bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Analysis of Machine Learning Techniques in Creating Virtual Replicas for Healthcare Simulations
Authors: Patil Yogita Manish , Abraham Arockia Raj , Chaubey Nirbhay Kumar , K. Baskar , Chidambaranathan Senthilnathan
Published: July 2024

This comparative analysis into various machine learning techniques employed on the development of virtual replicas (digital twins) for healthcare simulations. The study explores the effectiveness and applications of these methods, shedding light on their respective strengths and limitations. By examining diverse approaches, from traditional algorithms to deep learning models, the research explores to provide insights into the landscape of creating realistic healthcare simulations. Understanding the comparative performance of the techniques will be crucial for advancing the quality and authenticity of virtual replicas, thereby enhancing the utility in healthcare training and education. This analysis contributes to the ongoing discourse on leveraging machine learning for more immersive and effective healthcare simulations.
AI-Empowered Devices and Strategies to Reduce Cost in Business
Authors: Siddiqui Ahmad Tasnim , Jahangeer Gul Shaira Banu , Basha Amjath Fareeth
Published: July 2024

In today's rapidly evolving business environment, organizations are progressively turning towards artificial intelligence (AI) to enhance efficiency, streamline processes, and optimize resource utilization. This abstract explores the integration of AI-empowered technologies as strategic tools to reduce costs and improve overall financial performance in various business sectors. The adoption of AI technologies, including machine learning, predictive analytics, and natural language processing has enabled businesses to analyze vast amounts of data quickly and derive actionable insights. This capability allows for informed decision-making, process automation, and the identification of cost-saving opportunities. Furthermore, the chapter addresses the challenges connected with AI integration, such as data security, workforce upskilling, and ethical significances. Successful strategies encompass a phased approach, starting with a thorough assessment of existing processes and identification of areas where AI can deliver maximum value.
Business Security and Ethical Considerations in AI-Driven Digital Twins
Authors: Dashore Pankaj , Dashore Rachana
Published: July 2024

The combination of artificial intelligence (AI) and digital twin technologies presents new opportunities and challenges as businesses increasingly recognize their disruptive potential. The purpose of this study is to shed light on the intricate dynamics that result from the convergence of these technologies by examining the relationship between business security and ethical considerations in the context of AI-driven digital twins. Digital twins with AI integration provide previously unheard-of possibilities for optimization, prediction, and simulation in a variety of industries. However, there are serious concerns about the security of confidential company information, intellectual property, and the possibility of misuse raised by this synergy. In order to protect against cyber-attacks, data breaches, and unauthorized access, this chapter examines the security issues that are inherent in AI-driven digital twins and suggests strategies.
Role of Artificial Intelligence in Business Analytics
Authors: Gill Satinderjit Kaur , Chaudhary Anita
Published: July 2024

Artificial intelligence has a very important role in any type of business today. Because data is so voluminous, before taking any decision we have to perform analysis on it carefully; and because of the large amount of data, it is not always possible to do it manually, and the use of computers is necessary. This system the authors designed will save businesses time and cost both. They can take a quick decision if business routine processes and tasks would optimize automatically. By using artificial intelligence, the productivity and operational efficiency of any business can be improved. Businessman can expand their business in easy ways, and they can have the choice of customer and can update their products according to their requirements.
Significance of Transmedia Storytelling in Higher Education
Authors: Thrower Anika C. , Evangelista Alex
Published: July 2024

Institutions of higher learning are essential in society. In the year 2023, there were over 18 million students. Though this total is substantial, it is below par compared to past trends. Long-standing college enrollment has been a catalyst for educating individuals in their chosen fields. Education attainment over time assists people in increasing the quality of life for themselves and their families, optimal health outcomes, and higher levels of productivity in communities while opening themselves to a broader range of opportunities. Because of COVID-19, in recent years, enrollment, retention, and graduation rates have been a challenge, particularly among nontraditional college students. Ensuring mattering and providing an inclusive campus environment has been more critical than ever before. As college administration and instructors seek ways to alleviate such fluctuations, collaborative learning and transmedia are viable solutions.
Cryptographic Techniques for Securing Blockchain Transactions
Authors: Zanjat Shraddha N. , Karmore Bhavana S. , Barbudhe Vishwajit K.
Published: July 2024

