bluuebunny/crossref_metadata_2025 huggingface dataset:
Penerapan Effective Coughing pada Tn.T dengan Penyakit TB Paru dengan Masalah Keperawatan Bersihan Jalan Napas Tidak Efektif di Ruang Nurul Jannah 301 RSI.Malahayati
Authors: Dimas Agil Latunda  , Afiatika Ahsani
Published: October 2024

Pulmonary Tuberculosis is a disease caused by the bacteria Mycobacterium Tuberculosis which enters the respiratory tract and attacks the lungs so that in the alveoli there are nodules or inflammation in the walls of the alveoli which will shrink. One way to reduce secretions in pulmonary tuberculosis patients is through effective coughing exercises. This article uses a case study design and the subjects used in this case are pulmonary tuberculosis patients treated at RSI Malahayati Medan with the problem of ineffective airway clearance. The results of implementing the intervention showed that after applying the effective cough technique for 3 days the patient showed that the patient was able to expel secretions, the respiratory frequency decreased to 22 times per minute, but there were still crackles in the breath. Conclusion: applying effective coughing techniques to patients can be used to expel secretions and can reduce respiratory frequency in pulmonary tuberculosis patients. Suggestions are expected for patients to be able to take independent action (cough effectively) when experiencing problems with ineffective airway clearance.
PROFIL STATUS GIZI ATLET KEMPO SULAWESI UTARA
Authors: Christoforus Manopo  , Mokoagow Mokoagow  , Bokau Bokau
Published: October 2024

This research aims to determine the nutritional status profile of Kempo athletes in North Sulawesi. Nutritional status is an important factor in supporting athletic performance, especially in the sport of Kempo, which requires strength, speed, and endurance. This research uses a descriptive method with a quantitative approach to measure the nutritional status of athletes through Body Mass Index. (IMT). The research sample consists of 40 Kempo athletes in North Sulawesi aged 17 and above. The research results show that the majority of athletes have an ideal nutritional status, with 95% of the total sample falling into the normal weight category, while the remaining 5% are classified as having mild underweight. This finding shows that Kempo athletes in North Sulawesi generally have good nutritional status and are ready to compete in matches with optimal physical condition. This research is expected to raise awareness of the importance of balanced nutrition for athletes to support optimal performance in sports.
Pengaruh Mutu Pelayanan Kesehatan Terhadap Kepuasan Pasien di Ruang Rawat Inap RSUD Menggala Kabupaten Tulang Bawang Provinsi Lampung
Authors: Nia Arita  , Nur’aini Nur’aini  , Ramadhani Syafitri Nasution  , Juliandi Harahap  , Endang Maryanti
Published: October 2024

Hospitals are a comprehensive part of social and media organizations whose function is to provide complete health services to the community, both curative and rehabilitative, hospital services reach family and environmental services. The aim of the research is to analyze the influence of health service quality on patient satisfaction in the inpatient room of Menggala Regional Hospital, Tulang Bawang Regency, Lampung Province. Analytical survey research design with a cross sectional design. The total population of patients treated from June 2022 to August 2022 in the Inpatient Room at Menggala Regional Hospital, Tulang Bawang Regency is 167 people. The number of samples was 62 people. The results of the chi square test research show that there is an influence of 8 variables, namely technical competence, human relations, effectiveness, efficiency, continuity, security, human relations and comfort, which have a p-value <α 0.05, meaning that technical competence, human relations, effectiveness, efficiency, continuity, safety, human relations and comfort influence patient satisfaction in the Menggala Hospital inpatient room. The results of the multiple logistic regression test are the most dominant comfort variable with an odds ratio (OR) of 18.455, meaning that it influences patient satisfaction 18 times. The conclusion is that the comfort variable is the dominant variable that has the most influence on patient satisfaction in the Menggala Hospital inpatient room. It is recommended for hospitals to adopt policies to increase patient comfort in treatment rooms in order to produce optimal satisfaction for patients.
The Relationship of Food Intake and Mother's Parenting Patterns With the Incident of Stunting in Toddlers
Authors: Annisa Febriana
Published: October 2024

Stunting occurs when a child's height is lower than average age due to poor growth caused by chronic malnutrition, which occurs when a child's nutritional intake is insufficient for a long period of time. Stunting may have direct and indirect causes. Direct reasons include inadequate nutrition, while indirect causes include parenting. Food consumption is a habit that improves the body's nutritional state in a measurable way. Objective: This research is to determine the relationship between food intake and maternal parenting patterns with the incidence of stunting in toddlers at the Romana Clinic in 2024. Method: Quantitative, observational, cross-sectional techniques were used in this research. The months June to July 2024 were used for this research. Primary data and secondary data are two categories of data. Data were analyzed using the chi-square test for bivariate and univariate analysis.Research results: These findings show a significant correlation (p value = 0.000 <0.05) between food consumption and the incidence of stunting. P value = 0.002 <0.05, indicating a relationship between maternal parenting and the incidence of stunting.Conclusion: There is a strong correlation between calorie consumption and stunting. Parental involvement is significantly related to stunting levels. Suggestion: We hope that posyandu cadres and community health center officials in the study locations gain a deeper appreciation of the role parents play in monitoring the dietary needs of their toddlers.
Implementasi Nilai-Nilai Pancasila dalam Pelayanan di Puskesmas Nabarua Tahun 2023
Authors: Marthen Toding
Published: October 2024

