bluuebunny/crossref_metadata_2025 huggingface dataset:
Crack Detection and Cost Analyzer Using AI
Authors: Musale Kajal Jijabhau  , Gunjal Monali Rajendra  , Bhosale Ashwini Gitaram  , Prof. Pratiksha Pansare
Published: November 2024

Crack Vision is an innovative AI-powered Android application developed to detect and analyze wall cracks, providing users with real-time, automated repair cost estimates. By leveraging advanced object detection models such as YOLOv7 and Mask R-CNN, Crack Vision enhances both the accuracy and efficiency of crack detection, enabling precise measurement of crack dimensions, severity assessment, and quick identification of structural issues. This application simplifies the inspection and budgeting process for wall repairs, making it an essential tool for homeowners, contractors, and structural engineers who seek to minimize reliance on manual inspection methods.
The core functionality of Crack Vision combines high-resolution image processing with state-of-the-art machine learning algorithms, ensuring reliable detection across various wall types and crack textures. Using computer vision and deep learning techniques, the app can differentiate between structural and non-structural cracks, thereby offering a comprehensive solution for repair prioritization.
Furthermore, Crack Vision integrates with a robust backend that stores user data, allowing users to track the condition of their walls over time. This feature aids in preventive maintenance by identifying trends in crack expansion and deterioration, potentially mitigating costly repairs. Additionally, the application provides a detailed breakdown of estimated repair costs based on crack size, depth, and type, empowering users to make informed decisions about necessary repairs.
Crack Vision is designed with user-friendliness in mind, featuring an intuitive interface that guides users through the inspection process. The app also supports multilingual options and customizable settings to cater to diverse user needs. In sum, Crack Vision redefines wall crack inspection, offering a rapid, accurate, and accessible solution for both casual users and industry professionals, ultimately contributing to improved building safety and maintenance efficiency
Integrated Health Monitoring System using Fingerprint and Disease Risk Prediction
Authors: Prof. Shegar S. R.  , Thorat Sakshi Shankar  , Dhumal Rutuja Sanjay  , Dongare Sanika Santosh
Published: November 2024

Recent developments in machine learning and biometric systems have had a big influence on healthcare applications. In order to provide a holistic approach to health monitoring, this research introduces a unique method that combines disease risk prediction with fingerprint-based blood group recognition. Based on user-provided health data, the system uses machine learning algorithms to determine the risk of common illnesses including diabetes, cardiovascular disease, and chronic kidney disease (CKD) and convolutional neural networks (CNNs) to identify blood type from fingerprint photos. Through the integration of fingerprint biometric data with health risk modelling, the suggested approach seeks to increase the precision and usability of health forecasts. The system's effectiveness is demonstrated by the evaluation's excellent classification accuracy for blood groups and trustworthy estimates of illness risk.This work demonstrates the possibility of integrating biometric data with predictive health models and offers a promising step toward customized healthcare solutions
SmartStudy-Learning Path Recommender system using DS and ML
Authors: Ghanshyam Arjun Gund  , Neha Shantaram Jadhav  , Abhishek Gopinath Auti  , Prof. Gita Ghodke
Published: November 2024

Learning Path Recommender Systems (LPRS) utilize machine learning and data-driven approaches to personalize educational experiences, adapting content sequences based on individual learners’ needs and progress. With the rising demand for tailored learning, LPRS have emerged as vital tools to guide students through educational content, enhancing engagement and achievement. This review covers state-of-the-art algorithms, including collaborative filtering and reinforcement learning, used in LPRS to optimize learning paths. We discuss model accuracy, user interaction data, and adaptive feedback mechanisms, providing insights into the potential of LPRS to improve learning outcomes
Health Diagnostic Assistant using LLMs
Authors: Laxmikant Malphedwar  , Anerao Monika  , Dhole Mangesh  , Dixit Tanmay  , Gaikwad Raman
Published: November 2024

The Health Diagnostic Assistant leverages advanced Large Language Models (LLMs) and Natural Language Processing (NLP) techniques to enhance patient diagnosis and healthcare decision-making. This innovative system employs Retrieval-Augmented Generation (RAG) to combine the strengths of pre-trained language models with a dynamic retrieval mechanism, allowing it to access and synthesize real-time medical knowledge from a wide array of databases. By analyzing patient symptoms, medical histories, and contextual data, the assistant generates accurate, context-aware recommendations and insights. The project aims to streamline the diagnostic process, reduce the burden on healthcare professionals, and improve patient outcomes by providing evidence-based suggestions tailored to individual cases. Through continuous learning and integration of user feedback, the Health Diagnostic Assistant aspires to evolve into a reliable tool for both patients and clinicians, fostering informed decision-making in the healthcare landscape.
Formulation and Evalution of Herbal Beetroot Soap
Authors: Miss. Rutuja Dhakane  , Miss. Pooja Bangar  , Dr. Lahu Hingane
Published: November 2024

