bluuebunny/crossref_metadata_2025 huggingface dataset:
Compartiendo la Salud: La experiencia de la enfermedad del Personal de Salud en un Grupo de Ayuda Mutua
Authors: Cortés Cárdenas Cynthia Michel , Arganis Juárez Elia Nora
Published: February 2025

Este artículo forma parte de una investigación más amplia en la que se examinó la experiencia de la enfermedad crónica, en particular la diabetes mellitus tipo 2, desde la perspectiva de un grupo de profesionales de la salud que laboran en un centro de salud en la Ciudad de México. Durante cuatro años de investigación etnográfica con un grupo de colaboradores para personas con enfermedades crónicas, se llevaron a cabo entrevistas a profundidad, en las que se recolectaron y examinaron las experiencias de cinco profesionales de la salud que formaron parte de este grupo.  El objetivo de este estudio consistió en describir y analizar sus experiencias con la enfermedad. Los resultados se obtuvieron mediante un análisis exhaustivo de contenido, en el que se identificaron tanto las categorías establecidas previamente. Todo ello, con el fin de establecer un sistema de relaciones coherente con el marco teórico de la “experiencia de la enfermedad”, propuesto por Arthur Kleinman (1978). Este abordaje, permitió adentrarnos en la forma en que estos profesionales experimentan y reproducen sus conocimientos, más allá de los conceptos biomédicos. Este acercamiento, enriquece la comprensión sobre los diversos modos en que los las diferentes disciplinas experimentan los desafíos de la enfermedad en su vida profesional.
Study of Cutaneous Manifestations in Patients with Polycystic Ovarian Syndrome Attending a Tertiary Care Centre
Authors: Aleena Binte Khalid  , Sibghatullah Rao  , Umaima Malik  , Maria Sargana  , Amna Akbar
Published: February 2025

Background: Polycystic ovary syndrome (PCOS) is a common reproductive, metabolic, and psychological condition affecting up to 18% of women. It often manifests with dermatological symptoms, which may provide early diagnostic clues. Understanding the frequency and characteristics of these cutaneous manifestations is essential for effective management. Objective: To determine the frequency of cutaneous manifestations associated with PCOS. Materials and Methods: This descriptive cross-sectional study was conducted in the Department of Dermatology, CMH Multan, from June to December 2024. A total of 219 adult non-pregnant females aged 18–40 years, fulfilling the Rotterdam-2003 diagnostic criteria for PCOS, were enrolled through non-probability consecutive sampling. Participants with other endocrine disorders or hormonal disturbances were excluded. Clinical and anthropometric data, including BMI and cutaneous manifestations (hirsutism, acne, androgenic alopecia, seborrhea, acanthosis nigricans, and skin tags), were recorded. Data were analyzed using SPSS v26, with a Chi-Square test applied for significance. Results: The mean age of participants was 24.15 ± 7.10 years, and the mean BMI was 25.84 ± 6.00 kg/m². Hirsutism (93.26%) was the most prevalent manifestation, followed by androgenic alopecia (91.80%), seborrhea (89.40%), and acne (85.60%). Acanthosis nigricans and skin tags were present in 56.30% and 33.20%, respectively. Obese participants exhibited significantly higher rates of hirsutism compared to non-obese participants (82.5% vs. 39.7%, p<0.0001). Conclusion: Cutaneous manifestations are frequent in PCOS, with obesity significantly exacerbating hirsutism. Early dermatological assessment can aid in timely diagnosis and management of PCOS.
Association of Gestational Diabetes Mellitus with Multi Drug Resistant Vaginal Infections among Pregnant Women
Authors: Nida Tariq  , Maryam Iqbal  , Mehwish Sheraz  , Maher Ali Rusho  , Saira Naz  , Bilal Musa  , Usama Hameed  , Maryam Khalid
Published: February 2025

Background: Vaginal infections caused by various pathogenic microorganisms, along with the emergence of antibiotic resistance, pose significant medical challenges. Gestational diabetes mellitus (GDM) is a critical factor that can delay recovery from infections and lead to complications. Methodology: This study was conducted as a cross-sectional analysis involving pregnant women. A total of 120 vaginal swabs were collected from participants and analyzed to identify the microorganisms present and assess their antibiotic susceptibility. The subjects were categorized into two groups based on their diabetic status: those with GDM and those without. Various biochemical tests, culturing methods, and sensitivity patterns were performed on high vaginal swab isolates. Results: The analysis revealed that 56% of the women studied were aged between 23 and 37 years, with 67% in their third trimester. Among the microorganisms identified, Candida species accounted for 51%, while gram-positive bacteria comprised 24.3% and gram-negative bacteria 25.19%. Within the gram-positive category, Methicillin-resistant Staphylococcus aureus (MRSA) was the most prevalent at 30.25%, followed by Enterococcus faecalis at 15% and Streptococcus species at 3.11%. For gram-negative bacteria, Klebsiella pneumoniae was found in 44.4% of cases, E. coli in 31.3%, Pseudomonas aeruginosa in 14.1%, Pseudomonas stutzeri in 6.05%, and Acinetobacter baumannii in 3.02%. Susceptibility testing indicated that Staphylococcus aureus was primarily sensitive to Linezolid but resistant to azithromycin, while vancomycin and cotrimoxazole were most effective against MRSA, with cloxacillin showing significant resistance. Vancomycin was also the most effective treatment for E. faecalis, whereas azithromycin exhibited high resistance levels. Among gram-negative bacteria, Gentamicin was most effective against E. coli, while Rofloxacin showed the highest resistance; Imipenem was most effective against P. aeruginosa, with Amikacin showing significant resistance. A significant association was found between multidrug-resistant (MDR) vaginal infections and GDM. Conclusion: The study concluded that there is no significant association between MDR vaginal infections and gestational diabetes mellitus among pregnant women.
Frequency of Malaria in Children with Fever Without Localizing Sign in Age Less Than 36 Months
Authors: Muhammad Ibrahim  , Afzal Khan
Published: February 2025