Pancasila values ​​are not only implemented at that time but are preserved every day. As the basis of the Indonesian nation and state, Pancasila is essentially derived from cultural values, not just as reflections or thoughts of individuals like other foundations in the world, religious values ​​contained in the outlook on life of the Indonesian nation before the founding of a country. The aim of the research is to see the implementation of these values. -Pancasila values ​​in services at the Nabarua Health Center. The method used in this research is literature study (data collection, literature references related to the implementation of Pancasila values) with a case study type of research using research.  Qualitative descriptive approach. The results of the research. The implementation of Pancasila values ​​is reflected in five principles, starting from the value of God to the value of Justice which is implemented in health services for medical record officers. The first principle is demonstrated by the activity of greeting and saying hello, the second principle is an attitude of helping each other through humanitarian activities such as Health Services for Children, Toddlers, Adults and the Elderly. The third principle is to join a professional organization. The fourth principle is demonstrated by providing opinions during evaluation meetings held every month at the Community Health Center. The fifth principle is implementing working relationships between medical record officers in accordance with the professional code of ethics. The suggestion in this research is to apply Pancasila values ​​at the Community Health Center, there are internal obstacles such as officers being late in attending the morning roll call and some officers being unable to attend the evaluation meeting which is held once a month. The head of the Community Health Center has an important role in applying Pancasila values ​​to medical records officers. So, the head of the community health center and his staff must be more able to provide motivation, support and examples for officers in implementing the values ​​of Pancasila.
Analysis of the Effect of Family Support and Knowledge of Arv Therapy in Patients With HIV on Quality of Life With Adherence to Taking Arv Drugs as an Intervening Factor in the Outpatient Unit of RSUD Kabupaten Tangerang
Authors: Tasya Sabrina Chairunisa  , Intan Silviana Mustikawati  , Kemala Rita
Published: October 2024

Human Immunodeficiency Virus (HIV) remains one of the most serious health challenges in the world. Until now, people with HIV/AIDS have not been cured, but HIV infection and replication can still be prevented with medication. The treatment is known as antiretroviral therapy (ARV). Quality of life in HIV/AIDS patients is very important to note, because this infectious disease is chronic and progressive, so that it has an impact on various aspects of life, both physical, psychological, social, and spiritual. This study aims to identify factors that can affect the quality of life of HIV/AIDS patients through family support, knowledge of ARV therapy, and adherence to taking medication as intervening. Quantitative research method with cross sectional design. The sample technique in this study was purposive sampling. The minimum sample size was determined through Hair's formula and 140 samples were obtained. Data collection techniques with questionnaires and data analysis techniques using bivariate and multivariate analysis. The results showed that there was a significant positive influence between family support and knowledge of ARV therapy on quality of life through adherence to taking ARV drugs as an intervening variable. There is a significant positive influence between family support on quality of life. There is a significant positive influence between ARV therapy knowledge on quality of life. There is a significant positive influence between family support on adherence to taking ARV drugs. There is a significant positive influence between knowledge of ARV therapy on adherence to taking ARV drugs. There is a significant positive influence between adherence to taking ARV drugs on quality of life.
Design and economic analysis of energy storage optimization allocation for campus microgrid
Authors: Deng Zhihua
Published: October 2024

In the twenty-first century, the "double carbon" plan is advancing steadily. Energy saving and emission reduction is one of the key points of the plan. A power grid independent park, if energy storage equipment can be configured, it can greatly improve the park microgrid power utilization, in order to achieve the purpose of energy saving. Therefore, research on the optimization of the proportion of power grid and microgrid in the park and the optimization of the configuration of energy storage devices can greatly improve the energy utilization rate, so as to achieve the significance of environmental protection. After collecting and sorting the daily load, daily wind power generation and 12-month daily wind power generation data of the three parks A, B and C, and processing the data, a linear function model is established. After using linear programming, operations research and genetic algorithm, the research results are obtained when the three parks are combined and equipped with 50kW/100kWh energy storage devices.
Investigating Blockchain Technology's Integration in Financial Services
Authors: Niu Tianrun
Published: October 2024

