bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Loyalty through E-Service Quality and Brand Experience: The Role of Customer Satisfaction in Nike’s Indonesian Market
Authors: Havana
Published: February 2025

The rapid expansion of digital commerce has significantly elevated part of electronic service quality (e-service quality) and brand experience in influencing competitive strategies, especially for global brands like Nike. As a dominant force in the sportswear industry, Nike has continually adapted to meet its customers' evolving needs, not only by offering innovative products but also by delivering high-quality digital experiences. This study specifically examines Nike’s Indonesian market, exploring the effects of e-service quality and brand experience on brand loyalty, with customer satisfaction acting as a mediating variable. There was utilization of a quantitative research design and information was gathered through Google Forms using purposive non-probability sampling, resulting in a total of 207 respondents. The information was examined using Structured Equation Modelling-Partial Least Square (PLS-SEM) to investigate the connections between the variables. The outcomes show that e-service quality has a substantial beneficial result for both customer satisfaction and brand loyalty, indicating that a strong digital service environment is essential to fostering loyalty. Additionally, brand experience constructive effects customer satisfaction, though it doesn't directly impact brand loyalty. Customer satisfaction was found to mediate the relationship between e-service quality and brand loyalty, underscoring its crucial role in maintaining customer loyalty. However, the data did not support customer satisfaction as a mediator between brand experience and brand loyalty. These results offer valuable insights for global brands like Nike, highlighting the direct influence of e-service quality on brand loyalty. This underscores the importance of prioritizing customer satisfaction and enhancing the overall digital service experience to remain competitive in the market.
Exploring Teaching Methodologies and Business Management Education's Impact on Entrepreneurial Success
Authors: Mary Chris A. Austria
Published: February 2025

This study examines the impact of teaching methodologies in Business Management Education on the entrepreneurial success of 2023 alumni from Nueva Ecija University of Science and Technology. Using a descriptive research design and a 4-point Likert scale questionnaire, it analyzes alumni perceptions of instructional approaches and their influence on entrepreneurial skills, curriculum content, and support services. The findings emphasize the importance of experiential learning and practical skill application, suggesting enhancements in resilience training, resource access, and post-graduation support. This research provides actionable insights for educators and policymakers to optimize business management education for entrepreneurial success.
Empowering Startups through Accelerator Services in Lebanon: A Phenomenological Case Study
Authors: Manal Hamzah
Published: February 2025

This study explores the landscape of accelerator programs in Lebanon, a country plagued by severe political instability and economic issues. The research uses a qualitative methodology and is based on semi-structured interviews with 13 Lebanese entrepreneurs who launched firms between 2016 and 2019 and took part in accelerator programs. The interviews examine various aspects of accelerator programs, with a focus on the spectrum of services provided to startups and entrepreneurs, challenges, and the advantages gained from participation in accelerators. Key insights are revealed through the study including the importance of accelerator programs, the role they play in aiding startups, as well as the particular improvements or services that accelerators in Lebanon might provide to solve the unique challenges faced by entrepreneurs. The findings demonstrate that, despite accelerator programs being frequently seen as beneficial, there are distinct requirements and challenges that Lebanese entrepreneurs confront that may be better handled.
A Crypto-Spatial Framework for Landslide Susceptibility Assessment and Decision-Making
Authors: Djarot Hindarto
Published: February 2025

Areas where it rains a lot and the ground is unstable, landslides are quite dangerous for people as well as for buildings. Since they are not very accurate or clear, the conventional methods of determining the probability of a place sliding can slow down the decision-making process. Our response to these problems is a crypto-spatial framework based on blockchain technology meant to provide more accurate landslide risk assessments. Blockchain technology cannot be altered and is distributed rather widely. Together with geospatial data analysis, it has produced a fair and dependable approach to data exchange. Blockchain-based verification systems and geospatial analysis of environmental elements, including landforms and rainfall patterns, allowed one to confirm the accuracy of the evaluation data. Often, in areas prone to landslides, field tests ensure that the system operates as it should and consistently. More sensitivity produced more accurate estimations and improved collaboration amongst stakeholders. The present work addresses geospatial data analysis and blockchain technologies meant to reduce disaster risk. This approach increases the safety and efficiency of landslide-prone areas, so enhancing the data dependability and decision-making capacity.
A Natural Language Processing Model for Early Detection of Suicidal Ideation in Textual Data
Authors: Jocelyn M. Beriña
Published: February 2025

According to the World Health Organization, suicide is one of the top 10 causes of death. An estimated 138 people's lives are significantly impacted for every suicide death, and practically every other statistic pertaining to suicide fatalities is concerning. The widespread usage of social media and the almost universal mobile devices used to access social media networks present new opportunities for preventative intervention as well as new forms of data for studying the behavior of those who (attempt to) take their own life. We show that it is feasible to identify suicidal risk individuals using social media data. Specifically, we propose concepts for an automated system for detecting measurable signals around suicide attempts using natural language processing and machine learning (particularly deep learning) approaches. The goal of this project is to improve the automatic identification and reporting of suicidal posts. It offers a method that examines Twitter as a social media platform to find warning indicators for suicide in people. The previously mentioned approach's main goal is to automatically detect anomalous changes in a user's online behavior. The comprehension and identification of intricate factors of risk or warning indicators that might precede the incident provide difficulties in the prevention of suicide. Many natural language processing (NLP) approaches are used to measure textual variations and pass them via a unique framework that may be utilized broadly to accomplish this objective. Deep learning and machine learning-based categorization algorithms are used to identify suicidal thoughts in the early stages by analyzing tweets on social networking platform Twitter. We first performed data pre-processing for both classifiers, followed by feature extraction, and then machine learning and deep learning classifiers, respectively. We use a CNN-LSTM model for this purpose to assess and contrast it with other classification methods. In comparison to earlier CNN-LSTM systems, the study demonstrates that the CNN-LSTM framework using embedding of words techniques achieves 94% classification accuracy.
The Effectiveness of Implementing the Digitization Program for Integrated Procurement of Goods and Services to Achieve Procurement Goals and Targets at PT PLN (Persero)
Authors: Mario Hadi Kusuma. ST.
Published: February 2025