Background: Malaria remains a significant cause of fever in children in malaria-endemic regions, particularly in those presenting with fever without localizing signs. Early and accurate diagnosis is essential for timely intervention and effective treatment, but diagnostic challenges persist in resource-limited settings. Objective: To assess the prevalence of malaria in children aged 1 to 36 months presenting with fever without localizing signs. Study Design: Cross-sectional study. Duration and Place of Study: The study was conducted from February 2024 to August 2024 at the Pediatrics Department, Lady Reading Hospital (LRH), Peshawar. Methodology: A total of 121 children, aged 1 to 36 months, with fever (≥38°C) and no apparent localizing signs were enrolled. A 3 mL blood sample was taken for Giemsa-stained blood smear microscopy to detect malaria parasites. Demographic data, including age, gender, family history of malaria, and socioeconomic status, were recorded. Results: The study included 121 children, with a mean age of 20.0 ± 9.52 months. The prevalence of malaria was found to be 14%, with 17 children testing positive. Stratified analysis revealed no significant associations with age, gender, weight, socioeconomic status, or residential area, but a significant correlation was observed with a family history of malaria (p = 0.000). Conclusion: This study confirms malaria as a common cause of fever in children under 36 months in high-endemic areas. Despite coexisting infections, malaria remains a key concern. We emphasize the diagnostic challenge, highlighting the need for comprehensive strategies and awareness to ensure timely, accurate diagnosis and effective treatment of febrile illness in children.
ĐẶC TÍNH HÌNH THÁI THỰC VẬT CỦA CÂY CAM RỪNG ĐƯỢC PHÁT HIỆN TẠI TỈNH KHÁNH HÒA
Authors: Lê Đặng Công Toại , Phan Đức Ngại
Published: February 2025

This study described the
plant morphology of Wild Orange discovered in Khanh Hoa province. The description of
plant morphology was based on IPGRI (1999) descriptors for Citrus spp. by describing tree characteristics; Collect 30
samples of leaves and flowers, 10 samples of ripe fruit; Molecular genetic
analysis (gene); Analysis of essential oil content in leaves and fruit peels of
Wild Orange trees. The results showed that the Khanh Hoa forest orange tree has
the scientific name Citrus hystrix DC., the same name Citrus
macroptera Montrouz. and has a common
Vietnamese name of Chuc, is a highly adaptable species, has good resistance to
external conditions and has a very high essential oil value, an average of 2.3%
in leaves and 6.8% in oil. pods, but the number of individuals in the wild is
very small. The research results provide scientific data for the evaluation,
storage, conservation, and effective exploitation of wild orange genetic
resources.

Agile best practices, thought leadership collective impact impact
investing to families. And equal opportunity vibrant, the, storytelling
synergy metadata matters B-corp unprecedented challenge. Venture
philanthropy cultivate impact, state of play; white paper collaborative
consumption entrepreneur collaborative cities inclusive. Parse empower
communities movements targeted; radical; social enterprise issue outcomes
big data venture philanthropy.
Test đăng bài
Authors: Nguyễn N
Published: February 2025

c v b

Agile best practices, thought leadership collective impact impact
investing to families. And equal opportunity vibrant, the, storytelling
synergy metadata matters B-corp unprecedented challenge. Venture
philanthropy cultivate impact, state of play; white paper collaborative
consumption entrepreneur collaborative cities inclusive. Parse empower
communities movements targeted; radical; social enterprise issue outcomes
big data venture philanthropy.
Sprout Up Movement: Strategy Formulation Based on Factors Influencing Youth Intent to Pursue Agriculture
Authors: Barlongo Arvin Joshua P.
Published: February 2025

