bluuebunny/crossref_metadata_2025 huggingface dataset:
AI-Driven Personality Development: Enhancing Emotional Intelligence and Social Skills through Machine Learning
Authors: Tejaswini Panse
Published: February 2025

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has opened new frontiers in human personality development, particularly in enhancing emotional intelligence (EI) and social skills. Emotional intelligence, which includes self-awareness, self-regulation, empathy, and effective communication, is a crucial factor in personal and professional success. Traditional methods of personality development rely on human-led training, coaching, and therapy, but AI-powered systems now offer scalable, personalized, and data-driven alternatives. This paper explores the application of AI in personality development, emphasizing how ML techniques such as Natural Language Processing (NLP), deep learning, and reinforcement learning can facilitate emotional intelligence enhancement. Sentiment analysis software, virtual emotional coaches, chatbots, and affective computing systems—among other AI-powered tools—help people identify, understand, and control their emotions.  By means of conversational agents and virtual reality simulations, AI-driven social skills training offers real-time feedback, therefore empowering users to improve their interpersonal contacts.  AI-driven personality development poses ethical questions despite its transforming power including data privacy, algorithmic prejudice, and the possibility of over-reliance on AI for social contacts.  Dealing with these issues calls for a well-rounded strategy combining ethical artificial intelligence models with enhanced openness, human-AI cooperation in social skill development,  The research comes to the conclusion that artificial intelligence has great potential to improve communication abilities and emotional intelligence.  Through responsible use of AI's powers, people may increase their self-awareness and interpersonal efficacy, therefore enhancing their social contacts and professional performance.  To best maximise the advantages of AI-driven personality development, future studies should concentrate on improving AI models, reducing bias, and guaranteeing ethical deployment.
Model to Improve the Quality of Services and the Skills of Young University Students
Authors: Santiago Moquillaza-Henríquez
Published: February 2025

Introduction
This study explores how the Computer Laboratory Office (CLO) of the Faculty of Systems Engineering and Computer Science at the University of San Marcos can provide high-quality services and at the same time improve the skills of university students in providing these services. for which an innovative model is created.
Objectives
The research aimed to develop a sustainable model integrating the ISO 9001:2015 standard, Knowledge Management, Information Technologies (e.g., Support Information Systems, Dashboards), Empowerment, and the Servqual model. The objective was to improve service quality, ensure continuous improvement, and analyze user perceptions through a dashboard.
Methods
Over an eight-year period, the study employed a mixed-methods approach, including a literature review, framework development, and empirical testing. The model was implemented in the CLO, gathering user feedback and conducting statistical analyses to evaluate its impact on service quality and the technical and soft skills of students.
Results
The model significantly enhanced the competencies of students providing services and improved the quality of services offered to users. Notably, the CLO achieved ISO 9001:2015 accreditation for three processes. Statistical records demonstrated the model's effectiveness, reinforcing its success. It can be concluded that knowledge management implies better quality of service and in turn positively affects user satisfaction
Conclusions
This research developed an innovative model that enhances service quality and student skills in pre-professional practice. By integrating ISO 9001:2015, ICT, Empowerment, and the Servqual model, it filled a critical gap in the literature and demonstrated its potential for replication in other university training centers, ensuring sustainable quality improvement and student growth.
Multimodal Federated Transformer: Advancing Medical Image Captioning with MASNet-ViT Fusion and Enhanced Spiking Neural Networks
Authors: AVS Ratna Kumari
Published: February 2025

Determining the density, coefficient of thermal expansion of BaTiO3 across range of 400 K to 1075 K is principal goal of the investigation. Coefficient of temperature dependence of density and coefficient of volume thermal expansion of the compound is assessed. Additionally, the research has been broadened to evaluate the linear attenuation coefficient at various γ-energies over a temperature range using value of mass attenuation coefficient.
Leveraging Technology for Teaching and Learning: Developing a Django-based Quiz Application for Education
Authors: Aaron Paul M. Dela Rosa
Published: February 2025

This study presents the development and evaluation of the Rapid Personalized Assessment Platform for Quizzes (RPAP-Quiz), an innovative web-based application designed to enhance assessment practices in educational settings. Utilizing the Python Django web framework, RPAP-Quiz addresses critical challenges such as adaptability to diverse learning needs and secure assessment delivery. The application empowers educators to manage classes, create customizable quizzes, and monitor student performance while incorporating advanced anti-cheating measures to ensure academic integrity. On the student side, features like secure quiz participation, anti-cheating, and a user-friendly interface promote engagement and critical thinking. A descriptive research methodology guided the study, focusing on user perceptions of the platform’s acceptability, evaluated through ISO/IEC 25010:2023 quality standards. Sixty respondents, including teachers and students, assessed the application across nine criteria, achieving an overall rating of “Extremely Acceptable.” Key strengths identified were functional suitability, ease of interaction, and security, highlighting RPAP-Quiz’s capacity to meet the evolving demands of online assessments. Despite these strengths, minor concerns regarding reliability and performance efficiency were noted, attributed to network dependencies and the strict enforcement of anti-cheating protocols. This research stresses the potential of RPAP-Quiz to transform assessment practices, offering an accessible solution that aligns with modern educational objectives. Recommendations include expanding anti-cheating features and enhancing system flexibility to support broader applications. RPAP-Quiz exemplifies the integration of technology in fostering secure, efficient, and equitable educational experiences for teachers and learners alike.
The Impact of Reverse Logistics and Delivery on Customer Satisfaction in the supply chain in Vietnam
Authors: Nguyen Thi Van Nga
Published: February 2025

