bluuebunny/crossref_metadata_2025 huggingface dataset:
From Reflection to Practice: A Qualitative Study of Teaching Practicum Experiences
Authors: Anis Mohammad Ibne , Hasan Md. Mahadhi
Published: January 2025

This research explores the impact of the Teaching Practicum and Classroom Management course on the development of my pedagogical philosophy, lesson design, resource selection, and instructional methods in the context of TESOL. A qualitative reflective approach and in-depth interview with five student-teachers were used to explicate the learning gained during the teaching practicum that was part of the MA in Applied Linguistics and TESOL program. The research points out that reflection, feedback from instructors and peers, and self-evaluation are crucial in developing effective teaching strategies and mindsets. The practicum provided an interactive context that focused on active pedagogical approaches and peer cooperation. The findings highlight the fundamental importance of reflective practice, supportive feedback, and micro-teaching opportunities in the enhancement of my teaching skills and confidence. In addition, the study highlights the importance of cultural competence, flexibility, and ongoing professional development for future TESOL teachers. The results of this study suggest that professional development programs for teachers should focus on hands-on teaching experience, collaborative learning opportunities, and continual training to better prepare teachers for the dynamic challenges ahead as effective instructors. This study was conducted within a smaller-scale classroom setting, and future research directions include further development of these pedagogical methods and reflective tools in larger-scale classrooms to gauge their impact and effectiveness.
Gravitational higher-form symmetries and the origin of hidden symmetries in Kaluza-Klein compactifications
Authors: Gomez-Fayren Carmen , Ortín Tomás , Zatti Matteo
Published: January 2025

We show that, in presence of isometries and non-trivial topology, the Einstein–Hilbert action is invariant under certain transformations of the metric which are not diffeomorphisms. These transformations are similar to the higher-form symmetries of field theories with pp-form fields. In the context of toroidal Kaluza–Klein compactifications, we show that these symmetries give rise to some of the “hidden symmetries” (dualities) of the dimensionally-reduced theories.
Ukrainian universities in new realities: Strategies for preserving academic potential during the war
Authors: Suchikova Yana , Danko Yuriy
Published: January 2025

The war in Ukraine has been ongoing for 10 years, reshaping the lives of people, communities, institutions, and worldviews. The occupation of Crimea and significant parts of the Donetsk and Luhansk regions in 2014 marked the first wave of shocks for Ukraine's higher education system. The massive relocation of universities from these regions signaled the beginning of a new reality. During this time, frontline regions actively demonstrated their dedication to Ukraine.Universities transformed into volunteer hubs, collecting supplies, provisions, and protective equipment for the front. Students, faculty, and other staff became volunteers and joined the war effort.
Adapting hybrid approaches for electronic medical record management and sharing using blockchain sharding
Authors: Abbas Abdulmajeed , Hamid Md. Abdul
Published: January 2025

In the past few years, it is noticed that management and sharing medical records is a key step towards increasing healthcare provider connectivity and making the healthcare system more efficient. The scalability and sustainability issues confer to mismanagement of patient is record and also raised several issues in privacy and security. The study aims to suggest more efficient alternatives for Electronic Healthcare System. Scalability and privacy are the major limitations that existing systems contain so the goal of this study is to define alternatives about how parameters like scalability, usability and data protection could be achieved in an efficient manner for healthcare system. In the healthcare industry, providing accurate, thorough, and up-to-date information on patients is critical. Another feature that allows researchers to consider efficient EHR systems is rapid access to patient records for boosting efficiency and coordination. Blockchain sharding technique is utilized along with hyper-ledger protocols and Proof-of-Authority to carry out our model implementation.
Developing a water quality model using fuzzy approach for the Al-Gharraf River in Southern Iraq
Authors: Al Jawei, et. al. Abbas Y.
Published: January 2025

The present study develops a water quality model based on fuzzy approach to assessment of the surface water quality in Al-Gharraf River located in the South of Iraq. The water quality parameters, including Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD), Chloride (CL), Sulphate (SO4), Nitrate (NO3), and Phosphate (PO4), were selected as input parameters to fuzzy water quality model (FWQ). To evaluate the performance of the proposed model (FWQ) of Al-Gharraf River in the period of the study, the produces of our model were compared with those of the water quality index (WQI) and Canadian Water Quality Index (CWQI). They showed similar results and were sensitive to changes in the level of water quality parameters. However, the model proposed in the present study produced a more stringent produces compared to the WQI and CWQI. Results from the simulation indicate that the sensitivity analysis of the suggested approach will be improved by almost (17%, and 24%) more than that achieved by the processes WQI and CWQI, respectively. In conclusion, the proposed index seems to produce accurate and reliable results and can be used as a comprehensive tool for water quality assessment.
Structural behavior of reinforced concrete pre-stressed tapered beams
Authors: Jasim, et. al. Mohammed Dhaher
Published: January 2025