As one of the largest companies in Indonesia, PT PLN (Persero) has succeeded in entering the list of the top 10 largest companies in Southeast Asia according to the Fortune Southeast Asia 500 version in 2024, because it has successfully carried out business transformation and classy performance. PT PLN (Persero) has mapped all future business potential and carried out digital transformation through the development of revolutionary new technology. PT. PLN (Persero) has transformed IT system transformation, implementing smart technology and integrating the Internet of Things, Artificial Intelligence, Machine Learning and Big Data for operational efficiency and service improvement. -One of the Innovation initiatives of PT. PLN (Persero) in digitizing the procurement of goods and services is Smart Supply Chain and procurement such as e-procurement applications, e-catalog, e-DPT, e-marketplace, and vendor management system. The information systems and applications developed in the digitization of procurement have implemented regulations that have been updated based on Director's Regulation No. 0018.P/DIR/2023 dated 07 July 2023 concerning Strategic Policy for Procurement of Goods/Services for PT PLN (Persero). This article will analyze the effectiveness of the Implementation of Digitization of Procurement of Goods and Services at PT PLN (Persero) based on the latest board of directors' regulations to achieve targets for procurement of goods and services, namely appropriate quality, quantity, location, time, socioeconomic objectives and costs using the service availability variable, fulfillment, efficiency, and security. The method used in this research is a quantitative method with a purposive sampling survey approach with the criteria that the respondent is a user of the digital procurement system at PT PLN (Persero). Based on the results of questionnaire test analysis, observations, and other supporting data, it can be concluded that the  Implementing the Digitization Program for Integrated Procurement of Goods and Services to Achieve Procurement Goals and Targets at PT PLN (Persero) based on Directors' Regulation No.0018.P/DIR/2023 of this research are very effective because they fulfill all the criteria and variables tested.
A System Dynamics Model to Optimize Purified Water Supply from the Dam for Residences Use in Rural Communities
Authors: Lucas Khashane
Published: February 2025

The effective management of water supply is important to ensure sustainable health and wellbeing of residents in communities. This paper presents a system dynamics model to optimize the delivery of clean water from dams to communities more especially in rural areas. The developed model includes elements such as water inflow, purification processes, storage capacities, distribution channels as well as consumption patterns. The dynamics of water supply is influenced by various   factors such as seasonal fluctuations or variations, maintenance schedules, as well as population growth. The developed model employs feedback loops to simulate the interactions between these components and identify potential inefficiencies in the system. This study aims to suggest and develop strategies to enhance the reliability and efficiency of water supply to the targeted areas. Different scenarios are analysed to evaluate the impact of management and administrative practices, such as adjusting purification capacity, optimizing storage levels, as well as improving distribution methods. The objective of the study is to provide insights for policy makers and stakeholders to ensure sustainable and equitable water supply for rural communities. The results of the study demonstrate that system dynamics modelling can effectively identify key areas of improvement in the water supply chain and better service delivery. This approach presents a comprehensive framework for addressing the complex challenges associated with rural water supply systems and support informed decision making in water resource management.
A Comprehensive Study Using FAHP to Evaluate and Prioritize the Most Critical Skills Required for Success in the Rapidly Evolving IT Industry
Authors: D.Sudheer Reddy
Published: February 2025

In the rapidly evolving IT sector, staying competitive is crucial for both organizations and individuals. This study examines four key skills—Communication Skills, Teamwork, Critical Thinking, and Entrepreneurship Skills—using the Fuzzy Analytic Hierarchy Process (FAHP) for analysis. These skills are evaluated to help individuals build strong portfolios and enhance their career opportunities. By equipping students with best practices, the research aims to enable them to contribute effectively to the growth of the IT industry. Continuous learning and practical experience are emphasized as essential for staying ahead in the fast-changing tech landscape. The data for this study was collected from 150 students across various colleges. To ensure accuracy and reliability, a questionnaire was reviewed by experts with over 30 years of teaching experience. The questionnaire was developed in collaboration with two experts with extensive backgrounds in both teaching and industry. Their insights helped refine the design and improve the overall quality of the study. Based on the FAHP analysis, Communication Skills were identified as the most critical factor. These findings highlight the importance of prioritizing Communication Skills in education and training programs. By doing so, individuals can be better prepared for success in the competitive IT field.
Improving AQI Prediction and Optimization Using Graph Convolutional Networks and Transformer Models with Spatial Embedding Operations
Authors: Harna M. Bodele
Published: February 2025