Introduction: In the current context, when the market in Vietnam has many great fluctuations, the competitive pressure of businesses is increasing, the strong development of information technology and e-commerce is extremely exciting, making it difficult to increase customer satisfaction in the supply chain.
Objectives: This study focuses on reverse logistics and examines the impact of reverse logistics and delivery on customer satisfaction in the supply chain.
Methods: Based on a survey of 446 consumer customers in Vietnam, using regression using SPSS software.
Results: Research shows that reverse logistics and delivery both have a positive impact on customer satisfaction.
Conclusions: Some of the recommendations made include: first, businesses need to include the content of reverse logistics activities in their sales and operation policies. Second, enterprises need to invest in strengthening transportation activities through self-investment, being proactive in transportation activities or establishing the selection of strategic transportation service providers to ensure the requirements of speed, time and quality of delivery.
Web3 Subscriptions: A Catalyst for a More Inclusive and User-Centric Financial System
Authors: Greeshma Arya
Published: February 2025

By offering fresh approaches to solve long-standing issues like too much centralisation, not involving everyone, and not giving consumers enough autonomy, Web3 technologies are rapidly altering the way typical banking systems operate. One of the most fascinating fresh developments in the field is the growing Web3 membership. These empower consumers over their financial transactions by use of distributed platforms and blockchain technology. Unlike conventional membership models, Web3 payments let users to handle their own data, create explicit arrangements, and get services free from intermediaries. This article examines how Web3 subscriptions can transform the financial climate and open everyone's access. Subscription-based services let users freely access enhanced privacy, security, and control over their personal financial data. Web3 contracts remove obstacles to access so that those without bank accounts may utilize financial services, hence fostering financial inclusion. By shifting authority from centralized financial institutions to individuals, the decentralised framework of these models also allows consumers greater autonomy and independence. This paper investigates the advantages and drawbacks of Web3 accounts including legal concerns, user behavior problems, and growth capability. Following extensive research, we find methods to enhance Web3 membership systems so that they remain scalable, secure, and open for a broad spectrum of users. Finally, this research reveals how Web3 payments could alter the dynamics of financial models, therefore promoting a more open and user-centric attitude to financial services.
Data-Driven Prediction of Nitrogen Stress and Crop Yield in a Maize -Wheat Cropping System
Authors: Halley Okasa
Published: February 2025

This study uses predictive analytics to deal with nitrogen stress and get the best crop returns in a system that grows both wheat and corn. We measured the amount of nitrogen (N) in the leaves along with a number of important farming factors using modern plant monitors like the GreenSeeker and SPAD meter. Different field studies gave us a range of nitrogen treatment rates for wheat (0 to 240 kg N/ha) and maize (40 to 300 kg N/ha). Machine learning methods, like Random Forest and Support Vector Machines, were used to create models that can accurately predict crop yields based on nitrogen doses, Normalised Difference Vegetation Index (NDVI) values, SPAD values, and direct measurements of leaf-N content. The results from pair plot studies showed strong positive links between leaf-N content, NDVI, SPAD values, and the rates of N application. These connections support the accuracy of the prediction models. Notably, the model that was tuned for wheat showed that it could be used with other crops by correctly predicting corn yields. It was amazing how well the prediction models worked. Random Forest and Support Vector Machines were able to get 85.71% and 100% accuracy on the original dataset, respectively.
Classification of Brain Tumours in MRI Images Using VGG 19 Algorithm
Authors: Rahul Namdeo Jadhav, G.Sudhagar
Published: February 2025

For early identification and efficient treatment planning, brain tumour categorization is crucial. Deep learning in medical image analysis, models have lately shown remarkable outcomes, especially regarding MRI scan tumour categorization. This study proposes VGG-19 as the primary model and evaluates its performance against ResNet-50 and Google Net by comparing F1-score, AUC, precision, recall, and accuracy. Consequently, the suggested VGG-19 model had a maximum classification accuracy of 97.2%, outperforming GoogleNet at 96.4% and ResNet-50 at 95.3%. It proves from the confusion matrix that the classification of all kinds of tumours is superior, and minimal misclassifications are available with VGG-19. It is proven further by the ROC curve since AUC scored 0.97, giving excellent discrimination capability. GoogleNet was found to be competitive, especially in Glioma detection, while ResNet-50 provided a balanced classification in all classes. This outcome suggests that deep learning models, particularly VGG-19, efficiently classify brain tumour. Further studies can investigate transformer-based architectures, hybrid deep learning techniques, and the expansion of datasets to further enhance model generalization. Integration of explainable AI into medical imaging systems further improves transparency and clinical trust in using AI-assisted diagnosis in healthcare.
The Performance of Logistic Regression, Decision Tree, KNN, Naive Bayes and SVM for Identifying Automotive Cybersecurity Attack and Prevention: An Experimental Study
Authors: Vaishali Mishra, Sonali Kadam
Published: February 2025

The automotive industry has witnessed a significant increase in cyber threats as vehicles become more connected and reliant on software-driven systems. To safeguard against these threats, effective cybersecurity measures must be implemented. This paper explores the use of Support Vector Machine (SVM) algorithms as a means of bolstering automotive cybersecurity attack prevention. SVM algorithms have demonstrated remarkable capabilities in various domains due to their ability to handle complex and high-dimensional data. By leveraging SVM algorithms, this research aims to enhance the detection and prevention of cybersecurity attacks targeting automotive systems.The proposed approach involves training SVM models using labeled datasets that include both normal and anomalous driving scenarios. By analyzing various features and patterns extracted from the data, the SVM models can learn to differentiate between normal and malicious behaviour. These models can then be used in real-time to identify and mitigate potential cyber threats. The results of this study is compared with other machine learning algorithm like Logistic Regression, Naive Bayes, KNN, Decision Tree, highlight the effectiveness of SVM algorithms in detecting and preventing automotive cybersecurity attacks. The models exhibit high accuracy rates in distinguishing between normal and anomalous behavior, providing a robust defense mechanism against potential threats. In conclusion, this research emphasizes the significance of leveraging SVM learning algorithms for automotive cybersecurity attack prevention. By harnessing the power of machine learning, automotive systems can be fortified against cyber threats, ensuring the safety and integrity of vehicles and their passengers.
Characterization and Optimization of Hybrid Epoxy Composites Using Chicken Feather Fibers and TiO₂ for Enhanced Tensile Strength
Authors: Monika Shankarrao Satpute, Rajeshkumar U. Sambhe
Published: February 2025