Analysts predict the Philippines will face a deficit of farmers in the next 10 to 12 years, as the average age of farmers is 55 to 59 years. This challenges food security, with fewer youth interested in agriculture. To address this, the Sprout Up Movement was launched in 2022 to highlight the personal stories of those in agriculture through social media, to rebrand agriculture and engage young people. Theory of Planned Behavior argues that perceived behavioral control (PBC), including employment opportunities and personal confidence, significantly impacts attitudes toward agriculture, affecting subjective norms and intention to pursue an agriculture-related degree. A surprising finding is the indirect relationship between PBC and intention, mediated by attitude, a connection not widely explored in existing research. Strategies were developed using pseudo-quantitative methods like Internal Factor Evaluation and External Factor Evaluation, along with the I-E Matrix, SWOT Matrix, and Quantitative Strategy Planning (QSP) Matrix. The QSP matrix suggests the best path forward for the Sprout Up Movement involves expanding and building partnerships with higher education institutions and enhancing social media content to highlight employment opportunities and boost the youth’s confidence to pursue agriculture-related careers.
“Graduate-Gestalt” Case Study Analysis of DSU And DSBS Students
Authors: Tewari* Shweta ,   Assistant professor School of commerce and management, Dayananda Sagar university , Bengaluru Email: shweta.tewari@dsu.edu.in, Subbarao Nagaraj ,   DeanSchool of commerce and management, Dayananda Sagar university , Bengaluru. E, Kelkar Bhushan ,   Neuflex Talent Solutions Pvt. Ltd , Pune Director Neuflex Talent Solutions Pvt.Ltd., Kelkar Madhura ,   Neuflex Talent Solutions Pvt. Ltd , Pune Director Neuflex Talent Solutions Pvt.Ltd.
Published: February 2025

Openness to learning is a critical competence and capabilities as we advance in the new normal
and post-pandemic world. Assessing student personality, learning styles and ability to learn is
essential to any business school's success.
The Graduate-Gestalt Test is a personality assessment tool developed by Neuflex Talent Solutions
Pvt Ltd, Pune. This tool is beneficial in understanding the characteristics of a student to choose
first of all the most relevant career path and second, to know how to improve performance in
curriculum-based tests and exams using appropriate study methods that are relevant to the
student.
The assessment to delineate student characteristics and learning styles was carried out in February
2021 for students of the School of Commerce & Management Studies, Dayananda Sagar University,
Bengaluru. The test also placed students in various categories which are relevant to required job
skills as signified by industry in general and organizations in particular like, empathy, personality,
creativity, innovation, emotional and resilience. The test outcome is a brilliant foundation for
the mentorship process that follows the assessment and was used as a counselling tool where a
student's learning experience during their MBA program was immensely improved.
Software Defined Networking (SDN) (Analysis & Future Direction)
Authors: - Siva Kumar Mamillapalli
Published: February 2025

Software-defined networking (SDN) is a modern network architecture that separates the control and management planes from the data plane, aiming to enhance network manageability and programmability. Its programmable nature has led to widespread adoption in academia and industry. However, SDN faces various challenges during implementation and integration with existing technologies. This paper assesses different SDN approaches across seven key areas: network testing, flow rule installation, network security, and controller platforms. Each area significantly influences SDN implementation, ensuring efficient packet handling, secure policies, and effective resource management. Comparative analysis of existing studies offers insights into their classifications, benefits, and limitations, guiding future research directions.
Performance Analysis of J2SE and J2EE in Enterprise Level Applications
Authors: - Hareesh Kumar Rapolu
Published: February 2025

The following research project has exemplified the performance analysis of J2SE and J2EE in the context of enterprise level applications. It has measured the performance levels which has catered to explore the handling of both the frameworks to manage huge sets of data. J2SE provides limited scalability and security features while J2EE has nurtured advanced security and scalability characteristics. This has served to be crucial in the segment of lifecycle management for determining successful enterprise applications. Therefore, the relevant findings have promoted making curated decisions. This has been intriguing for selecting the best platform that is fully baked on application requirements.
Accelerating Clinical Trials with Gen AI-Powered Data Analytics: A Transformative Approach to Drug Development
Authors: - Ramesh Betha
Published: February 2025

Clinical trials represent one of the most critical and resource-intensive phases in drug development, often spanning several years and consuming substantial financial resources. This white paper explores how generative artificial intelligence (Gen AI) and advanced data analytics are revolutionizing the clinical trial landscape, offering unprecedented opportunities to accelerate the process while maintaining rigorous scientific standards. We examine the current challenges in clinical trials, present innovative solutions powered by Gen AI, and discuss their practical implementation across different phases of clinical research.
Developing a Sustainable Groundwater Management Plan of Udupi taluk of Udupi District- A Coastal area of Karnataka State
Authors: - Deepa Gupta , - Rahul R Shende
Published: February 2025