This research is focused on studying the flexural behavior of reinforced concrete prestressed (post-tensioned) tapered beams. The present study investigates the impact of compressive strength, prestressed reinforcement, and tapering ratio on flexural behavior. All tested beams have a total length equal to (2600mm) and a clear distance between supports equal to (2400mm), the width of the beam (250mm), and maintain the same amount of concrete volume. The experimental results showed that when a prestressed reinforcement changes from (one strand) for (two strands), this change will affect the prismatic beam, in which the first cracking and the ultimate load will be raised by (60% and 31.71%), respectively, and for a non-prismatic beam with tapering ratios of (1.5 and 2), the first cracking will increase by (12.5% and 2.63%) also the maximum load raised by (28.3% and 31.03%). The failure mode was flexural for all tested beams with crushing in the compression zone. This paper simulated a numerical analysis of experimentally tested specimens using a nonlinear finite element technique (ABAQUS/CAE 2021 software). The numerical outcomes revealed a good correlation compared with the results of the experimental study.
Molecular analysis of 16s-rRNA and associated gene segments for identification of probiotic phenotypes
Authors: Ćosić, et. al. Amar
Published: January 2025

The 16s-rRNA consists of hypervariable regions (V1 – V9) that demonstrate considerable sequence diver-sity among different bacteria. Species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. Usually, the size of the gene region is 1500 bp, which is large enough to be analyzed using bioinformatic tools and applied for detection. The need to advance the knowledge of the 16s-rRNA gene segments in bacterial strains would allow better understanding and better diagnostic possibilities when dealing with them. This could also be the basis for investigation of pathogenic microorganisms.
Determination of combined sibship indices using 15 STR loci and a grey zone in a small local population in central Bosnia and Herzegovina
Authors: Mušanović, et. al. Jasmin
Published: January 2025

This study investigates the genetic diversity and relatedness among a small local population in Bosnia and Herzegovina. In a genetic research study, a sample of 38 individuals was collected from the village of Vukotići, consisting of 21 male and 17 female subjects. The total genomic DNA was extracted using a mod-ified Miller protocol. The QUANTIFILER DNA identification kit was used to quantify the total human DNA in the sample. The sibship relationship was assessed by computing the likelihood ratio for each of the 15 STR loci in both relatives and non-relatives. Results showed a higher homogeneity of the small local population compared to the mixed population within the larger population. Variability in peak height ob-served in the genetic analysis was attributed to differences in DNA concentration in the extracted samples. Probability of relatedness among participants in the Vukotići village was found to be low. Central tendency and variability measures revealed valuable insights into sample distribution and variation. The study con-cludes that CSI=1 and CSI=3 can be used as reliable tools to determine sibship in small local populations without a "gray zone".
Crowd counting using Yolov5 and KCF
Authors: Maktoof, et. al. Mohammed Abdul Jaleel
Published: January 2025

Crowd detection has various applications nowadays. However, detecting humans in crowded circumstances is difficult because the features of different objects conflict, making cross-state detection impossible. Detec-tors in the overlapping zone may therefore overreact. In this paper, real-time people counting is proposed using a proposed model of the YOLOv5 (You Only Look Once) algorithm and KCF (kernel correlation fil-ter) algorithm. The YOLOv5 algorithm was used because it is considered one of the most accurate algo-rithms for detecting people in real time. Despite the high accuracy of the YOLOv5 algorithm in detecting the people in the image, video or real-time camera capturing, it needs an increase in speed.For this reason, the YOLOv5 algorithm was combined with the KCF tracking algorithm. Where the YOLOv5 algorithm identifies people to be tracked by the KCF. The YOLOv5 algorithm was trained on a database of people, and the system's accuracy reached 98%. The speed of the proposed system was in-creased after adding the KCF.
Decision support system based on BWM for Analyzing success factors affecting the quality in the Iraqi construction projects
Authors: Yas, et. al. Ali Hashim
Published: January 2025

Creating a balance between cost, time, and quality in construction projects is always expected. It is possible to have a project with excellent quality and minimal cost, but at the expense of time, or vice versa. The goal of this paper is to discover, evaluate and prioritize the factors that most influence the desired construction projects' level of quality (success factors) in Iraq. Over a comprehensive review of literature, 11 potential quality-related factors were found to fall into the following five categories: client, contractor, design, mate-rials, and project related factors. These factors' significance was determined using fuzzy Best Worst Method (BWM). Result shows the most three significant success factors influencing quality in the construction pro-jects were related to contractor, client, and designer. These factors were financial competence of contractor, technical capability of client, and designer suitable selection with weights (30.84%, 15.58%, and 10.05%) respectively. These results conclude that maximization of the success factors will guarantee that the building sector achieves its quality objectives.
Image filtering by convolution
Authors: Sultan, et. al. Nora H.
Published: January 2025