Introduction: Hybrid epoxy composites reinforced with chicken feather fibers (CFF) and titanium dioxide (TiO₂) are promising candidates for advanced structural applications due to their lightweight nature and enhanced mechanical properties.
Objective: In this study, the tensile strength of these hybrid composites was optimized using the Taguchi technique. An L27 orthogonal array was employed to systematically evaluate the influence of three critical factors: composite composition, filler type, and filler percentage on the tensile load.
Methods: The Taguchi method facilitated the identification of the optimal process parameters, providing a robust framework for understanding the interactions among the variables.
Results: Experimental results demonstrated that composites incorporating CFF exhibited superior tensile performance compared to those reinforced with TiO₂. Analysis of signal-to-noise ratios revealed that both the composite composition and filler type significantly affect tensile strength, with a notable optimum observed for a specific configuration where a 4% concentration of CFF yielded the highest tensile load.
Conclusion: This study not only highlights the potential of using chicken feather fibers as an eco-friendly and cost-effective reinforcement in epoxy composites but also underscores the efficacy of the Taguchi technique in material optimization. The findings offer valuable insights for the development of high-performance hybrid composites with enhanced tensile properties for diverse engineering applications.
A Modified Deep Neural Network-based Denoiser for Pre-Processing of Diabetic Retinopathy Images
Authors: Piyush Anand
Published: February 2025

Diabetic retinopathy (DR) is a significant reason for visual impairment all over the planet. Recognizing symptoms in the fundus picture is commonly utilized in illnesses connected with the eyes like diabetic retinopathy. It requires early detection through high-quality retinal imaging. However, noise and poor contrast degrade image clarity, affecting diagnosis. To overcome these limitations, pre-processing stage plays a vital role in clinical picture handling to build the nature of fundus images. Preprocessing technique is principally used to eliminate undesirable noises and improve some image features. Image processing makes use of a variety of pre-processing methods. This study presents an exhaustive preprocessing CAD model for diabetic retinal images. By harnessing both advanced deep learning methods and conventional image processing methods, this mechanized conclusion model (computer aided design) looks to work with better analysis and the executives of diabetic retinopathy - one of the main sources of vision misfortune all around the world. We propose a novel preprocessing pipeline integrating Wiener filtering, modified CLAHE, and a deep learning-based Retinal_Denoiser to enhance DR image quality. The proposed Retinal_Denoiser is utilized during the preprocessing phase of the computer-aided design model to eliminate noise and improve quality in retinal images, utilizing deep learning-based denoising autoencoder and protecting the fundamental features of DR pictures. Preprocessing steps were utilized to increase signal-to-noise ratio, our proposed model sets another best-in-class result with a peak signal-to noise ratio (PSNR) value of 62. The high PSNR achieved by our proposed method indicates that it is more effective in preserving the image details while effectively suppressing noise. The fundamental goal of this research is to improve the image by reducing noise, improving contrast, and preserving important structures such as blood vessels and the optical disc. Our method achieves a PSNR of 62.12, surpassing conventional CNN-based, RNN-based, DnCNN-based, and other well-known denoisers.
Alzheimer's Disease Detection Using RNN and CNN Based Deep Learning Approach
Authors: Khatal Sunil Sudam
Published: February 2025

Alzheimer's disease is a very widespread form of dementia and is the fifth leading cause of death among those aged 65 and older. Furthermore, official data indicates a significant increase in the number of fatalities related to Alzheimer's disease. The early discovery of Alzheimer's disease might potentially enhance patient survival chances. Machine learning technologies used for magnetic resonance imaging have been effectively employed for the detection of Alzheimer's disease to accelerate the diagnosis process and support medical practitioners. Conventional machine learning methodologies need the use of specialized feature extraction techniques on MRI images, a procedure that is arduous and demands the involvement of a skilled practitioner. The use of deep learning as a self-sustaining feature extraction method might potentially automate the process and diminish the need for manual feature extraction. This paper proposes a pre-trained masked CNN deep learning approach as an independent feature extraction method for detecting Alzheimer's disease using magnetic resonance imaging (MRI) scans. Subsequently, a masked RCNN was evaluated against RCNN and Faster RCNN using several criteria, including accuracy, to determine which performed superiorly. The results indicated that the proposed model surpassed existing state-of-the-art methods by achieving a higher degree of accuracy. The suggested methodology attained an accuracy of 98% when applied to algorithms using the MRI ADNI dataset.
The Impact of Digital Leadership on Achieving Institutional Agility through the Zero Bureaucracy Government Program in the United Arab Emirates (An Applied Study on the Sharjah Police Sciences Academy)
Authors: Saifan Ali Bin Saifan
Published: February 2025