The aim of our study was to develop the polyherbal hygienic soap by using cold process method and evaluate antimicrobial potential by agar Well diffusion method. Soap was prepared usin olive oil , Almond oil , Glycerine , Aloe Vera gel, Coffee powder , Vitamin E capsule, Glycerine soap base. Nosocomial infection has been recognized as a crucial issue in the outcome of hospital care, with Significant morbidity and mortality results. The primary routes of infection transmission to patients Are the hands of health-care workers. This also evokes utilization of antiseptics for hand- washing Purposes. Many of the antiseptics commercially available are sanitizers dependent on alcohol that Have certain shortcomings or harmful effects. Bacterial skin infections are most common amongst people, requiring significant attention for treatment and also for maintaining Healthy skin. Some herbal plant extracts and their oils were found to have antibacterial activity. The aim and objective of the present Study are to formulate and evaluate anti-bacterial herbal soapuse..
Formulation and Evaluation of Anti-Hyperlipidemic Tablet
Authors: Miss. Pooja Gangadhar Kunte  , Dr. Lahu Hingane
Published: November 2024

Hyperlipidemia is one of the leading causes of mortality in developed as well as in developing countries like India. It attributes to the high risk of coronary heart disease and atherosclerosis which is referred as a silent killer. Herbal treatment for hyperlipidemia is inexpensive, readily available locally, and has no negative side effects. Medicinal plants are the "backbone" of traditional medicine so considered as good source of life for all people due to its wealthy therapeutic properties and being 100% natural. Several drugs in Siddha have been found to be beneficial in lowering lipid levels without any major adverse effects. Numerous plants like arjuna, ashwagandha, garlic, guggul, etc. have been reported to have lipid-lowering effects. The goal of the review paper is to examine the potential anti-hyperlipidemic effects of herbal plants using a variety of models. The anti-hyperlipidemic activity of the most well-known medicinal herbs is the focus of this review.
A Comprehensive Survey on Requirements and Design of AI-Powered Clinical Intelligence Systems in Healthcare
Authors: Vaibhav Kusalkar  , Sarvesh Biwalkar  , Atharv Bhujbal  , Tushar Bansod  , Rohini Jadhav
Published: November 2024

With the increasing complexity of healthcare services, artificial intelligence (AI) is emerging as a vital tool to support medical practitioners by providing real-time clinical insights, automating routine documentation, and enhancing patient engagement. This survey investigates the design requirements, technical challenges, and ethical considerations for AI-powered clinical intelligence systems intended for healthcare environments. Our study is based on a survey conducted with healthcare professionals, patients, and AI researchers, capturing diverse perspectives on functionality, usability, data privacy, and ethical concerns. This paper synthesizes these insights into a detailed requirement analysis that can guide the development of clinically effective, ethically sound, and user-centric AI systems. Through this analysis, we aim to lay the groundwork for creating AIdriven tools that improve clinical workflows, foster better patient outcomes, and support healthcare professionals in delivering quality care.
Revolutionizing Startup Funding: A Centralized Platform for Startup Investment Using MERN Stack and Blockchain Technology
Authors: Prof. Sneha M. Patil  , Abhishek Chavan  , Vaibhav Chauhan  , Vaibhav Chauhan  , Nikhil Kothare
Published: November 2024

India has emerged as a global startup hub, ranking third worldwide with over 112,000 recognized startups and 111 unicorns valued at $350 billion. This growth is driven by government initiatives, enhanced digital infrastructure, and a growing wave of women-led startups. However, barriers such as limited funding access, complex regulations, and infrastructural challenges persist, particularly for early-stage startups. This is a proposed platform that integrates blockchain and modern web technologies to simplify and secure startup funding. It facilitates transparency in equity crowdfunding and angel investing, two critical funding methods that provide startups with financial backing and investors with access to high-potential. This paper discusses the architecture, components, and significance of the platform in addressing existing challenges and empowering India's entrepreneurial ecosystem
Além dos Limites Educação e Pesquisas Contemporâneas - Volume 3
Authors: Folmer Ivanio , Eldereti Machado Gabriella
Published: November 2024

"Além dos Limites" reúne contribuições de especialistas renomados e pensadores visionários, oferecendo uma visão abrangente das tendências emergentes e dos debates atuais na educação e na pesquisa. Cada capítulo mergulha em temas relevantes e desafiadores, desde a tecnologia na sala de aula até as abordagens inovadoras de pesquisa em diferentes campos do conhecimento.
Uso potencial de los Probióticos: Mecanismos Moleculares y aplicaciones clínicas en el manejo de enfermedades metabólicas
Authors: Eugenio Chafloque Capuñay Jose , Catalina Mechan Capuñay Paula , María Guerrero Laban Luz , Alcibíades Cayetano Vásquez Manuel
Published: November 2024

