bluuebunny/crossref_metadata_2025 huggingface dataset:
The concept of Minimal Spanning Tree (MST) for Symmetric Encryption
Authors: CH. Suneetha MPR Murthy,
Published: April 2024

As the digital communication has become a vital part of the human life nowadays, cybercrimes are ever expanding. One major tool to protect the message from hacking and tampering is concealing the original information.  Modern cryptography not only concerns the encryption of the message but also focuses on the protection of the encrypted information from cyber-attacks.Apart from secret communication modern cryptography focuses on authentication and integrity of the message. The present paper explains a symmetric block cipher basing on graph structures. In this technique the message is encrypted twice. The first stage encryption using adjacency matrix of undirected graph; the second stage using exclusive OR (XOR) operation on the output of first stage.  Encryption/Decryption Keys are distinct for distinct blocks and distinct rounds; derived from Minimum Span Tree (MST) technique of an undirected graph. Here multiple peers can communicate messages simultaneously. One of the entries selects some random ASCII characters whose number is same as the block length and uploads those characters in the cloud. All the members of the group establish block keys using key generation technique which is secret among them.
Optimizing Power Generation Scheduling: A Comparative Analysis of Metaheuristic Algorithms
Authors: Dilip Kumar Bagal Soudamini Behera,
Published: April 2024

Purpose: This research compares six optimization methods, including the Mayfly Optimization Algorithm, Genetic Algorithm, Simulated Annealing, Firefly Algorithm, and Differential Evolution (DE).
Design/Methodology/Approach: The evaluation of any algorithm is predicated on its ability to strike a balance between meeting demand, taking into account renewable energy sources, and lowering the total cost of producing power.
Findings: The analysis shows that although PSO and GA converge to similar overall costs, the algorithms' performances differ. Then come SA, FA, and DE in close succession, with the Mayfly Optimization Algorithm showing higher total costs than the other techniques.
Originality: By addressing difficult power generating scheduling problems, this work advances our understanding of the benefits and drawbacks of various optimization techniques.
Energy-Recognition Clustering Technique Based on Reinforcement Learning In WSN
Authors: K. Kavitha R. Rajalingam,
Published: April 2024

WSN (Wireless Sensor Network) technology has recently gained a lot of attention. This began with the deployment of small WSNs and moved to the deployment of big and IoT WSNs, all with an emphasis on energy conservation. Wireless sensor networks can benefit from network clustering to increase their energy efficiency. The practise of dividing nodes into clusters before picking multiple cluster heads is known as network clustering (CHs). Clustering in wireless sensor networks is known to save energy and extend the network's lifetime (WSNs). Energy efficiency is a hot topic in existing wireless sensor networks, although it's not generally discussed. In this research, we offer a reinforcement learning (RL) based energy-aware clustering approach, whereby peripheral cluster nodes monitor environmental factors like energy use and choose an optimal cluster leader (CH). Connect the CH (BS) to the base station. In the simulation (PDR), performance factors such as network lifetime, energy tax, network stability period, and packet delivery rate are all taken into account. The simulation results show that the proposed QL-ReLeC performs around 11% better than the reference protocol in terms of PDR and 11% better in terms of energy tax.
A Stochastic Regression and Sentiment Analysis-Based Approach for Forecasting Trends in the Stock Market
Authors: L. K. Vishwamitra Anjali Verma ,
Published: April 2024

Stochastic regression problems especially applied to time series forecasting problems often encounter the challenge of volatility and unpredictable seasonality in datasets. One such application happens to forecasting the movement of stock markets globally. Stock data across the world exhibits an intrinsic baseline noise, which often can’t be correlated to previous temporal patterns. Rather, such divergences are an effect of multiple non-numeric variables which govern stock movement such as political scenarios, trade wars, imminent economic waxing and waning trends to name a few. However, it is essential to incorporate these factors while training a model so as to design a strongly sentient and anticipatory regression algorithm which is both pervasive and robust, encompassing as many numeric and non-numeric factors as possible. While conventional machine learning and deep learning approaches tend to leverage tested model architectures, they often miss out on the optimization of both training data and training method to yield potentially high forecasting accuracy. The paper combines stochastic regression in terms of momentum based training and data optimization which is shown to exhibit considerable lower forecasting error compared to existing approaches. To encompass a wider feature space, sentiment analysis has been incorporated to correlate stock movements with public opinions. The proposed approach has been tested on a multitude of benchmark datasets, to validate the performance of the approach. The mean absolute percentage error (MAPE) and regression values have been selected as primary metrics for the performance evaluation.  The proposed approach attains a mean MAPE value of 3.22%. The analysis of the MAPE and forecasting accuracy w.r.t. existing benchmark approaches proves the improved forecasting performance of the proposed approach over a period of 300 days.
Enhancing Software Defect Prediction accuracy using Modified Entropy Calculation in Random Forest Algorithm
Authors: Suryawanshi,Amol Kadam Ranjeetsingh,
Published: April 2024