State-of-the-art models do not quite capture complex spatial-temporal dependencies driving variations in the AQI across different urban zones, particularly in areas characterized by heavy traffic and industrial emissions. Accurate and timely prediction of the AQI is critical since it could mitigate the health and environmental impacts of air pollution, especially in metropolitan areas like Delhi that frequent hazardous levels of pollution. They rely primarily on grid-based or very naive temporal schemes that hardly capture the real nature of an urban region. To overcome these shortcomings, this paper suggests three advanced paradigms: (1) Graph Convolutional Networks with Temporal Attention Mechanism, (2) Transformer-based AQI Prediction with Spatial Embedding, and (3) Multi-Agent Reinforcement Learning with Nash Equilibrium for AQI optimization. This model captures the complex spatial interdependencies among different monitoring stations and directs attention in time for emphasizing related important features in different time domains. Therefore, the prediction accuracy improves up to 20% with an average error of ~2.8 units in high-risk zones like Wazipur and Okhla. The Transformer model introduces spatial embeddings that improve the self-attention mechanism to accurately predict spikes in AQI during polluted episodes and provides an estimated 25% improvement with an average error at around ~2.6 units. Conclusion In conclusion, the MARL model improves optimizations of interventions applied in pollution control by representing several regions or sources via agents, achieving a 20% decline in high-pollution episodes. This work effectively improved upon spatial-temporal learning by great enhancements in prediction and optimization of AQI, leading towards a more accurate forecast and practical control strategy for pollution: an objective that lends environmental management improved as well as greater public health benefits for urban and industrial areas.
Leveraging Machine Learning for Enhanced Cloud Computing Load Balancing: A Comprehensive Review
Authors: Swetha.G
Published: February 2025

Popularized especially throughout the last decade, cloud computing has significantly changed the approach to the use of computational resources. But load balancing still persists as a very important issue of concern to achieve the right balance in order to optimize the various resources. This review paper aims at discussing the various Machine Learning (ML) techniques that can be used for the improvement of load balancing in cloud computing systems. Therefore, the analysis of the current methods is intended to reveal the advantages of the modern approaches to load balancing and put focus on the shortcomings of the traditional algorithms and the contribution of new machine learning approaches. ML techniques offer dynamic load balancing solutions which can handle the variance of the system load. These techniques mainly involve the use of historical data and applying statistical analysis to arrive at the best decisions thus reducing the time response, server usage, and resource utilization. Further, this paper presents how the state-of-the-art machine learning models can be implemented in the context of cloud environments focusing on the complexity and overhead, data protection, and scalability questions. It continues the review of the most advanced machine learning algorithms in the context of load balancing. Adding several examples of the current case studies and experiment results from the published researches of the recent years, the effectiveness of these techniques has been illustrated in the real cloud context. This paper is concluded with the generalization for the future works where the emphasis is placed for the improvement of load balance of machine learning for more demanding and secured cloud computing service.
Optimizing Service Enterprise Marketing Policies using Supervised Attention Multi-Scale Temporal Convolutional Network
Authors: Vimalnath V
Published: February 2025

While scientific and technical advancements have increased consumer knowledge, existing market economic models are rapidly deteriorating due to these same issues. To adapt to changing customer demographics in the digital age, marketing tactics must be constantly updated and optimized. In this Manuscript, Optimizing Service Enterprise Marketing Policies using Supervised Attention Multi-Scale Temporal Convolutional Network (SEMP-SAMSTCN) is proposed. Initially, the data gathered from dataset Marketing Analytics dataset. Collected data are pre-processed to Handling missing values and data cleaning using Pseudo linear Maximum Correntropy Kalman Filter (PMCKF).Later, pre-processed image are given to SAMSTCN for effectively predict the sales. In general, SAMSTCN predicts does not express adapting optimization strategies to determine optimal parameters to ensure accurate data prediction. Hence, proposed utilize Adaptive Lightning Attachment Procedure Optimizer (ALAPO) enhance Efficient Predefined SAMSTCN accurately predict the sales. Then, the SEMP-SA-MSTCN is implemented to Python and the performance metrics such as, accuracy, precision and recall. Finally, the performance of SEMP-SA-MSTCN method provides 20.47%, 24.35%, and 276.78% high accuracy, 19.57%, 25.45%, and 29.75%  higher Precision and 18.55%, 23.35%, and 27.63%higher recall while compared with existing Marketing Policy In Service Enterprises Using Deep Learning Model (MPISE-DNN), Lightweight deep learning model for marketing strategy optimization and characteristic analysis (LW-MSO-DCNN) and Evaluating cross-selling opportunities with recurrent neural networks on retail marketing (ECSO-RM-RNN) respectively.
A Novel Artificial Neural Network Approach for Troubleshooting of Sewage Treatment Plant Process
Authors: D.K. Khopade
Published: February 2025

Efficient operation and proactive fault diagnosis in Sewage Treatment Plants (STPs) are essential for maintaining water quality and ensuring regulatory compliance. This paper presents a detailed data analysis of two STP plants, focusing on key operational parameters, including influent and effluent characteristics, aeration rates, and environmental conditions. The target features of the study—Effluent BOD (mg/L), Effluent COD (mg/L), Effluent TSS (mg/L), and Operational Issue Detected—are critical indicators of the plant's treatment efficiency and potential operational issues. Using synthetic datasets, we conducted comprehensive exploratory data analysis (EDA) to identify correlations between influent parameters and effluent quality, revealing important patterns that influence plant performance. Visualizations, including correlation heat maps and scatter plots, provided insights into key factors affecting effluent quality and operational issues. Furthermore, the study demonstrates the potential of Artificial Neural Networks (ANNs) in predicting these target features, offering a predictive framework for fault detection and diagnosis in STPs. By integrating ANN-based models, this research contributes to improving predictive maintenance strategies, ensuring optimal performance, and enhancing decision making in sewage treatment operations. The findings underscore the value of data-driven approaches in optimizing the management and sustainability of wastewater treatment systems.
Assessment of Return Periods for Flood Frequency and Risk Mapping of Floods and Cyclones in India using Arcgis
Authors: Rajani Kant Awasthi
Published: February 2025