Actualmente el aumento de la prevalencia de enfermedades metabólicas, como la obesidad, la diabetes tipo 2 y la enfermedad del hígado graso no alcohólico, han originado la búsqueda de estrategias terapéuticas efectivas. En ese contexto, los probióticos, son definidos como microorganismos vivos que cuando se administran en cantidades adecuadas, brindan beneficios a la salud del huésped, por lo que surge como una alternativa prometedora
On Prognosis of Manufacturing of P-N-Heterojunctions in the Framework of a Multilevel Inverter with Reduced Number of Switches to Increase Their Integration Rate. On Influence Mismatch-Induced Stress
Authors: L. Pankratov Evgeny
Published: November 2024

In this paper we introduce an approach to increase density of p-n-heterojunctions in the framework of a multilevel inverter with reduced number of switches. Framework the approach we consider manufacturing the inverter in heterostructure with specific configuration. Several required areas of the heterostructure should be doped by diffusion or ion implantation. After that dopant and radiation defects should by annealed in the framework od an optimized scheme. We also consider an approach to decrease value of mismatch-induced stress in the considered heterostructure. We introduce an analytical approach to analyze mass and heat transport in heterostructures during manufacturing of integrated circuits with account mismatch-induced stress.
Beyond ‘Autocomplete on Steroids’: Testing a NEO-Aristotelian Theory of Some Emergent Features of Intentionality in LLMs
Authors: Cox Gray
Published: November 2024

This paper explores shortcomings in the “autocomplete on steroids” (AOS) way of conceptual framing Large Language Models (LLMs). It first sketches that view and some key reasons for its appeal. It then argues the view overlooks ways the Attention function in GPT systems introduces features of emergent intentionality in LLM behavior because it tacitly frames the description with the mechanistic metaphor of efficient causality. A conceptual analysis of the functions of variable Attention in GPT reinforcement learning suggests Aristotelian categories of formal and final causality provide a better understanding of the kinds of pattern recognition found in LLMs and the ways their behaviors seem to exhibit evidence of design and purpose. A conceptual illustration is used to explain the neo-Aristotelian theory proposed. Then descriptions and analyses of a series of preliminary experiments with three LLMs are used to explore empirical evidence for the comparative merits of that theory. The experiments provide preliminary evidence of the LLMs’ abilities to engage in the production of texts in ways that exhibit formal and final causality that would be difficult to explain using mechanical conceptions of efficient causality that are implied by the “autocomplete on steroids” theory. The paper concludes with a brief review of the key findings, the limits of this study, and directions for future research that it suggests.
MCGM: Mask Conditional Text-to-Imagegenerative Mode
Authors: Skaik Rami , Rossi Leonardo , Fontanini Tomaso , Prati Andrea
Published: November 2024

Recent advancements in generative models have revolutionized the field of artificial intelligence, enabling the creation of highly-realistic and detailed images. In this study, we propose a novel Mask Conditional Text-to-Image Generative Model (MCGM) that leverages the power of conditional diffusion models to generate pictures with specific poses. Our model builds upon the success of the Break-a-scene [1] model in generating new scenes using a single image with multiple subjects and incorporates a mask embedding injection that allows the conditioning of the generation process. By introducing this additional level of control, MCGM offers a flexible and intuitive approach for generating specific poses for one or more subjects learned from a single image, empowering users to influence the output based on their requirements. Through extensive experimentation and evaluation, we demonstrate the effectiveness of our proposed model in generating highquality images that meet predefined mask conditions and improving the current Break-ascene generative model.
Relationship of General Tobacco Products & E-Cigarettes on Oral Health: Considerable Risks Including Oral Cancer and Periodontitis
Authors: Park Charlie Jin Woo , Walker Dr. Douglas
Published: November 2024

The purpose of this literature review is to investigate the effects of e-cigarettes on oral health in young adults, highlighting the considerable risks associated with tobacco smoking, such as oral cancer and periodontitis. E-cigarettes first gained popularity in 2006 and are now used by over 40 million people worldwide; however, their impact on oral health and whether they have similar oral health risks as traditional tobacco products is not well understood. This study consolidates findings from basic science, microbiology, clinical research, and epidemiological studies to investigate potential oral health consequences of e-cigarette use. It also highlights the crucial role of dental professionals in educating patients and advocating for tobacco cessation, despite the challenges introduced by the novelty of e-cigarettes and existing research biases. For this study, a comprehensive literature search was conducted using PubMed to identify studies focused on tobacco smoking and vaping and its influence on dental healthof young adults aged 20 to 30. Initially, 30,000 papers were found, and after filtering, 14 relevant studies were included in the review. The studies reviewed indicates a correlation between vaping and an increased risk of dental caries. It points out the urgent need for more comprehensive studies to understandthe long-term effects of vaping on oral health. While traditional tobacco use's negative impact on oral health is well-documented, this review underscores that e-cigarettes also pose significant risks, highlighting the importance of ongoing research and education in the dental community to navigate the evolving landscape of tobacco use and its implications for oral health.
Prompt-Response (PnR) Cloud Computing -Intentions and Context
Authors: Pal Pronab
Published: November 2024