Image filtering is a common technique used in digital image processing that can be used to take a picture appear differently aesthetically. Noise, also known as distracting visual artifacts, can lower the overall quali-ty of a picture, which is why image improvement techniques are required to fix the problem. It can be uti-lized in a variety of ways, including smoothing, sharpening, reducing noise, and detecting borders, to name a few. In this piece, we will be using convolutional techniques to correct the images that were messed up. The first thing that needs to be done is a point-by-point multiplication of the frequency domain representa-tion of the picture that's being entered through a black image that has a small white rectangle in the mid of it. This is the first step. Only the lowest harmonics are kept after we apply a filter that gets rid of the higher ones. Because the high frequencies in the input picture are filtered out, the special domain of the image that is produced should look like a blurrier variation of the original picture. Therefore, a greater degree of detail preservation is indicated when the white rectangle W is larger because this indicates that more high-frequency components of I have been preserved.
Tuning parameter selectors for bridge penalty based on particle swarm optimization method
Authors: Sadik, et. al. Nazik J.
Published: January 2025

The bridge penalty is widely used as a penalty for selecting and shrinking predictors in regression models. Although its effectiveness is sensitive to the parameters you decide to use for shrinking and adjusting. The shrinkage and tuning parameters of the bridge penalty are chosen concurrently, and a continuous optimization process called particle swarm optimization is proposed as a means to do this. If implemented, the proposed method will greatly facilitate regression modeling with superior prediction performance. The results show that the proposed method is effective in comparison to other well-known methods, but this varies greatly depending on the simulation setup and the real data application.
Comparison of Weibull and Fréchet distributions estimators to determine the best areas of rainfall in Iraq
Authors: Noaman, et. al. Inam Abdul Rahman
Published: January 2025

In this research, an appropriate distribution of the amount of rain will be found in the Iraqi governorates for the period (2006-2014) and the researcher used two important distributions, namely, the Weibull distribution and the Fréchet distribution. Where the specific distribution was determined based on the minimum criteria (the criteria of goodness of fit) and the tests used are the Akaike Information Criterion (AIC) and the Bayesian In-formation Criterion (BIC). Rainfall in the Iraqi governorates for the stations (Mosul, Kirkuk, Tikrit, Khanaqin, Rutba, Baghdad, Karbala) is a Weibull distribution using the greatest possible estimation method, while the stations in other provinces (Najaf, Diwaniyah, Maysan, Basra) the Fréchet distribution was the distribution It is better to represent the data of these stations using the method of estimating the greatest possible as well. We also note the superiority of the method of maximum likelihood of least squares.
Exploring banking competition in Croatia by using the Panzar-Rosse model
Authors: Busatlic, et. al. Senad
Published: January 2025

The performance commercial banks in the Croatia have been widely studied, but there is little known about the examination of the nature of competition. For these reasons, it is important to investigate whether the banking sector in Croatia exerts monopoly or monopolistic behavior.  This research empirically explores the nature of competition in the Croatian banking sector by covering 24 commercial banks between 2008 and 2018. In this vein, the panel data analysis was used along with H-Statistics. This study for Croatia and its findings confirms early findings of the existence of monopolistic competition in the most transition and developing countries. In fact, the findings obtained from this study reveals that the commercial banks in Croatia operate under monopolistic structure. Moreover, the results reveal that variable of RIETD, RLTA, RETA, and RDTA are statically significant. It indicates that banks operated in Croatia are focus more on traditional loans than other activities.
Strategic ambidexterity and its role in achieving contemporary initiatives: an exploratory study of opinions of a sample of managers of travel and tourism companies in holy governorate of Kerbala-Iraq
Authors: Ahmed, et. al. Ahmed Hussein
Published: January 2025

The research aim to explore influential role of strategic ambidexterity through its two contradictory dimen-sions (exploration and exploitation) as two strategies that contemporary organizations can adopt in light of achieving contemporary initiatives required by current environment, especially tourism sector in Iraq after the paralysis it suffered as a result of spread of Corona virus and impact of repercussions of this pandemic on various Both industrial and service sectors, as researchers targeted tourism companies in Karbala gover-norate, which are characterized by attracting tourists to various visitors for religious tourism and in return, it is a port for their roaming to other cities and countries through tourism companies that need to keep pace with surrounding environment of developments and changes based on adoption of the two strategies of am-bidexterity in Facing those changes and responding to them, as well as their readiness for rapid develop-ments in this sector, as the questionnaire was adopted as a main tool for collecting data on this study by presenting it to the executive directors of those companies with (40) respondents, and after conducting nec-essary statistical tests using SPSS program, it was found that there are a strong positive and significant cor-relation between study variables, as well as a significant effect For strategic ambidexterity across its two dimensions in achieving and promoting contemporary initiatives at corporate level, the study community
A comparative study between shrinkage methods (ridge-lasso) using simulation
Authors: Ghareeb, et. al. Zainab Fadhil
Published: January 2025

