution in furthering the engagement and philanthropy of the alumni community. Throughout the journey, staff members must avoid taking volunteers’ anger and frustration personally but always remember to do what is in the institution’s best interest, even if that means parting ways with certain volunteers. Ultimately, volunteers should be a help, not a hindrance.
Translating the Public Sphere: Analyzing Linguistic and Cultural Dimensions in Publicistic Texts
Authors: Babazade Ayshan
Published: February 2025

This study explores the challenges and strategies involved in translating publicistic texts, which are characterized by their rich use of figurative language, complex syntactic structures, and culturally specific references. Publicistic texts play a critical role in shaping public discourse by conveying ideological and social narratives; however, their translation requires more than a literal rendering. Drawing on theories of figurative language (Glucksberg & McGlone, 2001) and intercultural communication (Iriye, 1979; Kulikova et al., 2017), the research examines how translators navigate linguistic complexities—such as idiomatic expressions and non-standard syntactic forms—while also adapting culturally embedded elements for target audiences. Employing a qualitative methodology that integrates comparative discourse and content analyses of selected texts and their translations, the study identifies common translation strategies, including domestication and the use of explanatory notes, as well as the inherent tensions between fidelity to the source and cultural adaptation. The findings underscore the translator’s role as an active mediator who shapes the final text, influencing its ideological and cultural impact. This research contributes to translation studies by offering insights into the effective handling of linguistic and cultural nuances in the public sphere, with implications for both academic practice and professional training.