bluuebunny/crossref_metadata_2025 huggingface dataset:
OPTIMIZATION OF DESIGN OF MECHATRONIC SYSTEMS USING INTEGRATED CAD/CAE TOOLS
Authors:   Kazan State Energy University, Kazan, Russian Federation, Malev Nikolay A.
Published: October 2024

The article discusses methods for optimizing the design process of mechatronic systems using integrated CAD/CAE tools. In the context of the growing complexity and interdisciplinary nature of mechatronic systems, the integration of CAD/CAE technologies is becoming a key element in reducing development time, reducing errors at the design stage and improving the quality of the final product. Based on the analysis of modern approaches and examples from industrial practice, the article presents the advantages of using integrated solutions, and discusses possible directions for further research.
ENERGY MANAGEMENT IN MECHATRONIC SYSTEMS: OPTIMIZATION OF ROBOT ENERGY CONSUMPTION
Authors:   Kazan State Energy University, Kazan, Russian Federation, Malyov Nikolaj A.
Published: October 2024

The article discusses methods for optimizing energy consumption in mechatronic sys-tems, with a special emphasis on robotics. Energy management strategies are presented, including en-ergy-optimized trajectory planning, dynamic energy management, and architectural approaches to sys-tem design. An analysis of the factors affecting energy consumption is carried out, and solutions are proposed to improve energy efficiency without compromising performance. The results demonstrate that the proposed methods can significantly reduce energy consumption, increasing the autonomous opera-tion time of robots. In conclusion, possible directions for further research in the field of integrating ma-chine learning methods and hybrid approaches to energy management are discussed.
Legal Chronicle
Authors:   Lomonosov Moscow State University, Golovko Leonid V. , Pleshanova Olga P. ,   Infralex Law Firm, Konovalov Sergey G. ,   Lomonosov Moscow State University, Zaripov Vadim M. ,   MEF Legal, Yankovsky Roman M. ,   Moscow Digital School,   HSE University, Popov Vladimir A. , Tereshchenko Tatyana A. ,   Prime Advice Consulting Group
Published: October 2024

In the September Chronicle, read comments on the criminal case of Pavel Durov in France, on the laws on amnesty for business crushing, on mining, on the introduction in the Criminal Procedure Code of an online form of meetings between a advocate and a prisoner, on changes in the foreclosure of a bankrupt’s only home, and on new approaches of the Supreme Court to the recognition and enforcement of international commercial arbitration awards.
Digital Ruble: Discussion on the Legal Nature and Prospects of Implementation
Authors:   Lomonosov Moscow State University, Lauts Elizaveta B.
Published: October 2024

The article analyses the policy documents and regulations on the basis of which the introduction of the digital ruble in Russia is carried out. The author addresses controversial issues related both to the ambiguity of the interpretation of the digital currency in relation to the digital ruble, and to the question of the legality of its attribution to non-cash funds. The article pays independent attention to negative and positive issues related to the prospects of the introduction of the digital ruble, analyses the risks of its implementation and suggests possible ways to minimise them.
Constitutional Development of New China: On the 70th Anniversary of the First Constitution of the PRC
Authors:   Institute of Oriental Studies of Russian Academy of Sciences, Troshchinskiy Pavel V.
Published: October 2024

The People’s Republic of China was established on 1 October 1949, and in the initial years after its emergence on the world stage, the country embarked on an active phase of law-making, culminating in the adoption of its first Constitution on September 20, 1954. This constitution was based on the Stalinist Constitution of 1936 and incorporated some of its constitutional and legal institutions, categories, and norms of the time. The 1954 Constitution of the PRC laid the foundation for the state system not only for the early period of the PRC but also for modern China. It served as the basis for the 1982 Constitution, which is the fourth and current Constitution in effect today. The foundational elements of the political system and the structure of the supreme and local bodies of state power and administration established in the early years of the PRC remain in place. The spirit of the 1954 Constitution has permeated all subsequent constitutional legislation in the PRC. Consultative democracy, democratic centralism, a unicameral parliament, and many other features that are now integral to China’s political system were established by the first Constitution of socialist China. Understanding the essence of the ideas enshrined in this foundational document is crucial to comprehending China’s unique constitutional way of development and providing a reasonable scientific forecast of its future evolution.
Unfair Commercial Practices of Professional Financial Market Participants
Authors:   Saint Petersburg State University, Petrov Dmitry A.
Published: October 2024

The article analyses the reasons for the formation and application of unfair commercial practices of professional financial market participants, issues of protection against unfair practices. The author’s concept and signs of unfair commercial practices are proposed. The types of unfair commercial practices of professional participants in the financial market are investigated and their division into practices is proposed, — i.e. the practices aimed at 1) clients who are professional participants in the financial market, or who are able to understand complex financial issues, and 2) clients who purchase financial services for personal use, which requires to provide them with a better protection.
The Moment of Conclusion of the Consumer Credit Agreement
Authors:   Saint Petersburg State University, Karpushkin Sergey M.
Published: October 2024