In today’s cloud-native multi-core environments, the deployment and runtime performance of applications often take precedence over the visibility and agility of business logic. While this prioritization ensures optimal responsiveness, it can inadvertently create barriers to real-time analysis and rapid business adaptability. Traditional approaches necessitate reproducing issues in development environments and implementing additional tracing mechanisms, leading to delays in problem resolution and business evolution. This paper introduces the Prompt and Response (PnR) computing model. This paradigm shift addresses these challenges by maintaining a clear representation of intention flow and object data throughout the application lifecycle. The PnR system enables real-time analysis and intelligence derivation in production environments, transcending the limitations of container boundaries and module isolation. By representing every input and result of each module associated with distinct intentions within the PnR framework, we create a unified and traceable computational space called Intention Space. This approach allows for precise identification and analysis of specific modules referred to as just ’Design Chunks’, regardless of their distribution across single or multiple containers or boundaries. We explore the architectural patterns of PnR transformations, illustrating how this model aligns with and extends current computing paradigms while offering a more flexible and transparent approach to managing complex, distributed systems. This paper aims to provide a computational foundation for implementing PnR systems, paving the way for more adaptable, analysable, and efficient cloud-native applications.
Artificial Intelligence Natural Language Processing: A Barrier to Knowledge Acquisition in Higher Education
Authors: Jedishkem Epilogue , Jedishkem Jesfaith
Published: November 2024

Higher education students are recognized for neglecting assigned readings hence, researchers explored artificial intelligence (AI) as an instrument of motivation; in the process of satisfying this demand, another interference developed, English, a linguistic barrier. Multi-cultural disparities impede literacy, equally, AI natural language processing (NLP) and prompts require fluency and command of English, which can be a hindrance for the underprivileged. The research aimed to determine the potential of AI educational tools in facilitating learning. Empirically, exploratory design was espoused to uncover the reasons behind college students’ lack of interest in reading and identify factors that can motivate them. A total of 162 first-year college students participated in the study. AI was specifically selected as a motivational instrument. Findings show students expressed optimism regarding the integration of AI into education, high-achieving students displayed confidence when interacting with AI, while those with lower proficiency faced difficulties due to NLP obstacles.
Research on Bank Customer Churn Prediction Model based on Ensemble Learning Algorithm
Authors: Xinping Shang , Yi Wang
Published: November 2024

With the rise of Internet finance, the competition of banking industry is becoming increasingly fierce. To gain more accurate and comprehensive insight into customer needs and improve customer loyalty, it is essential to establish a customer churn analysis model. This kind of model can help banks identify customers who are about to lose, facilitate business decisions, retain relevant users, and ensure that bank interests are not affected. Under this background, this paper establishes a customer churn prediction model using ensemble learning algorithm. Experimental data show that the model can effectively predict and analyse the loss of bank customers.
On Increasing of an Integration Rate of Bipolar Heterotransistors in the Framework of a Single Leg N-level Cascaded H-Bridge Multilevel Inverter
Authors: Pankratov E.L
Published: November 2024

In this paper, we introduce an approach for increasing integration rate of bipolar heterotransistors in the framework of a single-leg N-level cascaded H-bridge multilevel inverter. In the framework of the approach we consider a heterostructure with special configuration. Several specific areas of the heterostructure should be doped by diffusion or ion implantation. Annealing of dopant and/or radiation defects should be optimized.
On Decreasing of Mismatch-Induced Stress During Growth of Films During Magnetron Sputtering
Authors: Pankratov E.L
Published: November 2024

In this paper we analyzed mass transfer during the growth of epitaxial layers during magnetron sputtering. During the analysis we obtained modifications of properties of films with variation of several parameters. We analyzed possibility to decrease mismatch -induced stress on the considered films during their growth. An analytical approach for analyzing mass transfer was introduced, which makes it possible to take into account the nonlinearity of processes, as well as changes in parameters in space and time.
Modified Sand Cat Swarm Optimization (MSCSO) Based Feature Selection for Classification of Diseases in Tomato Leaves
Authors: Negi Chetan Singh , Mandoria H. L , Jalal Sunita
Published: November 2024

Food obtained from the plants is one of the most basic requirements for the survival of humanity. However, plant diseases produce low-quality products that adversely affect the country's economy. Machine learning based detection methods for such diseases can reduce these effects. However, these methods involve plant images and usually suffer the curse of dimensionality in terms of features. Features selection improves the performance of machine learning algorithms. Feature selection method aims to find optimal number of features for a machine learning algorithm such as classification, clustering and many more. This work proposed a Modified Sand Cat Swarm Optimization (MSCSO) algorithm based feature selection to find the optimal number of features. The algorithm performs well over other standard algorithm such as GA, PSO, and GWO. The performance of different classifiers are analysed for classification of diseases in tomato leaves based on features selected by MSCSO.
Baoulé Related Parallel Corpora for Machine Translation Tasks: Mtbci-1.0
Authors: Jean-Claude Kouassi Konan
Published: November 2024