This paper introduces a comprehensive analytical framework designed to assess the efficacy of blockchain technology in financial accounting and its broader implications for the financial sector. The analysis explores how blockchain can revolutionize financial accounting by enhancing both efficiency and accuracy, facilitating real-time financial reporting, and expediting audit processes. It also examines blockchain's current deployment across various financial domains, including insurance, banking, payment systems, asset trading, lending, and remittances, offering a detailed look at the technology's penetration and impact. The study identifies significant hurdles, such as elevated transaction fees and prevailing technical constraints, which currently impede broader adoption. It also discusses potential regulatory challenges and the need for sector-wide collaboration to realize the full benefits of blockchain. The results of this study provide critical insights for both researchers and developers within the financial sector, highlighting the transformative potential of blockchain and proposing directions for future technological advancements and application areas. This examination not only underscores the immediate benefits and challenges but also sets the stage for subsequent innovation in integrating blockchain into established financial systems, potentially leading to more robust, transparent, and efficient financial services.
Tennis Game Swing Prediction Model Based on ID3 Algorithm and Logistic Regression Model
Authors: Liu Yufeng , Ma Yiming , Liu Shichao
Published: October 2024

Tennis, as one of the most popular sports worldwide, includes exciting matches between players. In some matches, score advantage can swing constantly from one side to another. These score swings may impact players’ performance and the result. To accurately predict the swings during a match between players, the article aims at building a score swing prediction model based on ID3 algorithm and logistic regression algorithm. The article will focus on analyzing tennis players’ behaviors and performance during a match. The preparation is to form a decision tree to evaluate diverse events’ impact on players’ mental strength, using ID3 algorithm that can analyze desired indicators with relevant data. By using the results from the decision tree evaluation, indicators with higher priority will be analyzed by the logistic regression model. The following Omnibus test and Hosmer-Lemeshow tests will estimate significance value and prediction accuracy. The results can show the prediction of scores swings in a match and indicate the factors that impact the match more. The study can provide tennis players with theoretical advice on their training activities, which may improve the ability of reversing the match and being consistent under pressure effectively.
Classification and Comparison of Data Augmentation Techniques
Authors: Zhang Jingxing
Published: October 2024

Data augmentation is a technical method that generates additional data samples by applying different transformations and processes to the original training data. It aims to increase the size and diversity of the dataset, thus improving the models' generalization ability. This paper provides a detailed introduction to geometric transformations, data mixing, automated data augmentation methods, and generative adversarial methods. Geometric transformations manipulate the spatial configuration of data samples to create new variants that retain the original content. Data mixing techniques blend multiple data samples to produce novel training examples, promoting robustness and reducing overfitting. Automated data augmentation methods leverage search algorithms to discover optimal augmentation policies that improve model performance without manual intervention. Generative adversarial methods employ generative adversarial networks to synthesize realistic data samples that enrich the training dataset. These methods find broad application in domains including object detection, image classification, natural language processing, and speech recognition, significantly improving model performance. The paper explores the advantages and limitations of data augmentation techniques in practical applications and identifies future research directions and challenges. By systematically classifying and selecting appropriate data augmentation methods for specific application scenarios, this review provides a theoretical foundation and practical guidance for real-world applications.
Simulation Design and Research of Flame Generation in Virtual Fire Scene Based on Unity3D
Authors: Dong Lixiao
Published: October 2024

Since the 21st century, with the continuous development and progress of science and technology, the possibility of fire danger is also rising, the requirements of public fire safety management have also been improved accordingly, and the problems in its fire safety management work make it difficult to meet the management requirements. The selection of firefighters has also become the top priority of management, good psychological quality of firefighters can keep calm in the face of fire explosions and various emergencies, and can make the most correct choice to complete the rescue and fire fighting work. In this paper, a building in a certain location is selected as the location to simulate the scene of fire. Through human-computer interaction to judge the psychological quality of firefighters. First use major modeling software such as 3ds Max, Adobe Fusecc, or find material in the Unity3D store to create models of fire scenes and people and import them into Unity3D. Using Unity3D's own particle system component to build flame models, adding collision body components to all models to detect their collision detection mechanism and the mechanism of flame spreading combustion. A Scenario-based Communication Ability Evaluation System Based on Traditional Cognitive Behavior Measurement and Advanced Eye Movement, EEG and NIR Acquisition Techniques.
Research on Key Technologies of Spatial Domain Image Steganography and Analysis of Typical Applications
Authors: Zhang Chuanyue
Published: October 2024

In the digital age, secure storage and communication of information are crucial aspects of everyday life, drawing significant global interest. Steganography serves as a pivotal method for concealing private information within various media forms—such as images, videos, and text—enabling secure information transmission. This paper delineates the distinctions between information hiding and encryption and delves into image steganography. The focus here is on spatial-based image steganography techniques, which are broadly categorized into traditional and deep learning-based methods. Traditional methods rely on modifications to the pixel values of the host image, often resulting in minor but detectable changes if not carefully managed. On the other hand, deep learning-based methods leverage neural networks to learn how to encode data in an image in a way that is much harder to detect. A comprehensive performance analysis of these techniques is provided, complete with comparative tables to aid in clarity and reference. Additionally, this paper aims to guide researchers by charting current trends in the field and suggesting future research directions. By exploring these advanced techniques, the paper contributes to the broader discourse on enhancing the security and efficacy of steganographic practices.
Immersion in open-world games based on Grounded theory -- A case study of Genshin Impact
Authors: Wang Yang
Published: October 2024