Udupi taluk, part of Udupi district, is classified as "Safe" based on the 2022 dynamic groundwater resource assessment. To improve and manage groundwater resources effectively, a detailed study of aquifer potential is essential. Subsurface aquifer data has been gathered through exploratory drilling and used to create 2D and 3D sections, along with fence diagrams/models using Rockworks software. The Central Ground Water Board's National Aquifer Mapping and Management Program aims to map aquifers, characterize water-bearing formations, and develop management plans for sustainable groundwater use. Although Udupi taluk is categorized as "Safe," maintaining this status requires proper management. With the implementation of Artificial recharge structures, water use efficiency method and irrigation methods like drip and sprinkle can significantly enhance groundwater resources with changes in cropping pattern. The proposed groundwater development plan aims to increase groundwater development from 35% to 60% systematically using a scientific approach.
Thinking Styles and Work Performance of Accountants in their Workstations
Authors: - Maria Avegail B. Estrada
Published: February 2025

The influence of three thinking style approaches towards the level of work performance along counterproductive behavior, contextual and individual tasks of twenty-four accountants in government offices situated in Naga City during the Fiscal Year 2024 was determined using descriptive-correlational method. Findings indicated a strong significant relationship exists between thinking styles and work performances of government accountants. This meant that each thinking style is significantly correlated with the work performance of accountants. The use of a particular thinking style is dependent on a particular situation or task assigned to accountants. The extent of influence of the three thinking styles towards the aspects of work performance was moderately low as indicated in the statistical analyses. Comparable traits exhibited by accountants are connected to their choice of thinking style approach to accomplish tasks or to cope with problems. The use of specific thinking style approaches of accountants was molded in their homes, schools and workplace. Furthermore, a very satisfactory level was achieved for all three aspects of work performances of accountants.
Equity vs. Obligation: An Examination of How Mandatory Pro Bono will Affect Young Lawyers and the Justice Gap
Authors: - SK NOOR MAHAMMAD
Published: February 2025

The word justice simply signifies righteousness, reasonableness and just treatment. Access to justice means everyone is equally getting easily access to this justice system. Access to justice is the basis of rule of law without this no one can get access to justice even their rights are being hampered or an offence being committed against them. But in India there are lots of obstacles have on the path of this access to justice system i.e. Complex legal procedure, huge advocate fees, poverty, illiteracy, lack of infrastructure etc. And poverty among them is prevalent cause. India's maximum people have lower income and illiterate as well. Therefore they are not getting accessed to this justice system. Consequently many jurist or politicians suggesting to make pro bono legal services mandatory for lawyers to mitigate this issues. In this paper we will discuss the advantages and disadvantages of this thinking. And also will define the various term related to this.
Walkable Street Design for Congested Urban Areas: Pedestrian's Perception and Attitude
Authors: - Mansi Gambhire , - Ankita Patole , - Tejas Rokade , - Amruta Vyas
Published: February 2025

Many people concerned with pedestrian safety and "walkability" cares about these issues because they feel that walking is good exercise or that walkable places are more attractive or that walking is better for the environment than driving. These are all valid arguments and may convince some of those reading this article that walkability is important. But from user point of view, that is, streets where walking is safe and enjoyable, that people are drawn to visit on foot, and where fast and extensive car traffic is not the #1 priority. Streets where walking is safe and easy are streets where businesses usually thrive. Streetscape enhancements add value to an area and are associated with higher rents and the attraction of new businesses. In addition there is good evidence to show that improving walking and cycling environments raises private property values by significant amounts. So the current study focuses on the design of walkable streets for congested areas. While doing so, the focus is also kept on user’s perception and attitude towards walkable streets.
Integrating Quantum Blockchain and AI for Secure Healthcare Systems: Architecture and Future Directions
Authors: - J.Sivarani , - B.JayaVijaya , - C.Meena
Published: February 2025

The rapid evolution of healthcare systems, coupled with advancements in the Internet of Medical Things (IoMT), has introduced unprecedented security and privacy challenges. Traditional security solutions fail to address emerging threats posed by quantum computing and AI-driven cyberattacks. This paper proposes an Integrative Quantum Blockchain and AI-Driven Security Framework for Healthcare Systems, incorporating Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), and AI-powered threat detection. The proposed framework enhances data integrity, authentication, and resistance against cyber threats, while optimizing energy efficiency. This paper presents the architecture, security benefits, performance analysis, and future research directions for integrating quantum blockchain and AI in healthcare security.
BERT-Based Fake News Detection: A Transformer-Driven Approach for Misinformation Classification on Twitter
Authors: - Roise Uddin , - Abdul Basit , - Yearanoor Khan , - MD Sahria Jaman Shazib , - Shahadat Hossain
Published: February 2025