The article deals with the problem of determination of the moment of conclusion of a consumer credit agreement in comparison with a consumer loan agreement, and presents the results of the analysis of the conditions on the moment of conclusion of the agreement offered by Russian banks. The study showed that banks use both a consensual and a real contract model. The author answers the question of which model is acceptable.
Mobile Assisted Language Learning: Ecuadorian Undergraduate Polytechnic Students' Perceptions
Authors: Ibarra David Estrella
Published: October 2024

Despite the increased use of mobile devices for language learning, little research has examined Ecuadorian university students' perceptions of Mobile-Assisted Language Learning (MALL). This study aims to explore undergraduate polytechnic students' perceptions of using MALL for English skills development. Also, it looks at the different factors associated with the acceptance of technology and identifies those that are more common. This quantitative research design uses a survey adapted from the Technology Adoption Model (TAM). It counts with the participation of 126 Ecuadorian undergraduate polytechnic students taking English as a foreign language classes. Participants were very positive about using MALL applications to learn English during their off-classroom time. The average total mean score was 4.373. It was also determined, through multiple regression analysis, that Perceived Usefulness (t = 6.025, p < 0.000), Social Influence (t = 2.876, p < 0.000), and Perceived Outcomes (t = 3.903, p <0.000) were the highest predictors of MALL acceptance. The two main contributions of this study to the literature are that students feel a connection between their language learning aims and attaining them by using MALL. Perceived Outcome is a high predictor of MALL usage. The findings suggest that Ecuadorian educational practices should increasingly integrate Mobile-Assisted Language Learning (MALL) technologies, as students perceive them as highly useful, especially in improving language skills, fostering social collaboration, and offering personalized, flexible learning experiences that align with their technological readiness and cultural context.
The Effect of Wellness Programs on Employee Performance at The Technical University of Kenya
Authors: Kwasu Eucabeth Adoyo , Ombui Kepha Andrew , Siele Eric
Published: October 2024

The quest for organizations to improve the health, job satisfaction, and overall performance of their employees has resulted into the adoption of wellness program. This applies for the Technical University of Kenya (TUK) where employee performance is considered integral in delivering quality education to students pursuing various courses. However, the effectiveness of these programs adopted at the TUK remains underexplored and especially with regards to how they impact on employee well-being and performance. This study sought to address this gap by examining how wellness programs impact on the performance of the employees at the university. The study used the descriptive research design and targeted the entire staff population using stratified random sampling to gather data from a representative sample of 182 individuals. The collected quantitative data was analyzed using SPSS. The findings revealed a moderate positive relationship between wellness programs and employee performance, with regression analysis showing that these programs accounted for 31.4% of the variance in performance. The qualitative findings indicated that wellness initiatives boosted morale, reduced absenteeism, and enhanced staff retention, though there were gaps in stress management and sports participation. The study, therefore, concluded that while the wellness programs at TUK had a positive impact, targeted improvements were required in stress management and sports activities. The study recommended the implementation of stress management workshops, enhancement of sports programs, and establishment of a feedback mechanism to continuously adapt and improve wellness initiatives
Leveraging Technological Research Methodologies to Improve Employee Performance in Organizations
Authors: Kwasu Eucabeth Adoyo , Ombui Kepha Andrew , Siele Eric
Published: October 2024

The effective management of human resources in organizations is imperative for attaining optimum performance and eventual profitability. The increasingly competitive marketplace has compelled organizations to work towards attaining operational excellence, which heavily relies on the performance of its human resources. The adoption of cutting-edge research techniques has emerged as a pivotal strategy as organizations endeavour to achieve operational excellence. However, human resource managers have had to grapple with various challenges associated with the management of employee data generated and managed through digital platforms and tools, including issues such as data safety and security. This paper explores the intersection between tech-enhanced, advanced research methodologies and employee performance that is geared toward sustainable economic growth at the organizational level. Notably, the paper examines big data analytics as a tech-enhanced research tool leveraged by organizations in a bid to understand their human resource and the best way they can be managed to ensure high performance, which translates into high productivity and competitiveness in their respective sector or industries. In particular, this paper conducts a comprehensive review of recent extant literature regarding the adoption of big data analytics, which has revolutionized how organizations collect and analyze vast amounts of data, thereby enhancing their decision-making process. The reviewed literature focused on human resource aspects such as recruitment and selection; employee development; employee performance management and compensation structures. The review revealed that big data has emerged as a critical tool for managing large volumes of data that are acquired via numerous digital tools as organizations grapple with the integration of technology into their human resource practices. The technologies have helped human resource managers with these structured and unstructured data, they gain insight that in turn, guides their decision-making processes and improves the overall operational efficiency. The review outlines the transformative potential of integrating big data tools with human resource management and recommends that organizations should invest in these tools to enhance their recruitment and selection, employee development, performance measurement and upgrade their compensation structure.
Internal University Leading Function in Promoting Knowledge Economy in Tanzania
Authors: Shio Martha Mkasafari , Eduan Wilson , Kagoire Mary
Published: October 2024

