bluuebunny/crossref_metadata_2025 huggingface dataset:
On Strong Fuzzy Resolving Set of Fuzzy Wheel Graphs
Authors: Isnaini Rosyida
Published: February 2025

Let Image be a fuzzy set on Image. A fuzzy labeling graph Image is a graph with bijective membership functions Image and Image so that each vertex’s membership degree and every edge’s membership value are different. Further, it satisfies Image for Image. “A graph formed from a single vertex connected to the vertices of a cycle of length Image is called a wheel graph with Image vertices". In this paper, we construct an algorithm for fuzzy labeling of wheel graphs. Under the algorithm, we have the degrees of vertices and edges are different and the monotone decreasing. The vertex Image gets the biggest degree among other vertices. Further, the edge Image is assigned to the biggest degree, and Image obtains the smallest degree. We also show the “strength of connectedness" between vertices in the fuzzy wheel graph. Finally, we investigate the “strong fuzzy resolving set" (SFRS) of the fuzzy labeling wheel graph with Image vertices and get the strong resolving number Image.
LMI Approach to Dissipative of Memristive Inertial Neural Networks with Time-Varying and Distributed Delay
Authors: S. Premalatha
Published: February 2025

This article explores the dissipative property of Memristive Inertial Neural Networks (MINN) enclosed with the time-varying and distributed delay terms. Filippov solution approach is adopted to the memristive system for its memristive property. Variable substitution is applied to the MINN to reduce the system order. A suitable Lyapunov function is designed with the reduced system to ensure the dissipative of MINN. To ensure the dissipative criteria of the system, Linear Matrix Inequality (LMI) technique is employed. Besides, the bound of attractive sets of MINN are inferred. In the meantime, adopting the convex relaxation technique, a Parametrized LMI(PLMI) is employed to derive the dissipative criteria, which is less conservative. Finally, a numerical calculation is carried out for the verification of theoretical result.
Applications of Second-Order Differential Subordination Considering Mittag-Leffler Poisson Distribution Series to a Class of Analytic Functions
Authors: S. Sridevi
Published: February 2025

In this paper, we establish an innovative subclass of analytic functions by utilising the Mittag-Leffler poisson distribution series and acquire some number of Differential Subordination (DSO) results.
Utilizing YOLOv10 and YOLO11 for Tomato Ripeness Detection in Vertical Farming
Authors: Sarvesh Mahadev Shendkar
Published: February 2025

Introduction: With the increase in urbanization, the amount of available agricultural land is constantly decreasing. Vertical farming presents one such solution to this problem, combined with new technologies, making it a more reliable and profitable approach.
Objectives: This study is set to evaluate the performances of YOLOv10 and YOLOv11 models for the ripeness detection process in the harvesting of tomatoes with the aim of performing efficient and automatic harvesting.
Methods: The research used an open dataset containing 667 images, divided into three classes: ripe, rotten, and unripe tomatoes. The YOLOv10 and YOLOv11 models were trained and tested, and their performances were evaluated with the metrics mAP@0.5, precision, and classification accuracy.
Results: The YOLOv10 model had an mAP@0.5 of 0.706, and YOLOv11 had 0.695. The rotten class had the highest precision at 0.8, and the ripe class was the hardest to classify, being most frequently confused with background. YOLOv11n was faster but slightly less accurate compared to YOLOv10b.
Conclusions: YOLOv11n is faster but less accurate compared to YOLOv10b, and is more suitable for applications requiring precise image analysis in vertical farming. The choice of the model depends on the needs of the application, and the predictions can be used in automating harvesting with a robotic system. Also, if a dataset of large size having variety of images is trained using high GPU, then high increase in accuracy and precision can be seen.
The Comparison of Numerical and Analytical Methods of Concrete Tunnel Seismic Performance Considering to the Interaction of Structure and Soil
Authors: Walaa Hussein Kamil,
Published: February 2025

One of the new methods of industrial construction is the tunnel concrete structural system which makes the issues related to the construction process easier, It also reduces construction time and financial risks. One of the most important factors that cause axial and shear forces and even bending moment in concrete tunnels is the existence of an earthquake. The purpose of the present paper is to compare numerically and analytically the seismic performance of the concrete tunnel with regard to the interaction between the soil and the structure. This research wants to say that although analytical methods may eventually reach the answer, but in most cases, either the answers are very long and difficult, or we may not be able to measure the dynamic load correctly in the tunnels. So, in order to investigate the seismic performance of the concrete tunnel, taking into account the interaction between the soil and the structure, we use numerical methods. For this purpose, using numerical methods in this treatise, we use FLAC3D software in order to model the behavior of structures built in rock and soil. The main advantage of the numerical method of the current paper compared to other analytical methods is that it shows continuous maintenance coverage. In the analyses of the present research, types of coarse-grained sandy, sandy-grained and fine-grained soils were used so that a relatively complete range of soil types was considered. In addition to these, in order to investigate the effect of density, various types of soils with high density and low density were used. Also, the number of concrete pieces with continuous concrete coating - that is, 3, 5 and 7 pieces - was checked. Here, the results showed that by increasing the modulus of deformation of the bending moment value, the amount of axial force in the tunnel's concrete cover decreased. And on the contrary, the amount of force increases. Now, if we want to show the thickness of the tunnel maintenance cover more, we will face an increase in the amount of bending moment. Finally, if we want to increase the number of concrete parts of the maintenance cover, then the amount of axial force and maximum shear force will decrease.
Memory Effect of Deformable Mean and Deformable Standard Deviation
Authors: Hari Pratap
Published: February 2025