Imagine you are trying to classify software defect for a large dataset. How will you choose the best algorithm to do that? For the above problem we have various algorithms like Random Forest, Support Vector Machine, Neural Networks, Naive Bayes, K-Nearest Neighbours, Decision Tree, Logistic Regression etc. One of the most used methods is Random Forest algorithm, which uses multiple Decision Trees to make predictions. However, this algorithm relies on a complex calculation called Entropy, which measures the uncertainty in the data. Entropy is a function that uses natural logarithm which may be time consuming calculation. Is there a better way to calculate entropy? In this research, we have explored a different way to calculate the natural logarithm using the Taylor series expression. It is a series consisting of sum of infinite terms that approximates any function by using its derivatives. We further modified the Random Forest algorithm by replacing the natural logarithm with the Taylor series expression in the Entropy formula. We tested our modified algorithm on dataset and compared its performance with the original Entropy formula. We found that our modification in the algorithm has improved the accuracy of the algorithm on software defect prediction
Enhancing Energy Efficiency in Electrical Systems with Reinforcement Learning Algorithms
Authors: P. S. Patil
Published: April 2024

Improving the energy efficiency of electricity systems is important for lowering environmental damage and promoting sustainable growth. In recent years, reinforcement learning (RL) methods have become useful for finding the best ways to use energy in many areas. The point of this study is to look into how RL algorithms can be used to make electricity systems more energy efficient. The study looks into how RL algorithms can be used to make electricity systems more efficient by lowering waste, making the best use of energy, and maximizing energy use. The study suggests a new way to use RL methods to change things like power sharing, load scheduling, and resource allocation on the fly in order to keep system performance high while using as little energy as possible. Some important parts of the study method are creating RL models that work with electricity systems and their limitations, as well as coming up with the right payment functions to help people learn how to behave in ways that use less energy. Extensive models and real-world studies on sample electrical systems are used to test how well the suggested method works. According to the study's results, using RL algorithms can lead to big changes in how efficiently energy is used, with cuts in energy use running from [insert exact number range]. The study also shows how flexible and scalable RL-based solutions are when it comes to different system setups and operating scenarios. Overall, this study adds to the growing amount of research on energy efficiency by showing how RL algorithms can be used to solve difficult problems in electrical systems. Practical plans can be made to improve energy efficiency and promote sustainability in a wide range of businesses and uses based on what this study has taught us.
GTLNLP: A Mathematical Exploration of Cross-Domain Knowledge Transfer for Text Generation for Generative Transfer Learning in Natural Language Processing
Authors: Swati Bula Patil,
Published: April 2024

In the field of Cross-Domain Knowledge Transfer generative transfer learning in Natural Language Processing (NLP) used for creating text using generative math. The paper aims to improve the usefulness of text creation models in a variety of areas by using cutting edge deep learning and neural network methods. We come up with a new system that makes it easier for information to move from one domain to another, even when the language and situation are different in each domain. Using domain adaptation techniques to match feature distributions and reduce domain gaps is what our method is based on mathematically. It is a complex version of transfer learning principles. We test our model's abilities on a wide range of tasks by doing a lot of careful experiments. We focus on how well it can share information and write text that makes sense and is relevant to the situation across different areas. This study not only adds to our theoretical understanding of cross-domain knowledge transfer, but it also gives us useful tips on how to make NLP models more flexible and useful in the real world. The results of our study could help improve the state of the art in generative transfer learning and make text generation systems that work better and more reliably in a variety of language settings.
“An Extensive study of Symantic and Syntatic Approaches to Automatic Text Summarization”
Authors: Manisha Gaikwad,
Published: April 2024

Automatic text summarization (ATS) has emerged as a crucial research domain in the discipline of natural language processing (NLP) and information retrieval. The exponential growth of digital content has necessitated the need for efficient techniques that can automatically generate concise and informative summaries from lengthy documents. This article provided a comprehensive recap of automatic text summarization, covering both abstractive and extractive methods. Using extractive techniques, prime phrases or keywords from the original text are identified and chosen, while abstractive methods involve producing summaries by paraphrasing and synthesizing content in a more human-like manner. Discussed the advantages and limitations of each approach, including the challenge of ATS, which arises when summarizing content from external sources. Furthermore, reviews common evaluation metrics used for assessing the quality of summaries and discusses recent advancements in neural network-based approaches for text summarization. This survey aims to provide an overview of automatic text summarization which acts as a useful resource for researchers and practitioners in the fields of information retrieval and NLP.
Forecasting Energy Utilization in Residential Areas through Machine Learning Techniques
Authors: Pragya Nema Kalpana D. Vidhate
Published: April 2024

Analyzing and forecasting energy use in residential areas and buildings is critical for promoting sustainability and optimising energy usage. This paper describes a unique way for exact energy consumption analysis and forecasting that employs machine learning techniques such as linear regression and ridge regression. The proposed model intends to provide important insights and forecasts by combining historical energy data with relevant parameters such as building attributes, weather conditions, and tenant behaviour, improving energy usage in residential settings. The expected prototype is tested using a dataset accessible on Kaggle. The findings provided in the study show that our suggested model surpasses the state-of-the-art system, with accuracy rates of 66.56 percent for linear regression and 70.12 percent for ridge regression, respectively.
Advancements in Text Summarization Through Machine Learning: A Comprehensive Survey and Analysis
Authors: Vandana Jagtap
Published: April 2024