In response to the evolving demands of the knowledge economy (KE), Tanzanian universities are transforming their internal management practices to enhance effectiveness, competitiveness, and relevance. The study focuses on how universities manage activities that support knowledge creation, dissemination, and innovation. Data from 30 university leaders, gathered through document reviews and interviews, were thematically analysed. Findings reveal that leading include dynamism, empowerment, vision, and transparency motivate researchers to produce impactful academic research work with commercialization potential. However, the heavy reliance on institutional policies pushing rapid publication for promotion results in rushed, low-quality studies. The study emphasizes the need for leadership that goes beyond policy enforcement, fostering research with commercial value by leveraging personal leading qualities and providing adequate resources like grants and training
The Effect of Menstrual Hygiene Management on Girl Child School Attendance at St Marys Girls Vocational School in Kamukuzi Division, Mbarara City
Authors: Vanmark Tumusiime , Twebaze Richard , Barigye Enock
Published: October 2024

This study assessed the effects of menstrual hygiene management on school attendance among female adolescent students at St. Mary's Girls Vocational School in Kamukuzi Division, Mbarara City. The researchers employed systematic random sampling to select 45 respondents from Form One and Form Two, as these students were expected to have experienced their menstrual periods. The majority of the respondents were aged 13-14 years. While some girls used handkerchief cloths or hand towels as menstrual management materials, most of them used sanitary pads and disposed of them in the toilets. The researchers conducted a Pearson correlation coefficient analysis in SPSS to examine the relationship between menstrual hygiene management and school attendance. The analysis revealed a weak positive correlation coefficient of 0.210, indicating a weak relationship between menstrual hygiene management and school attendance. However, the p-value of 0.167 suggested that the results were not statistically significant. The study concluded that there is an impact of menstrual hygiene management on school absenteeism, as girls who experienced longer periods tended to miss more school days. However, the weak relationship and lack of statistical significance indicate that other factors may also contribute to school attendance among adolescent girls, and menstrual hygiene management alone may not be the sole determinant. This study provides valuable insights into the challenges faced by adolescent girls in managing menstruation and its potential impact on their school attendance. It highlights the need for comprehensive menstrual hygiene management education and support programs in schools to ensure that girls have access to appropriate materials and facilities. By addressing these challenges, schools can create a supportive environment that promotes regular attendance and educational opportunities for all female students, even during menstruation
Explainable AI for Transparent and Trustworthy Tuberculosis Diagnosis: From Mere Pixels to Actionable Insights
Authors: Joseph Tibakanya , Kenneth Male Henry , Rose Nakasi
Published: October 2024

Building transparent and trustworthy AI-powered systems for disease diagnosis has become more paramount than ever due to a lack of understanding of black box models. A lack of transparency and explainability in AI-driven models can propagate biases and erode patients' and medical practitioners' trust. To answer this challenge, Explainable AI (XAI) is drastically emerging as a practical solution and approach to tackling ethical concerns in the health sector. The overarching purpose of this paper is to highlight the advancement in XAI for tuberculosis diagnosis (TB) and identify the benefits and challenges associated with improved trust in AI-powered TB diagnosis. We explore the potential of XAI in improving TB diagnosis. We attempt to provide a complete plan to promote XAI. We examine the significant problems associated with using XAI in TB diagnosis. We argue that XAI is critical for reliable TB diagnosis by improving the interpretability of AI decision-making processes and recognising possible biases and mistakes. We evaluate techniques and methods for XAI in TB diagnosis and examine the ethical and societal ramifications. By leveraging explainable AI, we can create a more reliable and trustworthy TB diagnostic framework, ultimately improving patient outcomes and global health. Finally, we provide thorough recommendations for developing and implementing XAI in TB diagnosis using X-ray imaging
Artificial Intelligence and Employee Well-Being: Balancing Technological Progressions with Human-Centric Workplace Strategies, a Research Agenda
Authors: Kaaria Ann Gaceri
Published: October 2024