Memory effects can be easily understood with the help of fractional derivatives. In this paper with the help of Deformable fractional derivative we try to understand the role of deformability on memory effects of a normal distribution using moment generating function. First, we develop a formula for Deformable mean and Deformable standard deviation with the help of Deformable fractional derivative. Secondly, we calculate the value of Deformable mean and Deformable standard deviation for varying fractional order. Lastly, we draw plot of normal distribution for calculated value of Deformable mean and Deformable deviation with varying fractional order and give conclusion.
Sustainable Engineering and Management Practices Enabled by Green AI Technologies
Authors: Bajirao Subhash Shirole
Published: February 2025

The paper examines how Green AI combines with sustainable engineering approaches to management systems. AI stands as a revolutionary approach which improves ecological resource patterns while reducing environmental consequences across economic sectors because society demands sustainable efficient solutions. The research evaluated artificial intelligence techniques Support Vector Machine (SVM), Artificial Neural Networks (ANN), Decision Trees (DT) and Genetic Algorithms (GA) to study their specific applications toward sustainable development in the fields of agriculture, construction and urban planning. The analysis indicates AI-based solutions achieve better performance than traditional ones regarding energy efficiency and waste reduction as well as decision optimization. The predictive capability of SVM improved overall energy consumption by 25% but the resource utilization of ANN reached 20% better than existing models. AI integration into blockchain and IoT systems led to increased sustainability advantages that result in better operational performance in addition to improved environmental sustainability. The research illustrates how Green AI extends its reach toward enabling sustainable development together with fostering environmentally conscious practices for diverse academic disciplines. The urgent need for comprehensive research regarding AI applications for developing efficient resource-based and environmentally beneficial systems emerges as crucial.
A Study of Perceived Ease of Use, Perceived Usefulness and Self-Efficacy to use Artificial Intelligence Among Accounting Students in Malaysia
Authors: Noral Hidayah Alwi
Published: February 2025

The increasing use of AI-enabled tools and procedures in accounting is driving a dramatic shift in what students learn today, as well as the essential skills and talents required for future professionals to survive in this dynamic world. A national thrust on the digital economy has included artificial intelligence (AI) courses in response to the present global shifts impacting higher education across the globe. According to the Malaysia Digital Economy Blueprint (2021), digital skills should be incorporated into higher education curricula to ensure that graduates are agile and competent in the future workforce. As a result, introducing AI into daily accounting tasks will substantially affect the work environment. Students with poor levels of digital literacy may experience difficulty at employment. Therefore, the purpose of this study is to investigate how self-efficacy, perceived usefulness, and perceived ease of use relate to technology adoption of AI in their studies. A quantitative research survey was adapted to analyse 172 respondents for 24-question questionnaire. The results of the study indicate that all factors such as self-efficacy, perceived usefulness, and perceived ease of use significantly influence technology adoption among accounting students in distance education, particularly in their integration of AI tools into their learning processes.
Optimizing Graph Algorithms for Large-Scale Networks: A Mathematical Framework
Authors: Radheshyam R Sharma
Published: February 2025

A mathematical framework for optimising graph algorithms for large-scale networks is presented in this paper. The effectiveness and scalability of classical graph algorithms are severely hampered by the growing complexity and scale of networks. This study presents new optimisation strategies, such as graph partitioning, heuristics, and parallel computing tactics, that improve algorithm performance using sophisticated mathematical models. The framework exhibits enhanced computing efficiency and decreased processing time for a variety of graph-related activities, including network flows, connectivity assessments, and shortest path computations, by utilising rigorous theoretical analysis in conjunction with empirical testing. The results offer a significant step in facilitating the management of large datasets found in contemporary applications, such as social networks, biological systems, and telecommunications. In the end, by providing workable methods suited to the requirements of large-scale networks, this study advances the fields of graph theory and network optimisation and makes data administration and analysis more efficient.
Neighbourhood Sum VDB Indices and Entropy for Specific Types of Molecular Graphs
Authors: Vijayakumar K
Published: February 2025