The rapid spread of fake news on social media platforms, particularly Twitter, poses a critical challenge to information credibility. This research presents an advanced fake news detection framework leveraging deep learning models, including XGBoost, CNN-RNN, BERT, and RoBERTa + GNN, to enhance detection accuracy. Our approach integrates content-based analysis, social context features, and explainable AI techniques (SHAP, LIME) for robust classification.We trained and evaluated our models on the FakeNewsNet, PolitiFact, and Kaggle fake news datasets, employing state-of-the-art feature engineering techniques such as semantic embeddings (RoBERTa, XLNet), sentiment analysis, and network propagation modeling. Experimental results demonstrate that our RoBERTa + GNN model achieves the highest accuracy of 98.7%, outperforming BERT (98.0%), CNN-RNN (84.0%), and XGBoost (81.0%). The precision, recall, and F1-scores of our models also indicate strong classification performance, with RoBERTa + GNN achieving an F1-score of 98.4%.By integrating explainability techniques, we ensure model transparency, allowing insights into the key linguistic and contextual factors influencing classification. This research contributes to improving automated misinformation detection, reducing the impact of fake news, and supporting real-time deployment for social media monitoring. Future work includes expanding cross-lingual capabilities and enhancing early detection using temporal features.
The Role of Information technology in Improving the Accuracy and Efficiency of Accounting Data
Authors: - Md Firoz Kabir , - Md Imran Chowdhury Rana , - Md Atiqur Rahman
Published: February 2025

This paper aims to examine how info technology (IT) impacts accounting treatments, with a particular focus on how IT boosts the performance and quality of safe and transparent accounting operations.
Approach, method, and style: A quantitative analysis used a broad spectrum of academic literature and earlier research studies. 194 professionals and users of accounting details were given surveys to finish to collect information for the study, which used a sample of industrial enterprises in America. The information was evaluated, and the research study hypotheses were evaluated using analytical analysis, which consisted of structural formula modeling (SEM-PLS).
Findings: The findings reveal a strong positive correlation between cost, security, IT adoption, accounting data effectiveness, and efficiency.
Research study limitations and ramifications: The study points to various limitations that must be considered when translating the outcomes, such as sample size limitations and possible self-reporting predisposition.
Practical implications: The study recommends spending cash on accounting professional training and human resources to properly utilize necessary accounting software applications. Services can optimize the benefits of IT in their accounting details systems (AIS) by dealing with execution problems.
Originality/value: By providing insights into how innovation might improve organizational accounting procedures and performance, this research study adds to the expanding corpus of literature on the nexus of accounting and IT.
Unmasking Reality : Advanced Deepfake Detection for Images and Videos
Authors: - Dr. S. Brindha , - Ms. I. N. Sountharia , - Mr. V. S. Thaneshvar , - Mr. J. S. Jayanishanth , - Mr. R. Rathivarman , - Mr. R. Udaya Ganesh
Published: February 2025

Techniques for creating and manipulating multimedia information have progressed to the point where they can now ensure a high degree of realism. DeepFake is a generative deep learning algorithm that creates or modifies face features in a superrealistic form, making it difficult to distinguish between real and fake features. This technology has greatly advanced, promoting a wide range of applications in cinema, such as improving visual effects in movies, as well as various criminal activities, such as misinformation generation by mimicking famous people. To identify and classify DeepFakes, research in DeepFake detection using Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has attracted increased interest. Essentially, DeepFake is regenerated media obtained by injecting or replacing some information within CNN and RNN models. This paper summarizes the DeepFake detection methods for face images and videos based on their results, performance, methodology used, and detection type. The challenges in generating a generalized DeepFake detection model are also analyzed.
The Digital Transformation of Indian Elections: Opportunities and Challenges for Democratic Integrity
Authors: - Monika , - Shivam Chaturvedi
Published: February 2025

ABSTRACT
Good governance is fundamental to the stability and growth of any society, as it provides the foundation for a robust societal framework. In this context, digital transformation plays a crucial role in enhancing governance by fostering greater transparency, efficiency, and inclusivity. With two-thirds of India’s population currently using smartphones, and projections indicating one billion users by 2026, initiatives such as C-Vigil,Saksham ECI app, and the Digital India campaign have significantly empowered the nation, promoting civic engagement and voter awareness. These digital initiatives facilitate informed participation in the democratic process and enhance governmental accountability. While technology has undeniably improved decision-making and voter autonomy, it also introduces new challenges, including the potential for errors in judgment. The integration of technology in governance strengthens decision-making and public accountability, ensuring greater responsiveness and adaptability to future challenges. This study explores how digital technologies can enhance the efficiency, transparency, and inclusivity of India’s electoral processes, while also addressing risks to democratic integrity, such as cyber security concerns, unequal access to technology, and regional disparities. Additionally, challenges like the absence of independent vote verification, and the misuse of social media, artificial intelligence, and fake advertising, raise critical concerns for the integrity of digital elections. The influence of social media content from political rallies, along with the lack of transparency in advertisement funding and political messaging verification, underscores the need for a comprehensive approach to safeguard electoral integrity in the digital age. The digitalization of citizen services delivery in India is ushering in a new era of transparency and integrity, empowering citizens and strengthening the social contract. Digital platforms allow citizens to submit applications, track their status, and access information on various services offered by government departments. This eliminates the need for physical visits and reduces the risk of manipulation or delays. Integrity is critical to democratic governance, yet the concept is interpreted and applied in myriad ways. Electoral integrity is monitored worldwide to ensure that elections are free, fair, and competitive. Monitory institutions or watchdog bodies have been institutionalized to scrutinize abuses of power (Keane 2009). Within other areas of democratic innovation, debates on integrity are more advanced and have reflected on the elements of empowerment and control (e.g Goldfrank 2021).
Novel Insights into Oscillation of Impulsive Fractional Differential Equations with Caputo Derivative
Authors: Fatima Rabbiya , Niazi Azmat Ullah Khan , Raza Hassan
Published: February 2025