Artificial intelligence (AI) enabled technologies are now corporate organisations' top priorities due to the availability of large data and the advent of the Internet of Things during the past ten years. AI is becoming a crucial component of business model innovation, process transformation, disruption, and gaining a competitive edge for companies adopting digital and data-centric cultures. This study investigates the implications of smart technology, artificial intelligence, robotics, and algorithms (STARA) on the future of work, with a particular emphasis on employee well-being and workplace dynamics. As futurists project that by 2025, 52% of all work functions will be automated, replacing one-third of current jobs, the rapid advancement of STARA creates both opportunities and risks. While automation has the potential to produce 133 million new jobs, it also threatens to eliminate 75 million employments, raising employee anxieties about job security and future roles. Despite the rising volume of studies on smart automation, there is still a major vacuum in our understanding of its implications on employees' mental health, well-being, and the entire workplace. This study investigates STARA's dual influence: while technology reduces physical strain and automates tedious jobs, it also raises new difficulties such as job displacement concerns and shifts in worker dynamics. The study emphasizes the need of human resource professionals to develop methods that strike a balance between technological integration and employee assistance. Key areas of focus include providing reskilling opportunities, adopting mental health initiatives, and encouraging open conversation regarding AI's expanding role in the workforce. By addressing these concerns, organisations may build a more resilient workforce that is better suited to the fourth industrial revolution. The study intends to contribute to a better understanding of how organisations may safeguard and improve employee well-being in the face of fast technological change, ensuring that STARA integration encourages innovation while simultaneously supporting a healthy and engaged workforce
Estimation of Domestic Load Profile for Effective Demand-Side Management
Authors: Jalal Maryam , Rehman Attique Ur , Haq Azhar Ul , Khalil Ihsan Ullah
Published: October 2024

In this article domestic base and shift based load profile are estimated for effective Demand Side Management (DSM). Domestic electricity consumption in Pakistan accounts for approximately 40% of total electricity sales. Effective DSM can reduce electricity consumption. Power generation companies are increasingly recognising the importance of analysing their customers' consumption patterns. This article proposes an agent-based modelling approach for forecasting household electricity consumption profile. AnyLogic software is used for establishing the model that uses variables and functions to estimate base and shiftable load of three hundred households. This article also estimates the weekly and 24- hour load profile for effective DSM operations by smart grid infrastructure. The results show that the agent-based simulation closely approximates real-time data, with a difference of only 2.4%.
Sensitivity Analysis in Mathematical Models of the Hypothalamus-Pituitary-Thyroid Axis
Authors: Horvath Clara , Körner Andreas
Published: October 2024

Mathematical models are promising and important for advancing the current medical practice in the field of endocrinology. To assess the reliability of the range of mathematical models describing the hypothalamuspituitary- thyroid axis and to establish their applicability in clinical decision support, we conducted a local and global sensitivity analysis of the model. Thyroid regulation in euthyroid and diseased individuals may be quantified and dynamic behavior predicted through mathematical models, thereby revolutionizing the current clinical practice. We investigated the influence of model parameters of a selected mathematical model utilizing ordinary differential equations describing the HPT-axis. Motivated by a graphical depiction of the varying influence of the model parameters, feasible methods such as a local sensitivity analysis are conducted. Furthermore, to account for the influence of parameters on the output variance of the considered model, the theory of Sobol’ indices is utilized. Although the system of differential equations describing the hormone concentrations of thyroid-simulating hormones and unbound Thyroxine has similar equation structures, the results of the sensitivity analyses varied according to the equation.
Hayvan Besleme Biyokimyası
Authors: Akbağ Hande Işıl , Kop Bozbay Canan , İpçak Hasan Hüseyin , Coşkun İsa , Kamanlı Serdar , Üstündağ Ahmet Önder , Parlar Murat , Tüzün Cevdet Gökhan , Hanoğlu Oral Hülya
Published: October 2024

Sindirim Biyokimyasına Genel Bakış
Uğur SERBESTER
Mürsel ÖZDOĞAN
Suyun Biyokimyası ve Fonksiyonları
Hande Işıl AKBAĞ
Karbonhidratlar
Canan KOP BOZBAY
Hasan Hüseyin İPÇAK
Lipitler
İsa COŞKUN
Serdar KAMANLI
Proteinler
Hasan Hüseyin İPÇAK
Canan KOP BOZBAY
Bazı Etkicil Maddelerin Biyokimyası ve Fonksiyonları
Hande Işıl AKBAĞ
Mineraller
Ahmet Önder ÜSTÜNDAĞ
Murat PARLAR
Vitaminler
Cevdet Gökhan TÜZÜN
Enzimler
Hülya HANOĞLU ORAL
Effectiveness of Practical Skills Training on the Original Design Knee Joint Phantom
Authors: Sulyma V.S. , Omelchuk V.P. , Kuz U.V. , Omelchuk I.V. , Fedorkevych S.V. , Meniuk V.V. , Dubas V.I.
Published: October 2024