Introduction: Numerous TIs for different molecular graphs have been found and studied. The entropy measurements and the neighbourhood sum degree-based M-polynomial are derived for the six different anti-asthmatic drugs by using a set of 19 degree-based topological indices in this article.
Objectives: Develop the neighbourhood sum degree-based M-polynomial for different anti-asthmatic drugs to characterize their molecular graphs. Compare the entropy measurements obtained for them.
Methods: Based on these molecular descriptors, it is practical and effective to analyse the mathematical values and conduct additional research on a molecule's numerous physical properties. They offer helpful substitutes for drawn-out, costly, and labour-intensive laboratory investigations. Using quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs), the topological indices can be utilized to predict chemical structures, physicochemical properties, and biological activities.
Results: Based on their matching molecular structures, the topological indices of the six different anti-asthmatic drugs   are determined in this article.
Conclusions: A graphical comparison of the calculated indices is made to examine how they relate to the molecular structure and to one another.
A Study on Performance Measure of FM/FD/1 Queueing Problem using LR-type Trapezoidal Fuzzy Numbers by LR Method
Authors: S. Vijaya
Published: February 2025

Many Queueing models have been solved under fuzzy environment using triangular and trapezoidal numbers of fuzzy type where they are extensively used in real-life applications which are implemented frequently in day-to-day life. LR method has been presented in this paper to examine FM/FD/1 queueing model that directs to system performance measure implementing capacity in limited form and the calling source with unlimited form.  The expected inter-arrival interval, service interval follow fuzzy manner having single server  with no bounds and are expressed as LR-type trapezoidal fuzzy numbers.  Fuzzy environment has been preserved in this model with unlimited bounds with the circumstances related in direction to randomness and connected under fuzziness of LR-type.   A numerical illustration has been analysed and solved in this model using trapezoidal fuzzy numbers of LR type by LR method and taken for comparison with DSW(Dong, Shah & Wong) Algorithm.  The comparative example illustrates the applicability, efficiency and sustainability of the LR type model.
A Hybrid Model for Brain Tumor Segmentation using VGG16 and ResNet50
Authors: V.R. Elangovan,
Published: February 2025

Cancers of the brain are among the worst illnesses a person may get. The course of medical therapy is mostly determined by the tumor's location and kind. Neuro specialists and radiologists must carefully review Magnetic Resonance Imaging (MRI) pictures in order to arrive at a definitive diagnosis of a malignancy. Treatment option mapping, disease progression monitoring, and image-based tumor segmentation are of utmost importance in medical imaging because they provide information vital for cancer analysis and diagnosis. Some have speculated that deep learning might be the key to better brain cancer diagnosis and treatment. With its state-of-the-art segmentation and detection capabilities, the segmentation strategy has significantly improved the removal of abnormal tumor regions from the brain. In this study, we published a VGG16 and ResNet50 hybrid model for MRI brain tumor segmentation. With the use of the ResNet50 algorithm and the VGG16, a Transfer Learning method, brain tumors may be detected in segmented pictures. The findings show that our suggested approach is more accurate and performs better than other models when compared side by side.
On the Structure of σ_(1 )Near - Rings
Authors: V.Alies Anbukani
Published: February 2025

If, in a ring (N, +, ∙) we ignore the commutativity of ‘+’ and one of the distributive laws, (N, +, ∙) becomes a Near-Ring. If we do not stipulate the left distributive law, (N, +, ∙) is a right near-ring. This research aims to introduce the concept of σ_1near-ring. N is called σ_1near - ring if N is a right near-ring and xy^2=yxyfor all x,y∈N .The element wise characterization for σ_1near-ring will be investigated and shall establish theorems and properties in this near - ring.
Bridging AI and Human Understanding: Interpretable Deep Learning in Practice
Authors: Amith Kumar Reddy
Published: February 2025

Deep learning influences industry; hence, explainable artificial intelligence (XAI) is significant. Transparent deep learning models enhance the interpretability of AI-driven decision support systems. SHAP, LIME, and model-specific interpretability elucidate intricate AI system decisions. SHAP evaluates predictions in cooperative game theory. It assesses the least decision-making impact of each feature in the model. Locally interpretable surrogate forecasts are analogous to LIME black-box outcomes. Model behavior may validate expectations and expose deficiencies.
Management of Banks – An Empirical Study on Managers Role in Organising and Staffing Functions
Authors: Ramakrishna Sripada
Published: February 2025

In truism growth in developing economies  has profound impact on various sectors of it more specifically, Banking. As a territorial sector Banking plays a level playing field in an economy in general. On account of globalization of economic activities across the globe , the role of banking has also multiplayer in its role towards economy promotion.
A Qualitative Review On Islamic Microfinance
Authors: Melala Imane, Keffi Meriem
Published: February 2025

This qualitative review examines the evolving landscape of Islamic microfinance  through an analysis of 40 Scopus-indexed articles published between 2010 and 2023, which were then processed using Nvivo 12 software. This research found a strong emphasis on the core principles of Sharia compliance, poverty alleviation, and financial inclusion. Keyword analysis highlights the importance of institutional infrastructure, social impact, and operational realities in the IMF sector.
AI-Powered E-Commerce Personalization and Recommendation Systems
Authors: Sri Tulasi T, Inayath Ahamed S B
Published: February 2025