Due to the extensive amount of text available for any given task, for instance, a research project, it has become a need to have the gist of these documents in a succinct format. In this review paper, we discussed various methods used for single and multi-document summarization. It explores extractive, abstractive, and hybrid methods, along with the role of deep learning models like RNNs, CNNs, and transformers. The survey examines datasets, evaluation metrics, recent advancements, and future scopes in this field. A comparative analysis of methodologies and approaches is also presented.
Examining the Sustainability Strategies of Knowledge-Based Sports Enterprises Using the Three Branch Paradigm
Authors: Victoria Zaborova,
Published: April 2024

Sustaining knowledge-based enterprises is a crucial aspect of entrepreneurship. The current research aims to rank the sustainability strategies of knowledge-based sports enterprises in the industry using the three branch theory. The research is a descriptive analysis and field study. The population consisted of experienced managers from leading knowledge-based sports enterprises. 14 individuals were chosen as the research sample via snowball selection. The research questionnaire consisted of a researcher-developed survey. The questionnaire was created as a strategy matrix with three branches and utilized the TOPSIS approach. Sustainability strategies of knowledge-based enterprises in the sports industry were identified by utilizing theoretical underpinnings from research and expert opinions. The researcher identified strategies from articles and finalized them by consulting an expert team. 10 solutions for ensuring the sustainability of knowledge-based sports enterprises were identified and finalized in this research. The TOPSIS technique was utilized to select the optimal strategy for ensuring the sustainability of knowledge-based enterprises in the sports industry. The research data analysis method was exclusively conducted utilizing TOPSIS. The research results indicated that the most significant factor, with a coefficient of 0.6736, is the reform of the tender and transaction system and the elimination of complex regulations related to the development of sports-based knowledge enterprises.
DOI: https://doi.org/10.52783/pst.239
AKUNTANSI (PETANI) GARAM MADURA: ANTARA MENJAGA TRADISI DAN KETIDAKBERDAYAAN MELAWAN HEGEMONI
Authors: Setiawan Achdiar Redy
Published: April 2024

Pemahaman yang menyembul dari buku ini bisa dijadikan pintu masuk bagi penyusunan ulang pranata sistem dan tata kelola yang lebih kokoh guna mengawal peningkatan kesejahteraan petani di negeri tercinta. Harapannya, berangkat dari pemahaman lapangan ini, semua pihak menaruh perhatian besar pada permasalahan yang melingkupi petani garam di Madura. Salah satu yang perlu difokuskan adalah penataan kelembagaan yang secara sistematis dan terstruktur dapat membantu petani garam. Negara perlu hadir secara nyata untuk mendorong semua lembaga yang akan menempatkan kesejahteraan petani sebagai tujuan awal dan akhir.
Investigation of contact behavior on a model of the dual-mobility artificial hip joint for Asians in different inner liner thicknesses
Authors: Hidayat Taufiq , Ammarullah Muhammad Imam , Ismail Rifky , Saputra Eko , Lamura M Danny Pratama , K N Chethan , Bayuseno Athanasius Priharyoto , Jamari J
Published: April 2024

BACKGROUND

The four components that make up the current dual-mobility artificial hip joint design are the femoral head, the inner liner, the outer liner as a metal cover to prevent wear, and the acetabular cup. The acetabular cup and the outer liner were constructed of 316L stainless steel. At the same time, the inner liner was made of ultra-high-molecular-weight polyethylene (UHMWPE). As this new dual-mobility artificial hip joint has not been researched extensively, more tribological research is needed to predict wear. The thickness of the inner liner is a significant component to consider when calculating the contact pressure.

AIM

To make use of finite element analysis to gain a better understanding of the contact behavior in various inner liner thicknesses on a new model of a dual-mobility artificial hip joint, with the ultimate objective of determining the inner liner thickness that was most suitable for this particular type of dual-mobility artificial hip joint.

METHODS

In this study, the size of the femoral head was compared between two diameters (28 mm and 36 mm) and eight inner liner thicknesses ranging from 5 mm to 12 mm. Using the finite element method, the contact parameters, including the maximum contact pressure and contact area, have been evaluated in light of the Hertzian contact theory. The simulation was performed statically with dissipated energy and asymmetric behavior. The types of interaction were surface-to-surface contact and normal contact behavior.

RESULTS

The maximum contact pressures in the inner liner (UHMWPE) at a head diameter of 28 mm and 36 mm are between 3.7-13.5 MPa and 2.7-10.4 MPa, respectively. The maximum von Mises of the inner liner, outer liner, and acetabular cup are 2.4–11.4 MPa, 15.7–44.3 MPa, and 3.7–12.6 MPa, respectively, for 28 mm head. Then the maximum von Mises stresses of the 36 mm head are 1.9-8.9 MPa for the inner liner, 9.9-32.8 MPa for the outer liner, and 2.6-9.9 MPa for the acetabular cup. A head with a diameter of 28 mm should have an inner liner with a thickness of 12 mm. Whereas the head diameter was 36 mm, an inner liner thickness of 8 mm was suitable.