According to the Ethnologue platform, we have 7,164 known living languages in the World, and not all of them have data available over the internet to facilitate Artificial Intelligence (AI) tasks such as Machine Translation (MT). Consequently, there is a need for thorough Data Engineering tasks for most of these languages. Especially, the Baoulé living language normalized as ISO 639-3 (bci) is not yet supported on popular worldwide free translation platform such as Microsoft Translator, nor on the Official Wikipedias. In this paper, we have proposed the "Baoulé Related Parallel Corpora for Machine Translation tasks: mtBCI-1.0" to make parallel Baoulé-related datasets available to the scientific community for AI tasks implying Machine Translation. We have shown that, after a brief presentation of the Baoulé language in the proposed approach, we will focus on the Data Engineering Process itself before providing a baseline proving that the collected data is of scientific interest.
Resources Price Adjustment in Cloud Computing for Load Balancing and Fairness Between Users and Suppliers
Authors: Gherir Lilia Chourou , Elleuch Ahmed , Jemni Mohamed
Published: November 2024

Resource price adjustment is a challenging issue when building a cloud computing system. For this purpose, we present an approach that adopts a market-driven price adjustment model as an economic incentive model and ensures the balance between supply and demand. We show how this model may be adapted and applied to an infrastructure as a service (IaaS) in cloud computing. We place ourselves in the context of the virtual machines market. To achieve competitive equilibrium, prices are adjusted according to a tâtonnement-like process. The prices are computed by a third party, the auctioneer. However, this process requires several assumptions to ensure the existence and stability of competitive equilibrium, not all of which are verified by cloud computing systems. The atomicity and convexity of preferences are not guaranteed by cloud computing systems. These questions will be the subject of our empirical study. We find empirically that the change in the sign of excess demand, indicating the existence of equilibrium, occurs between two similar prices. The experimental results show that the proposed dynamic price adjustment approach is more profitable than fixed-price pricing, allowing dynamic suppliers to become important market agents.
Exploring the Selection and Training of Tour Leaders: An Evaluation Model Based on the Analytic Hierarchy Process
Authors: Sun Yuang-Liang , Huang Han-Chen
Published: November 2024

Since the outbreak of the global pandemic in 2020, the tourism industry in various countries has nearly come to a standstill, resulting in many individuals who previously worked as tour leaders shifting to other professions due to financial issues. As the pandemic gradually eases and border controls are progressively relaxed, the outbound travel market is seeing a glimmer of recovery. This signifies that the demand for tour leaders will increase for travel agencies. Tour leaders are not only promoters of business sales but also frontline service personnel who interact directly with customers. Their performance directly affects customer satisfaction with travel itineraries. Therefore, travel agencies must pay special attention to selection criteria when re-selecting tour leaders. This study aims to explore the selection criteria for tour leaders to assist travel agencies in objectively and effectively evaluating suitable candidates. Although tour leaders may not play as central a role in travel activities as tour guides, they remain crucial factors influencing the success or failure of travel activities. This paper collects expert opinions through the Delphi method and employs the Analytic Hierarchy Process (AHP) to categorize the selection criteria for tour leaders into five main dimensions and sixteen indicators, covering aspects such as personal conditions, professional knowledge, professional skills, service attitude, and execution capability. The ultimate goal of this study is to provide travel agencies with a more objective and effective basis for selecting tour leaders.
AI-Driven Threat Intelligence: Transforming Cybersecurity for Proactive Risk Management in Critical Sectors
Authors: Islam SA Mohaiminul , Bari MD Shadikul , Sarkar Ankur , Khan A J M Obaidur Rahman , Paul Rakesh
Published: November 2024

Notably, the current progresses in the field of information technology have highlighted the need to have adequate security measures that will help overcome the complicated dangers originating from the cyber space. In this journal article, the author discusses what AI means for the practice area of cybersecurity, what it means, and its application of threat intelligence. Stress is made on the pro-active identification and mitigation of threats, the processes and adjustment of the cyber defense, various issues and moral concerns connected with the use of AI in this area. The Future evolution of AI in cybersecurity is discussed, along with its prospects, Including AI-integrated SOCs and automated response capabilities. As will be highlighted by understanding and application of these advancements, vital areas can strengthen their resilience against cyber threats.
Incorporating Cross-Cultural Design into the User Interface
Authors: Nejati Bahareh , Manchi Ravi Teja , Schofield Damian
Published: November 2024