In recent years, with the expansion of the game market and the rapid growth of game users, the game market has great potential. At the same time, open world games are loved by the vast majority of users. [Purpose/Significance] Explore the factors that affect the immersion of players in open world games, drive the improvement of the quality of open world games, help improve the industrial ecology, and achieve richer functional values. [Research design/Methods] Taking the open world adventure role-playing game "Genshin Impact" as a case study, semi-structured interview was used to obtain first-hand interview data, and coded research was conducted using grounded theory. Through several processes such as open coding, spindle coding, selective coding and theoretical saturation testing, the corresponding theoretical model is finally formed. [Conclusion/Finding] The results show that the basic feature of immersion performance is concentration. The two factors, the in-game condition and the out-of-game condition, together constitute the pre-factors that produce immersion. After entering the state of immersion, the main performance is to produce tension and emotional resonance. [Innovation/Value] builds a theoretical model for the generation of immersion in open world games, which lays a theoretical foundation for future theoretical model testing and empirical research.
YOLO-based Face Emotion Recognition System for Teaching Scenes
Authors: Wang Yuxuan
Published: October 2024

The main way to get emotional data has been through how they looked, which are able to interact a variety of feelings like joy, grief, fear, rage, disgust, and surprise. These expressive emotions are vital to communication due to their enable people to better understand one another's thoughts and desires. Therefore, we thought that we could utilize technologies such as computer vision to obtain images of students' expressions in the classroom through cameras and other related devices. In order to create a database, the camera is used to build an image acquisition system. One image is preprocessed, the YOLOv5s algorithm is used to extract the features of the face, and the outcome of correct recognition is determined by comparing the feature vectors that were obtained. The expressions are then categorized using the extracted feature vectors based on a multilayer perceptual network (MLP). Lastly, the computer summarizes the identifying data and uses a WeChat applet to deliver it to the teacher.Teachers can more effectively comprehend the educational needs of their pupils surroundings and modify their approaches to instruction with the help of this WeChat applet. This will help improve the quality of online education.
Recent Progress in ECDSA and DSA Digital Signature Algorithms
Authors: Gong Senyi
Published: October 2024

Digital signatures are essential for verifying the authenticity and integrity of information, thus facilitating digital authentication. The Elliptic Curve Digital Signature Algorithm (ECDSA) and the Digital Signature Algorithm (DSA) play critical roles in the field of digital signatures. This paper explores the conceptual frameworks and mathematical underpinnings of these algorithms, providing an in-depth analysis of their advantages and disadvantages with a focus on computational time complexity and key length requirements. The distinct applications of ECDSA and DSA in various fields are examined, highlighting how the selection of an algorithm influences security and efficiency in different scenarios. This analysis also considers the algorithms' suitability for specific security applications, offering insights into their strategic deployment. By comparing these characteristics, the study aims to guide the selection of appropriate digital signature technology, tailored to meet operational needs and security specifications. This comparative approach not only elucidates the practical implications of each algorithm but also contributes to a broader understanding of their roles in securing digital transactions.
A Study of Distribution Problems Based on Express Transportation Networks
Authors: Deng Lige
Published: October 2024

This article uses the distribution data of rookie stations in Jinan City to explore the allocation problem of express delivery transportation networks. Firstly, in response to the uneven spatial layout of rookie Station, a corresponding evaluation index system was established based on K-means and TOPSIS models. The results showed that rookie Station exhibited characteristics of agglomeration in the central urban area and dispersion in the remote urban area. Secondly, by establishing a Floyd model to plan the route, the most reasonable transfer center was determined, and the results showed that the Shizhong District was the most suitable transfer station for Jinan City, while Zhangqiu District was selected as the second transfer station. Finally, based on the population density and express delivery demand in Jinan City, a model for express delivery allocation business points was established, and the optimal solutions for express delivery allocation business points in each district were obtained.
Analysis of machine learning methods applied to financial problems
Authors: Zhang Jiayi
Published: October 2024

With machine learning being widely used in many fields. In this paper, we study how machine learning methods can be used to make predictions in financial problems and analyze the applications.Machine learning is a branch of artificial intelligence that enables computer systems to learn from data and make decisions or predictions without being explicitly programmed at every step. Machine learning models are trained on large amounts of data to discover patterns and relationships in the data and use these patterns to make predictions or perform tasks. The purpose of this post is to illustrate the role machine learning plays in dissertation research.Machine learning can also be used for smart urbanization, industrial automation, fintech, healthcare, agricultural modernization, cybersecurity, etc. For example, extracting valuable information and knowledge from large amounts of data to help businesses and organizations make better decisions. By analyzing historical data, machine learning can predict future trends and behaviors, such as stock prices, house prices, weather, etc.
Multi-scenario Vehicle Detection Based on the YOLOv5 Algorithm
Authors: Zhou Liang
Published: October 2024