Background. Simulation training is a crucial aspect of intern training in Orthopedics surgery. Providing a practical and reproducible training environment, it helps interns avoid critical errors when working with future patients.
Objective. The objective of our study was to design, manufacture, implement in education course and evaluate the effectiveness of a knee joint phantom for training knee joint puncture.
Material and Methods. The knee joint phantom was created using Fusion 360 software and was printed using FDM technology on a Tevo Tarantula Pro printer with a Cura slicer with an insert container capable of repeated filling with various imitated liquids. To achieve a higher level of realism, the soft tissues were fully replicated. The phantom was fixed on two supports under the femoral and knee segments with a hinge, which provides the possibility of movements in the joint at different angles. 30 ordinators were involved in the study and divided into two groups: group I included 15 ordinators who conducted training on a knee model from the beginning of the 2nd year; group II consisted of 15 ordinators who conducted training from the beginning of the 1st year. The effectiveness of practical training was evaluated through statistical analysis of the results of OSCI, with a phantom being used.
Results. The mean score was 3.9±2.7 and 4.8±2.8 in group I and group II, respectively, with the maximum possible result of 5.5, which indicates the effectiveness of simulation training with the help of a manufactured knee joint phantom. A small number of participants were included in the study, so no significant difference in learning outcomes between the comparison groups was established (p=0.09492).
Conclusions. Simulation training with a knee phantom is an efficient method for educating orthopedic surgeons on how to perform manipulations on the knee joint. This training also aids in identifying those who have acquired the skill at a lower level. This approach can prevent potential errors when performing manipulations and minimize complications in the treatment of patients with knee joint pathology.
Analysis of Early Surgical Treatment of Incorrectly Consolidated Gunshot Fractures of the Scapula
Authors: Telepenko H.V. , Haiovych V.V.
Published: October 2024

Objective. The objective of our study was to analyze the structure of incorrectly consolidated gunshot fractures of the scapula and early outcomes of surgical treatment.
Material and Methods. We analyzed 10 cases of incorrectly consolidated gunshot fractures of the scapula in Ukrainian Armed Forces servicemen, received as a result of combat operations, and early outcomes of surgical treatment. The main indications for surgical treatment were as follows: severe impairment of function of the upper limb due to pain, fractures of the articular surface of the scapula with displacement of fragments over 2 mm, fractures of the acromion with displacement of more than 8 mm, and damages to muscles and skin. In addition to radiography in standard projections, preoperative examination included computed tomography (CT). Evaluation of functional outcomes was carried out within 1 to 4 months according to the Oxford Shoulder Score (OSS) scale. The average period of postoperative survey was 2.6 months.
Results. Incorrect consolidation of fractures was caused by a long period of preoperative preparation and conservative treatment of wounds in patients due to openness and infection of bullet wounds in 2 patients and shrapnel wounds because of mortar, artillery, tank and rocket attacks in 8 patients. Staged treatment until wound healing was carried out in hospitals and military hospitals of Ukraine using VAC (Vacuum-Assisted Closure) devices. Four cases were right-sided and six were left-sided; 7 of 10 cases were intra-articular fractures with displacement of fragments of the articular surface by 2 mm or more. The average duration of injury at the time of surgery was 4.2 months (range from 2 to 8 months). In addition to eliminating displacements and deformities of incorrectly consolidated fractures and osteosynthesis of fragments, the treatment included replacing the soft tissue defect of the shoulder and shoulder girdle with a non-free thoracodorsal musculocutaneous flap on a neurovascular pedicle in 3 of 10 patients. Seven patients had an isolated wound to the scapula area. Three of 10 patients had a combined wound to the scapula with a defect of the humeral head, upper third of the humerus, and acromial end of the clavicle. These patients underwent implantation of an articulating spacer, restoration of the configuration of the proximal end of the humerus, and reconstruction of the rotator muscles to make possible the shoulder joint arthroplasty. The average value according to the results of a survey of patients on the OSS scale was 20.2 (±4.39) points before surgery and 34.1 (±7.56) points after surgery, which can be considered a good result according to the OSS scoring system.
Conclusions. The analysis of the early outcomes showed that reconstructive treatment of gunshot old fractures of the scapula creates biomechanical prerequisites for restoring the function of the upper limb, reduces pain syndrome, and allows for active postoperative rehabilitation.
Hybrid inspection of printed board defects
Authors: Vengerenko V. V. , Inyutin A. V.
Published: October 2024

Objectives. A hybrid approach to the problem of searching and classifying defects in printed circuit boards (PCB) is proposed. Key factors and trends in the design and production of PCBs are considered. The relevance of the study is determined by the use of new materials and production technologies.

Methods. A hybrid approach based on the algorithm of comparison with reference and the use of the YOLO family of neural network models for detecting objects is used to solve the problem.

Results. Models were trained on public sets of PCB images with six classes of defects, and their accuracy was assessed using generally accepted metrics.

Conclusion. Experiments have shown that the YOLOv8 neural network architecture has high accuracy of defect detection, low sensitivity to image quality, presence of text and graphic objects on the PCB, but the low quality of training datasets imposes restrictions on the use of only neural networks for defect detection. It is proposed to use a hybrid approach to improve the quality of defect inspection by applying different methods depending on the quality assessment of the analyzed images.
Web search results processing in an information support system for decision-making processes
Authors: Lipnitsky S. F. , Stepura L. V.
Published: October 2024

Objectives. The problem of the web search results processing in an information support system for decision[1]making is solved in order to create and correct a meaningful description of a problem situation. An approach to solving this problem is proposed based on the use of thematic text corpora (collections of texts on a specific topic) as knowledge about the subject area, as well as a knowledge representation model based on verbal associations. When solving problems of the web search results processing in a decision-making information support system, five main goals are pursued: the formation of an extended description of a problem situation, the synthesis of a search prescription, an Internet search for information about decisions made, the synthesis of a retelling of the information found, and an assessment of the quality of the found analogues of the decisions made.

