bluuebunny/crossref_metadata_2025 huggingface dataset:
IMPACT OF NOVOROSSIYSK BORA ON THE UPPER LAYER OF THE BLACK SEA
Authors:   Marine Hydrophysical Institute, Russian Academy of Sciences, YAROVAYA D.A. , EFIMOV V.V. ,   Marine Hydrophysical Institute, Russian Academy of Sciences
Published: February 2025

The structure of atmospheric fields during the bora and the response of the sea to the strong Novorossiysk bora on February 7-8, 2012 have been simulated with the WRF-NEMO coupled numerical model with a resolution of 1 km. Development of strong air currents over the lee side of the Caucasus Mountains and a temperature rise in the atmosphere over the coastal part of the sea are noted. The parameters that determine the features of the bora development are estimated. The perturbations of temperature fields in the sea are analyzed. It is shown that the response of the sea surface temperature field to the wind impact was spatially heterogeneous: during two days of the bora, the water temperature decreased near the Caucasian coast and, on the contrary, increased further off the shore. A cause for such heterogeneity is considered. It is shown that the development of deep penetrating convection started about 0.5 days after the bora onset. As a result of the bora passage, the temperature at the depth of ~40 m, where the layer of the warmer water that remained from the summertime upper quasihomo-geneous layer was situated, dropped by 1-1.5°C, and the thickness of the quasihomogeneous layer increased by two times, up to 60 m. The changes in the temperature and thickness of the quasihomogeneous layer resulted from the entrainment of the warmer water from underlying levels and the cooling due to sensible and latent heat fluxes from the sea surface. A characteristic effect of the bora development is analyzed, namely, a mesoscale quasi-two-dimensional vortex in the atmosphere over the southeastern part of the sea, which is associated with the features of the air flowing around the northwestern edge of the Caucasus Mountains. A response of the sea to this vortex is considered.
SOURCES OF ERRORS IN FORECASTING SURGE LEVEL FLUCTUATIONS AT THE DON RIVER MOUTH BASED ON HYDRODYNAMIC MODELING
Authors:   Zubov State Oceanographic Institute, ZEMLYANOV I.V. , PAVLOVSKII A.E. ,   Zubov State Oceanographic Institute, MILYUTINA I.YU. ,   Zubov State Oceanographic Institute, GORELITS O.V. ,   Zubov State Oceanographic Institute
Published: February 2025

The paper deals with methodological aspects of short-term forecasting of water levels based on the hydrodynamic model of the Don River mouth area coupled with the hydrothermodynamic model of the Sea of Azov. The Don Model calculation-simulation package makes it possible to promptly transmit to interested users the information about water level changes in the navigable branch of the Don River so that this information is provided with a daily lead time and hourly discreteness. These calculations are especially relevant in forecasting surges. The paper analyses the results of prognostic calculations for the period of the trial operation of the Don Model package, as well as the results of diagnostic calculations aimed at identifying the main sources of forecast errors in the periods with intensive surge fluctuations.
CENTENNIAL VARIABILITY OF DISSOLVED OXYGEN IN THE UPPER LAYER OF THE BLACK SEA
Authors:   Institute of Natural and Technical Systems, Russian Academy of Sciences, POLONSKII A.B. , VALLE A.A. ,   Institute of Natural and Technical Systems, Russian Academy of Sciences
Published: February 2025

Archival data on the concentration of dissolved oxygen and the temperature of the upper layer of the Black Sea over the past 100 years are analyzed. It is found that in both the northwestern and open parts of the sea in the period from 1923 to 1932, the lowest concentrations of dissolved oxygen in the past 100 years were observed. They were equal to about 260 μM, which was significantly (by 14-33%) lower than the concentration of oxygen in the upper layer of different parts of the Black Sea observed during the period of its decline 50 years later. It is shown that the decrease in oxygen levels in the 1920s-early 1930s was primarily due to the anomalous heating of the surface water layer during this period. This is its fundamental distinction from the decline in dissolved oxygen that falls on the last quarter of the 20th century and the beginning of the 21st century. The main reason for occurrence of the secondary minimum of oxygen was eutrophication of water, which started in the northwestern part of the sea and then spread to the inner parts of the water area.
FREQUENCY OF STORM WAVES IN THE SEA OF AZOV ACCORDING TO MODELING
Authors:   Lomonosov Moscow State University, MYSLENKOV S.A. ,   Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, ARKHIPKIN V.S. ,   Lomonosov Moscow State University
Published: February 2025