The general linear model is widely used in many scientific fields, especially biological ones. The Ordinary Least Squares (OLS) estimators for the coefficients of the general linear model are characterized by good specifications symbolized by the acronym BLUE (Best Linear Unbiased Estimator), provided that the basic assumptions for building the model under study are met. The failure to achieve one of the basic assumptions or hypotheses required to build the model can lead to the emergence of estimators with low bias and high variance, which results in poor performance in both prediction and explanation of the model in question. The hypothesis that there are no multiple linear relationships between the explanatory variables is consid-ered one of the leading hypotheses on which the model is based. Thus, the emergence of this problem leads to misleading results and high (Wide) confidence limits for the estimators associated with those variables due to problems characterizing the model. Shrinkage methods are considered one of the most effective and preferable ways to eliminate the multicollinearity problem. These methods are based on addressing the mul-ticollinearity problems by reducing the variance of estimators in the model. Ridge and Lasso methods repre-sent the most and most common of these methods of shrinkage. The simulation was carried out for different sample sizes (40, 120, 200) and some variables (P=30, 60) in the first and second experiments arbitrarily and at the level of low, medium, and high correlation coefficients (0.2, 0.5, 0.8). When (p=30, 60) Lasso method has the smallest (MSE) than the Ridge method. The Lasso method proved its efficiency by obtaining the least MSE. Optimal Penalty parameter (λ) chosen from Cross-Validation through minimizing (MSE) of prediction. We see a rapid increase for (MSE) for both (Ridge-Lasso) where the top axis indicates the num-ber of model variables, and when the correlation between variables increases and sample size too, we can see the (MSE) values increase in the Ridge method than the Lasso method. A ridge method gives greater efficiency when the sample size is more significant than variables (p<n), but the Ridge method cannot shrink coefficients to precisely zero. So, the elasticity of ridge coefficients decreases, but variance increases bias, also (MSE) first remains relatively constant and then increases fast.
Dynamic response of reinforced concrete beams subjected to low-velocity impact loads using nonlinear finite element analysis
Authors: Abdulsahib,  et. al. Wael Shawky
Published: January 2025

The development of a nonlinear finite element method (FEM) for examining how reinforced concrete (RC) beams react to dynamic forces under the action of low-velocity impacting loads is presented in this article. The model was employed to analyze the stress distributions along with the time histories of impacting load and beam deflection, which were presented graphically. Comparisons with experimental data from previous-ly conducted studies have been performed to verify the precision of the studied model. The findings demon-strated that the developed model was acceptable. Furthermore, the study performed a detailed parametric analysis, focusing on various factors such as replacing conventional steel bars with FRP bars, increasing concrete compressive strength, changing the impact location, using different diameters of reinforcing bars, and changing the depth of the concrete beam. According to the findings, using FRP bars resulted in 36% less peak load due to the uplift pressure caused by the FRP bars' high strength, while the maximum observed deflection of the beam reinforced with FRP bars decreased by approximately 9%. When the position of the impacting force was applied at one-third of the span of the beam, deflection was decreased by 12% when compared to the RC beam has been impacted at its midspan. In addition, the depth of the beams had a sig-nificant impact on the impacting load. These presented findings of the study may contribute to a better un-derstanding of how a structure made of concrete responds to impacting loading.
Enhancing quality of service in IoT through deep learning techniques
Authors: Salman, et. al. Adil M.
Published: January 2025

When evaluating an Internet of Things (IoT) platform, it is crucial to consider the quality of service (QoS) as a key criterion. With critical devices relying on IoT technology for both personal and business use, ensur-ing its security is paramount. However, the vast amount of data generated by IoT devices makes it challeng-ing to manage QoS using conventional techniques, particularly when attempting to extract valuable charac-teristics from the data. To address this issue, we propose a dynamic-progressive deep reinforcement learning (DPDRL) technique to enhance QoS in IoT. Our approach involves collecting and preprocessing data sam-ples before storing them in the IoT cloud and monitoring user access. We evaluate our framework using metrics such as packet loss, throughput, processing delay, and overall system data rate. Our results show that our developed framework achieved a maximum throughput of 94%, indicating its effectiveness in im-proving QoS. We believe that our deep learning optimization approach can be further utilized in the future to enhance QoS in IoT platforms.
Estimating systems reliability functions for the generalized exponential distribution with application
Authors: Hamza, et. al. Zainab Falih
Published: January 2025