In this paper, we explore the oscillation of impulsive Caputo fractional differential equations. Conditions for both asymptotic and oscillatory outcomes are established through the application of the inequality principle and Bihari Lemma. An example is given to explain the results of all problems. This is the first time to study the oscillation of impulsive fractional differential equation with Caputo Derivative.
Acrylic Copolymer Stabilizer for Cost Optimization of Earthy Road Construction
Authors: Hamza Omer , Zumrawi Magdi , Mahmood Hassan
Published: February 2025

This study proposes an assessment of the utilization of acrylic copolymer as stabilizer in earthy road construction. The objective is to provide low-cost alternatives that reduce road maintenance annual cost and reduce the period between major rehabilitation. Conducting a suite of laboratory tests to evaluate the properties of soil and gravel mixture before and after the use of acrylic copolymer stabilizer and evaluating the cost feasibility by analyzing the test results. The soil engaged in this study was a local soil collected from borrow pit in Hadida oil field in west of Sudan, while the gravel soil was obtained from Altomat in west of Sudan too. The local soil was mixed with 30%, 50% and 70% gravel. Optimum moisture content and maximum dry density of the soil-gravel mixture were measured for each sample of proposed mixing percentage. CBR for each sample was measured before and after treatment by acrylic copolymer. The acrylic copolymer used in this study was obtained from Saudi Arabia provided by Sabco Co. and it is used for commercial purposes. The stabilizers amount used was 7% and it is in liquid formula. Remarkable improvement on compaction characteristics was obtained when 7% of liquid acrylic copolymer mixed with the soil-gravel. Addition of acrylic copolymer stabilizer to 50% soil and 50% gravel has increased MDD by almost 40%. The improvement on CBR when acrylic copolymer used is 180%. The results obtained from this experimental study evident the great effect of polymers on soil strength.
DESIGN AND PERFORMANCE OPTIMIZATION OF A HYBRID WIND-SOLAR ENERGY SYSTEM FOR HIGHWAY APPLICATIONS
Authors: Muhammad Nawazish Wasi  , Irfan Ullah Khan  , Muhammad Ibrahim Akbar  , Hafsa Asif
Published: February 2025

Rapid advancements in technology and the escalating demands of modern consumers have made energy an indispensable component of daily life, necessitating increased energy production. However, the predominant reliance on finite and depleting conventional energy resources presents challenges to energy security. Therefore, it is imperative to explore alternative and innovative technologies to fulfill energy deficit sustainability. The most viable solution to address this challenge is the adoption of renewable energy sources. Vertical-axis wind turbines, when integrated with solar panels, present an efficient hybrid system for electricity generation. The aim of this project was to maximize the efficient utilization of wind and solar energy to achieve optimal electricity generation. To accomplish this, a highway was selected as the project site, providing wind energy due to continuous movement of traffic. This project consisted of designing and testing of a Savonius Vertical axis wind turbine that harnessed energy from both wind and solar sources, with the generated energy being stored in batteries to subsequently power streetlights and other electrical systems. Measurements of wind speed at different time at location site revealed that the average wind speed in these areas is approximately 8.3 m/s, showing the potential for wind energy generation in such environments. The VAWT prototype has generated a peak power of up to 47.1 watts from moving traffic. It was concluded that Savonius Vertical axis wind turbine is ideally able to supply streetlights and other public amenities with power at an upgradable scale. It is recommended to implement and evaluate alike projects to assess their feasibility and efficiency, thereby contributing to long-term sustainability.
SONOGRAPHIC ASSESSMENT OF ACUTE APPENDICITIS IN PATIENTS WITH ABDOMINAL PAIN:PREVELANCE AND DIAGNOSTIC ACCURACY EVALUATION IN DISTRICT MANSEHRA
Authors: Waqas Ahmad  , Zoha Shafique  , Eisha Razia  , Ibrar Ahmad  , Asad Ur Rehman  , Naima Mobeen
Published: February 2025