The storm activity in the Sea of Azov from 1982 to 2020 is analyzed. The data on the wind wave parameters have been obtained using the WAVEWATCH III model and NCEP/CFSR/CFSv2 reanalysis. The ESA SST CCI and C3S analysis was chosen as a source of data on sea ice concentration. The calculations were performed on an unstructured computational grid with a spatial resolution of 3-5 km for the open part of the Sea of Azov and 200-400 m along the coast. Analysis of the frequency of storm waves with a height of 2-3 m has been carried out. An average significant wave height equal to 0.6-0.65 m is observed in the center of the sea. The maximum significant wave height for the entire simulation period is 3.42 m. A significant negative trend has been found for storms with the wave height above 2 m. A positive significant trend has been revealed for the average annual wave height in the western part of the sea.
SPATIOTEMPORAL DYNAMICS OF TOTAL PETROLEUM HYDROCARBONS IN THE WATER OF THE TAGANROG AND TEMRYUK BAYS
Authors:   Zubov State Oceanographic Institute, POSTNOV A.A. , CHEKMENEVA N.A. ,   Zubov State Oceanographic Institute, KORSHENKO A.N. ,   Zubov State Oceanographic Institute, DOLGOVA A.O. ,   Zubov State Oceanographic Institute
Published: February 2025

Based on the long-term data from the state marine environmental monitoring system, comparison of the parameters of the long-term regime of total petroleum hydrocarbons (TPH) in the water of the Taganrog and Temryuk bays of the Sea of Azov during 1993-2022 was carried out. It was found that the long-term average level of TPH in the Taganrog Bay is spatially homogeneous and does not differ from that in the mouth area of the Don River. In the Temryuk Bay, the most polluted water was detected in the mouth areas of the Kuban River and the approach channel of the port of Temryuk, while the least polluted water was found at the offing at some distance from the coast. In this bay, the greatest contrast in TPH between the mouth area and the offing was observed during the river flood in June-August. In the Taganrog Bay, in addition to the Don runoff, the TPH sources in the bay itself are of great importance. They are probably associated with unintended leakage of fuel and lubricants from ships due to the busy navigation in the bay.
Analisis Biaya Produksi Berbasis Pendekatan Variable Costing pada UMKM Catering Dapur Mutiara
Authors: Zulfatillah Auliya , Basyari Alif Sulthon , Cahyadi Nur
Published: February 2025

The purpose of this research is to analyze how to estimate production costs at the Dapur Mutiara Catering business in October 2023 using a variable costing approach. Cost analysis with the variable costing method is a calculation of production costs that only includes variable cost elements. The method used in the research is a qualitative method with a case study approach. Through cost analysis and preparation of income statements, the study concludes that the sales value of Dapur Mutiara in October 2023 was Rp 20,332,000 with total variable costs to produce the products is Rp 15,113,000, thus in that period the contribution margin value was Rp 5,219,000 with a contribution profit ratio on sales reaching 25.67%. Meanwhile, the total fixed costs reached Rp 500,000, resulting in a net profit value of Rp 4,719,000. Thus, the profit target of 35% targeted by the business owner has not been achieved because the percentage value of net profit on sales is only 23.21%, this happens because the production costs are too high and the selling price is set too low.
La música fílmica de John Williams como transmisora de la esperanza ligada a la tierra
Authors: Valverde Amador Andrés
Published: February 2025

La presente investigación tiene como objetivo evidenciar la presencia de la idea de esperanza, como estado de ánimo ligado a la tierra, en la música fílmica de John Williams, mostrando los recursos empleados para ello por el compositor. De este modo, se propone el análisis de tres secuencias cinematográficas cuyo hilo conductor es la tierra como sustento vital del ser humano. En ellas la música constituye un elemento decisivo para la construcción narrativa de la esperanza, elemento que llega a ser esencial en momentos en que ni imagen ni diálogos hablan de ella. Partiendo de una metodología que se nutre, principalmente, del análisis musical y fílmico, junto a aportaciones de la filosofía, la estética, la psicología y la semiótica, se mostrarán los mecanismos generadores de esperanza en la música creada por Williams.
The Impact of Digital Marketing on Enhancing Entrepreneurial Performance: An Analytical Study in the General Company for Electrical and Electronic Industries
Authors: Ali Abdulsada Ruaa
Published: February 2025

In light of the rapid technological developments and transformations witnessed by the digital world, digital marketing has become an essential strategic tool to enhance the entrepreneurial performance of institutions. The current research aims to study and analyze the role played by digital marketing in achieving entrepreneurial performance by reviewing the basic concepts of both variables and understanding the interactive relationship between them. The research relied on the analytical approach, and the General Company for Electrical and Electronic Industries was chosen as a site for applying the research. A purposive sample of 100 employees in the company was selected, and 93 valid responses were retrieved for measurement. The study concluded that there is a significant relationship and correlation between digital marketing and entrepreneurial performance and that digital marketing is a major driver for achieving entrepreneurial performance through its ability to improve customer experience, increase innovation, and enhance interaction with target markets.
The reflections of organizational communication on decision making: Kurdistan Institute of public administration (KIPA) as a case study
Authors: Muhammed Othman Wuria
Published: February 2025