Due to its diverse geography and climate, India is highly susceptible to natural disasters like floods and cyclones, with an 8,000-kilometer coastline exposed to 10% of the world's tropical storms, five to six form annually, with the Bay of Bengal being particularly affected due to its higher frequency. This study aims to conduct a detailed flood frequency analysis and risk mapping for the 2014 Srinagar flood, utilizing statistical techniques and GIS-based tools to evaluate the return periods and recurrence frequencies. The study incorporates data from three gauging stations, Asham, Sangam, and Ram Munsi Bagh, regarding discharge rates in cubic meters per second (cms). Statistical models were applied, including Normal, Log-Normal, Log-Pearson Type III, and Gumbel distributions. GIS data was sourced from USGS, DIVA-GIS, and WorldClim to assess flood risk and affected areas. The study’s result revealed that while Log-Normal and Log-Pearson models did not exceed threshold values, the Gumbel distribution indicated potential exceedance at a 95% confidence level, suggesting enhanced safety measures were needed. The analysis shows varying risk levels across gauging stations, with recommendations for improved flood management strategies, especially for areas prone to high flood risk. Further research should focus on refining flood prediction models, enhancing GIS capabilities for risk assessment, and implementing comprehensive flood mitigation strategies.
Artificial Intelligence Technologies in Predicting Life Insurance Premiums: A Case Study on the Iraqi General Insurance Company
Authors: Zena Abdulstar Allayla
Published: February 2025

The insurance sector relies on considerable amounts of data and statistics where standard actuarial computations form the basis for determining risks, liabilities, and appropriate premiums. The traditional methods make predicting life insurance premiums complex task and less efficient. This affects the overall cost and development of proper insurance solutions. However, the rapid development of artificial intelligence technologies presents great opportunities to reshape traditional processes to improve efficiency and accuracy within the insurance industry. The presented work focuses on applying artificial intelligence in developing actuarial calculations, aiming to find a better estimate of the life insurance premium and providing better quality reports for the Iraqi General Insurance Company. In the current study, we used three machine learning algorithms, namely XGBoost, Random Forest (RF), and Decision Tree (DT), to analyze the collected data and estimate the life insurance premium. Different regression evaluation metrics, including MAE, RMSE, R², and Adjusted R², were applied in testing the performance of the algorithms. The results from the experiments showed that the XGBoost algorithm was the highest performing compared to other algorithms that recorded the lowest MAE and the highest R² score. The research also suggested that incorporating artificial intelligence techniques into actuarial analysis can enhance financial reporting efficiency, thus increasing insurance companies' competitiveness in the important sector. Consequently, Iraqi insurance companies need to adopt such technologies to face the changing insurance conditions by training employees and adopting digital transformation to stay competitive and benefit from innovation.
Flex and Flow: Enhancing Employee Engagement and intention to stay through Flexibility with Insights from Spill over Theory
Authors: Reginold John
Published: February 2025

This article seeks to examine the relationship between workplace flexibility and employee engagement, with a focus on how the implementation of flexible work arrangements can enhance employees' likelihood of remaining within the organization. The article makes references to the Spillover Theory, which posits that an experience that occurs in one domain (work) will affect the experience in the second domain (personal life). This study brings together current literature to emphasize the relevance of flexibility in creating a supportive workplace. According to the research, firms that embrace flexible policies boost employee engagement while also reducing turnover intentions.
Comparison between traditional models and artificial neural networks as estimators of the growth of the Tigris scraper Capoeta umbla (Teleostei: Cyprinidae) in the Munzur River, Turkey
Authors: Ozcan Ebru Ifakat , Serdar Osman
Published: February 2025

In this study, a comparison of traditional growth methods (length-weight relationships and von Bertalanffy growth function) with artificial neural networks in growth models was carried out in the growth of 783 specimens of Capoeta umbla from the Munzur River, Turkey from September 2019 to May 2021. The length-weight relationships of C. umbla W = 0.0085L3.013 R2=0.943 was determined for all individuals. The ages of the specimens were from 0 to 11 years old. The von Bertalanffy growth function was Lt = 46.15 [1-e-0.139 (t + 2.57)] and Wt = 856.32 [1-e-0.139 (t + 2.57)]3.013 for all individuals. Ф' value was 2.471 all individuals. The training stopped and the best validation performance was fixed at 8.1473 × 10-5 at epoch 42. The validation checks were reached as 6, at epoch 48 and the gradient = 5.6566 × 10-5, at epoch 48. The target output R value was 0.98584 for training, 0.98969 for validation, 0.98757 for testing and 0.9868 for all. The calculated MAPE values were 0.140 and 0.578 for artificial neural networks, 1.168 and 2.726 for length–weight relationships, 5.721 and 4.013 for von Bertalanffy growth function, respectively. The calculated SSE values for length and weight were 0.0128 and 30.864 for artificial neural networks, 1.3985 and 350.786 for length–weight relationships. The results of the present show that artificial neural networks can be superior estimators than length–weight relationships and von Bertalanffy growth function. Therefore, artificial neural networks models are an effective tool to describe body weight and length in fish.
Testicular biometrics of Murrah buffaloes in different age groups
Authors: Carrascal-Triana Erly L. , Mejía Lúquez Jorge , Agudelo Gómez Divier , Ramírez Toro Edison Julián
Published: February 2025