Blockchain technology is revolutionizing the world of digital transactions. Imagine it as a shared digital ledger that is distributed across numerous computers. This setup ensures that transaction records and user details are secure and resistant to tampering. For blockchain to be effective, it's crucial that user information remains protected. The technology uses cryptographic methods to provide this protection, enabling secure and anonymous financial transactions among users within the network. Each transaction is verified and approved by all network participants, creating a transparent and trustworthy system.
Evaluation of Security Risks and Countermeasures in Blockchain Generations 1.0, 2.0, and 3.0
Authors: Chaudhary Sania , Sindhu Neha , Sharma Garima
Published: July 2024

The growing use of Blockchain technology across several industries emphasizes how important a role it plays in streamlining vital business processes. Ethereum and Hyperledger Fabric are prominent frameworks utilizing complex middleware for executing smart contracts that define collaborative application logic. Maintaining safety standards across many Blockchain generations depends on the detection and mitigation of vulnerabilities and dangers in Blockchain systems. Testing Blockchain applications serves to ensure superior quality, comprehensive test coverage, and risk mitigation particularly when considering inadequate insights during the software development lifecycle. The paper introduces a novel taxonomy of attacks targeting various Blockchain generations and assesses multiple static analysis tools tailored for Ethereum and Hyperledger Fabric. Two quantitative analyses are conducted, evaluating the tools' performance in detecting vulnerabilities within Blockchain 2.0 and chain code vulnerabilities within Blockchain 3.0. This comprehensive investigation significantly contributes to the research community's understanding of distinct Blockchain generations.
Secure Digital Identity Cards With Blockchain and Digital Twins Approach
Authors: Satsangi Ankit , Dashore Pankaj , Dashore Rachana
Published: July 2024

In today's increasingly digital world, the demand for secure and dependable identity management systems is on demand. Traditional methods of identity verification frequently fall short of addressing the issues raised by fraud, identity theft, and data breaches. This chapter proposes a novel solution with Secure Digital Identity Cards (SDICs), which combine blockchain technology and digital twins. SDICs improve the security, privacy, and efficiency of identity management by leveraging block chain inherent security and immutability, as well as the concept of digital twins. This chapter also r looks at the architecture, key components, benefits, challenges, and potential applications of SDICs, laying the groundwork for future research and development in this promising field. So we developed an Secure Digital Identity Cards with blockchain and digital twins technology.
Early Detection of Birth Defects Using Machine Learning
Authors: Mahalle Parikshit N. , Mahajan Rupali Atul , Takale Dattatray G.
Published: July 2024

Finding birth flaws early is important for getting help right away. Machine learning (ML) methods promise recognition processes more accurate and faster. Convolutional neural networks (CNNs) and gradient boosting machines (GBMs) are used to find complicated patterns that could point to early birth problems. A variety of datasets like fetal ultrasound pictures, genetic data, mother health records, and demographic data are used in this study. The ML models are taught on labelled data, which includes accurate diagnoses of birth defects, and they are checked for accuracy using strict cross-validation methods. The proposed method is not only focused on getting at classifying things, but also on figuring out learning of biological processes that cause birth problems. The easy-to-use interface can be designed for healthcare professionals. Initial results show that the proposed method can correctly find neural tube defects and fetal heart and chromosomal abnormalities. This gives healthcare workers the ability to offer quick guidance and assistance to pregnant parents.
AI at the Womb's Edge
Authors: Shobarani R. , Dhivya P. , Radha D. , Kavitha R. , K. Surya Prakhash , Suganthi T.
Published: July 2024

Fetal monitoring is a critical aspect of prenatal care, aimed at assessing the well-being of the fetus during pregnancy and labor. Traditional fetal monitoring techniques, such as cardiotocography (CTG) and ultrasound, have been instrumental in reducing perinatal morbidity and mortality. However, these methods have limitations in accuracy, reliability, and interpretation. In recent years, the integration of artificial intelligence (AI) technologies into fetal monitoring systems has shown promising results in enhancing diagnostic accuracy and improving patient outcomes. This chapter provides a comprehensive review of the advancements in AI-powered fetal monitoring techniques, including machine learning algorithms, deep learning models, and computer vision approaches. The review also discusses the challenges, opportunities, and future directions in the field of AI-powered fetal monitoring.
Digital Doulas
Authors: Satpathy Ipseeta , Nayak Arpita , Jain Vishal , Nimalathasan B.
Published: July 2024