The study aimed to explore the reflections of organizational communication on decision-making within the Kurdistan Institute of Public Administration in the Kurdistan Region of Iraq (KIPA). To address the research questions, the researcher adopted a sample survey method. Due to the small size of the target population, the questionnaire was distributed to 81 employees, achieving a 100% response rate. Statistical analysis of the collected data was performed using SPSS software. The collected data were analyzed using SPSS software, with regression analysis employed to evaluate the relationship between organizational communication and decision-making effectiveness. The results demonstrated a strong positive correlation (R = 0.699) and an R Square value of 0.488, indicating that 48.8% of the variance in decision-making can be explained by organizational communication. Furthermore, the study underscored effective information management substantially contributes to achieving a competitive advantage, with organizational communication playing a pivotal role in improving decision-making processes. Finally, the study acknowledged certain limitations and proposed avenues for future research to deepen the understanding of this critical relationship.
The role of electronic management in enhancing human resources skills: An analytical study of the opinions of a sample of employees at the College of Administration and Economics/University of Mosul
Authors: Ali Abood Alobeidi Noor
Published: February 2025

The current research focuses on measuring e-management requirements (administrative, human, technical, financial) and human resources skills (technical, intellectual, and communication). In addition to identifying the nature and trends of the influence relationships between them, the study adopted a descriptive-analytical approach and a sample of employees in the College of Administration and Economics at the University of Mosul. The researchers adopted the questionnaire form as the primary tool in collecting data from the individuals who were being researched. After distributing (260) questionnaires, (246) of them were relied upon in the statistical analysis and using some statistical tools, which are (arithmetic mean, standard deviation, relative importance, and confirmatory factor analysis). Accordingly, a number of conclusions were presented, the most prominent of which is that e-management plays a vital role in enhancing human resources skills in the researched college. This is due to the nature and trends of the influence relationship between them, which indicates the level of actual conformity between what the theoretical frameworks include and what the field frameworks produce. The researchers also made a set of recommendations, including the need to move towards enhancing human resources skills in the college under study by benefiting from the contributions of electronic management in a way that leads to the possibility of improving the reality of work at the individual and organizational levels.
The dot total graph of a commutative ring without the zero element
Authors: Asalool Jaber , Ashraf Mohammad
Published: February 2025

Let $\mathcal{R}$ be a commutative ring with $1\neq 0$, $Z(\mathcal{R})$ be the set of zero-divisors of $\mathcal{R}$, and $Reg(\mathcal{R})=\mathcal{R}\setminus Z(\mathcal{R})$ be the set of regular elements of $\mathcal{R}$. The dot total graph of $\mathcal{R}$ is the simple (undirected) graph $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R}))$ with vertices all elements of $\mathcal{R}$, and two distinct vertices $x$ and $y$ are adjacent if and only if $xy\in Z(\mathcal{R})$. In this paper, we study the (induced) subgraph $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R^{*}}))$ of $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R}))$, with vertices $\mathcal{R^{*}}=\mathcal{R}\setminus \{0\}$. After that, connectivity, clique number, and girth of $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R^{*}}))$ have also been studied. Finally, we determine the cases when $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R^{*}}))$ is Eulerian, Hamiltonian, and $T_{Z(\mathcal{R})}(\Gamma(\mathcal{R^{*}}))$ contains an Eulerian trail.
A Study to Assess Structured Teaching Programme on Knowledge regarding Worm Infestation among school age children at selected area Ariyagoundampatti, Salem
Authors: Rajeswari. G Raja
Published: February 2025

Background: Worm infestation is one of the most widespread health problem in the world, especially in developing countries. World Health Organization (WHO) estimated that about 400 million people are infected with intestinal helminthiasis. Helminthic infestations in children are widely prevalent in many developing countries especially in the tropical and sub- tropical regions. Most of these are essentially preventable through good personal hygiene, improved environmental sanitation and effective public health measures. Objectives: 1. To assess the knowledge on worm infestation among school age children. 2. To find out the association of knowledge regarding Worm infestation among school age children with there selected demographic variables. Methods: The design adopted was quasi experimental (pre test and post test) research design. Setting of the study was Urban area (Ariyagoundampatti), Salem. The sample size was 53 and selected through convenience sampling technique by using semi-structural questionnaire. Results: Among 53 samples in pre test, the highest percentage of samples 34(64.1%) of them had moderately adequate knowledge and 19(35.8%) of them had inadequate knowledge. In post test 43(81.1%) of them had adequate knowledge and 10(18.1%) of them had moderately adequate knowledge. Conclusion: There was a significant association in pre test scores on knowledge regarding worm infestation among school children and their selected demographic variables.
A Cross Sectional Study to Asses the Knowledge on Risk Factors of Diabetes among Rural Elderly at Pillahalli Village, Mysuru
Authors: C Ashwini , CM Lingaraju , Munirathnamma Munirathnamma
Published: February 2025