The study aimed to measure the impact of digital leadership on achieving institutional agility and to examine the mediating role of the Zero Bureaucracy Government Program's requirements in the relationship between digital leadership and institutional agility from the perspective of employees at the Sharjah Police Sciences Academy in the United Arab Emirates. The study adopted a quantitative approach, using a questionnaire to collect data distributed to a randomly selected sample of 288 administrative and academic staff members at the academy. The results indicated a very strong, statistically significant positive relationship at the level of (α ≤ 0.05) between digital leadership and institutional agility. Moreover, the independent variable (digital leadership) had a statistically significant impact on the dependent variable (institutional agility) at the level of (α ≤ 0.05). The findings also revealed that the Zero Bureaucracy Government Program partially mediates the relationship between digital leadership and institutional agility, according to the employees of the Sharjah Police Sciences Academy in the UAE. The study recommended enhancing strategic partnerships between the Sharjah Police Sciences Academy and relevant government entities in the UAE that are involved in the academy's activities and fields of work, with the aim of reengineering operational and administrative processes at the academy to align with the objectives of the Zero Bureaucracy Government Program.
Assemblage of Benthic Macroinvertebrates in Soft Bottoms of the RIÍTO ARM, Rancheria River Deltaic System
Authors: Geomar Molina-Bolívar
Published: February 2025

Benthic macroinvertebrates associated with soft bottoms are a key element in the balance of aquatic ecosystems, as they play an important role in ecological processes, such as nutrient cycling, dispersal and particle capture, among others. For this reason, the objective of this work was to analyze the assembly of benthic macroinvertebrates associated with soft bottoms in the Riíto arm of the estuarine deltaic system of the Ranchería River, in the department of La Guajira (Colombia). This system has been shown to be highly changeable in previous studies, so it is necessary to carry out environmental monitoring. During the period from September 2022 to January 2023, temperature, pH, conductivity, transparency, depth, alkalinity and hardness of the water were measured in situ, as well as sediment samples were taken to determine its granulometry and organic matter, and to analyse benthic macroinvertebrates, at three sampling sites:  Desembocadura (DB), Mirador (EM) and Villa Fátima (VF) along the El Riíto arm in the Rancheria River delta. Two species were found: Pyrgophorus platyrachis and  Mytilopsis leucophaeta. The density of organisms was higher in MS, with 62.5 individuals per square meter, although the sampling sites presented only a slight separation according to their physicochemical characteristics, mainly due to the variability of oxygen saturation and mean sand. Only fine sand was associated with the density of P. platyrachis as the dominant species of the El Riíto arm (87.1 % of the total abundance). It is concluded that, according to the composition and abundance of organisms, DB and VF are different from EM, since the latter site showed the highest densities of organisms, which indicated slightly more favorable conditions for them. Likewise, it was evidenced that the physicochemical variability within the estuary is mainly temporary.
Tác dụng giảm đau và phục hồi chức năng vận động khớp gối của điện châm kết hợp đắp bột đại hoàng
Authors: Phúc Phùng Minh , Vĩ Nguyễn Văn , Lụa Trịnh Thị
Published: February 2025

Mục tiêu nghiên cứu nhằm đánh giá tác dụng giảm đau và phục hồi chức năng vận động của điện châm kết hợp đắp bột Đại hoàng trên người bệnh thoái hóa khớp gối. Nghiên cứu can thiệp, có nhóm chứng trên 68 người bệnh được chẩn đoán Thoái hóa khớp gối theo ACR, 1991 tại bệnh viện Y học cổ truyền Vĩnh Phúc. Nhóm nghiên cứu được điều trị bằng phương pháp điện châm kết hợp đắp bột Đại hoàng, nhóm đối chứng được điều trị bằng phương pháp điện châm. Kết quả: sau điều trị nhóm nghiên cứu có điểm VAS trung bình thấp hơn nhóm chứng (2,62 ± 0,85 và 3,68 ± 0,48). Điểm WOMAC trung bình của nhóm nghiên cứu thấp hơn nhóm chứng (23,94 ± 3,94 và 31,29 ± 6,04). Tầm vận động khớp gối của nhóm nghiên cứu tốt hơn so với nhóm chứng (131,18 ± 4,45 và 120,15 ± 3,14), với p < 0,05. Phương pháp điện châm kết hợp đắp bột Đại hoàng trên người bệnh thoái hóa khớp gối có tác dụng giảm đau và cải thiện tầm vận động khớp tốt hơn rõ rệt (p < 0,05) so với phương pháp điều trị điện châm đơn thuần.
Một số đặc điểm của hồng ban cố định nhiễm sắc và hồng ban cố định nhiễm sắc do Trimethoprim - Sulfamethoxazol
Authors: Huyền Trần Thị , Hương Bàn Thị Thu
Published: February 2025

Nghiên cứu này được thực hiện nhằm cập nhật về hồng ban cố định nhiễm sắc (fixed drug eruption, FDE) nói chung và FDE do trimethoprim-sulfamethoxazol nói riêng. Kết quả cho thấy độ tuổi thường gặp nhất là trên 50, tuổi trung bình là 46 tuổi; các thuốc gây dị ứng phổ biến nhất là các kháng sinh, trong đó trimethoprim-sulfamethoxazol (Biseptol) hay gặp nhất, chiếm 32,8%. Trong nhóm có tổn thương sinh dục, nam giới chiếm 85,2%, cao hơn so với nữ giới (14,8%), p = 0,009. Người bệnh đã có tiền sử FDE có tỷ lệ khởi phát bệnh sau khi dùng thuốc dưới 24 giờ cao hơn trên 24 giờ (58,8% so với 41,2%, p < 0,01). Trong số các bệnh nhân FDE do Biseptol, có đến 90,5% có tiền sử từng bị FDE, thời gian từ khi dùng thuốc đến khi khởi phát dưới 24 giờ chiếm tỉ lệ cao (57,1%). FDE do Biseptol có tổn thương niêm mạc chiếm tỉ lệ cao (66,7%), phần lớn người bệnh có nhiều tổn thương (95,2%), tất cả các bệnh nhân có dát đỏ/ tăng sắc tố và ngứa, rát tại tổn thương.
Huyết thanh chẩn đoán virus herpes simplex 1,2 ở các bệnh nhân hồng ban đa dạng, hội chứng Stevens-Johnson và hoại tử thượng bì nhiễm độc
Authors: Huyền Trần Thị , Phương Phạm Thị Minh , Doanh Lê Hữu
Published: February 2025