This article dealt with estimating and analyzing the reliability function for hybrid systems. The hybrid sys-tems included series-parallel and parallel-series with symmetric components representing the machine's op-eration times; these times follow a generalized exponential distribution. Furthermore, we suggested employ-ing a hybrid system parallel series in the application part of this research, which includes the operation times of Baghdad's Vegetable Oil factory machines. The results of the reliability function for the factory system indicate that the probability that the factory machines will stop during the first hour is more than 40%. Still, if the hybrid parallel-series system is applied, the probability that the factory operating system will not stop during the second hour becomes 80%.
Road conditions monitoring using semantic segmentation of smartphone motion sensor data
Authors: Mahmood, et. al. Emad
Published: January 2025

Many studies and publications have been written about the use of moving object analysis to locate a specific item or replace a lost object in video sequences. Using semantic analysis, it could be challenging to pinpoint each meaning and follow the movement of moving objects. Some machine learning algorithms have turned to the right interpretation of photos or video recordings to communicate coherently. The technique converts visual patterns and features into visual language using dense and sparse optical flow algorithms. To semanti-cally partition smartphone motion sensor data for any video categorization, using integrated bidirectional Long Short-Term Memory layers, this paper proposes a redesigned U-Net architecture. Experiments show that the proposed technique outperforms several existing semantic segmentation algorithms using z-axis accelerometer and z-axis gyroscope properties. The video sequence's numerous moving elements are syn-chronised with one another to follow the scenario. Also, the objective of this work is to assess the proposed model on roadways and other moving objects using five datasets (self-made dataset and the pothole600 da-taset). After looking at the map or tracking an object, the results should be given together with the diagnosis of the moving object and its synchronization with video clips. The suggested model's goals were developed using a machine learning method that combines the validity of the results with the precision of finding the necessary moving parts. Python 3.7 platforms were used to complete the project since they are user-friendly and highly efficient platforms.
Artificial intelligence: A review of the scientific literature in Scopus
Authors: Bellido-Valdiviezo, et. al. Omar
Published: January 2025

Artificial intelligence (AI) has revolutionized conventional work methods in all areas of knowledge. The aim of this study is to analyze the current state of research in this field. To this end, a systematic review was carried out with a bibliometric approach that included analysis of the distribution of scientific production by year, the most relevant sources, Bradford's Law to identify the main sources, the most prominent authors, Lotka's Law to analyze the productivity of authors and the author's "h" index. Through the review of the scientific literature available in the Scopus database, 609 relevant results were identified, of which 414 were articles in Spanish. A total of 205 articles were selected as the final publication of the study and 113 of them were open access. The empirical studies demonstrate that AI presents both opportunities and ethical and social challenges, especially in areas such as health, communication, law and artistic practices. In healthcare, AI can improve patients' quality of life. In journalism, AI streamlines the production of objective news and helps reduce misinformation, although it also poses ethical and professional challenges. In the field of law, AI offers opportunities to improve efficiency in judicial decision-making and legal work, but it also brings ethical and legal considerations. It is therefore essential to strike a balance between harnessing the benefits of AI and protecting rights, privacy and ethics in each of these fields, in order to maximize its potential for the benefit of society.
FQMaP: Towards a framework quantitative management of processes in small software development organizations
Authors: Ardila Carlos A. , Pino Francisco J. , Pardo César J.
Published: January 2025

Software development organizations need to control and improve their practices, seeking to reduce variability when executing the necessary processes to elaborate software; therefore, these organizations implement improvement plans to identify factors that affect the processes. Quantitative Management deals with identification, tracing, and control of those incident factors, using data proactively to predict performance and the effect of possible changes in a process. Reference models in software processes development such as CMMI V2.0 and ISO/IEC 33061:2021 address Quantitative Management, but are aimed at big enterprises. Other models such as MoProSoft, COMPETISOFT, and MPS.BR are aimed at small enterprises, but do not include enough elements on Quantitative Management. Execution of a systematic literature review permitted searching for works on Quantitative Management intended for small software development enterprises, indicating necessary practices and how to perform them. This search showed that a proposal is not available that incorporates Quantitative Management practices for software processes aimed small software development enterprises. The referred aspects make it difficult to adopt a Quantitative Management culture within these organizations, it which has become a problem, consisting in that small software development enterprises that do not execute quantitative management practices will have difficulty identifying and focusing on the factors that impact the process performance and, therefore, on the results of their projects. This work sought to tackle this problem by proposing the “framework for quantitative management of processes in small software development organizations” (FQMaP), which allows incorporating practices and techniques that support Quantitative Management of software development processes in these kinds of enterprises. From the evaluation of FQMaP, carried out by following Focus Group technique guidelines, it can be demonstrated that it is a simple proposal and with elements that can serve a company to quantitatively manage software development processes. Also, it has clearly specified its components, showing that its structure is familiar with other process patterns, that would facilitate their interpretation.
A multi-story reinforced concrete structure's physical and geometric nonlinear evaluation based on open sees seismic analysis in architectural engineering building design
Authors: Al Hassan Hiba Mazen Kamel
Published: January 2025