Adopting pregnancy-specific mobile health applications has increased access to critical prenatal information and help. These apps include a variety of features for monitoring pregnancy development, tracking maternal health indicators, and accessing evidence-based diet, exercise, and delivery preparation materials. By allowing women to communicate directly with healthcare providers and delivering interactive educational information, these applications empower them to actively manage their pregnancy experience and make educated decisions about their health and well-being. Mobile health applications can help pregnant women manage their symptoms, relieve stress, and get mental healthcare. These applications promote a sense of connection and empowerment among pregnant women by offering symptom monitoring, meditation sessions, and community forums, improving their entire maternity care experience.The chapter aims to give an overview of different aspects of mobile health apps (mhealth) apps for expectant mothers.
Evolution of Generative AI in Healthcare
Authors: Thakur Nikita
Published: July 2024

AI in healthcare is not a coincidental development; rather, it is a revolutionary force that has the potential to completely alter patient experiences and medical practices. Artificial intelligence (AI) methods, and processes of natural language, especially machine learning, are progressively effective in the health profession and education. Generative AI is one of the common types of artificial intelligence that should be used for making and creating new data, such as text, images, and music. This technology could transform completely healthcare by contributing to new approaches to improve the care of the patient, develop new treatments, and diagnose diseases. Nowadays, Generative AI plays a significant part in healthcare to improve mental health, New drug discovery, personalized medicine, Improved diagnosis, More efficient surgery, and enhanced rehabilitation. Potential hazards, however, include the use of biases or inaccurate statistics for algorithms to train them, relying too heavily on generative AI lacking supervision of humans, concealment issues with patients, besides the moral ramifications of applying AI to decision-making for medical. Oversight and careful regulation are required to assurance that the generative AI's promises in neuro-interventional surgeries are appreciated while minimizing its potential perils. AI has had a huge impact on healthcare, changing the sector in a variety of ways. In the end, it has saved lives by lowering expenses and raising the standard of care. We accept that true artificial intelligence (AI) will have a big impact on healthcare services in the future. Machine learning is the prime technology forward precision medicine, which is commonly perceived as a much-needed advancement in healthcare. We trust AI will eventually become accomplished in providing that diagnosis and treatment recommendations, even still early creativities in that area have demonstrated stimulating.
Mathematical Modelling in the Analysis of Viral Diseases and Communicable Diseases
Authors: D. Saravanan , Subramanian Vaithyasubramanian , R. Delhi Babu , R. Sundararajan , C. K. Kirubhashankar , K. Vengata Krishnan
Published: July 2024

The differential equation is the most powerful platform in mathematics and is useful in engineering and science disciplines. The use of different calculus can significantly predict the world around us. Differential equations are used in various fields, such as biology, economics, physics, chemistry, and engineering. They can describe rapid growth and decay, population growth of organisms, or changes in investment returns over time. Among these models, delay models are well known for virology analysis and predicting disease transmission, which controls infection. To define four population spatial evolution: easily unaffected, untreated infections, treated infections, recovered, and to develop a strategy of factors affecting the human body delay differential equation (DDE) is used. In this paper, we review some mathematical modeling that interprets viral discrimination with the influenza virus. Examples are used to predict some solution measures to underline and apply DDE to model infectious diseases. This study provides a wide range of factors that play a role in mathematical models of epidemiology and public health policy. This study is helpful for those who are interested and help the fieldworkers to learn about it. We discuss delay models using differential equations to measure the spread of viral diseases. The disease control predictions discussed may be helpful for more projection.
Generative Intelligence
Authors: Kaur Jaspreet
Published: July 2024

Generative intelligence is changing healthcare prevention, diagnosis, and therapy. Advanced technologies like AI enable individualized care, predictive analytics, and streamlined workflows. This study examines generative intelligence's significance in medication discovery, disease prediction, and patient outcomes. To protect privacy and encourage innovation, regulation, ethics, and implementation must be addressed. Generative intelligence can transform healthcare into a predictive, preventive, and personalized system that improves global well-being.
Agile Practices for Software Development for Numerical Computing
Authors: Tamilarasan B. , Gollavilli Venkata Surya Bhavana Harish , Alagarsundaram Poovendran , Muthu BalaAnand
Published: July 2024