This paper addresses the issues of increasing traffic volume leading to frequent traffic congestion and accidents by studying the effectiveness of occluded vehicle detection based on the YOLOv5 algorithm. The aim is to explore the performance of this algorithm in various occlusion scenarios. Firstly, we introduce the occluded vehicle images used for testing and describe different types of occlusions in detail. Then, the basic principles and construction process of the YOLOv5 algorithm are explained. Subsequently, we propose a vehicle detection and recognition model based on YOLOv5 and validate the model's effectiveness through convergence analysis of the training loss curve and accuracy analysis of the test set. Finally, experimental results demonstrate that the YOLOv5 algorithm can efficiently and accurately detect vehicles in complex scenarios and partially occluded conditions, showcasing its application potential in intelligent transportation systems.
Cargo Volume Forecasting for Logistics Sorting Centers Based on Random Forest Model
Authors: Zhao Wenfei , Li Xinyang , Li Zhaoxin
Published: October 2024

With the rapid development of logistics industry, logistics sorting center, as a key node in e-commerce logistics network, its cargo volume prediction and personnel scheduling strategy are of great significance to improve operational efficiency and reduce costs. The purpose of this study is to deeply analyze the cargo volume data of 57 sorting centers through machine learning method, establish an accurate cargo volume prediction model, and optimize the personnel scheduling strategy based on the prediction results. In this study, we preprocess the historical cargo data, including missing value filling, time series conversion and feature construction. Then, the random forest model was used to carry out fitting analysis on the cargo volume data of different sorting centers. By comparing the evaluation indexes such as mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE), the superiority of random forest model compared with neural network, support vector regression and linear regression models was verified. This study not only improves the accuracy of cargo volume forecast, but also realizes the reasonable allocation of human resources, and provides scientific decision support for the operation and management of logistics sorting center.
Research on Momentum Prediction of Tennis Match Based on Scoring Model and Multilayer Perceptron
Authors: Dong Jiaze , Feng Qilang
Published: October 2024

During a tennis match, players may encounter various circumstances that can significantly influence their performance. This force, known as "momentum," can drastically alter the game's flow and ultimately determine the winner. Addressing the challenge of analyzing and predicting momentum shifts, this study applied the Entropy Weight TOPSIS method combined with fuzzy comprehensive evaluation to assess player performance across technical, physical, and psychological factors. These methods provided a comprehensive analysis of the players' performance metrics, revealing patterns linked to momentum changes. Following this, Pearson correlation analysis was conducted to identify key performance indicators strongly associated with match outcomes. These indicators were then integrated into a Multilayer Perceptron (MLP) model, which demonstrated high predictive accuracy, with an R-value of 0.868, effectively capturing momentum shifts in real-time. The study's findings offer valuable insights for improving strategic decision-making during matches and hold potential applications in other fields that require real-time predictive analysis.
Research on Speech Emotion Recognition Method Based on ResSE_CNN1D
Authors: Zhang Yingcheng
Published: October 2024

This article examines a speech emotion recognition (SER) technique based on the enhanced one-dimensional convolution neural network ResSE_CNN1D. With the artificial intelligence developing rapidly, SER has a profound impact in many areas. The model of this article is used to extract the characteristics of the input data through opensmile, and is sent into the ResSE_CNN1D model, which is eventually classified by the softmax activation function and obtains the final results. The key to this model is efficient learning of decimal sets and the rapid deployment in resource-constrained environments. The ResSE_CNN1D model improves the performance of the model by adding the residual connection and the SE module on the basis of cnn1d. This increasing the accuracy of the recognition and preventing the fitting problem. After the model was created, the study adopted the audio sampling and training of the casia data concentration. The final accuracy was 0.900, which increased the accuracy of 2.9 percent compared to the cnn1d method. And by the analysis of the relationship diagram of the confusion matrix and the accuracy and loss rate relative to the number of training, the model has a high robustness and effectively prevents the appearance of the fitting problem. And it also can achieve high precision and achieve a lightweight goal relative to less training.
შარლ ბოდლერის „კატები“
Authors: იაკობსონი რომან , ლევი-სტროსი კლოდ
Published: October 2024

Roman Jakobson, Claude Lévi-Strauss. Baudelaire's „Les Chats“.
Roman Jakobson, Language in LIterature,The Belknap Press of Harvard University, Cambridge,Massachusetts, London, England, 1987, pp.181-197.
The Reverse Side of the Socialist Realist Canon: the Experience of Ukrainian Literature
Authors: Dzyk Roman , Shutiak Liliia
Published: October 2024