Diabetes is one of the most prevalent common problem all the part of the world India also will became capital on diabetes. International diabetic federation gave danger messages related to diabetes. The WHO estimates that diabetes resulted in 1.5 million deaths in 2012, making it the 8th leading cause of death. However another 2.2 million deaths worldwide were attributable to high blood glucose and the increased risks of associated complications, which often result in premature death and are often listed as underlying cause of death on death certificates rather than diabetes. Hence The aim of this study is to assess the knowledge of risk factors of diabetes mellitus among rural elders at pilllahalli village under Varuna PHC, Mysuru. Objectives: A cross sectional study to Asses the knowledge on risk factors of diabetes among rural elderly at Pillahalli village, Mysuru. Methods: The research design selected for this study was descriptive design. Non-Probability convenient sampling technique was adopted to select 50 rural Elderly at Pillahalli, Mysuru. Result: Result revealed that majority of Rural elderly are have adequate knowledge there is association between the Knowledge with the selected variable such as gender, education, income and also awareness programme. Conclusion: It was concluded that the rural Elderly having Adequate Knowledge on risk factors of diabetes mellitus and there is statistical significance association between The knowledge and demographic variable such as age, gender and occupation. Religious, income, awareness programme.
To Assess the Awareness about the Causative Factor, Control and Prevention of Oral Cancer among the Supportive Staff of The selected Organisation in the Urban Area
Authors: Angad Garje Krishnali
Published: February 2025

Cancer isn’t a single disease. Cancer is a group of diseases characterized by the uncontrolled proliferation of cells. Ignoring the body’s signal to stop, malignant cells multiply to form tumors in organs and tissues or, in the case of blood cancers, crowd out normal cells in the blood stream and bone marrow. When the genetic material of a cell– the DNA– is damaged, mutations can arise, potentially disrupting normal growth and division. An accumulation of mutations can turn normal cells into precancerous cells, which sometimes multiply and evolve into cancer cells. Cancer is a result of the accumulation of this cells.
A Descriptive study to assess knowledge regarding Burn Out Syndrome among the teachers of selected senior secondary schools of district Mandi, Himachal Pradesh.
Authors: pathania Shalini , Sharma Kanupriya , Deepti Deepti , Indu Indu , Deepa Deepa , Deepali Deepali , Deeksha Deeksha
Published: February 2025

Burn-out is a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed. Workplace burnout is described as a state of emotional, mental and physical exhaustion caused by chronic workplace stress that has not been successfully managed. As the stress continues, work interest or motivation is depleted. In the study, “A descriptive study to assess knowledge regarding burn out syndrome among the teachers of selected senior secondary schools of district Mandi, Himachal Pradesh”. A non-experimental research approach and descriptive design was used to assess the level of knowledge of burnout syndrome among the school teachers. Total samples of the study were 100 teachers. A convenience sampling technique was used to select the sample. A self-structured knowledge questionnaires was prepared to assess the level of knowledge regarding Burnout syndrome among the school teachers. There is an association of level of knowledge with gender and area of residence. Whereas the other sample characteristics (age, type of family, religion, marital status, educational status, monthly income, food habits, exercise pattern, previous knowledge) were not statistically significant at 0.05 level of significance. The study concludes that the 50% participants have adequate knowledge regarding Burnout syndrome.
Understanding Postpartum Depression: A Comprehensive Review
Authors: Bharti Neha
Published: February 2025

Postpartum depression (PPD) represents a major public health issue that affects women globally, with substantial implications for maternal well-being, infant development, and family dynamics. Unlike the transient and relatively mild "baby blues," PPD involves persistent emotional, psychological, and physical changes that can severely impair a mother’s ability to care for herself and her child. This comprehensive review explores the multifaceted etiology of PPD, encompassing hormonal, genetic, psychological, and social factors that contribute to its onset. It also examines the diverse risk factors, including hormonal fluctuations postpartum, genetic predispositions, pre-existing mental health conditions, and socio-environmental stressors such as lack of social support and marital discord. The clinical manifestations of PPD are varied, ranging from persistent sadness and fatigue to severe anxiety and difficulty bonding with the infant. Accurate diagnosis is essential and is typically achieved through standardized screening tools like the Edinburgh Postnatal Depression Scale (EPDS) and the Patient Health Questionnaire (PHQ-9). Effective treatment modalities are discussed, including pharmacological interventions, primarily selective serotonin reuptake inhibitors (SSRIs), and non-pharmacological approaches such as cognitive-behavioral therapy (CBT) and interpersonal therapy (IPT). The importance of social support and counseling in the management of PPD is also highlighted. This article underscores recent advances in PPD research, such as the identification of potential biomarkers for earlier diagnosis and the exploration of the gut-brain axis and nutritional interventions. The need for early identification and intervention is emphasized, as these measures are crucial in mitigating the adverse effects of PPD on mothers and their families. By providing a detailed understanding of PPD's etiology, risk factors, clinical manifestations, and treatment options, this review aims to equip healthcare professionals with the knowledge necessary to effectively address this pervasive condition.
Topical Fluorides
Authors: G. Sathyavathy
Published: February 2025