Background:
 Acute appendicitis is a common condition that typically affects individuals with abdominal pain, especially those aged 10 to 19. There is a 7% life time risk of acute appendicitis. Ultrasound is the most commonly used diagnostic tool, offering high sensitivity and specificity for identifying acute appendicitis.
OBJECTIVES:
To diagnose the acute appendicitis by using ultrasound in patients presenting with abdominal pain in District Mansehra.
METHODOLOGY:
This cross-sectional study included 101 patients. This study specifically focused on patient presenting with abdominal pain of age group 10 to 40 years both males and females. Acute appendicitis was measured via ultrasound.
RESULTS:
The peak age for acute appendicitis is between 10 to 19 years. The ultrasound  has a sensitivity of 85% and a specificity of 67%.
CONCLUSION:
Ultrasonography is a reliable, non-invasive diagnostic tool for assessing the acute appendicitis. Ultrasound has a high sensitivity of 85% and specificity of 67%, with an overall diagnostic efficacy of 81%.
ASSESSING THE IMPACT OF E-CRM ON CUSTOMER LOYALTY: THE MODERATING ROLE OF SERVICE QUALITY
Authors: Maryam Ahmad  , Farhina Hameed
Published: February 2025

This study examines the impact of Electronic Customer Relationship Management (e-CRM) on service quality and its subsequent effects on brand image and customer loyalty within the banking and retail sectors, using data from branches of Al-Falah and MCB Bank in Islamabad and Rawalpindi. Employing a quantitative research methodology, the study collected data from 300 customers using a structured questionnaire based on validated scales. The research specifically inspected whether improved service quality mediated by e-CRM enhances brand image and how this, in turn, influences customer loyalty. The study also examines the mediating factor of consumer satisfaction serving in these relationships. Preliminary findings indicate that effective e-CRM implementation significantly enhances service quality, which positively affects brand image and strengthens customer loyalty, particularly when consumer satisfaction is high. The paper highlights the importance of integrating e-CRM into the customer service strategies to boost customer perceptions and create loyalty, offering valuable theoretical and practical implications.
ENHANCED CROWD EMOTION DETECTION IN OCCLUDED ENVIRONMENTS USING YOLOV5 AND CONVOLUTIONAL NEURAL NETWORKS
Authors: Tahmeena Mai  , Nazia Batool  , Mehreen Fatima
Published: February 2025

A deep learning methodology examines facial emotional identification when faces exist in partially obstructed conditions of crowds. YOLOv5-tiny functions for face detection while RepVGG handles emotion classification within this method. Training of the emotion recognition model employed FER-2013 dataset but detection enhancements came from processing WIDER FACE dataset. Experimental testing shows that YOLOv5 reaches a 91% detection success rate while RepVGG delivers an 87.5% accuracy level in emotion classification above standard CNN architectures such as ResNet and Efficient Net. The system detects emotions directly in real-time streaming video data which qualifies it for application in crowd monitoring and surveillance and behavioral analysis solutions. Future research initiatives aim to develop better methods for handling obscuration along with methods to optimize speed when applying the system to large-scale deployments.
ENHANCING IOT SECURITY: THREAT MODEL-BASED ANALYSIS IN THE WEB OF THINGS ECOSYSTEM
Authors: Noreen Khalid  , Shafaat Ahmed Bazaz
Published: February 2025

The Internet of things using collaborative technologies such as 5G, cloud, artificial intelligence, analytics, and automation enables people and objects/devices to communicate with each other at anytime and anywhere using the internet. The aim of this study is to understand the phenomenon of the Internet of Things and identify security, privacy, and trust threats associated with it. For this, we used a renowned Microsoft threat model such as STRIDE and a threat analysis tool like DREAD to examine the security threats through IoT Soil moisture system and this application is deployed on an IoT device as Nucleo board. Using this threat modeling technique, we came to know the security gaps of an IoT based system and how to find the threats of that particular system. Also, we found that how to secure that particular system by using this threat modeling technique. Moreover, how IoT devices are perceived in terms of privacy and security by people and what factors they must keep in mind while buying, using, and disposing of such devices.
PREDICTIVE MODELING OF CARDIOVASCULAR DISEASE USING MACHINE LEARNING APPROACH
Authors: Sadia Latif  , Sami Ullah  , Aafia Latif  , Ghazanfar Ali  , Muhammad Hassnain Azhar  , Salman Ali
Published: February 2025

The primary causes of death worldwide are Chronic Cardiac diseases. Accurately diagnose and predicting chronic cardiac disease is important to the proper treatment of cardiac patients before a heart attack occurs. The goal of accurate disease prediction will be achieved using a ML algorithm with health examination data. Early prediction of the risk factors of cardiac disease is critical for preventing heart disease. In our research, this is a follow-up study the statistical analysis will be used to assess the prediction of CCD as many high-risk factors (hypertension, smoking, high blood cholesterol, increasing age, male gender, being overweight) are involved. The heat-map cluster and machine learning algorithm provide interactive visualization for the classification of patients with different CCD stages. Early stages of cardiac patients are grouped into one cluster and advanced staged cardiac patients could be at high risk for the expeditious decline of heart function and should be closely monitored. The clustering heatmap provided a new predictive model for health care management for patients at high risk of rapid CCD progression. This model could help physicians make an accurate diagnosis of this progressive and complex disease.
The current situation of the application and the factors affecting the implementation of Vietnamese public sector accounting standards in non-business units
Authors: Nguyen Thi Minh Giang
Published: February 2025