The rapid growth of e-commerce has necessitated advanced AI-driven solutions to enhance user experience through personalization and recommendation systems. This research explores the application of Deep Reinforcement Learning (DRL) as a cutting-edge AI method for optimizing e-commerce recommendations, dynamically adapting to user behavior in real time. Additionally, TensorFlow Recommenders (TFRS), an advanced AI tool, is leveraged to build scalable and efficient personalized recommendation models. By integrating DRL and TFRS, this research demonstrates how AI can improve customer engagement, increase conversion rates, and drive business growth in the digital marketplace. The findings highlight the potential of AI in transforming e-commerce personalization with intelligent, data-driven recommendations.
Sustainable Business Growth- Perception and Perseverance of Women Entrepreneurs
Authors: Radha Thangarajan
Published: February 2025

The primary goal of any developing nation like India has been achieving sustainable economic growth since independence. Development of an economy of a country and the society could be achieved through sustainable growth of women especially in rural India equivalent to urban region. The government of India has been framing many developmental schemes and policies for promoting women entrepreneurs. But still, the sustainable growth of rural women entrepreneurs is a big dream. The problems and factors behind such volatility are multidimensional and need to be examined well. This empirical paper aims to analyze the factors for volatility in the sustainable growth of women entrepreneurs. 180 rural women entrepreneurs registered under Tamilnadu MSME have been selected from Virudhunagar district using a questionnaire and personal interview through multistage cluster sampling. The study finds that the level of engagement of rural women in the entrepreneurial arena has been swiftly increasing every year which is not matching with the economic growth of women due to multidimensional challenges such as lack of knowledge in accessing resources, demographic reasons, lack of competency, lack of awareness and education, lack of entrepreneurial and technical skill, etc. Apart from framing policies and promotional schemes, the government has to take measures to ensure the reach of the same in rural areas for attaining the sustainable growth of women entrepreneurs and the rural economy as well
Enhanced Customer Churn Prediction for CRM Using PBGL-WPLM and Optimized ANN Models
Authors: N. Senthil Madasamy
Published: February 2025

In today.s digital landscape, the information sector is the dominant service provider, results intense competition among them. To maintain strong market presence, service providers need to concentrate on customer churn, retention and customer satisfaction. Customer relationship management (CRM)  strategies were particularly developed to improve , maintain and establish long term relationship with customer.  Churn occurs when a customer switches from one service provider to another one. Predicting customer churn is challenging due to the lack of identifying churn reasons for customer churn. As a result, determining the efficiency of a prediction model is also dependent on how well the data can be interpreted in order to identify potential reasons for churn. Here Populace Based Gradual Learning — Wide and Profound Learning Models(PBGL-WPLM) method, Structure Optimized Simulated Annealing ANN, and Structure Optimized Hybrid  SA-PBIL ANN methods are evaluated using the CRM dataset from the American media transmission associations and compared with novel technology called Populace Based Gradual Learning — Wide and Profound Learning Models Network Factorization(PBGL-WPLM-NF). Agitate is determined as the quantity of clients who leave the help somewhere in the range of 61 and 90 days subsequent to being tested.
Dynamic Nonlinear Analysis of Human Resource Management in Public Administration and Regional Development
Authors: Anna Levchenko
Published: February 2025

This article presents a comprehensive dynamic nonlinear analysis of human resource management (HRM) within the context of public administration and regional development. By employing advanced mathematical modeling techniques, we explore the intricate relationships between HRM practices and their impact on organizational effectiveness and regional growth. The study utilizes nonlinear differential equations to capture the dynamic interactions among various HRM variables, including recruitment, training, retention, and performance evaluation. Through simulations and case studies, we demonstrate how nonlinear dynamics can reveal critical insights into the adaptive behaviors of public institutions in response to changing socio-economic conditions. Our findings highlight the importance of strategic HRM in fostering sustainable development and enhancing public service delivery. This research contributes to the theoretical framework of HRM in public administration and offers practical implications for policymakers and administrators aiming to optimize human capital in regional development initiatives.
The Importance of Financial Management for Blind Students at School
Authors: Ashari Ismail
Published: February 2025

This review article explores the significance of financial management education for blind students in school settings. It highlights the unique challenges that visually impaired students face in managing finances and the critical role of financial literacy in promoting their independence and self-sufficiency. By examining current literature, best practices, and educational strategies, this article aims to emphasize the need for inclusive financial management programs tailored to the needs of blind students. The findings underscore the necessity of equipping these students with the skills and knowledge required for effective financial decision-making, which is essential for their future success.
Advanced Predictive System for Diagnosing Patient Disease through Machine Learning Techniques
Authors: Vivek Raj Singh, Shwet Ketu
Published: February 2025

The aim of this research is to develop a web application that predicts multiple diseases, including Diabetes, Breast Cancer, Heart Disease, Alzheimer disease, brain tumor, Covid-19, and Pneumonia, using machine learning and deep learning models. The models were trained on large datasets sourced from Kaggle. The study includes data collection, preprocessing, model selection, and deployment of the trained models. The application uses Python Flask as the web framework, and models such as CNN (for Covid-19, and Pneumonia) are integrated to ensure accurate predictions. This project achieved prediction accuracies of up to 97% for certain diseases, showing the viability of machine learning in healthcare applications. The findings suggest that the developed system could support early detection of disease and improve healthcare outcomes.
DOI:https://doi.org/10.52783/pst.1562
專題式學習運用在國小環境教育課程之實踐歷程與成效
Authors: 姜緯珊 姜緯珊 , 詹惠雪 詹惠雪
Published: February 2025