CONCLUSION

The contact pressures and von Mises stresses generated during this research can potentially be exploited in estimating the wear of dual-mobility artificial hip joints in general. Contact pressure and von Mises stress reduce with an increasing head diameter and inner liner’s thickness. Present findings would become one of the references for orthopedic surgery for choosing suitable bearing geometric parameter of hip implant.
APRENDER ALÉM DAS PAREDES DA SALA DE AULA
Authors: Belo Cibelli Batista , Zimer Tania Teresinha Bruns
Published: April 2024

A Educação Infantil é a primeira etapa da Educação Básica e tem relação com o desenvolvimento integral da criança, partindo de brincadeiras e interações, conforme documentos oficiais. O objetivo deste trabalho é analisar aspectos de aprendizagens desenvolvidas pelas crianças de dois a três anos em uma prática pedagógica além das paredes da sala de aula. Baseia-se nas Diretrizes Curriculares Nacionais para a Educação Infantil (2010) e na Base Nacional Comum Curricular (2018), e autores que abordam sobre a história da Educação Infantil no Brasil, o brincar, as interações, as Ciências e a Matemática na Educação Infantil, assim como aqueles que tratam sobre a interdisciplinaridade. A metodologia utilizada é qualitativa, e enquadra-se no estudo de caso. A coleta para a análise de dados foi feita por fotos e vídeos. Nesta prática, foram abordadas noções matemáticas e de ciências, possibilitando a exploração do ambiente fora da sala de aula, observação e conhecimento de diferentes espaços e situações cotidianas, como o lugar de onde vem o leite. A prática se constitui em uma experiência prazerosa e diferente do que as crianças estão acostumadas.
NECESSIDADES FORMATIVAS DE PROFESSORES DE MATEMÁTICA DOS ANOS FINAIS DO ENSINO FUNDAMENTAL DAS ESCOLAS ESTADUAIS NO MUNICÍPIO DE BARRA DO BUGRES-MT
Authors: Cunha Paulo Adriano Torres da , Kapitango-a-Samba Kilwangy Kya
Published: April 2024

Neste artigo apresentamos o recorte de uma pesquisa cujo objetivo foi analisar as necessidades formativas dos professores de matemática dos anos finais do Ensino Fundamental, das escolas da rede estadual situadas no município de Barra do Bugres-MT. O levantamento foi realizado por meio de um questionário online aplicado a amostra de 20 Professores de matemática, num universo de 25 Professores. Os dados foram analisados por representação gráfica e análise de frequência. A investigação foi conduzida com o seguinte problema: quais são as necessidades formativas dos professores de matemática dos anos finais do Ensino Fundamental das Escolas Estaduais em Barra do Bugres, que sirvam de indicadores de formação continuada? Como resposta ao problema de pesquisa, os resultados indicaram que os professores participantes da investigação apresentam necessidades de formativas, observadas a partir dos seguintes indicadores: a) dificuldade para ensinar conteúdos matemáticos para os anos finais do Ensino Fundamental; b) dificuldade de uso de Recursos de Tecnologia Digital; c:) dificuldade no ensino de matemática com uso de métodos ativos de ensino e teorias da aprendizagem; d) dificuldades para ensinar matemática à estudantes com necessidades especiais; e) dificuldades para produção de material didático. Os resultados constituem indicadores robustos da urgência de intervenção formativa baseada nos contextos das especificidades educacionais.
Demiryollarının Somut ve Somut Olmayan Kültürel Miras Değerlerinin Kolektif Bellekteki Yeri: Sivas Demiryolu Yerleşkesi Örneği
Authors: Ede Ayşenur , Çelen Öztürk Ayşen
Published: April 2024

Kentlerin gelişiminde şehirlerarası ulaşım olanaklarının önemli bir rolü vardır. Cumhuriyet ile birlikte genişletilen demiryolu ağı ve kurulan sanayi tesisleri kentlerin gelişmesinde atılan önemli adımlardan biridir. İnsanlık tarihini değiştiren endüstri devriminin en önemli tamamlayıcısı olan demiryolları; yapıldıkları dönemin mimarisi, teknolojisi, yapım tekniği, toplumun sosyo-kültürel yapısı gibi birçok alanda fikir sahibi olmamızı sağlamaktadır. Yapıldıkları dönemde ve kullanıldıkları süreç boyunca demiryolu yapıları kentlerin simgesel yapılarından olmuş ve kentlinin hafızasında önemli bir yer edinmiştir. Demiryolu taşımacılığıyla ilgili her türlü yapı, mobilya, belge ve dokümanın korunması, gelecek kuşaklara aktarılması önem arz etmektedir. Somut ve somut olmayan kültürel miras değerlerine sahip kentler için demiryollarının ne kadar önemli olduğunu ve bunu sürdürmek için kentlinin kollektif belleğindeki durumunu incelemek gerektiğinin üzerinde durularak Sivas demiryolu yerleşkesi ve Cer Atölyesi örneği üzerinden irdelenmiştir. Demiryolu kültürü, ancak paylaşıldığı noktada çoğalacak ve toplumsal hafızalardaki yerini her zaman diri tutacaktır. Bu çalışma kapsamında kentlerin en önemli toplumsal ve fiziksel bileşeni olan demiryollarının, geçmişte ve günümüzde kolektif bellekteki yerini sorgulayarak somut ve somut olmayan kültürel miras ögelerini ortaya çıkarmak amaçlanmaktadır. Bu tez çalışmasında; öncelikle konu ile ilgili yapılan literatür taramasından sonra, demiryolu ve kent ilişkisini sorgulamak amacıyla Sivas kentinin fiziksel analizinde bu durum irdelenmiştir. Kevin Lynch’in ‘Kent İmgesi Parametreleri’ üzerinden analizler yapılarak; yollar, sınır/kenarlar, bölgeler, işaret ögeleri ve odak/düğüm noktaları belirlenmiştir. Analiz sonrasında Sivas demiryolu yerleşkesi ve Cer Atölyesi’nin (TÜRASAŞ) anket sorularına öncülük edecek parametreler belirlenmiştir. Belirlenen parametreler, odak noktaları ve işaret ögelerinin kolektif bellekteki yerini sorgulamak amacıyla anket soruları hazırlanmıştır. Demiryollarının somut ve somut olmayan kültürel miras değerlerinin kolektif bellekteki yeri anket sorularıyla belirlenmeye çalışılmıştır. Çalışma sonucunda, bu alanın kentlinin hafızasındaki yeri üzerindeki etkileriyle beraber, farklı bakış açıları ortaya koymaktadır.
Empowering Teachers through Design Thinking: Developing Learning Prototypes for Multilingual Students
Authors: Goldman Shelley , Kuo Annie Camey , Pozos Rose K. , Mesinas Melissa , Lange Kimiko E.
Published: April 2024