Topical fluorides play a vital role in preventive dentistry by reducing the incidence of dental caries and promoting oral health3. The primary etiological factor in caries development is the demineralization of enamel caused by acids produced by bacterial fermentation of dietary carbohydrates. Indications for topical fluoride use include individuals at increased risk of dental caries, such as children, adolescents, and individuals with compromised oral hygiene, orthodontic patients, and those with dry mouth conditions2. Topical fluorides exert their preventive action by enhancing demineralization, inhibiting bacterial metabolism, and promoting the formation of acid-resistant fluorapatite crystals within the tooth structure. By incorporating topical fluorides into comprehensive preventive care, dental professionals can contribute to improving oral health outcomes and enhancing the overall well-being of their patients6.
Optimizing Soil Moisture Forecasting with Deep Learning Approaches
Authors: Hem Chandra Joshi
Published: February 2025

Humidity alone is an important factor in agricultural production. This influences plant growth, water use, and overall productivity. Accurate moisture forecasts alone are critical to optimizing an irrigation program. conserve water resources and improve agricultural sustainability Traditional moisture prediction models often face the problem of non-linearity and complexity of environmental factors. meteorology and related factors This research present a new deep learning architecture for slowness prediction that combines convolutional neural networks (CNN) and long-term and short-term memory networks (LSTM) to exploit spatial dependencies. Both spatial and temporal information the proposed model combines a variety of data sets. Including past soil moisture measurements. Meteorological information soil properties and culture-specific information. CNNs are used to extract spatial features from multidimensional input data such as satellite images and climate variables, while LSTMs are used to detect temporal dependencies in sequence data. This coupled approach allows the model to efficiently predict soil moisture at multiple spatial and temporal scales. To evaluate the effectiveness of the proposed model. Performance is compared with traditional forecasting methods such as linear regression and decision tree-based models. and other deep learning techniques including single layer models, LSTM and CNN, which are controlled by metrics such as mean square error (MSE), root mean square error (RMSE), error, etc. The R square value of this research emphasizes the potential of deep learning techniques to improve the accuracy of soil moisture forecasts. This provides great benefits for irrigation and water management. Resource Optimization The proposed model provides more accurate and reliable predictions. It can help increase crop yields, reduce water use and promote sustainable agricultural practices. Future research will investigate integration of additional data sources and further refinement of the model to improve accuracy and scalability.
The Triadic Edge: Balancing Innovation, Risk, and Organizational Ambidexterity
Authors: Muhammad Faisha Shahriman
Published: February 2025

Purpose - This paper examines the critical balance between risk management and innovation through the lens of organisational ambidexterity. Ambidexterity, the ability of an organisation to simultaneously explore new opportunities and exploit existing capabilities, is vital in navigating volatility of business environment. Organisations must balance these two approaches to foster growth while mitigating risks. However, achieving this balance poses significant challenges, including resource conflicts, cultural misalignment, and leadership dilemmas.
Design/methodology/approach - The study adopts a conceptual approach, reviewing key literature to identify frameworks and practices that enable ambidexterity. It focuses on the roles of leadership, strategic resource allocation, and adaptive risk management frameworks to build a cohesive theoretical foundation for fostering ambidextrous strategies.
Gaps addressed and contribution - Existing research on organisational ambidexterity predominantly focuses on its application to innovation and market adaptability. However, limited studies address its effectiveness in managing internal organisational issues such as unethical practices, risk control, and leadership challenges. This paper contributes to filling this gap by exploring how ambidextrous principles can be applied to improve internal organisational dynamics.
Findings - Findings suggest that organisations leveraging hybrid leadership models and integrating risk management with innovation processes are better positioned to achieve sustainable growth. The paper highlights the importance of cultural adaptability, dynamic resource allocation, and technological integration as pivotal components of ambidextrous strategies. Case studies and industry examples from sectors such as technology and healthcare provide empirical support for these findings.
Practical implications - The study offers actionable recommendations for practitioners, including adopting governance mechanisms to address resource conflicts, cultivating leadership adaptability, and embedding innovation within risk management frameworks. These insights aim to enhance organisational resilience and competitiveness in rapidly evolving markets.
Originality/value - This paper contributes to the growing discourse on organisational sustainability by exploring ambidexterity. It highlights the intersection of innovation and risk management as a pathway for organisations to thrive amid uncertainty and disruption.
Real-Time Traffic Sign and Signal Recognition for AI-Based Vehicular Control
Authors: Akshay S. Utane
Published: February 2025