მიუხედავად იმისა, რომ ლიტერატურული კანონის კონცეფცია სრუ­ლიად განსხვავებული ტრადიციიდან იღებს სათავეს, ის საოცრად ორგანული აღმოჩნდა იმის აღსაწერად, რაც ტოტალიტარული სახელმწიფოს მექა­ნიზმების საშუალებით ჩამოყალიბდა, მათ შორის, უკრაინულ საბჭოთა ლიტერატურაში. ასეთი კანონი უკიდურესად სტრუქტური­რებულია, მაგრამ არ არის გაყინული, რადგან მან განიცადა ტრანსფორმაციები „პარ­ტიული ხაზის“ ცვლილებების მიხედვით. ამ კანონის ტოტა­ლიტარული ბუნება იმას ნიშნავდა, რომ მის გარეთ ვერაფერი იარსებებდა. ყველაფერი, რაც ამ საზღვრებს მიღმა არსებობდა, ან აკრძალული იყო ან დაგმობილი (უმე­ტესად, არა მეტაფორული, არამედ ამ სიტყვის სრულიად პირდაპირი გა­გებით). სწორედ ამას ვგულისხმობთ სოციალისტური რე­ალიზნის  კანონის მეორე მხარეში. ტოტალიტარული სახელმწიფოს დაშლამ, მთელი მისი ზედამხედ­ველობითი და სადამსჯელო მექანიზმებით, ერთი შეხედვით, თითქოს მიგვიყვანა იმ ფაქტამდე, რომ „უკანა მხარე“ ავტომატურად გადაიქცა „წინა მხარედ“. ყოველ შემთხვევაში, როგორც კვლევის ობიექტი, ის სათანადო ყურადღების ღირსია. საუბარია აკრძალული და დაუმსახურებლად მარ­გინალიზებული ავტორებისა და ტექსტების „დავიწყებიდან დაბრუნებაზე“. ჩვენ  ბოლო ოცდაათი წელია ვაკვირდებით ასეთ პროცესებს. ამავდროულად, ოდესღაც „კანონიკური“ ავტორების შემოქმედებაც რეგულარულად  განიცდის გადაახედვასა და გადააზრებას. აქცენტიც გადაინაცვლებს საპი­რისპირო მხარეს, რომელიც ადრე შეფასებული იყო როგორც გარკვეული გადახრა „ერთადერთი სწორი გზიდან“. ორივე შემთხვევაში, შეიძლება მოვიყვანოთ პოეტების პავლო ტიჩინისა და ვასილ სტუსის მაგალითები. მეორე მხრივ, ჩვენ შეგვიძლია დავაფიქსიროთ უკრაინული სოციალისტური რეალიზმის  კანო­ნის გარკვეული სიცოცხლისუნარიანობა ჩვენს დრომდე, სხვადასხვა ჰიპოს­ტასებით. როგორც უახლესი კვლევები აჩვენებს, შეუძლებელია მისი საპი­რისპირო მხარის სრულად გაგება, ამ ფენომენის საფუძვლიანი შესწავლის გარეშე.
THE ESSENCE AND BASIC CONCEPTS OF THE RECREATION PROCESS IN THE DAILY LIFE OF CITIZENS
Authors:   The State University of Physical Education and Sport, Republic of Moldova, POPESCU Darius-Liviu
Published: October 2024

The significance of the recreation phenomenon has increased greatly in today's fast and competitive world, in the conglomerate of society and situations as a whole, people devote many hours to academic learning, being they theoretical or practical ones, and the activity of improving knowledge. To this is added the current way of daily life in which people work between 10 and 12 hours daily, even on weekends, office work, sedentary life as well as diminishing direct human-to-human communication and isolation in the online environment - internet, the result being the diminished time and the desire to practice the sport for recreation. Recreation occupies an important place in the structure of physical culture, as recreational elements are used in sports, physical education and physical rehabilitation. In the current situation, the prevention of diseases and the consolidation of the population's health goes from medical to social. There is a constant tendency to increase the social role of the recreational phenomenon through sport in order to strengthen and maintain health as well as a more physically active life of people. This is an integral part of the development strategy of the modern society, which aims to humanize and democratize its potential.
ANIMAL ASSISTED THERAPY FOR INMATES
Authors:   Jilava Penitentiary, Psychosocial Assistance Service, 1, Sabarului Street, Ilfov, Jilava, 077120, România,Tel.: 021 457 0181, ZAHARIA Magdalena
Published: October 2024