Nghiên cứu mô tả cắt ngang trên 54 bệnh nhân hồng ban đa dạng (erythema multiforme-EM), 30 bệnh nhân hội chứng Steven-Johnson (Stevens-Jonhson syndrome-SJS)/hoại tử thượng bì nhiễm độc (toxic epidermal necrolysis-TEN) và 30 người khỏe mạnh nhằm xác định tỷ lệ huyết thanh dương tính với virus herpes simplex 1, 2 (HSV1, 2) và mối liên quan của virus này với một số đặc điểm lâm sàng. Kết quả cho thấy, trong nhóm SJS/TEN, nhóm EM và nhóm khỏe mạnh, tỷ lệ huyết thanh HSV1, 2 - IgM dương tính lần lượt là 20%; 22,22% và 6,67%, không có sự khác biệt giữa các nhóm. Tỷ lệ huyết thanh HSV1, 2 - IgG dương tính ở cả ba nhóm khá cao; trong đó, nhóm SJS/TEN cao hơn nhóm EM (100% so với 87,4%, p < 0,05). Trong nhóm EM, tỷ lệ HSV1, 2 - IgM dương tính ở nhóm < 30 tuổi cao hơn ở nhóm ≥ 30 tuổi; tỷ lệ HSV1, 2 - IgG dương tính ở nhóm ≥ 30 tuổi cao hơn ở nhóm < 30 tuổi; tỷ lệ HSV1, 2 - IgG dương tính ở nhóm có thương tổn lan tỏa cao hơn ở nhóm có thương tổn đầu cực, khu trú (p < 0,05); tỷ lệ HSV1, 2 - IgM dương tính ở nhóm có thương tổn đầu cực, khu trú (50%) cao hơn so với nhóm lan tỏa (18,75%), p > 0,05.
Đánh giá kết quả phẫu thuật u màng não có nút mạch trước mổ tại Bệnh viện Hữu nghị Việt Đức
Authors: Tuyển Nguyễn Duy , Tùng Trần Sơn , Hưng Cao Việt , Sơn Nguyễn Hoàng
Published: February 2025

U màng não chiếm 36% tổng số u não. Một số khối u kích thước lớn, tăng sinh mạch máu, xâm lấn xương, và liên quan chặt chẽ với các cấu trúc thần kinh. Phẫu thuật lấy toàn bộ u là thách thức lớn. Mục tiêu của nghiên cứu là đánh giá kết quả phẫu thuật u màng não có nút mạch trước mổ. Nghiên cứu mô tả cắt ngang trên 52 bệnh nhân được nút mạch và phẫu thuật từ tháng 1/2022 đến tháng 10/2024 tại Bệnh viện Hữu nghị Việt Đức. Kết quả cho thấy tuổi trung bình là 52,23, tỷ lệ nữ/nam là 1,74/1. Đa số là u màng não độ I chiếm 76,92%, độ II là 23,07%. Các triệu chứng lâm sàng thường gặp nhất là đau đầu chiếm 59,62%. Phần lớn u ở nền sọ (75%). Thể tích u lớn trên 50cm3 chiếm 69,23%. Nút tắc hoàn toàn mạch nuôi chiếm tỷ lệ cao (84,62%), không có biến chứng sau nút mạch. Thời gian phẫu thuật trung bình là 5,48 giờ. Lượng máu truyền trung bình là 298ml. Phẫu thuật cắt toàn bộ u đạt 48,08%. Biến chứng sau mổ thấp dưới 5%. Nút mạch trước mổ u màng não có kích thước lớn, giàu mạch máu nuôi u, u vùng nền sọ là phương pháp an toàn và hiệu quả.
Gây mê hồi sức để mổ lấy thai cho sản phụ thông liên thất có tăng áp lực động mạch phổi nặng: Báo cáo một ca lâm sàng
Authors: Anh Dương Nữ Diệp , Thắng Nguyễn Toàn , Tú Nguyễn Hữu , Huyền Nguyễn Thanh , Tiến Lê Văn , Hùng Trần Thanh , Cúc Trần Thị
Published: February 2025

Thai kì bị chống chỉ định ở bệnh nhân có tăng áp lực mạch phổi vì tỉ lệ tử vong cao, tuy nhiên một số bệnh nhân lựa chọn mang thai hoặc mới phát hiện bệnh khi khám thai định kì. Gây mê mổ lấy thai cho bệnh nhân tăng áp lực mạch phổi là một thách thức lớn đòi hỏi bác sĩ gây mê hồi sức cần có chiến lược gây mê thận trọng, phối hợp đa chuyên khoa: bác sĩ sản khoa, tim mạch, sơ sinh. Chúng tôi báo cáo một trường hợp lâm sàng hiếm gặp, bệnh nhân nữ 28 tuổi, tiền sử thông liên thất – tăng áp lực mạch phổi cố định, bỏ theo dõi và điều trị tim mạch sau khi quyết định mang thai. Bệnh nhân vào viện khám trong tình trạng Thai 35 tuần – Thông liên thất phần màng shunt hai chiều, áp lực động mạch phổi đo được trên siêu âm là 128mmHg, chúng tôi lập tức hội chẩn đa chuyên khoa và ra kế hoạch mổ lấy thai cấp, chủ động. Bệnh nhân được mổ lấy thai thành công dưới phương pháp gây mê toàn thân với sự kiểm soát huyết động chặt chẽ, trẻ sơ sinh APGAR 8-9 điểm. Bệnh nhân tiếp tục được theo dõi, điều trị tích cực sau mổ và được ra viện sau 21 ngày.
Đặc điểm lâm sàng, cận lâm sàng và kết quả điều trị nhiễm khuẩn do Staphylococcus aureus ở trẻ sơ sinh
Authors: Quang Lê Đức , Nga Nguyễn Thị Quỳnh
Published: February 2025