Knowledge of the testicles’ biometric parameters is fundamental to performing an andrological evaluation of a breeder. The present study was conducted to determine Murrah buffaloes’ testicular biometry. Twenty-four buffaloes were classified into three age groups: G1 (15 to 19 months), G2 (20 to 23 months), and G3 (>24 months), located in Montelíbano, Córdoba, Colombia, from March to November 2022. The measurements analyzed were scrotal circumference (SC), spermatic cord circumference (CC), Testicular volume (TV), Testicular length (TL), and width (TW). To measure the TL, testes were measured, excluding the epididymal tail in the dorsal-ventral direction. In contrast, TW was measured in the middle portion of each testis in the lateral-medial direction. The TV was determined using the equation of the spheroid prolate and represented the average of both testes. Descriptive statistics were performed for each variable; for the SC and TV, a linear regression model as a function of age and weight was analyzed, and simple Pearson correlations were performed. The mean values observed for G1, G2, and G3 were SC (21.7 ± 2.2.0 cm; 24.2 ± 1.2 cm and 27.4 ± 1.2 cm), CC (18.3 ± 2.7 cm; 20.0 ± 2.7 cm and 25.7 ± 2.1 cm), TV (79.7 ± 41.6 cm3; 142.2 ± 32.8 cm3 and 220.7 ± 39.5 cm3), right TL (6.8 ± 1.7 cm; 8.2 ± 0.8 cm and 9.0 ± 0.4 cm), left TL (6.7 ± 1.7 cm; 8.2 ± 0.8 cm and 9.0 ± 0.5 cm), Right TW (3.5 ± 0.5 cm; 4.2 ± 0.3 cm and 5.0 ± 0.4 cm) and left TW (3.4 ± 0.5 cm; 4.2 ± 0.2 cm and 5.0 ± 0.3 cm). The average weights of the groups were: G1 (350.0 ± 27.6 kg), G2 (387.9 ± 45.6 kg), and G3 (469.3 ± 40.1 kg). Positive and significant correlations of weight and age were found with SC (R: 0.86 and 0.90, respectively), as well as with TV (R: 0.85 and 0.87, respectively). From the linear regression models, the estimated monthly variations were for 1.16 ± 0.01 cm (p<0.01), and the TV grows by 8.2 ± 0.3 cm3 (p<0.01). In addition, it was estimated that, for each kilogram of live weight that the animal gains, the SC grows 0.05 ± 0.00 cm (p<0.01) and TV 0.42 ± 0.1 cm3 (p<0.01). Some testicular biometry parameters typical of the Murrah breed were known, and the variations concerning age were identified. In addition, it was possible to estimate the relationship with body weight, which will allow us to establish precision and comparison of testicular development models. More studies are necessary to standardize the morphofunctional changes of buffaloes chronologically.
A first study on sperm sexing in water buffalo through magnetic nanoparticles
Authors: Murtaza Hassan Andrabi Syed , Fayyaz Muhammad Hammad , Shafiq Haider Muhammad , Ali Ghulam Muhammad
Published: February 2025

Gender pre-selection is a genetic tool of economic significance, as it permits animal breeders to produce sex- specific progeny, thereby increasing profitability and genetic gain in the livestock industry. A higher percentage of female calves is preferable for dairy production. In Pakistan, water buffalos are primarily kept for dairy purposes. Therefore, this study was designed to optimize the magnetic nanoparticles (MNPs) based sperm sexing technique in water buffalo. Qualified semen samples from five buffalo bulls were pooled and divided into four aliquots. Each aliquot of 50 million sperm was diluted in 1 mL of modified human tubal fluid (mHTF). Three ali-quots (sexed groups) were incubated with 0.67 ml of negatively charged MNPs suspension. The fourth aliquot was incubated without MNPs (called “control group”). Each tube containing sperm-MNPs suspension was slowly shaken for 5 minutes for uniform mixing. The MNPs were negatively charged and (provided by Clemente Associates Inc, Prescott, Arizona, USA) had a diameter of 50 nanometers. The interaction between the negative charge of MNPs and the Z electrical potential of spermatozoa was different for those spermatozoa carrying an X chromosome (-20 mV) and those carrying a Y chromosome (-16 mV). Therefore, the Y chromosome-bearing spermatozoa remained closer to MNPs. Three sexed groups were exposed to a magnet for 10, 20, and 30 minutes. The control group was exposed to the magnet for 20 minutes. Consequently, in the sexed groups, the Y-bearing sperm-MNP complexes remained attached to the tube’s inner wall due to the magnetic force. In contrast, the X-chromosome spermatozoa remained suspended in the medium. Then, suspended spermatozoa carrying the X chromosome were slowly aspirated. The control group was also aspirated and transferred to a new tube. After aspiration, each group’s progressive motility (PM, %) of spermatozoa was assessed through a computer-assisted sperm analyzer (CASA). After that, spermatozoa were centrifuged at 226 × g for 5 minutes to remove the mHTF, and DNA was extracted. Validation of the sexing technique was done through SYBR® Green Real-Time (RT) PCR using two sets of primers for gender-specific genes, i.e., X-linked proteolipid protein (PLP) and sex-determining region Y protein (SRY). Results revealed that PM was similar (p>0.05) in all groups (ranging from 62 to 65%). The mean fold expression of the PLP gene (X chromosome bearing sperm) was higher (p<0.05) in all sexed groups (average: 15.34-fold = 91.09% X chromosome bearing sperm) as compared to control (1.60- fold). In conclusion, the MNPs-based technique appeared to be an effective method for water buffalo sperm sexing as validated by RT PCR.
Authorization for the trade of medicines in 19th century Spain: reports from the Royal Academy of Medicine (1800-1874)
Authors: Martínez González Cristina , González Bueno Antonio
Published: February 2025