Methods. Methods of set theory, graph theory and mathematical linguistics are used.

Results. A mathematical model has been developed for the web search results processing in an information support system for decision making. The concepts of verbal association of words and texts, as well as pragmatically complete lexical structure, are formalized. The proven properties of such structures provide algorithmization of information processes in the model under consideration.

Conclusion. The approach to modeling is based on the formalization of the concepts of the informativeness of words, sentences, texts and the informativeness of verbal associations between them. As an implementation of the model proposed in the article, algorithms have been developed for creating a dictionary of pragmatically complete lexical structures, creating structural-lexical templates for sentences, texts and subject areas, synthesizing a brief retelling of the information found, and assessing the quality of the found analogues of the decisions made.
HUBUNGAN SENAM PROLANIS TERHADAP PENURUNAN KADAR GULA DARAH SEWAKTU PADA PASIEN DIABETES MELLITUS TIPE 2 DI PUSKESMAS SEI LEKOP
Authors: Indriasari  , Elvita Nora Susana  , Muthiah Ramadhani
Published: October 2024

Background : Type 2 diabetes mellitus is a chronic metabolic disease characterized by elevated blood glucose levels in the body due to insulin resistance or inadequate insulin production. The purpose of this study is to investigatethe relationship between physical activity and blood sugar levels in patients with type 2 Diabetes Mellitus who participated in the PROLANIS program at the Sei Lekop Community Health Center in 2023.
Methods : This study is an observational research with an analytical cohort design. Data collection was obtained from the medical records of patients with type 2 diabetes mellitus who are registered under BPJS. The data analysis methods include univariate analysis and bivariate analysis, with a standard error of estimate set at 5% or 0.05
Results : The results of the Wilcoxon test showed that PROLANIS exercise had a relationship with reducing blood sugar levels during type 2 diabetes mellitus patients at the Sei Lekop Community Health Center in 2023. The results of the Wilcoxon test were p = 0.001.
Conclusion : Based on the results of this study, it can be concluded that there is a relationship between PROLANIS exercise and random blood sugar levels in patients with type 2 diabetes mellitus at Sei Lekop Health Center in 2023
 
 
Keywords : Diabetes Mellitus, Blood Glucose Levels, and PROLANIS Exercise.
PERBANDINGAN EFEKTIVITAS MADU DAN EKSTRAK ETANOL DAUN KELOR (MORINGA OLEIFERA LAMK) TERHADAP PERCEPATAN PENYEMBUHAN LUKA BAKAR DERAJAT II PADA TIKUS PUTIH JANTAN (RATTUS NORVEGICUS STRAIN WISTAR) SECARA MAKROSKOPIS
Authors: Muhammad Azmi Fanany  , Andi Ipaljri Saputra  , Wifa Nur Yasmin
Published: October 2024

Background: Burns are damage to the skin or other tissues caused by high temperatures, radiation,electricity, or contact with chemicals. Healing by maintaining resistance that has potential to killbacteria at affordable prices is to use the active substances contained in honey and Moringa leaf.Methods: Research with True Experimental design by giving honey and ethanol extract of moringaleaves in gel preparation to affect the acceleration of second degree burn wound healing in ratsmacroscopically. With the design of "Post Test Only Control Group Design". The data were analyzedusing the Mann Whitney nonparametric test.Result: Analysis of data on the average diameter of wound healing and percentage of wound reductionon day 7 between honey and ethanol extract of moringa leaves with a significance value of 0.000, onday 14 a significance value of 0.000 was obtained which means sig.<0.005 It can be concluded thereis a significant difference between the treatment groups.Conclusion: Ethanol extract of moringa leaves has a smaller wound diameter value, which is anaverage of 12.09 mm compared to honey which has a wound diameter of 14.54 mm. Based on thepercent reduction value, moringa leaf ethanol extract has a percent wound reduction of 39.90%compared to honey which has a percent wound reduction value of 27.26%.
The Effectiveness of Implementing a Milling Process in Reducing Production Process and Costs: A Case Study
Authors: Osman Saliza Azlina , Dainil Nur Fitrah , Osman Shahrul Azmir
Published: October 2024