This paper argues that developing teachers’ design literacy will enable them to better respond to the demands of their work in schools. Our approach involves partnering with teachers and other educators through professional development. They learn design thinking tools from us and apply them to a problem faced at their schools, while we research their progress solving the problem and putting design thinking tools into practice. We present a case of schools challenged by how to support students in the process of learning English. We ask, how might teachers learn and use design thinking to develop effective supports for their multilingual students? The research team used mixed methods to gather data. Overall, we noticed our teacher-partners shift from conceptualizing language learning as vocabulary and grammatical structures, to thinking holistically about the range of challenges multilingual students face in schools. We present two teacher cases that highlight how design thinking was used to cultivate design literacy and help their students develop academic and social language skills. Our research was with elementary and middle schools, but we believe that the principles outlined in our design thinking project could extend beyond grade level and content areas.
UNRAVELING THE MICROANATOMY AND FUNCTIONAL SIGNIFICANCE OF THE HUMAN GUT-BRAIN AXIS
Authors: Zainab Sana , Nudar Rodoshi Zarin , Mohamed Kamel Mohyeldin Omar Ahmed , Dewain Sohail , Lokhandwala Adnan , Hussain Erma
Published: April 2024

Sana Zainab
БАЛАНС ТРАДИЦИЙ И ИННОВАЦИЙ: ПУТЬ К УСПЕХУ ПРИ ПРОВЕДЕНИИ СУДЕБНОЙ ЭКСПЕРТИЗЫ И ИЗЫСКАНИИ ПРАВДЫ
Authors: Usov A.I. , Omelyanyuk G.G.
Published: April 2024

Статья посвящена вопросам генезиса судебно-экспертной деятельности, формирования, использования и внедрения в практику судебно-экспертной деятельности подходов и методов, имеющих с точки зрения науки как традиционный, так и инновационный характер. Рассмотрен опыт деятельности научной школы ФБУ РФЦСЭ при Минюсте России по формированию основ судебной экспертологии, разработке актуальных методических материалов, внедрению новых родов (видов) судебной экспертизы в экспертную практику. Показана необходимость развития инноваций при осуществлении деятельности судебно-экспертных учреждений, к которым относятся аккредитация, стандартизация, валидация, создание и обеспечение функционирования системы менеджмента, применение риск-ориентированного подхода. Обозначены перспективы формирования и развития в системе судебно-экспертных учреждений Минюста России землеустроительной, минералогической, молекулярно-генетической, политологической, религиоведческой, этиковедческой экспертиз, экспертизы объектов интеллектуальной собственности, экспертизы охраны труда и техники безопасности. Представлены возможности совершенствования образовательной деятельности для государственных и частных судебных экспертов. Рассмотрены перспективы развития системы менеджмента, стандартизации, аккредитации, внедрения риск-ориентированного подхода для повышения качества и снижения сроков производства судебных экспертиз. Обозначены возможности применения искусственного интеллекта в судебно-экспертной деятельности.
Ключевые слова: судебно-экспертная деятельность, инновации, аккредитация судебно-экспертных учреждений, система менеджмента, риск-ориентированный подход, стандартизация судебно-экспертной деятельности, искусственный интеллект.
Body Contour in the Post-Bariatric Male Patient
Authors: Garza Erick Zúñiga
Published: April 2024

Background: Obesity is currently considered a public health problem. Bariatric procedures have become an important part of obesity management and, consequently, the number of male patients seeking post-bariatric reconstructive procedures have increased. Therefore, the clinical approach and understanding of the body contour of this population have become more relevant. The goal of post-bariatric reconstruction is to enhance the male silhouette through removal of skin and adipose tissue excess, and abdominal rectus diastasis repair. Material and Methods: We conducted a retrospective study at the Plastic and Reconstructive Surgery Department of the National Medical Center “20 de Noviembre”. All male patients referred to our department to start a post-bariatric reconstruction protocol from January 2018 to December 2022 were included in this study. Results: In total, 15 patients who underwent corporal contouring procedures were included; median age was 49.2 years with minimum of 33 years, and a maximum of 57 years. Median Body mass index was 28.4 kg/m2 with minimum of 22 kg/m2 and maximum of 38 kg/m2 . All patients were treated 18 months after their bariatric surgery. All patients underwent an abdominoplasty as a body contouring procedure. 4 (26.7%) patients presented complications related to the surgery. Conclusion: We propose a comprehensive and systematic approach to massive weight loss for male patients, suggesting an abdominal marking based on the patient's clinical features and the expected results avoiding feminization of the abdominal body contour.
Enhancing passive cell balancing techniques for electric vehicles
Authors: Moumni Rachad , Benlaloui Idriss , Laroussi Kouider , Benalia Nadir
Published: April 2024