Nghiên cứu mô tả đặc điểm lâm sàng, cận lâm sàng và kết quả điều trị nhiễm khuẩn do Staphylococcus aureus ở trẻ sơ sinh tại Trung tâm Sơ sinh, Bệnh viện Nhi Trung ương, từ tháng 01/2022 đến tháng 06/2023. Trong 108 trẻ, 81,5% sinh đủ tháng, 77,8% cân nặng ≥ 2500g, 88% nhập viện sau 3 ngày tuổi với triệu chứng bú kém (63,9%) và sốt (65,7%). Tổn thương chủ yếu ở da-mô mềm (58,3%), nhiễm khuẩn huyết (35,2%) và viêm phổi màng phổi (25%). 32,4% bạch cầu ≥ 20 G/L và 59,3% CRP ≥ 15 mg/L. Tỷ lệ MRSA cao (81,5%), với MIC ≥ 1 µg/mL ở 46,3%. Vi khuẩn nhạy cảm hoàn toàn với vancomycin và linezolid (100%). Thời gian điều trị trung bình là 16,9 ± 11,6 ngày. 87,9% trẻ điều trị bằng vancomycin, và 63,9% phối hợp kháng sinh khác. Can thiệp trích rạch áp xe (31,5%) và dẫn lưu màng phổi (14,8%). Tỷ lệ tử vong là 7,4%, chủ yếu do nhiễm khuẩn huyết và viêm phổi hoại tử. Việc tối ưu hóa chẩn đoán và điều trị là rất cần thiết để cải thiện kết quả điều trị và giảm biến chứng nghiêm trọng.
The Effect of Employee Resilience, Work Flexibility, and Gamification Training Program as Intervening Variables on Employee Performance
Authors: Uli Artha Citra , Sitorus Sunday Ade , Nopeline Nancy
Published: February 2025

This study aims to determine how the influence of employee resilience, work flexibility, and gamification training programs as intervening variables on employee performance at PT Nusareka Prima Engineering. This research uses quantitative methods with incidental sampling techniques and involves 109 respondents as samples. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS software version 4.0. The results showed that employee resilience did not have a significant effect directly on employee performance, with a significance level of 0.074 (>0.05). However, work flexibility has a significant direct effect on gamification training programs with a significance level of 0.005 (<0.05), although work flexibility has no direct effect on employee performance (0.566 > 0.05). Gamification training program as an intervening variable significantly affects employee performance with a significance level of 0.002 (<0.05). Employee resilience through the gamification training program also significantly affects employee performance with a significance level of 0.041 (<0.05). Work flexibility through the gamification training program significantly affects employee performance with a significance level of 0.028 (<0.05). This study concludes that the gamification training program is an important intervening variable in improving employee performance. Work flexibility has a significant influence on the success of the gamification training program, which has an impact on improving employee performance.
Understanding Financial Risk Dynamics: A Qualitative Inquiry into Credit, Market, and Operational Risks in Banking, Investment, and Corporate Sectors
Authors: Sapiri Muhtar
Published: February 2025

This qualitative study explores the dynamics of financial risk management, specifically focusing on credit, market, and operational risks within the banking, investment, and corporate sectors. The research investigates the interconnected nature of these risks, their implications for risk management practices, and their impact on systemic stability. The research methodology involves a comprehensive review of existing literature and qualitative interviews with experts in the field. Thematic analysis is employed to identify recurring themes and patterns within the data. The findings highlight the intricate interconnections between different types of risks and underscore the importance of adopting integrated risk management frameworks. The analysis shows that events associated with one kind of risk can have far-reaching implications for others, amplifying overall risk exposures and vulnerabilities. The study emphasizes the need for a holistic approach to risk management that considers the interdependencies between credit, market, and operational risks. The implications for risk management practices, regulatory frameworks, and systemic stability are discussed, highlighting the significance of enhancing operational resilience and promoting collaboration between academia, industry, and regulatory bodies. Overall, the research contributes to a deeper understanding of financial risk dynamics and provides insights for enhancing risk management practices within the economic system.
Legal Protection of Buyers in the Sale and Purchase Agreement of Uncertified Pangkalan Mansyur Land
Authors: Hutagaol Delvia Sawita Lestari Br , Simamora Janpatar
Published: February 2025

This article discusses legal protection in land sale and purchase agreements in Pangkalan Mansyur conducted informally (underhand) and without certificates. Legal protection is provided through agreement clauses and statutory provisions such as the Civil Code and the Basic Agrarian Law (UUPA). This article highlights the importance of land certificates as legal evidence of legal ownership and the legal risks that arise in transactions without certificates, including land disputes. A normative juridical approach evaluates how legal regulations protect parties in such transactions. In conclusion, land without certificates presents legal challenges, and legal protection must ensure fairness and legal certainty for all parties involved. Educational efforts and ease of land titling are also proposed to reduce the potential for future disputes.
Analysis of Bawaslu's Responsibility in Violations of the Neutrality of the State Civil Apparatus that Result in Losses to Voters in the 2024 Election
Authors: Marbun Enjelika , Sinaga Budiman
Published: February 2025