Driving Assistance Systems (ADAS) have become integral to enhancing road safety and driver convenience in autonomous and semi-autonomous vehicles. One key component of ADAS is the accurate recognition of traffic signs and traffic lights to assist drivers in following road regulations and improving decision-making. This paper proposes a vehicular control system based on Computer Vision and Deep Learning techniques, designed to recognize traffic signs and lights and provide real-time driving assistance with distance estimation. The system employs Convolutional Neural Networks (CNNs) for traffic sign recognition and a hybrid detection model for traffic light detection, ensuring accuracy in dynamic environments. The proposed system was tested on publicly available datasets and demonstrated significant improvements in detection accuracy and response time, contributing to the development of safer and more efficient autonomous vehicles
Impact of HPC on Multi-Modal Data Integration for Heart Failure Prediction in Clinical Decision Support Systems
Authors: Santosh Kumar
Published: February 2025

Introduction: High-performance computing (HPC) integrated CDSS has played a vital role in making healthcare decisions using the latest computational techniques. This study emphasizes the impact of HPC-enhanced methods on decision support systems (DSS) in healthcare informatics. It focuses on improvements in accuracy, reliability, and usability, and their effects on patient outcomes and healthcare delivery efficiency.
Objectives: Our study aims at designing and implementing an HPC-integrated CDSS framework for the prediction of heart failure. Thus, it can be used for concatenating multimodal data and examining the impact of HPC-integrated CDSS on various types of healthcare informatics, such as EHR, ECG, and medical imaging. In order to improve predictive accuracy, reliability, and operational efficiency with ensemble learning methods.
Methods: The study integrates multimodal data, including Electronic Health Records (EHR), ECG signals, and medical imaging, with advanced machine learning techniques. The proposed ensemble model is benchmarked against traditional approaches like 3D-CNN, RNN, VGGNet, and YOLOv5. The performance of the model was evaluated on several criteria, such as accuracy, precision, sensitivity, and specificity. ROC curve analyses were conducted to examine the performance improvements of the model-based fusion approach over concatenation fusion.
Results: The proposed ensemble model demonstrated excellent outcomes over traditional approaches. Also, it shows superior accuracy, precision, sensitivity, FPR, FNR, and F1 measure.ROC curve analyses demonstrated that the model-based fusion approach significantly enhanced predictive precision as well as clinical decision-making.
Conclusions: This study provides empirical evidence on the benefits of HPC in healthcare decision-making. HPC-integrated CDSS impacts the quality of patient care outcomes and enhances the efficiency of healthcare delivery.
Integrating AI into Constructivist Pedagogy: Strategies and Outcomes
Authors: Zainuddin Wahono
Published: February 2025

This review article examines the integration of artificial intelligence (AI) into constructivist pedagogy, exploring innovative strategies and their educational outcomes. As education increasingly embraces technology, the synthesis of AI and constructivist principles offers promising avenues for personalized learning experiences. This article synthesizes recent literature (2013-2024) to identify effective strategies for incorporating AI in constructivist settings, analyzes the impact on student engagement and learning outcomes, and discusses the challenges educators face in implementation. Findings indicate that AI can enhance collaborative learning, facilitate adaptive learning environments, and promote metacognitive skills. However, the integration of AI in education must be approached with caution, considering ethical implications and the need for professional development for educators. This article concludes with recommendations for future research and practice.
Compute a Finite Presentation for the Automorphism Group of Free Group and Free Abelian Group Using GAP System
Authors: Abdulsatar Jmah AL-Juburie
Published: February 2025

I have developed an algorithm and written a GAP functions pautfreegroup:=function(n)  (Finite Presentation of automorphism Groups of Free group of Rank n), and autfreeabeliangroup:=function(n)  (Finite Presentation of automorphism Groups of Free abelian group of Rank n).  Functions using GAP system for computation of a finite presentation for Aut(F_n ) and GL(n,z) respectively. In order to do that we have given a description for the presentation of  Aut(F_n) and GL(n,z), the automorphism groups of free groups and free abelian groups respectively.
Exploring Magnetohydrodynamic Nanofluid Flow: A Fractional Differential Approach with Homotopy Perturbation Method
Authors: Saranya.K
Published: February 2025