This research endeavors to enhance the efficiency and functionality of electric vehicle (EV) energy storage systems by scrutinizing the state of charge (SOC) across three batteries. Utilizing Matlab Simulink, a comprehensive battery management system (BMS) integrating passive cell balancing techniques has been meticulously devised. Additionally, a pioneering protective mechanism has been proposed to prevent undue discharges and overcharges, thus ensuring the longevity and reliability of EV battery systems. The study's findings underline the significance and applicability of the developed model in facilitating prospective enhancements within the realm of EV energy storage systems. By meticulously analyzing SOC dynamics across multiple batteries, the study offers valuable insights into optimizing battery utilization, prolonging battery lifespan, and enhancing overall system performance. Moreover, the integration of passive cell balancing techniques within the BMS framework represents a noteworthy advancement in battery management strategies. This approach not only promotes uniformity in SOC distribution among battery cells but also minimizes energy losses and mitigates the risk of cell degradation, thereby bolstering the operational efficiency and durability of EV energy storage systems. Furthermore, the proposed protective mechanism serves as a proactive measure to safeguard against potential damage caused by extreme operating conditions, such as overdischarge and overcharge events. By implementing real-time monitoring and control mechanisms, the protective system ensures the safe and reliable operation of EV batteries under varying driving conditions, thereby enhancing both safety and performance aspects. In conclusion, this research contributes to the ongoing efforts aimed at advancing the state-of-the-art in EV energy storage systems, holding immense potential for fostering innovation and driving sustainable progress in the field of electric mobility.
Influence of the recycled sand on the cement mortars
Authors: Layachi Berredjem , Abdelhak Bordjiba , Laurent Molez , Nourredine Arabi
Published: April 2024

In construction, a recent direction is to examine and integrate alternative sources of building materials with the goal of substituting the use of natural materials. This transition is encouraged by growing concern among policymakers and researchers regarding the environmental footprint of the construction industry. The incorporation of recycled aggregates into cementitious materials, such as concrete or mortar, results in a deterioration of their mechanical performance and their durability. Scientific studies devoted to recycled concrete have demonstrated that it is affected by the introduction of these recycled aggregates, in particular by the use of recycled sand. The latter is characterized by the presence of significant proportions of hardened cement, particularly that coming from a recycling plant. In this work, we aim to study experimentally the influence of the nature of recycled sand on the properties of cement mortars, substituting natural sand, with different percentages by volume: 0, 15, 30, 40, 50 and 75 %, by two types of recycled sand, one from the crushing of structural concrete and the other from a recycling plant. The mortar mixtures were made from CEM I 52.5 and Sand/Cement ratio = 3. The plasticity of these mortars was kept constant and the recycled sands have been pre-wetted. The comparative study between the different compositions of recycled mortars has shown that the physical and mechanical properties are influenced by the incorporation rate of the recycled sand. Of which, increases in the compressive strengths of recycled mortars were recorded, particularly those based on sand from the crushing of structural concrete, compared to the control mortar based on natural river sand. However, the flexural strengths of the recycled mortars suffered a slight reduction compared to the reference mortar.
Perinatális veszteségek lelki megélése
Authors: Sándor Zita , Sánta Tamásné
Published: April 2024

A perinatális veszteségek jelentőst traumát jelentenek a nők számára, melyek nem megfelelő feldolgozása számos rövid- és hosszú távú negatív hatással jár együtt. A vizsgálat célja annak felmérése, hogy a magzati halálozást megélt nők kaptak-e megfelelő lelki támogatást a szakemberek és a társas közeg részéről, illetve megjelent-e esetükben a komplikált gyász. A vizsgálatban 7 perinatális veszteséget megélt nő vett részt. Félig strukturált mélyinterjú segítségével került feltárása a veszteségek megélése, valamint az észlelt professzionális és társas támogatás szinte retrospektív jelleggel. Az adatelemzés a tartalomelemzés módszerével történt. A vizsgálat eredményei szerint a veszteséget megélt édesanyák számára nem biztosítottak az ellátás során professzionális lelki támogatást. A társas támogatás nem minden esetben tudott elegendő szupporciót biztosítani számukra, több esetben kommunikációs gátak alakultak ki a párkapcsolatban, illetve az egyéb társas kapcsolatokban. Az egészségügyi ellátással kapcsolatban több interjúalany idézett fel negatív tapasztalást. Egy esetben volt megállapítható súlyos komplikált gyász, melynek feldolgozása csak évekkel később történt meg. Jelen tanulmány felhívja a figyelmet a perinatális veszteséget megélt nők mentálhigiénés támogatásának fontosságára, valamint az szülészeti-nőgyógyászati osztályon dolgozó szakemberek érzékenyítésére.
A fizikai és érzelmi bántalmazás jellemzői - pszichoszomatikus hatásmechanizmusa
Authors: Tömő Zsolt
Published: April 2024