Every product's design has a different process flow. Sometimes, designed products consist of a repeated process flow. Repeated processes are a problem that can affect production management and production output. This study has potentially proposed a new process that can replace the existing process by adding a milling process. The result shows that introducing a milling process was added to item 2 to produce a step slot and reduced the number of items used (Item 3). The assembly of Item 2 and Item 3 was converted into Item 6, which showcases a more substantial time differential, with the existing process taking 12.25 minutes and the new process requiring 0 minutes. The additional process of the new alternative milling machine reveals lower Watt, less time duration for the welding machine, reduced energy consumption for a hand-grinding machine, and lower cost demand for the welding machine than the existing process. In addition, the total cost of the added milling process shows a slight reduction in overall cost and is associated with energy consumption.
Video Content Analysis for Detection of Road Traffic Congestion Pattern: An Optimized YOLOv8 Based Approach
Authors: K.C. Hari , Pokharel Manish , Shrestha Sushil
Published: October 2024

This paper presents a new approach to Video Content Analysis (VCA) with a specific focus on detecting and analyzing road traffic congestion patterns. The implemented methodology deploys the YOLOv8 (You Only Look Once) object detection framework, which has been optimized to accurately and efficiently identify road traffic objects within video streams. The primary goal is to improve traditional VCA systems by capturing and understanding complex road congestion scenarios. This research develops a customized YOLO model optimized specifically for road traffic analysis. The optimization process addresses the challenges inherent in real-world traffic scenarios including variations in lighting conditions, diverse vehicle types and dynamic traffic flow patterns. The developed model seeks to enable robust and real-time detection of congestion-related events such as heavy congestion and normal congestion thereby contributing to improved traffic management and overall road safety. Moreover, the paper explores the integration of advanced techniques for congestion pattern analysis including vehicle detection, tracking, and counting. The combination of these features facilitates a comprehensive understanding of traffic dynamics and congestion evolution over time. The proposed approach is trained and evaluated on benchmark datasets and real-world video footage to assess its performance. Experimental results demonstrate the effectiveness of the optimized YOLOv8-based approach in accurately detecting and analyzing road traffic congestion patterns. The system exhibits promising capabilities in handling diverse and challenging scenarios thereby serving as a valuable tool for intelligent transportation systems, urban planning and traffic management. This research significantly contributes to the advancement of video-based traffic analysis, providing a robust solution for monitoring and mitigating congestion-related challenges on road networks.
Development of Prediction Models to Detect the Presence of MGMT Promoter Methylation for Prognosis of Brain Tumor
Authors: Abdullah Azian Azamimi , Ali Askar Musaab Nabil , Ul-Amin Md Altaf , Kanaya Shigehiko
Published: October 2024

Methylation of the MGMT promoter is a molecular marker of predictive relevance in brain tumors. Methylation of the MGMT promoter is related to an improved prognosis and may influence therapy decisions. According to the most recent Malaysian National Cancer Registry Report (MNCRR) for 2012–2016, there were 2097 cases of brain tumors in Malaysia overall, with 1117 cases involving men and 908 cases involving women. This research aims to create prediction models for detecting MGMT promoter methylation in brain tumors. So, a dataset from the BraTS (Brain Tumor Segmentation) challenge, which included MRI scans and clinical data for patients with brain tumors, was utilized and explored using Exploratory Data Analysis (EDA) and data visualization techniques. The dataset has 306 methylation cases identified as “1” and 276 unmethylated cases identified as “0”. The average number of scans of train data for modality per patient is between 127 and 171, which provides a wealth of information for pattern learning while the average number of scans of test data for modality per patient is between 124 and 165. In both sets, FLAIR has the least number of files while T2w has the highest number of files among them. Two models of deep learning approaches, ResNet50 and EfficientNetV2, were used to construct and form the prediction models. Various criteria were employed to evaluate the performance of the models. The T2w modality consistently achieved the highest validation accuracy, precision, recall, and F1-score for both the ResNet50 and EfficientNetV2 models. Specifically, the T2w modality achieved a validation accuracy of 0.9453 and a validation loss of 0.2417 for ResNet50. Furthermore, the brain tumor diagnosis interface utilized DICOM images from MRI scans to identify MGMTp methylation status, aiding in therapy effectiveness prediction. Pre-trained ResNet50 model on T2w images was used for classification. The interface displayed the original MRI image, predicted state, and treatment effectiveness indication, while promptly notifying users of invalid or inadequate data for accurate analysis.
Comparing the Effectiveness and Efficiency of Machine Learning Models for Spam Detection on Twitter
Authors: Chua Stephanie , Tan Amy , Nohuddin Puteri Nor Ellyza , Ahmad Hijazi Mohd Hanafi
Published: October 2024