The Royal Academy of Medicine issued reports on the quality of products used as medicines from its earliest moments. After the health law was enacted in 1855, this activity acquired regulatory overtones. Our objective is to make known how the members of this corporation assumed this new role attributed by Spanish legislation.

Keywords: Royal Academy of Medicine; Medicines; Spain; 19th century
Innovation in the future Pharmaceutical Legislation of the European Union
Authors: Noguera Peña Alfonso
Published: February 2025

The European Commission, within the framework of the implementation of the Pharmaceutical Strategy for Europe, has recently published a regulatory package that will replace the current regulation of medicines for human use in the European Union and that aims to provide a global response to current challenges. that the pharmaceutical sector faces.
Due to the relevant role that innovation plays in the future regulatory framework, our work delves into the main measures that affect the promotion of research and development and, in particular: (i) regulatory data protection periods, (ii) the approach of unmet medical needs, (iii) application requirements for marketing authorisations, (iv) post-authorization measures; (v) pre-authorisation regulatory support; (vi) orphan medicinal products; (vii) paediatric medicinal products; (viii) regulatory sandbox; and (ix) manufacturing.

Keywords: Medicines; Pharmacy; Regulatory framework; Orphan medicinal products; Paediatric medicinal products
Tingkat Pengetahuan Mahasiswa UPI Mengenai Informasi Polusi Cahaya di Kota Bandung
Authors: Rahmadiny Aulia , Nurlaili Dalfah , Zulfa Haikal , Rahmawati Rivani
Published: February 2025

This study aims to determine the level of knowledge among UPI students regarding information on light pollution. The research employs a descriptive survey method by distributing questionnaires to 26 respondents, namely students within the UPI campus environment. Based on the students' level of knowledge, it was found that their understanding of light pollution information falls into the "very good" category. The study shows that the majority of UPI students (88.5%) have understood the concept of light pollution, including its causes and impacts on space research and daily life. However, 11.5% of students still lack an understanding of the concept of light pollution, particularly regarding its impacts on daily life and its causes. This research provides important insights into students' knowledge of light pollution. The findings can serve as a basis for increasing students' awareness of the importance of preserving the quality of the night sky and reducing the negative impacts of light pollution.
BIOECONOMIA NAS REGIÕES NEA ARGENTINA E AMAZÔNIA DO BRASIL
Authors: Niezwida Sonia Romina , Pires Renata Quemel , Michalus Juan Carlos
Published: February 2025

O estudo compara a bioeconomia do nordeste da Argentina (NEA) com a da região amazônica do Brasil, avaliando as diferentes abordagens, conquistas e desafíos enfrentados em duas regiões florestais de países distintos. Na região NEA, a bioeconomia concentra-se na agricultura sustentável e nos biocombustíveis, amparada por políticas e tecnologia. Em contraste, a região Amazônica se dedica à conservação e ao uso sustentável da sua biodiversidade, enfrentando desafios como o desmatamento e a exploração não sustentável. Este trabalho integra uma pesquisa exploratória e interdisciplinar conduzida pelos autores do Brasil e da Argentina, com foco em realizar uma investigação, especialmente nas atividades relacionadas à sustentabilidade e à interação de atores-chave nos municípios. A análise dos resultados ressalta a importância da colaboração entre governos, comunidades e o setor privado para promover iniciativas que apoiem o desenvolvimento local sustentável das regiões.
Результаты хирургического лечения аневризмы грудного отдела аорты
Authors: S
Published: February 2025

Цель. Изучение непосредственных результатов хирургического лечения аневризм восходящего отдела и дуги грудной аорты.Материал и методы. Проанализированы исходы 30 операций, выполненных в 20172023 гг. Все больные были прооперированы по поводу осложненных форм аневризм в экстренном порядке. Описаны показания к хирургическому лечению, на основании которых были проведены различные виды протезирования аорты как с сохранением аортального клапана, так и с одновременной коррекцией клапанной патологии.Результаты. Наиболее часто выполнялись операции с использованием клапансодержащих кондуитов. Госпитальная летальность составила 26%. Основная доля смертельных исходов связана с развитием в раннем послеоперационном периоде кровотечения и полиорганной недостаточности, обусловленной синдромом мальперфузии.Заключение. Хирургическое лечение аневризм восходящего отдела и дуги грудной аорты остается весьма актуальной проблемой. Согласно статистике нашего центра как стационара, оказывающего неотложную хирургическую помощь пациентам с острым расслоением аорты, выживаемость составляет около 74%. Разработанный нами вариант укрепления линии анастомоза двойным обвивным швом с применением синтетических материалов заслуживает внимания специалистов как наиболее эффективный метод в профилактике кровотечения
Cравнительный анализ результатов интервенционного и хирургического лечения стенозирующего атеросклероза каротидных артерий
Authors: S
Published: February 2025