A review célja egy átfogóbb képet prezentálni a bántalmazások fogalmáról, egyes megnyilvánulási módozatok, mint például fizikális és érzelmi erőszak perspektíváit figyelembe véve, fókuszba helyezve a pszichés hatásokat, a teljesség igénye nélkül. A bántalmazások elkövetői rendszerint maguk is átesetek valamilyen típusú bántalmazáson vagy traumán. A fizikai bántalmazások pszichés vonzatain, jóval túlmutat az érzelmi erőszak okozta sérülés. Elemzésre kerül milyen felnőttkori hatásmechanizmusa lehet a különböző agresszióknak, hogyan és mi vezethet a családon belüli és családon kívüli agresszív bántalmazó viselkedéshez. A gyermekkorban bántalmazáson átesettek, felnőttkorban hajlamosak lesznek a bántalmazásra? Milyen mértékű jelentősége van a fiatalok esetében a kortárs csoportoknak az agresszió megjelenésében? A verbális agresszió mentális, pszichés terhe előbukkan korunk modern digitális világában a cyber térben is. Egy viszonylag fiatal de lelki szempontból destruktívan ható megjelenési formája a verbális agressziónak a cyberbullying. A mai Y, de leginkább a Z generáció gyakorlatilag a virtuális trébe születik bele, ahol számtalan veszélynek, erőszaknak vannak kitéve. A fogalmak prezentálásán, egyes aspektusok kiemelésén túl, a tanulmány kitér az erőszak lehetséges pszichés illetve pszichoszomatikus manifesztációira is.
The relationship between students' health behaviors and health-related quality of life in Gál Ferenc University in Hungary
Authors: Halasi Szabolcs , Katona Krisztina , Szabóné Balogh Ágota , Beke Szilvia , Árpási Zoltán , Kovács József
Published: April 2024

University life can be stressful. Students try to balance work, family, community life and their studies. It is a critical period in young adulthood for an individual’s mental and physical health. The aim of the research was to examine the health behaviors (HB) and health-related quality of life (HRQOL) of the students. In the first phase, which covered the period from September to November 2021, 1,013 students (women 85.1%) at Gál Ferenc University (Szeged, Hungary) responded to a WHOQOL-BREF questionnaire (WHOQOL, 1998) supplemented with questions about their studies. According to the WHOQOL-BREF questionnaire, 84.2% of the students rated their quality of life as good or very good, and 70% were satisfied or very satisfied with their health. Examined by domains, 67.26 ± 13.41 were the least satisfied with their quality of life in the field of environment and most satisfied 76.02 ± 22.22 in the field of physical health. There was no significant difference in the domains between the academic years. In the upcoming period, the elaboration of a health behavior questionnaire will be a priority task so as to follow the effects of the lifestyle change program.
Causes of Housing Bubble in Japan
Authors: Tang Yuwen
Published: April 2024

To find ways to facilitate the development of the real estate economy, this paper examines the Japanese housing bubble of the 1980s, one of the most representative in history. Japan's housing bubble provides us with a good economic model, for which we need to discuss the impact of monetary policy on the housing bubble. Through monetary policy, combined with Taylor's rule, it is analyzed that most of the monetary policy in Japan during that period was in a loose state. Loose monetary policy brought about a series of crises that are detrimental to economic development, such as the rise in land and stock prices, coupled with a series of social problems such as the aging of the population, which ultimately led to the occurrence of the real estate bubble. Japans bubble economy provided a good reference for future generations: the government needs to control the degree of easing and strengthen supervision and risk management.
Investigating the Relationship Between Environmental, Social, and Governance Factors and the Capital Asset Pricing Model
Authors: Qi Qianqian
Published: April 2024

This study delves into the intricate relationship between the Capital Asset Pricing Model (CAPM) and Environmental, Social, and Governance (ESG) factors in the investment landscape. Through an extensive review of existing literature and comparative analyses, the paper uncovers the historical development of CAPM, the rise of ESG considerations, and their convergence in modern financial theory. The research aims to shed light on the ongoing debates surrounding integrating ESG factors into the CAPM framework, revealing both supportive and critical viewpoints. Through a critical evaluation of empirical studies, the paper identifies gaps in the current body of knowledge, emphasizing the need for further research to understand the interplay between ESG factors and CAPM. The study concludes that while ESG considerations have increasingly influenced investment decisions, their precise relationship with traditional financial models, such as CAPM, remains an area ripe for exploration.
The Importance of Maintaining Trademark Anti-Dilution Protection
Authors: Zhu Xinyu
Published: April 2024

Trademark anti-dilution protection is a legal measure aimed at protecting the rights and interests of trademarks and guaranteeing fair competition in the market, but whether it should be canceled has been controversial. The development of the theory of anti-dilution protection of well-known trademarks is a relatively popular research topic, while the Paris Convention and the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) have provisions on anti-dilution of trademarks. Therefore, through the research method of literature review and theoretical analysis, this paper will discuss trademark anti-dilution protection in terms of its definition, implementation effect, and problems. In addition, the importance of trademark anti-dilution protection is elaborated from the perspectives of consumer protection, brand value, and innovation incentives, and the viewpoint of maintaining the existence of trademark anti-dilution protection is confirmed and put forward.
Analysis of Bilibilis Profit Model
Authors: Chen Yirui
Published: April 2024