A comprehensive study focused on the efficiency and effectiveness of machine learning models for Twitter spam detection was presented in this research. Spam detection on social media platforms is not only vital for user experience but also poses computational challenges due to the vast and dynamic nature of Twitter data. This investigation encompassed a range of machine learning models, including Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (LR), k-Nearest Neighbours (KNN), and Decision Trees (DT). Their performances were scrutinized across two critical dimensions: classification accuracy and computational efficiency, as measured by the time taken for model execution. The results of the analysis revealed valuable insights into model performance. The NB and LR models emerged as the most computationally efficient models, with execution times ranging from 1.016 to 1.949 seconds. These models offered an attractive balance between speed and accuracy, making them suitable for real-time or resource-constrained applications. SVM, LR, KNN and DT were effective in classification with a performance of 98%. However, SVM models demanded longer execution times, ranging from 7.670 to 37.657 seconds. KNN and DT stroked a balance between accuracy and efficiency, with execution times ranging from 2.852 to 10.941 seconds and 1.080 to 2.442 seconds, respectively. Our research underscores the importance of considering both model effectiveness and computational efficiency when selecting a Twitter spam detection model. By offering a comparative assessment of these models, this study equipped researchers with valuable insights for making informed decisions in Twitter spam detection. It highlighted the trade-offs between model performance and efficiency, paving the way for more effective and resource-conscious approaches to combating spam on social media platforms.
Development of Eco-Friendly Refrigerants for Industrial Refrigeration to Minimize Greenhouse Gas Emissions and Environmental Harm
Authors: Al-Zurfi Hazim A. , J. Aljabri Ghaith , Hammodi Abd Ahmed , Al-Gburi Zaid M.
Published: October 2024

Development of Eco-Friendly Refrigerants for Industrial Refrigeration to Minimize Greenhouse Gas Emissions and Environmental Harm
Cyber Security Awareness Model Based on NIST (National Institute of Standards and Technology) for Secondary School Students in Malaysia
Authors: Zulkifli Zahidah , Ismail Ahsiah , Mat Surin Ely Salwana , Okfalisa Okfalisa
Published: October 2024

As cybersecurity issues surge, it highlights the pressing need for increased awareness. In our digitally interconnected world, where information technology underpins the lives of individuals, businesses, and even national security, the threat of cyberattacks looms large. To enhance national cybersecurity preparedness, there is a critical call to action: we must promote public awareness of cybersecurity issues and bolster the ranks of trained cybersecurity professionals. This research introduces a novel cybersecurity awareness model based on the National Institute of Standards and Technology (NIST). Its primary goal is to make NIST accessible to secondary school students pursuing ICT courses and their invaluable resource, the school counselling units. The model aims to instil cybersecurity awareness in secondary school students and guide them in choosing the most suitable higher education paths, particularly in the ICT and cybersecurity fields. The study comprises three phases. In the first phase, a systematic literature review (SLR) examines globally applicable cybersecurity education models. The second phase investigates the implementation of cybersecurity education for secondary school students in Malaysia. This includes interviews with school counselling units responsible for guiding students toward higher education and surveys of students in grades four and five enrolled in ICT courses. The third and pivotal phase focuses on developing the proposed model. It involves analysing and implementing the results of the SLR, mapping them to the NIST framework, and incorporating themes from interviews and surveys. As a tangible representation of the model, a mobile application prototype has been developed. The Cybersecurity Awareness Model empowers school counselling units to seamlessly integrate career exploration with career decision-making for secondary students at any stage of their development. Moreover, it offers a means to create strategies for after-school programs, particularly in the dynamic field of cybersecurity. This model is expected to guide students in exploring academic majors and careers, preparing for higher education post-high school, initiating internships or job searches, and adapting to a world in constant flux. In doing so, it not only empowers individuals but also strengthens the nation's resilience in the face of cybersecurity challenges.
Effect of Climate Change on Wildlife
Authors: Salma Hafiza , Nadeem Muhammad , Khalid Nimra , Imran Ashraf Muhammad , Nawaz Dr. Haq , Ayub Muhammad Ashar
Published: October 2024

Climate change is a global catastrophe that disrupts the balance of ecosystem by altering the climatic measures. Human being are not the only living species on earth that is affected by climate change. All the inhabitants on Earth are dependent on suitable living conditions for their survival. All human and non-human species on Earth either directly or indirectly relying on each other. Wildlife is the key indicator of climatic changes in the environment as they are part of various biological and ecological cycles in the atmosphere. Over the century, the atmospheric temperature has increased around 1.1°C. Changes in climatic conditions is affecting the terrestrial and aquatic biomes in plenty of ways. Limiting basic living conditions of animals by destruction of their natural habitation and its transformation into urban lands which intensifies the human-wildlife interactions. Migration of temperature sensitive species to the areas of higher altitude. High temperatures have increased the occurrence of wild-land fires, floods and droughts five times more than past 50 years. Animals naturally respond to altering climatic conditions by exhibiting changes in their general and reproductive behavior, growth patterns, increased zoonotic diseases. All these above cited effect put them to the status of endangered species and ultimately to the extinction. Strategic approaches i.e., protection, management, planning and evaluation of natural biomes to conserve the Earth’s biodiversity must be opted to avoid the extinction of wild species.