Цель. Оценка краткосрочных и долгосрочных результатов стентирования сонных артерий (КАС) и каротидной эндартерэктомии (КЭЭ) у пациентов с гемодинамически значимым стенозом сонных артерий.Материал и методы. В клиническое исследование включены 100 пациентов с диагнозом «стеноз сонной артерии (≥70%)», подтвержденным с помощью допплеровской ультрасонографии и КТ-ангиографии. Группу каротидного стентирования составили 50 больных, группу каротидной эндартерэктомии – также 50 пациентов. Решение принималось на основании предложенного алгоритма, основанного на данных ультрасонографии и КТангиографии.Результаты. В непосредственном послеоперационном периоде, а также при наблюдении в течение 1-го года КАС и КЭЭ продемонстрировали сопоставимые показатели рестеноза, рецидивов острого нарушения мозгового кровообращения и повторного вмешательства. Это свидетельствует о сопоставимой эффективности КАС и КЭЭ в профилактике цереброваскулярных событий у пациентов со стенозами сонных артерий.Заключение. КАС и КЭЭ демонстрируют схожие профили краткосрочной безопасности, без существенных различий в основных нежелательных явлениях, включая инсульт, инфаркт миокарда или смерть в течение 30 дней. Сопоставимая частота инфарктов миокарда указывает на то, что как КАС, так и КЭЭ относительно безопасны с точки зрения серьезных неблагоприятных сердечно-сосудистых событий в течение 30 дней после процедуры
Upaya Meningkatkan Keterampilan Membaca Permulaan Melalui Media Flashcard Kelas 1 Sekolah Dasar Di Gunungkidul Yogyakarta
Authors: Utami Nadia Mega , Utomo Khoirul Budi
Published: February 2025

This study aims to improve the beginning reading skills of grade 1 elementary school students through the use of flashcard learning media. This study uses a Classroom Action Research (CAR) approach which is implemented in two cycles, each consisting of four stages: planning, implementation, observation, and reflection. The subjects of the study were seven grade 1 students, consisting of five male students and two female students. The results of the study showed a significant increase in students' reading skills after the application of flashcards. In the pre-cycle stage, only one student was able to read fluently, while in Cycle 1 there were two students who showed improvement, although the other five students still had difficulty in recognizing letters and words. Evaluation at the end of Cycle 1 showed that flashcards were effective in attracting students' attention and increasing their motivation to learn to read. However, further practice is still needed for students who have difficulty. This study concludes that the use of flashcard media can be an effective alternative to improve the beginning reading skills of grade 1 elementary school students.
MENANAM POHON BERSAMA DALAM UPAYA MENYELARASKAN GAYA HIDUP SEHAT DAN KEINDAHAN LINGKUNGAN SEHARI-SEHARI SEBAGAI BENTUK RASA SYUKUR KEPADA ALAM SEBAGAI SUMBER KEHIDUPAN
Authors: Juhrani Juhrani , Irtania Irtania , Ahmad Shofi Khairian
Published: February 2025

Lingkungan seringkali dipahami secara terpisah. Pemahaman tersebut berkembang selama ini, sehingga agama cenderung tidak memberikan kontribusi yang memadai terhadap kesadaran umat dalam menjaga lingkungan. Agama dan lingkungan dianggap dua hal yang terpisah dan tidak berhubungan satu sama lain. Padahal terdapat hubungan yang erat antara agama dan lingkungan hidup, khususnya pada kontribusi agama dalam mempengaruhi perilaku manusia terhadap persepsi dan tingkah lakunya dalam menjaga dan melestarikan lingkungan hidup di sekitarnya.
Pada metode pelaksanaan kegiatan pengabdian kepada masyarakat tentang Menanam Pohon Bersama dalam Upaya Menyelaraskan Gaya Hidup Sehat dan Keindahan  Lingkungan Sehari-Sehari Sebagai Bentuk Rasa Syukur Kepada Alam Sebagai Sumber Kehidupan,  sebagai salah satu wujud dari tim abdi negara sekaligus memberikan keselarasan kehidupan dengan menanam pohom sebagai rasa syukur atas nikmat yang diberikan oleh Tuhan kepada makhluknya. Dengan demikian, pada lingkungan penduduk diberikan arahan untuk melaksanakan kegiatan tersebut dengan upaya saling bergotong toyong sekaligus memperkenalkan kegiatan dipagi hari dengan menanam pohon dan memeberishkan lingkungan sekitar agar masyarakat menyadari pentingnya kehidupan sehat dengan menjaga sekitaran lingkungan salah satunya adalahan menanam pohon ataupun menanam jenis yang bermanfaat pada lingkungan rumah mereka.
 