本研究旨在探討專題式學習運用在國小五年級環境教育課程的實踐歷程，以及透過自編環境教育素養量表了解學生之學習成效，自112年10月至12月以Big6技能作為教學步驟進行二循環20節課程，透過環境素養量表、Big技能評量表、教師省思札記、課堂觀察紀錄、訪談紀錄、Big6學習單等多方面的資料，進行綜合分析。本研究主要發現如下：一、先由教師引導專題式學習再逐步釋放由學生自主探究，但仍需持續深化。二、Big6技能需結合多元策略協助學生完成專題實作。三、專題式環境教育課程能提升學生環境素養。四、學生在Big6技能的取得資訊、利用資訊與整合資訊方面有顯著提升。

 

This study investigated the application of Project-Based Learning in the fifth-grade environmental education curriculum of elementary schools, with the aim of understanding its effectiveness and impact on students’ learning as measured against a self-developed Environmental Education Literacy Scale. From October to December 2023, two cycles of 20 lessons were conducted using Big6 skills as the teaching steps. A comprehensive analysis was performed using various data sources, including the Environmental Literacy Scale, the Big6 Skills Assessment Scale, teachers’ reflective notes, classroom observation records, interview records, and Big6 worksheets. The findings showed that (1) teacher first led students to complete the Project-Based Environmental Education Curriculum and then gradually released them to explore on their own, but there was still a need for continuous deepening of learning; (2) Big6 skills needed to be combined with multiple strategies to help students complete the project; (3) the Project-Based Environmental Education Curriculum could improve students’ environmental literacy; and (4) students’ Big6 skills of “Location & Accessing,” “Use of Information,” and “Synthesis” significantly improved through Project-Based Learning.

 
ONE APPROACH TO ASSESSING THE ENERGY INTENSITY OF DRY TURNING AND BORING OF METALS WITH A CUTTER WITH A MULTI-STEP BLADE
Authors: Arshakyan A.L. , Zakaryan M.E. , Balasanyan B.S.
Published: February 2025

The aim of the work is to find ways to reduce the energy intensity of dry turning and boring of hard-to-cut metals with a cutter with a multi-step blade by determining the cutting depth of each cutting step based on the condition of equality of their effective cutting powers.
A virtual laboratory for studying the total power of turning and boring processes of metals using a multi-step blade cutter has been developed in the LabView software environment.
It has been established that the use of a cutter with a multi-stage blade allows to significantly reduce the energy intensity of the processes of turning and boring of metals in comparison with the process of cutting with a conventional cutter, which monotonically decreases with an increase in the number of its cutting stages. It has been shown that even in the case of using a two-stage cutter, the energy intensity of the process of turning the materials under study decreases 1.45 ... 1.73 times, and with an increase in the number of cutting stages of a multi-stage cutter upto k = 9, the energy intensity of the process of turning the materials under study decreases 2.93 ... 5.00 times.
Research in this direction is going on. It is planned to conduct research on the process of turning metals with a multi-stage cutter, the cutting depths of the cutting stages of which will be determined from the condition of equality of the periods of resistance of each cutting stage.
The developed virtual devices can be used in the design processes of multi-stage passing and boring cutters at the stage of developing the technology of external turning and internal boring of various metals and alloys, which can be useful for graduate, postgraduate students and researchers engaged in mechanical engineering specialties to conduct their own virtual research.
The authors are ready to provide the virtual devices they developed in the LabView software environment free of charge to all interested parties for studying the total power of metal turning and boring processes using a multi-stage blade cutter.
THE POSSIBILITY OF INCREASING THE PRODUCTIVITY OF DRY TURNING AND BORING OF METALS WITH A MULTISTAGE BLADE CUTTER
Authors: Balasanyan B.A.
Published: February 2025

Processing of external and internal surfaces with a turning passing or boring cutter is one of the main and common types of mechanical processing of materials by cutting with a blade tool, which is widely used in various branches of mechanical engineering, automotive, shipbuilding, and aircraft engineering. It is shown that the main problem of the dry turning process is its low productivity. It is proved that an additional reserve for increasing its productivity can be the use of a turning passing or boring cutter with a multistage blade. A virtual laboratory has been developed in the LabVIEW software environment to establish the possibility of improving the productivity of dry turning and boring of metals and alloys, as well as their quantitative assessment for various numbers of cutting stages of a multi-stage cutter compared with the turning and boring process with a conventional cutter using a coolant. It has been found that the use of a cutter with a multistage blade, compared with the processes of turning and boring metals and alloys with a conventional cutter with the use of coolant, allows the dry turning of these metals with a simultaneous increase in processing productivity up to 28%. The results obtained can be used in the metalworking industry, which will allow, in addition to increasing processing productivity, to improve the environmental friendliness of production of various machine parts. Research in this area is going on. In order to determine the optimal modes of dry turning of metals with a multistage cutter, it is planned to conduct comprehensive virtual studies of this process using the methods of mathematical planning of experiments. The developed virtual device has a user-friendly interface and will find application both in the design processes of multistage cutters. It can be useful to undergraduates, graduate students and researchers of engineering specialties when conducting their research. The author is ready to immediately provide the virtual device he developed in the LabVIEW software environment to all the interested parties.
Acceptability, Feasibility, and Preliminary Effectiveness of a Wellbeing Coordination Program in an Integrated Health and Social Care Hub: A Mixed Methods Study
Authors: Chen Lingling , White Natalie , Patten Emma , Barth Danielle , Constable Leanne N. , Hall Teresa , Kabir Ashraful , Hiscock Harriet , Loveday Sarah
Published: February 2025