Introduction  This paper investigates the heat and mass transfer processes in a steady nanofluid flow confined between two parallel plates under the influence of a uniform magnetic field. The model incorporates the effects of thermophoresis and Brownian motion, key phenomena in nanofluid dynamics, to better understand the fluid behavior.
Objectives To enhance the model's accuracy and flexibility by reformulating the governing equations into fractional differential equations, which account for memory effects and non-local interactions in the flow dynamics.
Methods  The fractional model is analyzed using the Homotopy Perturbation Method (HPM), an effective semi-analytical technique that provides accurate solutions for nonlinear fractional differential equations.
Conclusion  The results reveal that the Nusselt number decreases with higher thermophoretic and Brownian parameters but increases with the viscosity coefficient. Additionally, nanofluid concentration decreases with increased Brownian motion but rises with the augmentation of the thermophoretic parameter. These findings underscore the advantages of the fractional approach in capturing complex dynamics in nanofluid flows.
Effect of Edge Deletion on the Weak Roman Domination Number of a Graph
Authors: P. Roushini Leely Pushpam
Published: February 2025

Consider a graph Γ with vertex set V and edge set E. For a function g defined on the vertex set having values in the set {0,1,2}, the weight of a vertex x is g(x). The weight of a subset X of V is denoted by g(X) and is defined as the sum of the weights of all the vertices in X. An undefended vertex under g is a vertex a in Γ with a neighbourhood with weight 0. A weak Roman Dominating Function g (WRDF) is a function such that for any vertex x having weight 0, there is a vertex y in the open neighbourhood of x having positive weight such that, under the function h defined on V having values in the set {0,1,2} defined by h(x)=1,h(y)=g(y)-1,h(z)=g(z), if z∈V-{x,y}, there are no undefended vertices in Γ. The number γ_r (Γ), the minimum of the weights of all the WRDFs defined on Γ is called the weak Roman Domination Number of  Γ. The WRDF whose weight is γ_r (Γ) is called a γ_r- function and  γ_r (Γ) is called the γ_r- value of  Γ.With respect to a graph Γ, we say that an edge x∈E^- if and only if its removal will reduce the γ_r- value of Γ. Similarly, we say that an edge x∈E^+ if and only if its removal will increase the γ_r- value of Γ and an edge x∈E^0 if and only if its removal will leave unaltered the γ_r- value of Γ. In this paper, we categorize edges of a graph as belonging to E^-,E^+ or E^0.
Mixed Stereographic Circular Probability Model: A comparative study using M. L Estimation
Authors: D.V. L. Prasanna
Published: February 2025

Now a days, circular statistics has a wide range of applications in the fields of Engineering, Geosciences, Environmental studies, Medicine, Psychology, Economics and Finance etc., such as analyzing angular movements in robotics, orientations in structural Engineering, Seismic wave directions, water and air flow patterns, brain waves in EEG signals, eye ball movements, modeling of economic indicators behaviors which cannot be analyzed using linear statistical methods as the data involves periodic nature.
Many researchers have presented discrete and continuous circular probability models; their properties are discussed. By combining two distinct probability distributions rather than utilizing a single probability model, the T-X family of probability distributions is intended to increase the efficiency and reduce errors. We developed a mixed stereographic circular probability model with this interest. Study is done on same attributes. The maximum likelihood estimators, AIC and BIC values were determined in this study. The model’s output is compared with those of the current existing single circular probability models by using an eye data set from a glaucoma clinic at the University of Malaya Medical Centre in Malaysia.
Building Inclusive Early Childhood Education Through the Role of Parents and Communities
Authors: Wawan Sofwanudin
Published: February 2025

This study explores the role of parental and community involvement in Early Childhood Education (ECE) and its impact on education policies. The main objective is to review existing literature from the past decade (2014-2024) to analyze how these stakeholders contribute to shaping policies that support inclusive, equitable, and sustainable ECE practices. The research design involves a comprehensive literature review, utilizing academic databases like Google Scholar, ScienceDirect, and JSTOR, with a focus on keywords such as "parental involvement in ECE," "community participation," and "ECE policy." Key findings highlight that parental involvement significantly improves children's educational outcomes and fosters stronger connections between home and school. Community participation also plays a critical role in providing support, particularly in under-resourced areas, helping to mitigate educational inequities. However, several research gaps remain, including challenges related to the sustainability of engagement efforts, socio-economic barriers, and the need for more cross-cultural comparisons. The study suggests that policies should be designed to reduce barriers for underrepresented families, promoting long-term engagement through community partnerships. Additionally, schools should adopt culturally responsive strategies to involve families from diverse backgrounds. The implications of this research are significant for policymakers and educators, emphasizing the need for more inclusive policies that foster both parental and community involvement. Future research should focus on longitudinal studies, comparative cross-cultural analyses, and addressing structural barriers to engagement in disadvantaged areas. By addressing these gaps, future studies can further strengthen the role of stakeholders in improving ECE outcomes globally.
Blockchain-Enhanced Project Management Systems in Engineering and Construction
Authors: Nischal silwal
Published: February 2025