Research Purpose: The purpose of this research is to analyze a G+20 reinforced concrete building in Am-man, specifically focusing on its behavior under gravitational loading and wind, Applied Research Method: The research employs four types of static analysis: linear elastic analysis, geometric nonlinear analysis, physical nonlinear analysis, and physical and geometric nonlinear analysis. The OpenSees open-source pro-gram, developed at the University of California, Berkeley using C++ language, is used as the platform for the study, Principal Results: The research reveals significant differences in the results obtained from the various types of analyses performed. The linear elastic analysis, geometric nonlinear analysis, physical non-linear analysis, and physical and geometric nonlinear analysis produce varying results. The effort (forces and stresses) experienced by a specific beam on different floors also exhibits reasonable variation, Major Conclusions: Based on the analysis results, it can be concluded that considering geometric and physical nonlinearity is crucial in accurately modeling the behavior of the reinforced concrete building. The use of the OpenSees program, along with the corotational formulation to account for large rotations and the P-Delta method for result validation, proves effective in capturing the complex behavior of the structure. The study highlights the importance of considering concrete cracking and reinforcement plasticity with precision to better understand the structural response.
Machine learning methods based on mammogram images to estimate survival times for breast cancer patients
Authors: Mohammed Noor Ayad , Fadam Entsar Arebe
Published: January 2025

Estimating survival times based on medical images resulting from radiological imaging of some parts of the body affected by tumors and making a predictive system for them is considered one of the very important fields at the present time. This is because radiological imaging is one of the first and most important stages of medical diagnosis. Therefore the process of linking medical images including them within the work steps of the statistical analysis for estimating survival times is a modern and important topic. Its importance is helping doctors and medical specialists to determine the influencing factors and risk percentage associated with survival for each patient based on the medical image of the affected part.In this paper, the medical images extracted from the mammogram device for breast cancer patients in Iraq. These images were included in the machine learning method for estimating survival of patients. Based on two methods to extract features, The first one is the Fast independent component algorithm (Fast ICA algo-rithm) and the second one is Nonnegative Matrix Factorization (NMF algorithm). With two machine learn-ing algorithms, The first method is Random survival forests algorithm and the second method is support vector machine algorithm SVM (SVM).Through the application of the supervised machine learning method on mammogram images of patients with breast cancer, it was found that the best model for estimating survival according to the mean square error (MSE) and concordance index (C-Index) criterion is the model resulting from the use of the Fast ICA algo-rithm with the random survival forest algorithm compared with the other three models. Accordingly, It is recommended that interested medical agencies and institutions to adopt this model.
Algorithm for ensuring the minimum power consumption of the end node in the LoRaWAN network
Authors: Yaser Muhanad Jabar , Polshchykov Konstantin A. , Polshchikov Ilya K.
Published: January 2025

The paper approves the relevance of the development of theoretically justified tools aimed at power con-sumption minimization in the data transmission network of the LoRa WAN standard. Such a network is used to monitor various objects in a distributed system of the Internet of things. LoRa WAN end nodes have au-tonomous power supplies, for which energy costs saving is important. The paper presents expressions for estimating the power consumption of a LoRa WAN end node. Based on the results of computational exper-iments, a database was formed containing signal attenuation values and their corresponding recommended values of transmitter power and spectrum spreading factor. This database is used in the algorithm for ensur-ing the minimum power consumption of the end node.
Exploring the relationship between knowledge management and core competencies to improve universities success in Jordan: Testing the mediating effect of employee engagement
Authors: Alsheikh, et. al. Ghaith Abdulraheem Ali
Published: January 2025

Strong job results require a lot of work and assistance from many people, particularly when it comes to aca-demic accomplishment. Therefore, the justification for this research is that success at universities involves knowledge, effort, and significant academic engagement. To encourage change and success in universities. Also, it is crucial to possess the necessary skills even when achieving this goal. Therefore, this research seeks to explain the relationship between knowledge management, core competencies, and university suc-cess with employee engagement as mediating. The data was gathered from ten Jordanian public universities. was also chose respondents were chosen using convenience sampling, and the data, which included respons-es from 365 respondents, were analyzed using the Partial Least Squares (PLS) modeling technique. The results of the research found that knowledge management and core competencies are significantly influ-enced by employee engagement and organizational success. Moreover, employee engagement has a signifi-cant relationship with organizational success. More importantly, the analysis revealed that employee en-gagement plays a mediating role between knowledge management, core competencies, and organizational success. Top management must begin planning the changes required to meet the demands of knowledge management and core competencies while also capitalizing on opportunities to improve organization success and employee engagement.
Ranking the risks of drawing up the state budget in Iraq for the period from 2003 to 2021
Authors: Qllam Askri Raied Abbas , I. E. Mizikovsky
Published: January 2025