 
                Hasil pada kegiatan menanam pohon bersama dalam upaya menyelaras gaya hidup sehat dan keindahan lingkungan sehari-hari sebagai bentuk rasa syukur kepada alam sebagai sumber kehidupan, pohon bukan hanya  elemen dekoratif semata, namun juga menjadi kebutuhan bagi lingkungan yang sehat dan sejuk. Saat ini, dengan lahan yang cukup di sekitar rumah, menanam pohon bukanlah ide yang buruk. Bahkan, hal tersebut bisa memberikan berbagai manfaat yang tak terduga. Dalam tips ini, kita akan membahas mengapa menanam pohon di sekitar rumah adalah tindakan bijak yang tidak hanya bermanfaat bagi lingkungan, tetapi juga bagi kesehatan fisik dan mental kita.
Menanam pohon merupakan langkah kecil namun signifikan dalam mengatasi masalah polusi udara. Pohon memiliki kemampuan alami untuk menyerap gas polutan seperti nitrogen oksida, ozon, amonia, dan sulfur dioksida dari udara yang kita hirup. Selain itu, mereka juga berperan sebagai penyaring, menangkap partikel-partikel kecil yang bisa membahayakan kesehatan pernapasan kita
Pengaruh Pengetahuan Investasi, Financial Literacy dan Pendapatan terhadap Minat Investasi pada Mahasiswa Gen Z
Authors: Audinasyah Chika Syifa , Nurhasanah Nunung
Published: February 2025

Pada zaman ini investasi merupakan salah satu cara memperoleh pendapatan diluar gaji/upah seseorang atau individu sebagai karyawan. Kemahiran dalam ilmu, pemahaman serta literasi menjadikan mahasiswa mempunyai keunggulan untuk ikut berpartisipasi dalam mengawali penanaman modal. Pendapatan para siswa juga jadi kendala dalam memulai investasi sehingga mengurangi minat investasi pelajar. Observasi ini bertujuan guna menentukan, mengevaluasi dan menjelaskan dampak pengetahuan berinvestasi, finansial literacy dan pendapatan terhadap hasrat penanaman dana pada pelajar gen Z. Studi ini dilakukan dengan metodologi deskriptif kuantitatif dan memakai data primer dan data yang sudah tersedia. Populasi pada riset ini sebanyak 500 para siswa dan penetapan sampel ditetapkan dengan teknik non probability sampling, dan didapatkan sampelnya yaitu 83 mahasiswa. Metode analisa mengenakan analisis deskriptif dan analisis regresi linear berganda. Data diolah secara angka memakai SPSS 25. Hasil dari studi ini adalah variabel pengetahuan tanam modal dan financial literacy memberikan akibat terpisah terhadap keinginan berinvestasi, sedangkan variabel pendapatan tidak memberikan pengaruh parsial pada minat berinvestasi. Secara bersama-sama variabel pengetahuan investasi, financial literacy dan pendapatan berdampak secara signifikan pada minat investasi.
Peran Guru dalam Pengelolaan Kelas Perspektif Teori Pendidikan Modern
Authors: Junaidah Junaidah , Fadila Putri , Masruroh Waqiatul
Published: February 2025

Pengelolaan kelas adalah elemen kunci dalam menciptakan lingkungan belajar yang kondusif dan sesuai kebutuhan siswa. Dengan berkembangnya paradigma pendidikan, teori seperti konstruktivisme, humanisme, dan pembelajaran berbasis teknologi memberikan pemahaman baru tentang peran guru. Guru kini berperan sebagai fasilitator, motivator, dan pemimpin dalam pengelolaan kelas berbasis siswa. Penelitian ini mengkaji peran tersebut melalui studi pustaka dengan pendekatan deskriptif-analitis, memadukan teori pendidikan modern dan temuan terkini. Hasil kajian menunjukkan bahwa penerapan teori ini memungkinkan pembelajaran kolaboratif, inklusif, dan relevan bagi abad ke-21. Guru sebagai fasilitator memandu pembelajaran berbasis pengalaman, sebagai motivator membangun motivasi siswa, dan sebagai pemimpin mengelola interaksi sosial kelas. Namun, tantangan seperti kurangnya pelatihan profesional, resistensi terhadap perubahan, dan minimnya dukungan institusional masih menghambat implementasi. Solusi mencakup penguatan kompetensi guru dan pembaruan kebijakan pendidikan.
Penerapan Karakter Kedisiplinan melalui Kolaborasi Orangtua Dan Guru terhadap Motivasi Belajar dan Hasil Belajar Peserta Didik
Authors: Namira Namira , Hadi Muhamad Sofian
Published: February 2025

Penelitian ini bertujuan untuk mengevaluasi penerapan karakter kedisiplinan melalui kolaborasi antara orang tua dan guru terhadap motivasi belajar serta hasil belajar peserta didik kelas VI di SD Al Mujtahidin kota Sorong. Penelitian menggunakan metode deskriptif dengan pendekatan kualitatif melalui wawancara, observasi, dokumentasi, dan angket untuk mendapatkan data yang valid. Hasil penelitian menunjukkan bahwa penerapan kedisiplinan dengan dukungan kolaborasi intensif antara guru dan orang tua secara signifikan meningkatkan motivasi dan hasil belajar peserta didik. Peserta didik menunjukkan perubahan positif dalam sikap seperti ketepatan waktu, kepatuhan terhadap peraturan, dan tanggung jawab dalam menyelesaikan tugas. Kolaborasi ini juga mendukung pembentukan lingkungan belajar yang kondusif. Selain itu, pemberian penghargaan, penggunaan media pembelajaran menarik, serta kegiatan belajar berbasis keterampilan turut meningkatkan motivasi belajar peserta didik.