Introduction: Families experiencing adversity often have complex needs and face barriers to accessing health and social care. This study evaluated the acceptability, feasibility and preliminary effectiveness of a Wellbeing Coordination (WBC) program to improve access to services. The program combined care navigation and social prescribing within an integrated health and social care Child and Family Hub.
Methods: Mixed-methods design, with data collected through surveys and interviews from: 1) caregivers who participated in the WBC program (n = 11) and those who did not (n = 18), and 2) practitioners working in the Hub (n = 21).
Results: Caregivers and practitioners found the WBC program acceptable and mostly feasible, demonstrating the potential to alleviate caregivers’ loneliness and enhance their health, connection to the community, and knowledge and confidence in supporting child and family health and wellbeing.
Discussion: Future WBC program enhancements could include a robust communication strategy to ensure what the program offers is clearly understood by practitioners and caregivers, establishing organisational structures to provide adequate support for the wellbeing coordinator and adopting flexible eligibility criteria.
Conclusion: The WBC program appears acceptable and feasible. Future research should establish program effectiveness with larger and more diverse caregiver samples.
First reported case of a synchronous occurrence of cervical carcinosarcoma and endometrial adenocarcinoma showing radiological differentiation on MRI: A case report and diagnostic challenges
Authors: Koike Hirofumi , Kurohama Hirokazu , Nakamura Takaaki , Takenoshita Shintaro , Koga Miyuki , Oka Taiga , Morikawa Minoru , Harada Ayumi , Toya Ryo
Published: February 2025

Introduction: Synchronous cancer, which is when a secondary cancer occurs simultaneously or within six months of a primary cancer diagnosis, is rare for malignant female genital tract neoplasms. Despite cervical and endometrial cancers being very common gynecologic malignancies, they do not frequently occur synchronously.

Case Report: Here, we report a case of a 49-year-old female patient with a synchronous occurrence of endometrial adenocarcinoma and cervical carcinosarcoma (CCS), an extremely rare and aggressive cervical cancer subtype. Transvaginal ultrasonography showed two non-contiguous masses: one in the cervical canal and one in the uterine cavity. Magnetic resonance imaging (MRI) was then used for further examination. The two masses showed similar high signal intensity on the T2-weighted images and low apparent diffusion coefficient values. T2-weighted images suggested that they were contiguous at the cervix. However, retrospective analysis indicated that the cervical mass showed a relatively higher signal intensity on the T2-weighted images and a stronger, more heterogenous enhancement on the early-phase contrast fat-suppressed T1-weighted images. Additionally, constricted morphology was observed in the cervix, which is not consistent with what is typically observed with invasive endometrial or cervical cancer. Further analysis using histopathology and immunohistochemistry methods indicated a synchronous occurrence of CCS and endometrial adenocarcinoma, which is very rare.

Conclusion: This case effectively demonstrates the diagnostic challenges associated with magnetic resonance imaging (MRI)-based interpretation of synchronous gynecologic cancers, as well as highlights the key imaging features that may help facilitate differentiation of the two pathological types.
"Classroom Perspectives: Student Teachers’ Views On Ict Integration in Teaching"
Authors: Sambasivarao Dr. Rachumallu , Santhi Nehru Dr. Ravipalli Sri , Rajamani Dr. J. , Varahala Dora Dr. R. S.
Published: February 2025

This research paper investigates the perspectives of teacher trainees regarding integrating Information and Communication Technology (ICT) in pedagogical practices within the classroom. The study uses qualitative methodologies to gather insights from diverse student teachers across various disciplines and educational backgrounds. A self-constructed questionnaire is employed to uncover the challenges and opportunities perceived by future educators in incorporating ICT into their teaching. The findings reveal key factors, including the effectiveness of digital tools in enhancing student engagement, the necessity for comprehensive ICT training, and the importance of institutional support. Additionally, the research highlights the role of ICT in promoting collaborative learning environments and its potential to reduce educational disparities. The study contributes to the ongoing discourse on educational technology, offering actionable recommendations for teacher training programs and policymakers to better equip student teachers for the evolving needs of modern classrooms. By amplifying their voices, the research sheds light on how ICT can be leveraged to enrich the teaching and learning experience.
Pedagogical Aspects of the Electronic Lesson in Physical Education Training
Authors: Vakleva Zlatka
Published: February 2025