This paper focuses on the significance of culturally tailored digital products for Arabic-speaking users, examining how cultural relevance influences user satisfaction and engagement. This research study aimed to provide guidelines for incorporating cross-cultural designs in interfaces for Arabic-speaking users. Utilizing Hofstede's cultural dimensions as a framework, the study employs A/B testing, surveys, and interviews to reveal the importance of cultural inclusivity in interface design. The finding of this research demonstrated that the ease of understanding and interaction with digital products varies for native Arabic speakers and that feature and functionality requirements differ based on users' nationality. This, in turn, highlighted the pivotal role of culturally adapted UI/UX in improving user experience, advocating for digital products that are both empathetic and inclusive. By emphasizing cultural considerations, this research contributes to the broader discourse on creating user-centric digital environments that resonate with a diverse global audience, aiming to enhance connectivity between brands and their diverse user bases.
Comprehensive Performance Testing Analysis and Security Vulnerability Detection of a 5G Stand Alone Network using a Firecell Testbed
Authors: Anyakora Ndidi , M. Akujuobi Cajetan , F. Chouikka Mohamed
Published: November 2024

With the proliferation of 5G networks, evaluating security vulnerabilities is crucial. This paper presents an implemented 5G standalone testbed operating in the mmWave frequency range for research and analysis. Over-the-air testing validates expected throughputs up to 5Gbps downlink and 1Gbps uplink, low latency, and robust connectivity. Detailed examination of captured network traffic provides insights into protocol distribution and signalling flows. The comparative evaluation shows only 0.45% packet loss on the testbed versus 2.7% in prior simulations, proving improved reliability. The results highlight the efficacy of the testbed for security assessments, performance benchmarking, and progression towards 6G systems. This paper demonstrates a robust platform to facilitate innovation in 5G and beyond through practical experimentation.For access to the code, data, and experimental results, visit our GitHub repository(https://github.com/Didilish/5G-SA-Testbed-Analysis)
Josué de Castro
Authors: Accioly Elizabeth , Andrade Lucia Pereira de , Santos Maria Luiza Moreira dos
Published: November 2024

A presente biografia é uma breve revisão sobre a vida e obra de Josué de Castro. O objetivo é resgatar sua trajetória e contribuições, especialmente no campo da alimentação e nutrição (A&N). As fontes primárias de consulta foram livros do acervo bibliográfico do Instituto de Nutrição Josué de Castro da Universidade Federal do Rio de Janeiro e publicações de pesquisadores e instituições/organizações científicas sobre o biografado. Os resultados demonstraram o papel relevante dessa personalidade como professor, escritor, diplomata e parlamentar. O objeto de seu interesse foi a fome no Brasil e no mundo, denunciando as raízes econômico-político-sociais do problema. Revisitar a obra de Josué de Castro possibilita ao leitor conhecer suas contribuições ao debate sobre a fome e no combate a esse mal. Permite ainda entender como seus estudos deram origem a políticas públicas na área de A&N, algumas ainda existentes.
The Mediator Role of Social-emotional Learning Skills in the Relationship Between Depression and Mental Well-being
Authors: Demir Berkan , Büyükçolpan Hakan
Published: November 2024

Well-being is a multifaceted concept encompassing a broad spectrum of dimensions, including mental well-being, which has been an appealing area of study for scholars from different parts of the world. The current study aims to explore the relationship among depression, social-emotional learning skills, and mental well-being in a conveniently selected sample of college students. The sample consisted of 237 public school undergraduate students, of whom 151 (63.29%) were women. The results indicated that social-emotional learning skills partially mediated the relationship between depression and mental well-being. The findings show that social-emotional learning skills pose a protective factor against lower levels of mental well-being occurring as the result of depressive symptoms. The overall model explained 32% of variance in mental well-being. Findings were discussed in the light of the relevant literature. Through synthesizing current literature knowledge and results derived, this study aims to provide a foundation for further research and practice that promotes mental well-being.
Upper eyelid reconstruction due to scar contracture following major burn injury: A case series
Authors: Zakaria Iskandar , Rizal Syamsul , Irwansyah Denny , Chintia Amelia Pratiwi
Published: November 2024

Background: Upper eyelid contracture is a regular occurrence after severe facial burns. Numerous problems, such as corneal ulcers and exposure keratitis, may result from it. It is difficult for plastic surgeons to operate in this situation to preserve worst-case scenarios and enhance palpebral function.
Methods: In this piece, we showcase two instances: (1) Eight months after suffering a chemical burn injury, a 26-year-old male was diagnosed with bilateral superior palpebral contracture with iris prolapse. Both eyes' visual acuity was 6/6 - 1/¥. A 75-year-old female patient was identified as having a corneal ulcer and a contracture on her left upper eyelid. Both eyes' visual acuity was 20/6 - 1/¥. In order to restore the top eyelid in both patients, we undertook a contracture release and a full-thickness skin graft.
Results: Evaluation five days after surgery revealed no evidence of graft lysis and that the graft had taken nicely. On the patient graft from the second, we discovered shifting, although new epithelization will take place. Both of the patients had good eyelid looks following restoration.
Conclusion: Plastic surgeons should be aware of the seriousness of significant burn injuries to the face. Patients must receive appropriate instruction on the significance of avoiding consequences from eyelid contractures. In this instance, creating the top eyelid via a skin graft and contracture release technique made sense. We acknowledge that one of the limitations of our study is the brief observational period of the patient's conditions.
Analysis of the heterogeinety impact of oil prices shocks on exchange rates in oil exporting countries: evidence of quantiles-on -quantiles approach
Authors: ATEBA Joseph  , EWONDO Dieudonne  , ABEGA Daniel Armando  , ENAMA Alice  , ABOMO ZANG Julie Christianne
Published: November 2024