Vietnam's accounting system, particularly in the public sector, is experiencing significant changes to align with international regulations. Accordingly, the Ministry of Finance has been gradually issuing and implementing the Vietnamese public sector accounting standards to provide regulations and principles as a basis for recognizing, presenting, and disclosing information in line with international practices. However, the implementation is not straightforward due to the incompleteness of the issued standards. Additionally, public sector accounting, especially in non-business units, is governed by accounting standards, the accounting regime, and various other financial regulations. This article employs both qualitative and quantitative research methods to examine the current state of application and the factors influencing the adoption of Vietnamese public sector accounting standards in non-business units. The research results identify four factors affecting the adoption of Vietnamese public sector accounting standards in non-business units. These factors include the accountants' qualifications and experience, their awareness of usefulness, coercive pressure, and the legal documentation system. The article proposes recommendations to enhance the application of public sector accounting standards in non-business units. This will contribute to information transparency and improve the accountability of these units.
Factors influencing customer satisfaction in digital banking: The case study of Vietnam
Authors: Ngo Duc Tien
Published: February 2025

The satisfaction of customers is a crucial determinant of the success or failure of commercial banks in Vietnam. The primary aim of this study is to discover the crucial aspects that have a substantial impact on the happiness of individual consumers about digital banking services offered by Vietnamese commercial banks. For this study, we conducted a survey of 290 individual customers from multiple commercial banks in Vietnam. The findings from the Exploratory Factor Analysis (EFA) revealed that the pleasure of individual customers was highly influenced by five factors: Tangibles, Responsiveness, Empathy, Reliability, and Assurance. Hence, the results of this study have consequences for the development of solutions, aiming to enhance digital banking services for individual clients in commercial banks in Vietnam.
Motivations for organic rice purchase: The case of Vietnamese consumers
Authors: Nguyen Thi Hong Cam , Nguyen Thuy Phuong
Published: February 2025

Green consumption has become the prominent topic in contemporary marketing. While developed countries have embraced the concept for decades, it is relative new in many developing countries. Hence, this study aims to explore green consumption with the case of organic rice in Vietnam, a developing country with significant population. 249 Vietnamese consumers were involved in the study with factor analysis and multiple regression specifications. The results indicated that affordability concerns have the most influence on the purchase decision, followed by health and packaging considerations. Based on these results, the study had enriched the organic consumption literature and had suggested implications for the stakeholders.
Economic motivation and other drivers of consumers for public transportation - Metro forward circular economy in Hanoi
Authors: Nguyen Thi Thuy Dung
Published: February 2025

The article studies the economic efficiency of switching the transportation of a group of individuals (96 people) in Hanoi in March 2024 from existing means to public transport, Metro. The research calculates the economic efficiency of that transfer activity for individuals based on three factors: age, income, and distance travelled, and it finds out whether the factors influence these groups by One-way ANOVA Test. In addition, the study also found seven groups of factors that can significantly influence consumers' switching decisions and conducted an AHP Analytic Hierarchy Process (AHP) analysis to determine the main factors promoting their switching. The study results found several statistically significant differences, showing that distance will significantly impact economic efficiency. The study also supported the idea that economic benefits are not the leading factor in the switching decisions. From there, the study also made several related comments and recommendations.
The impact of multi-cultural environment on employee performance at multinational companies in Ho Chi Minh City
Authors: Tran Quoc Dat , Vo Khac Thuong
Published: February 2025

This research aims to analyze the impact of a multicultural environment on employee performance in multinational companies (MNCs) in Ho Chi Minh City. The author then uses SPSS and AMOS software for quantitative data analysis through the following steps: descriptive statistics, Cronbach's Alpha analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). The research model on the impact of the work environment on employee performance is tested through these analyses.
Factors affecting the efficiency of Vietnam's joint stock commercial banks
Authors: Nguyen Anh Thu
Published: February 2025

Five years after the National Assembly's Resolution 42/2017/QH14 on the settlement of credit institutions' bad debts and the Prime Minister's Decision 1058/QD-TTG approving a plan for credit institution restructuring, this study assesses the effectiveness of Vietnam's Joint Stock Commercial Banks (JSCBs). Using the Data Envelopment Analysis (DEA) technique, a quantitative method, this study evaluates the efficiency of 18 selected JSCBs in Vietnam between 2018 and 2022. It employs the Tobit model and Ordinary Least Squares (OLS) model to investigate the factors that affect efficiency. The findings demonstrate that, with an average technical efficiency index of 44.09%, banks underutilize their input resources between 2018 and 2022. To increase business efficiency, JSCBs in Vietnam should manage human resources, increase capital mobilized from deposits, and enhance income from credit activities. Furthermore, empirical data indicates that JSCBs can function more efficiently if their total assets and equity are increased, and their existing loan portfolio is reduced.