The electronic lesson and the possibilities for its application in physical education classes is a sustainable trend in the educational process. The development of its pedagogical aspects will support the work of physical education teachers to confidently and flexibly implement the electronic lesson in their professional practice. The article presents a pedagogical study with the aim of developing and popularizing the main pedagogical characteristics of the electronic lesson in physical education. The following are presented: The model and design of the pedagogical study; A brief theoretical overview of the research topic; The steps for developing, the structure and a sample physical education lesson. Conclusions were drawn about: The characteristics and role of electronic lessons in renewing traditional approaches in physical education teaching; The challenges and opportunities they offer in their application in practice; Motivation and engagement of participants.
Deserción Estudiantil en la Universidad Nacional Autónoma de Nicaragua, FAREM-Chontales en el período 2017-2020 (II FASE)
Authors: Cajina Pérez Ligia Nancy , Martínez Jiménez María Francisca
Published: February 2025

Este artículo destaca la deserción estudiantil en la Universidad Nacional Autónoma de Nicaragua, Managua, UNAN-Managua, FAREM-Chontales, en la Cohorte 2017 - 2020. Para ello, se comprobó la relación de esta y las variables: carrera elegida, semestres estudiados, modalidad de estudio y sexo. En este se describen factores psicológicos, motivacionales, personales y familiares que incidieron en su deserción. Asimismo, se describen elementos académicos, personales e institucionales que motivaron su salida. Esta situación afecta a todas las universidades en el mundo entero y la UNAN-Managua no es la  excepción; año con año se ve afectada por este mal. Antecedentes similares han sido investigaciones cualitativas, en las cuales no se observaron análisis estadísticos con pruebas de hipótesis; por lo que se considera diferente. Se trabajó con dos muestras, la primera fue de 1,215 estudiantes, de estos 446 no desertaron y 769 sí lo hicieron. En la segunda, se trabajaron con 293 alumnos, 108 no desertaron y 185 sí. El método utilizado es cuantitativo y el alcance explicativo.  Por su temporalidad es un estudio transversal. Los aspectos más relevantes del estudio son: la probabilidad de que un estudiante termine el  segundo año de su carrera es de 60% y de que llegue al quinto año es de 35%. Las variables que tienen influencia estadística sobre el abandono estudiantil son: carrera elegida, modalidad de estudio, edad, condición laboral, número de hijos, nivel académico de la madre y del padre, guías  didácticas, material multimedia en clases, modalidad donde cursó la secundaria,  compañerismo, número de asignaturas reprobadas durante la carrera, complejidad de las asignaturas y otros motivos, tales como: económicos, salud y trabajo.
Percepções das práticas pedagógicas: um estudo sobre o Ensino Superior na UEG
Authors: Porfírio Lais Moraes de Oliveira , Vieira Vânia Maria de Oliveira
Published: February 2025

Este estudo analisou as práticas pedagógicas dos professores de licenciatura da Unidade Universitária de Itapuranga, da Universidade Estadual de Goiás (UEG), com o objetivo de entender como essas práticas influenciam o ensino-aprendizagem. A pesquisa se propôs a explorar as estratégias de ensino, métodos de avaliação e a interação professor-aluno no contexto do ensino superior. Para isso, foi realizada uma pesquisa quantitativa, utilizando um questionário estruturado aplicado a 17 professores. Os dados foram tratados com técnicas descritivas e analisados no Microsoft Excel. Os resultados mostram que as metodologias expositivas e dialogadas, apoiadas por recursos audiovisuais, são amplamente utilizadas, acompanhadas por atividades em grupo e práticas colaborativas. Observou-se também uma forte presença de avaliações formativas, focadas no acompanhamento contínuo dos alunos, embora métodos tradicionais, como avaliações pontuais e provas objetivas, ainda sejam comuns. A relação entre professor e aluno se destacou como essencial para o sucesso educacional, reforçando a importância de uma interação positiva. Conclui-se que práticas pedagógicas diversificadas, que conciliam métodos tradicionais e inovadores, são fundamentais para melhorar a qualidade do ensino superior e favorecer o desenvolvimento acadêmico dos alunos.
Diodos emissores de luz de diferentes cores na produção de poedeiras comerciais – revisão de literatura
Authors: Monteiro Nicoly Maria Peres , Verza Samara , Sato Denis , Tamehiro Cláudia Yurika , Porto Petrônio Pinheiro , Bombem Beatriz Del Rey , Santos Ana Paula Millet Evangelista dos , Silva Marcos Augusto Alves da
Published: February 2025