The paper analyzes the potential budgetary risks in Iraq and offers recommendations for mitigating the ef-fects of those risks. For the purpose of carrying out the study, the AHP-Fuzzy technique is utilized. This approach includes the following steps: creating criteria, acquiring and processing data, assigning weights to the criterion, and evaluating budgeting risks. The following is a list of twenty specialists in the area who have identified the risks that are related with the budgeting of the Iraqi government in the year 2023: erro-neous estimating or forecasting of the budget; expenses that were not anticipated or unforeseen; fluctuations in revenue or cash flow; inadequate implementation or communication of the budget; and a lack of oversight or insufficient monitoring and control measures. Investing in state institutions as a means of fostering politi-cal stability is one of the practical strategies that are suggested by the report. The expansion of income streams beyond oil exports, the improvement of anti-corruption legislation, the encouragement of social development, and the implementation of appropriate budgeting procedures are some other proposals. Providing assistance to the expansion of Iraq's economy is something that the international community can also do. The findings of the study can be utilized by policymakers in order to gain a better understanding of the budgetary dangers that Iraq is currently facing and how to avert them in the future.
REGIMES OF REMITTANCE DEPENDENCY: GLOBAL STRUCTURES AND TRAJECTORIES OF THE FORMER SOVIET “BLOC”
Authors: Böröcz József
Published: January 2025

The re-integration of the societies of the erstwhile state socialist bloc into global flows of capitalism is emerging as a major issue in the sociology of labour migration. Changes in the magnitudes of  migrant remittances can be of crucial social and political importance. In this study, I link a conceptual contribution with a three-step empirical inquiry. First, I conceptualize migrant remittances as a form of external economic dependency. Next, I describe recent changes in the strength of the empirical relationship between migrant remittances as percentages of the GDP and per capita GDP for all societies of the world utilizing data from two online data sets. Employing what Charles Tilly (1984) called “variation-finding comparison,” I examine, next, the – as it turns out, quite sizeable – residual variation in the relative magnitude of remittances that remains after controlling for per capita GDP, and interpret it as a marker for patterns of remittance dependency. Finally, I trace the recent trajectories of the societies that had, until one generation ago, constituted the Soviet “bloc” against the backdrop of the global distribution in remittance dependency.
The different faces of cohabiting unions in the new millennium
Authors: Murinkó Lívia
Published: January 2025

The rise of unmarried cohabitation in the late 20th century has increased the diversity of couples’ family situations and partnership trajectories, calling for a differentiated approach to this partnership form. This is one of the first studies to examine how the typology of cohabitation in a society has changed over time, using both subjective and objective criteria, and recognising the different role of cohabitation at different stages of family life, including situations characteristic of later life.
Based on data from the first (2001) and fifth (2016/17) waves of the Hungarian Generations and Gender Survey, this analysis aims to establish an empirical typology of the cohabiting population. Family trajectories, relationship commitment and attitudes towards marriage were included as grouping criteria in the latent class analysis. Four types were identified: trial marriage, alternative to marriage, stepfamily and post-marital cohabitation. Contrary to the international literature, we did not find any groups who do not marry because of their anti-marriage attitudes or poor financial situation, or who see their cohabitation as an alternative to being single. The findings are discussed in the light of theories of the changing meaning of unmarried cohabitation.
Analysis of Pesticides by Ultra-High Performance Liquid Chromatography in Combination with High Resolution Mass Spectrometry (UPLC-Orbitrap MS): Case Study for Application on River Water Samples in Vietnam
Authors: Vu Duc Nam , Minh Le Thuy , Nguyen Thi Xuyen , Bui Van Hoi , Tu Vu Cam , An Vu Thi Hong , Binh Chu Dinh
Published: January 2025