The objective of this study is to investigate the heterogeneous dynamic between exchange rate returns and oil prices in oil exporting countries. Precisely, the researchers used the exchange rates returns of both low incomes, emerging and developed majors oil exporting countries, and decomposed oil price shocks to study the heterogeneity of the intrinsic dynamic between the two variables in these countries, using the quantile-on-quantile analysis. The findings revealed that, although the dynamic between oil prices shocks and exchange rates returns is largely negative in these countries, there are important variability of the shocks impacts across  the quantile distribution of both exchange rates returns and the different oil price shocks. More precisely , the study reavealed the heterogeneity of the different oil shocks impacts (oil aggregate demand , oil supply and oil specific demand shocks) on the exchange rates  return of a  given country , with the shape of the QQR graphs  being different according to the source  of shock  and the magnitude of oil demand and oil specific demand shocks being more significant than that of oil supply shocks in many of the cases. In the same way , the analysis  results also indicate that the dynamic between oil price shocks and exchange rate is heterogenous across the countries , with the impact of the shocks being more significant in developing countries than it is in developed countries . As well the behavior of the exchange rates returns at extreme values is different from one country to another. From this insight, the researcher recommends an economy diversification mainly for oil developing countries, and country-specific economy policies to mitigate the incidence of oil shocks, as the impact differs from one country to another..
Keywords: Exchange Rates, Oil Prices, Quantile-on-Quantile, Oil Exporting Countries.
Antibiotic Resistance in Mycobacterium Tuberculosis and Non-Tuberculous Mycobacteria
Authors: Wamalwa Ronald , Guyah Bernard , Shaviya Nathan
Published: November 2024

Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM) antibiotic resistance presents an important challenge to the treatment of mycobacterial infections. The therapeutic approaches are complicated by the resistance of both MTB and NTM to a variety of antibiotics. Resistance to first-line drugs such as isoniazid, rifampicin, ethambutol, and streptomycin has been consistently increasing in MTB, underscoring the necessity of effective treatment strategies. Conversely, the necessity of species-specific treatment regimens is underscored by the high resistance rates of NTM species, such as Mycobacterium avium complex, M. kansasii, and M. abscessus complex, to commonly used anti-tuberculosis pharmaceuticals. A combination of intrinsic and acquired factors are involved in the mechanisms of antibiotic resistance in these mycobacteria. Features such as biofilm formation, thick cell walls, and reduced drug uptake are responsible for intrinsic resistance in NTM, whereas acquired resistance can develop as a result of protracted antibiotic exposure. Understanding these resistance mechanisms is essential for the development of new therapies and the prevention of the increasing prevalence of drug resistance in mycobacterial infections. The significance of continuous surveillance, species-specific treatment protocols, and the development of novel antimicrobial agents to effectively manage mycobacterial diseases is emphasized by the prevalence of antibiotic resistance in MTB and NTM. This review article focuses on the molecular mechanisms that have resulted in the development of resistance in both MTB and NTMs, as well as the extent to which various classes of antimycobacterial drugs act.
Neuromarketing Applied in Organizations: A Scientific Production Study
Authors: Gonzales Ana Valeria Díaz , López Rosa Johanna Clavijo , Neyra-Panta Marlon Joel , Calderón Enzo André Bautista , Rojas Carlos Quinto Huamán , Vela Jerris Rojas
Published: November 2024

The objective was to identify the literary contributions that support neuromarketing, using a literature review study, with an exploratory-explanatory scope, using literature review as the data collection technique. For the identification of publications, from 2020 to 2024. There were a total of 30 articles. The results mention, to study the benefits and limitations of neuromarketing tools in a series of market entry devices. Neuromarketing contributes to customer acquisition and better positioning of the company, in addition to achieving loyalty and love for the brand. Neuromarketing is regarded as a recent development in marketing since it applies neuroscience to market research to analyze which stimuli cause a particular kind of customer behavior. It also helps to uncover feelings and perceptions about a business in order to create strategies that increase customer loyalty.
The Impact of Digital Transformation on Customer Experience: A Study of How Firms Use Digital to Enhance CX
Authors: Sehgal Rajesh , Soni Sandeep
Published: November 2024