A avicultura de postura é uma atividade que vem crescendo a cada dia, desencadeado por diversos fatores, como a evolução tecnológica no setor, sanidade, genética e a mudança na dieta da população. Programas de iluminação artificial têm sido instalados em granjas avícolas com o intuito de aumentar a produtividade e a qualidade dos ovos produzidos, destacando-se a utilização dos Diodos emissores de luz (LED). Diversas pesquisas com diferentes fontes de iluminação e diferentes cores vêm sendo realizadas e melhorias no desenvolvimento reprodutivo e nos índices de qualidade dos ovos vêm sendo observadas. Este trabalho tem como objetivo revisar a literatura produzida referente à utilização da lâmpada LED na avicultura de postura utilizando diferentes base de dados, como Scielo, Science Direct, Elsevier e Google Acadêmico. Conclui-se que as diferentes cores de LED influenciam em diversos parâmetros produtivos em galinhas poedeiras, como o número, peso e massa dos ovos, fertilidade, eclodibilidade, peso do albúmen, índice da forma do ovo, unidade Haugh, peso e índice da clara, peso e espessura da casca, conversão alimentar e ganho de peso, se tornando uma ferramenta útil e de baixo custo para aumentar a produtividade, reduzindo o custo de produção no setor avícola.
Revolutionizing Disease Detection with U-Net: Enhancing Biomedical Image Segmentation in Healthcare
Authors: Fan Zehao
Published: February 2025

The growth of the global population and environmental pollution have led to an increased prevalence of diseases, putting significant pressure on medical systems worldwide. Manual detection methods are time-consuming and inefficient, highlighting the need for advanced solutions. U-Net, a robust deep-learning architecture designed for biomedical image segmentation, offers a transformative approach to human disease detection. Capable of generating its input data, the U-Net model requires reasonable training time and demonstrates high robustness, making it stable and suitable for real-world applications. This study explores the fundamental concepts and background of U-Net, emphasizing its practical application in patient care. Drawing from past studies, this paper underscores the urgency of integrating U-Net into healthcare for disease detection. It summarizes the impact and improvements of U-Net on biomedical image classification, identifies challenges in building and training the U-Net architecture, and proposes strategies for implementing this deep learning model in health systems to enhance disease detection.
On the Practical Value of Musical Theater Art in Music Education in Colleges and Universities
Authors: Bian Tong
Published: February 2025

As a comprehensive art form, musical theater not only enriches people's cultural life and enhances the cultural taste of the society with its unique charm, but also shows far-reaching multiple values in music education in colleges and universities. It is not only a pusher of cultural prosperity, enhancing social cohesion through entertainment and emotional transmission, but also a valuable resource for art education, effectively cultivating students' aesthetic ability, performance skills, innovative thinking and teamwork spirit, and laying a solid foundation for students' comprehensive development. At the same time, musical theater also carries the important responsibility of cultural heritage, integrating excellent traditional cultural elements into modern artistic expression, and promoting the national spirit. This paper centers on the practice of music teaching in colleges and universities, and discusses in depth the multiple values of the artistic practice of musical theater, including its social practice, artistic education and cultural inheritance. Through the meticulous analysis of the significance and practical value of musical drama carried out in music teaching in colleges and universities, with a view to further promoting the effective application and development of musical drama in music education in colleges and universities.
Research on Production Decision Making Based on Differential Evolutionary Algorithms and Optimisation Models
Authors: Zhao Haihan
Published: February 2025

In this paper, the problem of defect detection and production decision-making in the production process of electronic products is studied in depth. The optimization model and differential evolutionary algorithm are used to solve the challenges of quality control and cost optimization. Firstly, this paper proposes a defect detection scheme based on statistical sampling and hypothesis testing, which optimizes the sample detection cost; secondly, this paper constructs a production cost optimization model based on the defective rate of spare parts and the detection cost, and derives the optimal decision-making scheme under different strategies using differential evolution algorithms; lastly, this paper further extends the model and optimizes the production flow to address the cost optimization problem in a multi-process production process, which indicates that the quality control and cost optimization problems in electronic products production are solved. Finally, this paper further extends the model and optimizes the production process for the cost optimization problem in the multi-process production process, and the results show that the model can effectively reduce the production cost and improve the decision-making efficiency.
Fluorosilicone Surfactants: Properties, Synthesis Methods, and Industrial Applications
Authors: Wang Qianyi , Yang Yilin , Zhang Xinyue
Published: February 2025

Fluorosilicone surfactants have garnered significant attention in recent years due to their superior properties resulting from the integration of silicone and organic fluorine materials. Their unique molecular structure imparts exceptional attributes, including heat resistance, weather resistance, corrosion resistance, and hydrophobic and oleophobic characteristics. These properties render fluorosilicone surfactants indispensable in various industrial applications, such as the rubber industry, coatings, metal lubrication, and electronics. The chemical structure of fluorosilicone surfactants predominantly comprises Si—O—Rf and Si—C bonds. The Si—O—Rf bonds confer notable flexibility and reactivity, while the Si—C bonds provide enhanced stability. Among the synthesis methods for fluorosilicone surfactants, hydrosilylation and free radical polymerization are the most prevalent. Researchers are also investigating more environmentally friendly synthesis techniques to advance green chemistry. This article provides a comprehensive review of fluorosilicone surfactants, including their structural characteristics, physicochemical properties, synthesis methods, and applications. It emphasizes their extensive potential across various sectors, such as rubber, coatings, metal lubrication, and emerging fields. Furthermore, it explores future application prospects and the potential for environmentally sustainable development in novel industries.