From the perspective of the psychosocial intervention models, programs focused mainly on aspects such as increasing self-esteem, promoting positive feelings towards oneself and others, stress management and effective communication strategies. Animal Assisted Therapy (TAA) promotes positive human-animal interaction by incorporating the psychological, behavioral and physical traits of an animal into a therapeutic environment, in order to facilitate the recovery process of a patient in need of physical and / or mental care (Chandler, 2005). Since 1990, the results of animal-assisted therapy in treating attention deficiencies or anxiety states have been made known in the specialized literature, in solving the problems related to social relations and integration, but also in improving the quality of life. The categories of people and the environments in which the TAA programs were applied are extremely varied, including penitentiary systems. The animal-assisted therapy program can provide the ethical and moral framework that emphasizes the positive examples that can produce a change of perception and attitude regarding drug use, strengthening the inmates motivation in their own recovery process. The therapy is based on the fact that the animals love unconditionally and accept the others as they are, without judging them. In animal-assisted therapy, the dog is frequently used because of its docile nature, the ease with which it can be trained and because, in general, people show sympathy for this animal. The results of the activities carried out in this field have shown that following the TAA, the inmates have registered an improvement of the positive behaviors, as well as a reduction of the disciplinary sanctions. Also, there were no more aggressive manifestations from the animals, they benefiting from decent accommodation and care conditions. Following the analysis of the needs for the year 2019, at the level of the Bucharest-Jilava Penitentiary, it was found that 13.41% of the custodial convicts used drugs. This aspect, as well as the research in the field, justify the addressability of the general intervention program "Assisted Animal Therapy" (TAA) to inmates with a history of narcotic use.
COMPARATIVE STUDY REGARDING THE OPTIMIZATION OF THE PHYSICAL TRAINING AND THE EFFORT CAPACITY OF THE FEMALE STUDENTS, PARTICIPATING IN THE PHYSICAL EDUCATION COURSES AT THE UNIVERSITY OF BUCHAREST
Authors:   Department of Physical Education, University of Bucharest, Romania, GULAP Monica
Published: October 2024

In the paradigm of the modern pedagogy, a "physically educated" person is a person: with a good physical condition, aware of the importance of practicing physical exercise in order to maintain and strengthen health, keen to move and who enjoys the physical effort, which promotes an active, dynamic, healthy and balanced life style as a social value, which develops social relations.1 Starting from this premise, we propose in this paper to identify the extent to which the objectives of physical education in higher education, related to physical, somatic and functional parameters, are achieved through the participation of female students in aerobics, fitness, volleyball and table tennis courses. The hypothesis of our experimental approach: The means specific to each sports discipline listed above, used in the physical education lessons with the female students in the higher education, will influence differently the level of the physical training and the somatic and functional parameters of them, some of the sports being more efficient in this regard. The research methods used: the analysis of the specialized literature, the pedagogical observation, the method of the tests, the pedagogical experiment, the statistical method of data processing and the graphical method of presenting the results. Subjects: In our study, were involved 80 students from first year enrolled in aerobics, fitness, volleyball and table tennis courses, 20 for each sports discipline mentioned. Results: We recorded the results aimed at the somatic, motor and functional evaluation both at the beginning of the academic year 2018-2019 and at the end of it, after completing the specific programs of the four sport disciplines. Conclusions: The sports disciplines included in our experimental study had different effects at the level of the investigated parameters, the specific means of aerobics having by far the most significant contributions to the somatic and functional progress that the girls, in general, and the students of our sample in particular, wish from a motor activity.
STUDY ON THE ATHLETIC PREPARATION OF JUNIOR HANDBALL PLAYERS IV (12-13 YEARS)
Authors:   Ecological University of Bucharest/ Faculty of Physical Education and Sport, Bucharest, Romania, Neder Florina Liliana
Published: October 2024

Background. Handball is accessible to everyone. It can be practiced by children and young people, men and women and even older people. Most technical procedures are executed by hand, and the ball being small can easily control. In the process of continuous lifting of athletes' capacities, physical and technical training are factors whose weight is special for the successful solving of the objectives and tasks of a certain stage of training. Their judicious ratio and connection depends to a large extent on the level of training an athlete can achieve. Objectives.  Studying the methodology for developing specific motor skills through investigations and documentation on the literature, as well as on the training programs used by junior handball players in the training process, in the preparatory stage;  The collection of data from the coach's practice on the basis of which, by processing, the characteristics of the methods for developing specific motor qualities will be established;  Comparing all these data and studying the existing concordances or discrepancies in the training plans of junior handball players. Based on this, the conclusions of the paper will be drawn up to improve the methodology for the development of motor skills in the preparatory phase. Study hypothesis. If a systematization of the means and methods of developing the motor skills specific to athletics is achieved in the preparatory stage, of the training programmes, then we will be able to contribute to a better athletic training of junior handball players IV. Methods. The research methods used in this study were: The bibliographical study method; The Observation method; The Testing method; The Statistical and mathematical method; The Graphic method. Conclusion. At the final time of the study, the experimental group achieved better results than the control group in all tests carried out. In this study it was observed that by systematizing the means and methods of development of the motor qualities specific to athletics in the preparatory stage, the training programs, improved the preparation of junior handball players.
Global Power Shifts: The Role of Emerging Economies in International Relations
Authors: Krishna Pasupuleti Murali
Published: October 2024