This pandemic harmed all economies, developed and developing, because the entire world was under lockdown. The corporate community is also experiencing instability as a result of this outcry. Numerous people have experienced job loss for a variety of causes. It was hard for the business organisations to continue because the market and all of the operations were reduced or stopped. Business organisations really needed to change their strategies because the ones they had been using to succeed were no longer workable. Lockdowns, social isolation, and other restrictions made it extremely difficult for businesses to provide customers a genuine sense of their goods or services. Businesses have been forced by COVID-19 to move their product and service promotion and advertising online. in order for them to build a solid clientele even after lockdown scenarios. For corporate companies, virtual buying and an awareness of online customer behaviour are becoming essential. Due to the competitive virtual marketplace, business businesses are prioritising these things, which is the genuine requirement of the current moment. Gradually, regular Internet development and expansion have made eCommerce a part of mainstream corporate operations.
A Study on Problems in the Insurance Repository System in India
Authors: Pius Ashish C , Velmurugan R.
Published: November 2024

This section discusses the problems of the insurance repository system and it is possible to state that the situation is quite chaotic here. Due to the availability of many repositories in the industry, policyholders are confused and the emergence of repository services distorts the insurers-policyholders nexus. Further, the majority of the policyholders have low computer literacy which extends the problem as far as the adoption of the repository services is concerned and also increases the possibility of exploiting the policyholder information. But when arrangements are made to try and bring the services closer to ensure that they are availed to all the various policyholders of the repository services, it is realized that many of the life insurance firms do not encourage the policyholders through active marketing. And, it contributes to the other issue which makes the policyholders’ attitude towards the repository system not highly positive. Promoting the use of the repository system has also been lacking tangent arising from the interface initiates that copy with the hands of the regulatory bodies such as IRDA. In the context of this research, system barriers, including network availability bear more difficulty in being solved, hence resulting in higher variability in as well as levels and patterns of use of the repository system compared to consolidated groups like the CPRP. These complex challenges underscore the need to come up with suitable and feasible interventions to address the issues that have characterized the insurance repository system, with the view to making it functional for all the targeted users and other stakeholders.
Analysis of the Scientific Production on Direct Consumer Behavior
Authors: Villacis Ximena Lucia Rodríguez , Zuta Esmeralda Rojas , Lozano Sharon Mendoza , Ramírez Segundo Víctor León , Lozano Danny Alonso Ramírez , Vela Jerris Rojas
Published: November 2024

The objective of the research was to analyze the scientific contributions that underpin the behavior of the direct consumer. The methodology was basic, non-experimental design, exploratory-explanatory scope, whose sample consisted of 30 articles. The results showed that the analysis of behaviors can also be developed through the collection of information about the preferences and interests of consumers; there are also various variables that intervene in the behavior of consumers, which is why the analysis of these aspects must be taken into account for the formulation of precise strategies. Concluding that, it is possible to get to know the consumer and the reasons, both internal and external, that involve their decision making, therefore it is significant to be able to factor them to allow it to be visualized with a broad panorama and to know how it impacts them and its evolution.
Investment Pattern and Behaviour of Rural Households on Investment Avenues with Special Reference to Ernakulam District
Authors: Raj Drishya S , Dharmaraj A.
Published: November 2024

Two-thirds (67.63% of the total population) of the people in rural India live there and contribute one-third of the country's GDP1. One of the most significant areas that increases gross domestic savings is the household sector. The main objective of the study is to understand rural household savings and investment behaviour that is influenced by a number of factors including years of age, schooling, financial status, and occupation. According to the study, the majority of respondents have lower earning potential, and even those who did earn more only set aside a little fraction of their income for savings. In India, there are numerous investment opportunities and there are advantages and disadvantages to any investment strategy. Making the best investment decisions will meet the various demands of different people requires having a thorough understanding of these investing options. This paper projects various investment options and the level of household awareness in rural areas areas. The study utilized a meticulously designed questionnaire to explore the investment preferences and awareness levels of rural investors. The primary aim was to gain insights into their preferred investment avenues and their level of understanding regarding various investment options. For data analysis, simple percentages were employed to summarize the findings, and the chi-square test was used to assess relationships between categorical variables. 300 rural households selected as sample size from Ernakulam District through convenience sampling method.
Socio-Emotional Well-Being and its Determinants in School Students: A Comprehensive Review
Authors: Mitra Sarbani , Acharya Shnaoli Chakraborty
Published: November 2024

This systematic review aims to present an overview of existing research on the socio-emotional well-being of students and other associated factors. After a rigorous search through Shodhganga, SAGE Journals Online, Elsevier, Springer-Journals Archive, Research Gate, and ERIC-Education Resources Information Centre, articles were carried out from 2000 to 2024. The review resulted in the identification of a total of 26 articles based on pre-established inclusion criteria. The results indicate that the Socio-emotional well-being of school students is associated with and influenced by other significant factors like school climate, mental health, peer support, etc. The results prominently identify the directions of other research conducted in the same domain, indicate thematic research trends, and highlight gaps to be further investigated. A limited study in the Indian context with adolescents clearly shows an extensive need for research on primary school students. Context-specific research is needed to understand the socio-emotional well-being status of students in a diversified and multicultural country like India.