The 2024 elections in Indonesia face various challenges, including violations of election neutrality committed by the State Civil Apparatus (ASN). This violation not only damages the integrity of the election but also has the potential to cause harm to voters. This study aims to analyze Bawaslu's obligations related to these violations and the impact on voters who feel disadvantaged. The research method used is normative juridical analysis with data analysis obtained from relevant legal regulations, official documents, and previous studies. The results showed that violations of ASN neutrality significantly impacted people's voting rights, and many voters felt pressured or disadvantaged by these actions. The research also identified that Bawaslu is legally responsible for addressing these violations and compensating the aggrieved parties. The implications of these findings point to the importance of implementing strict sanctions for violators to ensure fairness in the electoral process and the protection of voters' rights. In conclusion, there is a need to strengthen regulations and education for ASNs to prevent the recurrence of violations in the future.
Civil Liability for the Use of Personal Data by Political Parties in Election Testimony Verification
Authors: Sipakkar Rika Yanti , Sinaga Budiman N.P.D
Published: February 2025

In a democratic system, regional head elections Pilkada are one of the important pillars to elect leaders and representatives of the people. However, inaccurate voter data in the integrity of elections often causes problems in the implementation of elections including double data. Double data not only undermines the principle of fairness but also has the potential to reduce public trust in democracy. Therefore, election monitoring is essential to maintain the fairness and openness of the voting process. People's constitutional rights are affected by this issue, as they need assistance to report changes in voter data or match unregistered data. Almost all communities in Medan have conducted matching and research coklit properly, according to the election monitoring results. However, the issue of double data is still a problem that must be monitored again by Bawaslu. The author collects information about the 2024 Pilkada from the Election Supervisory Board of Medan City. That there are still many double data that occur in the community. The purpose of this research is to find out how well the coklit works to avoid double data and how it affects voting and fairness. This research shows that most citizens of Medan City have followed the procedures when conducting coklit, thus reducing the possibility of double data. Transparency, public trust, and community engagement in the elections also increased as a result. In addition, this monitoring activity also provides suggestions for improving the double data prevention system, including increasing cooperation between election organizers and independent monitors, expanding coklit socialization to the community, and using artificial intelligence-based technology for automatic detection. Such measures are essential to ensure integrity, fairness and transparency in elections.
The Complex Reality and Trans-disciplinary Approach in World of Higher Education
Authors: Lubis Akhyar Yusuf
Published: February 2025

This paper discusses the transdisciplinary approach and its importance to be discussed and applied in the world of higher education research to understand and address the complexity of socio-cultural problems. Gillez Deleuze and Felix Guattari through a famous book, A Thousand Plateaus proposed two terms "arborescent" and "rhizome" as a metaphor for two paradigms and scientific approach in teaching and research. The concept “aborrescent” in many respects considered inadequate applied in the scientific world that tends to see reality is atomistic, but complex and mutually overlap (networking). Giles Deleuze and Felix Guattari proposed the concept of the rhizome as a metaphor for the paradigm and post-disciplinary scientific approach. UNESCO, CIRET and many scientific institutions and university in developed countries have done symposium, seminars and carry out research with a trans-disciplinary approach. The development of science-technology and complex and fast-changing cultural reality, requires colleges to understand and apply the trans-disciplinary approach.
Evaluation of The Implementation of Community-Based Independent Curriculum in Madrasah in The City of Tidore Islands
Authors: Adam Adiana , Syawal Zulkarnain , Djasman Chaerunnisa H. , Akhsan Sahjad,M. , Juliadarma Minggusta
Published: February 2025

This research evaluates the implementation of the Independent Community-Based Curriculum in Tidore Islands City madrasah, with a focus on the quality and suitability of the Madrasah Operational Curriculum (KOM) documents and the Mapping of Strengthening Character Education and Religious Risk Assessment (P5 P2RA). Through a qualitative approach with case study methods, this research involved four state madrasas as the main locations: MAN 1, MAN 2, MTsN 2, and MTsN 3. The results of the research showed that the level of suitability and quality of documents varied, with MAN 1 and MAN 2 having documents that superior to MTsN 2 and MTsN 3. The curriculum at these madrasah successfully integrates local cultural values, character education, and 21st century skills such as critical thinking and collaboration. However, the main challenges include a lack of supporting facilities and the need to increase teacher competency. Research recommendations include teacher training, strengthening facilities, and collaborating with the community. This research emphasizes the importance of curriculum relevance to local contexts to create more inclusive and contextual education.
Untheilbarkeitsgesetz im Württembergischen Fürstenhause nach seiner geschichtlichen Entwicklung
Authors: Adam Albert Eugen
Published: February 2025

Inaugural-Dissertation, Univ. Tübingen
Rezension von: Münsterblätter, 3. und 4. Heft, 1883
Authors: H. P.
Published: February 2025

Münster-Blätter, 3. und 4. Heft, Ulm: Ebner, 1883.
Pengaruh Penggunaan Multimedia Interaktif Terhadap Hasil Belajar Dasar-dasar Desain Komunikasi Visual Siswa SMK Negeri 1 Tondano
Authors: Malolo Yusuf Tomisa Sombolayuk , Olii Djami , Manggopa Hiskia Kamang
Published: February 2025