Abstract: This chapter explores the significant role of emerging economies in reshaping global power dynamics and international relations. It analyzes how countries like China, India, Brazil, and Russia are driving shifts in global governance, economic power, and political influence. The chapter examines the economic growth drivers of these nations, their increasing participation in global institutions, and their role in forming new alliances such as BRICS. Additionally, it discusses the strategic importance of energy, trade, and regional security in the geopolitical landscape, highlighting how emerging economies are challenging traditional Western dominance. The chapter also addresses the challenges these economies face, including governance issues, environmental concerns, and their future impact on the global order. Keywords: emerging economies, global power shifts, international relations, BRICS, China, India, Brazil, Russia, economic growth, global governance, geopolitical influence, energy security, trade, regional security, global institutions, challenges in governance.
AI and Blockchain in Law: Shaping the Future of Legal Practice
Authors: Krishna Pasupuleti Murali
Published: October 2024

Abstract: This chapter explores the transformative impact of AI and blockchain technologies on the legal industry, highlighting their potential to revolutionize key aspects of legal practice, including research, contract analysis, compliance, and dispute resolution. AI enhances efficiency by automating labor-intensive tasks, such as legal research and due diligence, while predictive analytics offer insights into case outcomes and legal strategies. Blockchain’s decentralized ledger ensures transparency, security, and tamper-proof record-keeping, making it ideal for managing legal documents, smart contracts, and digital identities. The chapter also examines ethical and regulatory considerations, addressing concerns about bias in AI systems and the legal enforceability of smart contracts. As AI and blockchain continue to evolve, their integration will create more secure, transparent, and efficient legal processes, enabling lawyers to focus on creative problem-solving and strategic decision-making. By embracing these technologies, the legal profession can enhance client outcomes and navigate the complexities of modern legal systems in a rapidly changing digital landscape. Keywords: AI in law, blockchain in law, legal technology, smart contracts, legal research, predictive analytics, digital identity, legal compliance, contract analysis, dispute resolution, decentralized ledger, transparency in law, legal document security, ethical AI, blockchain regulation, legal automation.
Advanced AI for Topological Data Analysis: Decoding Complex High-Dimensional Structures
Authors: Krishna Pasupuleti Murali
Published: October 2024

Abstract: This chapter explores the integration of advanced AI techniques with topological data analysis (TDA) to decode complex high-dimensional data structures. It examines how AI-driven TDA can identify and analyze the geometric and topological features of datasets, offering deeper insights into patterns, clusters, and anomalies that traditional methods might overlook. By leveraging machine learning algorithms such as neural networks, graph neural networks, and autoencoders, AI enhances the ability to process and interpret high-dimensional data from various fields, including biology, finance, and network analysis. The chapter also discusses the application of persistent homology and multi-scale analysis in AI-driven TDA, emphasizing the future potential of these technologies in fields such as genomics, neuroscience, and sensor networks. Challenges related to computational complexity, scalability, and interpretability are addressed, as well as emerging trends in the field. Keywords: advanced AI, topological data analysis, TDA, high-dimensional data, machine learning, neural networks, graph neural networks, autoencoders, persistent homology, multi-scale analysis, data patterns, data clusters, anomaly detection, genomics, neuroscience, sensor networks, computational complexity.
AI-Driven Mutation Detection: Transforming Genomic Data into Insights for Disease Prediction
Authors: Krishna Pasupuleti Murali
Published: October 2024

Abstract: This chapter explores how AI-driven mutation detection is revolutionizing genomic data analysis and transforming it into actionable insights for disease prediction. By leveraging advanced machine learning algorithms, such as convolutional neural networks and deep learning models, AI can accurately identify genetic mutations, including single nucleotide polymorphisms (SNPs) and structural variations, that are linked to various diseases. The chapter highlights AI's ability to process vast amounts of genomic data, uncover hidden patterns, and predict disease risk with unprecedented precision. Additionally, it examines AI's integration with bioinformatics tools, next-generation sequencing, and clinical databases to drive personalized medicine and enhance predictive capabilities in areas like cancer, cardiovascular disorders, and rare genetic diseases. Ethical considerations and challenges related to data privacy, model interpretability, and the future potential of AI in genomics are also discussed. Keywords: AI-driven mutation detection, genomic data, disease prediction, machine learning, deep learning, SNPs, structural variations, bioinformatics, next-generation sequencing, personalized medicine, predictive analytics, genetic mutations, cancer prediction, cardiovascular disorders, rare genetic diseases, ethical considerations.
Mathematical model of fatigue degradation of cylindrical piezo element of linear
micro piezo motor
Authors:   Azerbaijan Technical University,
            Baku, Azerbaijan, Mehman Hasanov
Published: October 2024

In the article, a mathematical model has been constructed and investigated by
analyzing the problem of disintegration during torsion of the cylindrical shaped piezo
element in the linear piezoelectric engine. Nonlinear differential equations expressing
the expansion of the disintegration surface formed during the torsion of the piezo
element under the influence of variable torsional moment have been formulated.
Guidelines determining the initial degradation period for the development of the
disintegration process have been obtained, and based on the developed mathematical
model, displacement curves of the disintegration surface motion have been
established.