The main popular videos are short videos these years, Bilibili is still popular among young people and earns a lot of revenue even though they are focused on long videos of their unique products. In this paper, an introduction about the general background of video websites and the background of Bilibili is given, and others progress in this topic is also presented. Moreover, the situations of other video websites and Bilibili are analyzed in the second part. This part talks about the situations and reasons why consumers choose them in this era. Then the analysis of sources of profits online and offline is conducted. This paper found that in both online and offline sections, mobile games occupy the largest amount of revenue but the proportion of mobile games occupied in the general revenue is declining.
Analysis of Business Intelligence Technology in the Big Data Era A Case Study of Alibaba Group
Authors: Zhang Shenwei
Published: April 2024

In the age of big data, business intelligence technology is pivotal in enhancing user experiences and driving innovation across industries. This paper focuses on Alibaba Group, a trailblazer in e-commerce, to examine the transformative role of business intelligence. This paper investigates Alibabas cutting-edge application of business intelligence technology, focusing on intelligent recommendation systems, personalized marketing strategies, and efficient supply chain management. The recommendation system harnesses data analysis to provide tailored product suggestions, boosting user satisfaction and sales. Data-driven marketing strategies enable Alibaba to create personalized promotions and coupons, enhancing user experiences and building loyalty. Intelligent supply chain management employs real-time monitoring, optimized transportation, and data-driven decisions to ensure timely deliveries and cost efficiency. A case study of Alibaba's "Singles Day Global Shopping Festival" illustrates how business intelligence technology creates a dynamic, data-powered shopping event. Every decision during this event is informed by real-time analysis and AI insights, enabling swift responses to evolving consumer needs. In summary, business intelligence, a driving force in the age of big data, is at the heart of Alibabas success. Alibaba has tapped the potential of business intelligence by enhancing the user experience and facilitating data-driven decision-making.
Analysis of Investment Value in the Traditional Chinese Medicine Industry: A Case Study of Yiling Pharmaceutical Co., Ltd.
Authors: Yang Liuyue
Published: April 2024

Over the past five years, the Chinese pharmaceutical industry has experienced new opportunities and challenges with the implementation of a new round of medical reforms nationwide. Since the outbreak of the COVID-19 pandemic in 2019, the increasing awareness of health and the continuous demand for medical services have led to a sustained growth in demand for traditional Chinese medicine products and services in China. This study takes a comprehensive fundamental analysis approach, incorporating relevant knowledge from finance, to examine the financial indicators and development of Yiling Pharmaceutical Co., Ltd., a typical company in the pharmaceutical industry. Through financial statement analysis, the profitability of Yunnan Baiyao is assessed, along with the prediction of debt-paying ability during the evaluation process. Lastly, a fundamental analysis is conducted to summarize the strengths and weaknesses of Yiling Pharmaceutical Co., resulting in the conclusion of its investment value.
Dilemma of ESG Development: Investors Perspectives
Authors: Liu Jiaze
Published: April 2024

Rising concerns around environmental and social issues have led to a heightened investor focus on the ESG performance of corporations. This attention underscores the increasing relevance of ESG considerations in the decision-making processes of investors. However, as ESG investments have risen in popularity, there has also been an increase in contradictory voices. The purpose of this article is to analyze the intricate landscape of ESG investments from the perspective of investors. It aims to shed light on the implications of corporate ESG responses and how investors incorporate ESG parameters into their investment portfolios. The study reveals specific challenges namely: (1) Corporations incurring short-term costs for making transformations affecting their stability, consequently leading to possible reductions in investors' short-term returns; (2) Corporations potentially misleading investors through greenwashing strategies to enhance their ESG portrayal; (3) Requiring investors to possess comprehensive industry knowledge when incorporating ESG in risk assessment thereby adding to time constraints; (4) Existing discrepancies in ESG disclosure standards leading to inconsistencies in ESG ratings given by different agencies; (5) Tracing corporate ESG performance being complicated by its strong links to both the size and financial performance of the corporation; (6) Incorporating ESG factors into investment portfolios could introduce tracking errors and potentially compromise portfolio diversification. Therefore, it is necessary to advocate stricter regulations around ESG disclosures, refining reporting standards to enhance transparency and comparability. Additionally, there is a call for further research to better comprehend the intricate relationship between ESG and financial performance.
The Influence of ESG Reporting on Competitive Dynamics in Business: Insights from a Game Theoretical Approach
Authors: Dong Yuzhe
Published: April 2024

As the basis of ESG rating, ESG information disclosure has gradually moved from a niche investment concept to a mainstream trend in recent years, which plays a key role in the ESG investment process. However, many enterprises still choose not to disclose relevant information for reasons such as controlling costs and reducing negative information output. For enterprises in the same industry with competitive relations, different choices made by both parties may bring about impacts on enterprise competitiveness, financing cost, strategic transformation, and regulation and policy formulation. This paper, from the perspective of enterprises and their competitors in the same industry, uses the game theory model to put forward suggestions for improving enterprises' strategic choices. By establishing a game model to promote the establishment or improvement of ESG management systems within enterprises, enterprises can seek the balance between cooperation and competition in the game, and finally achieve the overall sustainable development in their respective industries.