ABSTRAK
Penelitian ini bertujuan untuk melihat adanya pengaruh penggunaan multimedia interaktif terhadap hasil belajar Dasar-Dasar Desain Komunikasi Visual siswa SMK Negeri 1 Tondano. Metode yang digunakan ialah kuantitatif dengan menggunakan metode quasi-eksperimen tipe Pretest-Posttest Control Group design. Penelitian ini dilakukan 3 tahapan yaitu tes awal, perlakuan, dan tes akhir. Perlakuan menggunakan multimedia interaktif diberikan pada kelas eksperimen, sedangkan kelas control diberikan perlakuan dengan cara konvensional. Hasil dari post-test dari penelitian ini menampilkan perbedaan yang didapat dari hasil belajar kelas kontrol dan kelas eksperimen yang berarti bahwa adanya pengaruh positif dalam penggunaan multimedia interakhif terhadap hasil belajar Dasar-Dasar Desain Komunikasi Visual siswa SMK Negeri 1 Tondano.
ABSTRACT
 This study aims to examine the influence of interactive multimedia use on the learning outcomes of Basic Principles of Visual Communication Design among students at SMK Negeri 1 Tondano. The method employed is quantitative, utilizing a quasi-experimental Pretest-Posttest Control Group design. The research was conducted in three stages: a pre-test, a treatment, and a post-test. The experimental class received the interactive multimedia treatment, while the control class was subjected to conventional methods. The results from the post-test in this study show a difference in learning outcomes between the control and experimental classes, indicating a positive impact of interactive multimedia use on the learning outcomes of Basic Principles of Visual Communication Design among students at SMK Negeri 1 Tondano.
Penerapan Model Pembelajaran Problem Based Learning untuk Meningkatkan Hasil Belajar Desain Produk Siswa Kelas X DKV SMK N 3 Tondano
Authors: Maroi Cindy Marcely , Palilingan Verry Ronny , Togas Peggy Veronica
Published: February 2025

ABSTRAK
Penelitian ini dilaksanakan dengan metode Penelitian Tindakan Kelas (PTK) yang terdiri dari dua siklus dan setiap siklus terdiri dari empat tahap yaitu: perencanaan, tindakan, observasi, dan refleksi. Hasil penelitian menunjukan bahwa presentase hasil belajar yang diperoleh siswa pada siklus I adalah 44% dan pada siklus II 88%. Berdasarkan hasil penelitian tersebut, dapat ditarik kesimpulan bahwa penerapan model pembelajaran Problem Based Learning dapat meningkatkan hasil belajar Desain Produk siswa kelas X DKV SMK N 3 Tondano. Berdasarkan kesimpulan peneliti dikemukakan saran, bagi guru kelas diharapkan dapat menerapkan model pembelajaran Problem Based Learning, dalam rangka untuk memperbaiki pembelajarn Desain Produk di SMK.
ABSTRACT
 This research was carried out using the Classroom Action Research (PTK) method which consists of two cycles and each cycle consists of four stages, namely: planning, action, observation, and reflection. The research results showed that the percentage of learning outcomes obtained by students in cycle I was 44% and in cycle II 88%. Based on the results of this research, it can be concluded that the application of the Problem-Based Learning learning model can improve the Product Design learning outcomes of class X DKV students at SMK N 3 Tondano. Based on the researchers' conclusions, suggestions are made that class teachers are expected to be able to apply the Problem Based Learning learning model, to improve Product Design learning in vocational schools.
Penggunaan Aplikasi LW-Learning Berbasis PHP Terhadap Peningkatan Hasil Belajar Siswa Kelas IX MTsS PUI Kancana
Authors: Iping Iping , Mahpudin Asep
Published: February 2025

ABSTRAK
Penelitian ini bertujuan untuk Membuktikan dampak penggunaan aplikasi lw-learning berbasis PHP terhadap peningkatan hasil belajar siswa kelas IX bidang studi Pendidikan Kewarganegaraan (PKn) materi makna alinea pembukaan UUD tahun 1945 pada MTsS PUI Kancana. Metode penelitian yang digunakan yaitu penelitian tindakan kelas, Melalui penelitian tindakan kelas, diharapkan dapat memperbaiki kondisi di mana praktik pembelajaran sebelumnya dapat mencapai tujuan yaitu meningkatkan hasil belajar siswa. Pelaksanaan dalam kegiatan ini dilakukan dalam dua siklus. Dari penelitian dihasilkan, bahwa penggunaan aplikasi lw-learning berbasis PHP di kelas XI MTs PUI Kancana pada Tahun Pelajaran 2023/2024 telah berhasil meningkatkan hasil belajar siswa pada bidang studi Pendidikan Kewarganegaraan (PKn) materi makna alinea pembukaan UUD tahun 1945 dengan prosentase perolehan ketuntasan pada siklus I sebesar 36% pada siklus II menjadi 100% dan diikuti dengan meningkatnya tingkat minat belajar siswa pada siklus I yaitu ranah perhatian siswa 64%, keterlibatan siswa 66%, rasa senang 72% dan ketertarikan siswa 66% , pada siklus II ranah perhatian siswa 94%, keterlibatan siswa 91%, rasa senang 90% dan ketertarikan siswa 93%.
ABSTRACT
 This research aims to prove the impact of using the PHP-based lw-learning application on improving the learning outcomes of class IX students in the Citizenship Education (PKn) study area regarding the meaning of the opening paragraph of the 1945 Constitution at MTsS PUI Kancana. The research method used is classroom action research. Through classroom action research, it is hoped that it can improve conditions in which previous learning practices can achieve the goal of improving student learning outcomes. Implementation of this activity was carried out in two cycles. From the research, it was found that the use of the PHP-based lw-learning application in class cycle I was 36% in cycle II to 100% which was followed by an increase in the level of student interest in learning in cycle I, namely in the domain of student attention 64%, involvement in learning 66%, enjoyment 72% and interest in learning 66%, in cycle II the domain student attention 94%, involvement in learning 91%, enjoyment 90% and interest in learning 93%.