This study covers the integration of blockchain technology with project management systems in the field of engineering and construction to create an efficient project workflow with regard to transparency, security, and efficiency. In this research, a blockchain-based framework was created for the sake of streamlining workflows in the management of projects, resources, and waste management. Key algorithms relevant to the implementation of blockchain technology were covered, including PoW, PoS, PBFT, and DPoS. Results will be highly improved in data integrity, real-time monitoring, and cost-effectiveness. For example, resource tracking using blockchain led to a reduction of 25% in the delay of operation. The recycling rates of the waste management system also increased by 30%. Also, the security of project data was improved by 40%, minimizing unauthorized access incidents. Comparative analysis against traditional project management methods also showed the superiority of blockchain in traceability and fraud reductiveness besides better accuracy in decision making. From the findings, there is a tremendous potential of revolutionizing construction project management by providing a secure, transparent, and an efficient platform for all stakeholders. Hence, research benefits may point toward sustainable innovation for future developments in engineering projects, promoting the application of this technology to other industries in the future.
Enhancing Gastrointestinal Disease Detection through Augmented Deep Learning
Authors: Rakesh Sharma
Published: February 2025

In recent years, deep learning has become a cornerstone of advancements in medical imaging, facili- tating significant improvements in early disease detection. This study presents a phased approach to optimizing gastrointestinal (GI) disease diagnostics by implementing a structured data augmentation and preprocessing phase. Leveraging an expanded dataset with novel clinically rele- vant classes, this phase seeks to increase model robustness and classification accuracy. Our methodology employs targeted data augmentation techniques coupled with Ef- ficientNetV2 for detailed feature extraction in endoscopic imagery. Initial results underscore the potential for sub- stantial improvements in diagnostic precision, particularly in identifying nuanced GI conditions. By focusing on this foundational phase, this work establishes a framework for developing advanced AI-driven diagnostic tools tailored for GI disease detection.
The Lorenz Attractor: A Fractal Perspective using MATLAB
Authors: Meghana Bagwe
Published: February 2025

In a 1963 paper, Lorenz proposed that the Lorenz attractor is a complex, infinite surface. We examine this fractal aspect of Lorenz System using MATLAB. Here, we create detailed visualizations of the attractor's fractal structure and corresponding chaotic behavior of the systems. In this article we have demonstrated the fractal graph for real Lorenz as well as fractional ordered real Lorenz system for both real initial conditions.
MATLAB model on Intelligent Controlled Active Filter to Minimize Harmonics in Generated Voltage at Solar Grid with Variable Load
Authors: Rituraj Jalan
Published: February 2025

In the realm of renewable energy integration, such as solar power grids, mitigating harmonic distortions in voltage is crucial for efficient and reliable operation. This paper proposes an intelligent controlled active filter framework designed to reduce harmonic distortions in a solar grid with variable loads. The active filter system utilizes advanced control algorithms to dynamically adjust its operation in response to varying load conditions and harmonic content in the grid voltage. Key components of the framework include real-time harmonic detection algorithms, which enable the active filter to accurately identify harmonic frequencies present in the grid voltage. Based on this information, a control strategy is employed to generate compensating currents that effectively cancel out these harmonics, ensuring that the voltage supplied to the grid remains within acceptable limits as per regulatory standards. Furthermore, the intelligent aspect of the framework involves adaptive control mechanisms that optimize filter performance under changing operating conditions, such as fluctuating solar generation and load variations. This adaptability not only enhances harmonic reduction capabilities but also contributes to overall grid stability and power quality improvement. The effectiveness of the proposed intelligent controlled active filter framework is validated through simulation studies and practical implementation in a solar grid environment. Results demonstrate significant reduction in harmonic distortions, thereby enhancing the reliability and efficiency of solar power integration while complying with stringent voltage quality standards.
Human Gender Identification from Facial Images: A Deep Learning Approach
Authors: Ponukumati Jyothi
Published: February 2025

These in turn find broad applications in security, human-computer interaction, targeted marketing, and social analytics. In this work, we propose a new hybrid deep architecture that reduces the complexity and improves the accuracy of gender classification. Three different models are proposed and tested, namely: (1) a pre-trained EfficientNetB2 model with a classifier on top performed with an average accuracy of 96.73%, thus proving to have strong capability in feature extraction and classification; (2) a hybrid architecture that combines MobileNetV2 and LSTM to leverage the benefits of sequential learning with an average performance of 80% which may indeed capture the temporal dependencies in facial representations; and (3) CNN-LSTM, which combines convolutional feature extraction with sequential processing, giving an average accuracy of 85%. Our comparative analysis with existing methodologies reveals that the proposed model using EfficientNetB2 outperforms conventional approaches in terms of classification accuracy as well as in terms of computational efficiency, and hence is more suitable for real-world deployment scenarios with resource constraints. Moreover, many experiments has been conducted on benchmark datasets which justifies the robustness, generalizability of our proposed models. This presents more significant insights about the development of efficient and high-performing gender recognition systems based on deep learning from facial images, thereby contributing to the advancement of research in facial analysis.