This study introduced mass spectrometry (MS)-based method for analysis of 118 pesticides
after applying solid phase extraction (SPE) for 26 water samples collected in Red River, Northern
Vietnam. The excellent limit of quantitation of the developed method ranged from 0.0005 to
0.015 µg L-1. Intra- and inter-day repeatability of the developed method was achieved below
15%. Specific procedure of the liquid chromatography Orbitrap mass spectrometry (LC-Orbitrap
MS)-based analytical method for target compounds was identified by retention time, precursor
ion, product ions, accurate mass of precursor and product ions and fragmentation pathway in high
resolution mass spectrometry. Mass accuracy of all precursor ions and product ions were achieved
below 5 ppm in this work. It demonstrated that the concentration of most studied analytes was
below the allowable level according to National Technical Regulation in Vietnam (QCVN 08:2023/
BTNMT). Alachlor, fenobucarb and acetochlor were often determined at levels in the range between
0.099-8.978, 0.058-18.776, and 0.073-1.460 µg L-1, respectively. Their concentrations were much
higher than regulated pesticides mentioned in QCVN 08:2023/BTNMT (0.02 to 1.0 µg L-1 for
chlorinated pesticides). Therefore, it is necessary to propose a national regulation regarding the
levels of the three analytes above to control pesticide pollution in Vietnam.
The criteria for the effectiveness of the cytokine hemoadsorption in the treatment of the patients with cytokine storm associated with COVID-19
Authors:   St. Petersburg State University, Sarana Andrei ,   Health Committee of the Administration of St. Petersburg, Gladysheva Tatyana ,   City Hospital no. 40, Garbuzov Evgeny ,   City Hospital no. 40, Mosenko Sergey ,   St. Petersburg State University,   City Hospital no. 40, Urazov Stanislav ,   City Hospital no. 40, Klitsenko Olga ,   City Hospital no. 40, Asinovskaya Anna ,   St. Petersburg State University,   City Hospital no. 40, Shcherbak Sergey ,   St. Petersburg State University,   City Hospital no. 40
Published: January 2025

The new coronavirus infection COVID-19 is often accompanied by the development of a cytokine storm in patients. Сytokine hemoadsorption is used to reduce cytokine levels along with anti-cytokine therapy. Criteria for the effectiveness of the cytokine hemoadsorption in patients with severe COVID-19 remain undeveloped. Purpose of the study: based on clinical and laboratory indicators, to develop a model and criteria for assessing the effectiveness of the cytokine hemoadsorption for the treatment of the cytokine storm in patients with severe COVID-19. The non-interventional observational clinical study included 171 patients (119 men, 52 women) aged 54± 12 years diagnosed with COVID-19 who were treated
at City Hospital no. 40 of St. Petersburg during 2020–2021. The patients were assessed for clinical and biochemical blood parameters, the clinical state according to the NEWS,
SOFA, PSI, and the cytokine hemoadsorption to reduce cytokine levels. Endpoints were biological death or discharge. The prognostic significance and threshold criteria for assessing the effectiveness of the cytokine hemoadsorptio were determined by constructing a “tree
classification”. In 171 patients with severe COVID-19 infection, the most significant indicators of survival during the cytokine hemoadsorption were determined: age, time of onset of the cytokine hemoadsorption, Charlson index, NEWS, PSI, SOFA scale values, volume of lung damage on CT, D-dimer levels, LDH and CRB. For these indicators, odds ratios were determined and threshold values were obtained that affect the effectiveness of the cytokine hemoadsorption. Using the logistic regression method, a comprehensive prognostic model was built to assess the effectiveness of cytokine hemoadsorption in patients with severe COVID-19 with a sensitivity of 89 %, specificity of 70 %, and diagnostic accuracy of 80 %. The most significant indicators of patient survival during the cytokine hemoadsorption were determined and, on its basis, the prognostic model to assess the effectiveness of the cytokine hemoadsorption procedures in patients with severe COVID-19 was developed.
System and structure of public-legal support of internal state sovereignty
Authors:   Kutafin Moscow State Law University, Sitnik Alexander A. , Polyakov Maksim M. ,   Kutafin Moscow State Law University
Published: January 2025

The article is devoted to the analysis of public-legal support of internal state sovereignty from the point of view of systems theory. It is emphasized that the category under consideration is not limited exclusively to a set of normative legal acts regulating public relations in the relevant sphere — this approach reflects the understanding of public-legal support for internal state sovereignty in a narrow sense. From the point of view of a broad approach, it is a complexly structured system consisting of individual elements that are interconnected and interact with each other. As elements of this system, the authors distinguish the purpose and principles of public-legal support for internal state sovereignty (value-oriented subsystem), normative legal acts in this area (normative subsystem), subjects, their rights and obligations in the field of ensuring internal state sovereignty (institutional and competence subsystem), effective law enforcement, reflecting the real implementation of the national legislation of the Russian Federation, legal norms in specific life circumstances (subsystem of law enforcement), the legal culture of an individual, group and society as a whole (subsystem of legal education and enlightenment), as well as control in the field of public relations under consideration (control subsystem). It is noted that the system of public-legal support for internal state sovereignty has undergone significant changes in the context of countering unfriendly actions of the United States and other foreign states. In particular, this led to the expansion of the powers of federal executive bodies in order to protect state sovereignty, the formation of collective management bodies with special powers, the actual granting of individual decisions of a non-normative nature with the status of normative legal acts and, conversely, the loss of some normative legal acts of signs of normality, the emergence of new types of state control and strengthening.