Software development is an extremely complex activity. It brings with it a very large number of variables. Software engineering was created to try to bring order to this activity. It initially came with the engineering bureaucracy and brought a very large diversity of documents and artifacts. Over time, the excessive amount of bureaucracy within the existing methodologies in software engineering became a burden in certain projects and there was a need to create agile techniques so that time is optimized and better applied, also bringing new ways of managing the team and developing the software. These new techniques have brought a great evolution in the exchange of experience, communication, transmission of knowledge, people's trust, customer trust. This increases the team's productivity and also increases customer satisfaction. Agile techniques have as their basic principles simplicity and easy adaptation to changes, making them very well accepted by systems development teams and gaining more and more space among them in the current scenario.
Parallel Computing Techniques
Authors: Tayyeh Alnoman Mundher , Shather Akram H. , Anaz Saja Sumiea , Jasim Firas T.
Published: July 2024

Meshless methods are numerical methods for solving partial differential equations. The connectivity relationships between the discretized nodes do not need to be explicitly established. Instead, a collection of nodes is distributed over the problem domain. This represents an advantage when it is necessary to generate a new mesh several times, as in the case of moving structures. However, this advantage has its price, as this class of methods consumes more computing time than methods such as finite element methods. Thus, for more complex problems that require “remesh” such a moving electrical machine models, this work aims to apply parallel programming techniques to accelerate the execution of computational codes that solve mathematical models of electromagnetism based on meshless methods. Programming with threads, in this case open multi-processing, was used to parallelize the most time-consuming parts of the code of an electromagnetic model of an induction machine based on the Element-Free Galerkin meshless method.
Utilizing Graphics Processing Units (GPUs) for Numerical Computations
Authors: Tayyeh Alnoman Mundher , Shather Akram H. , Hussein Husam Abdulhameed , Abdalbaqi Luma Saad
Published: July 2024

Initially designed for graphics processing, GPUs (graphics processing unit) only contained fixed rendering functions. As they are parallel processors with high computational power for arithmetic calculations, GPUs have been evolving rapidly with the inclusion of programmable pipelines. The trend is for the GPU to become a generic processor (GPGPU). Furthermore, the integration between GPU and CPU cores within a single chip also tends to become a standard among processors. GPUs are also becoming the target of massively parallel systems such as supercomputers. Today, the fastest supercomputer in the world has thousands of GPUs, which has significantly increased its performance compared to its predecessors.
Technological Convergence Unifying Threads Across Scientific Disciplines
Authors: Taneja Vijayta , Gaur Vandana , Jauhari Sonal
Published: July 2024

Scientific investigation has traditionally been split into several disciplines, each with its own methodology and areas of emphasis. This compartmentalization, while fostering deep specialization and remarkable discoveries, has also created silos that can hinder a more holistic understanding of the natural world. However, a new era of convergence is being ushered in by the swift development of technology. This phenomenon transcends the mere sharing of information between disciplines. It signifies the merging of concepts, tools, and methodologies, blurring disciplinary boundaries and leading to a more unified approach to complex problems. In this chapter, the authors delve into this exciting new era, examining concrete instances of convergence across diverse fields. While challenges exist, the potential benefits of convergence are undeniable. By embracing this new era of scientific exploration and navigating the associated challenges, numerous ways can be discussed to unlock a future brimming with groundbreaking discoveries and advancements that benefit all of humanity.
The Role of Interdisciplinary Collaboration Driving Sustainable Commercial Innovation
Authors: Tanwar Sweta
Published: July 2024

The study will demonstrate how the nexus of multiple professions may unlock commercial value and establish new ways to sustainability. With the goal to clarify best practices, obstacles, and possibilities in this crucial field, this research will draw on expert perspectives to investigate the role of interdisciplinary collaboration in fostering sustainable commercial innovation. It uses an extensive review of academic literature and empirical data to investigate the methods, benefits, and challenges of interdisciplinary collaboration in the context of sustainable commercial innovation also by drawing five cases of projects. The study helps to evaluate the impact of interdisciplinary collaboration on long-term commercial innovation, drawing on expert viewpoints from several disciplines. Analyze various case studies and empirical evidence to understand how interdisciplinary collaboration affects the development and implementation of long-term commercial breakthroughs.
Innovation Ecosystem Cultivating Environment for Sustainable Commercial Success
Authors: Pal Purnima , Thakur Harshit , Grover Veena
Published: July 2024

In today's rapidly evolving global economy, cultivating a thriving innovation ecosystem is essential for achieving sustainable commercial success. This chapter explores the fundamental elements necessary for such ecosystems, including the pivotal roles of government policies, financial institutions, entrepreneurs, academic institutions, and established businesses. There is a systematic discussion of methods for cultivating a collaborative culture, building infrastructure that supports it, guaranteeing financial availability, and encouraging talent development. The chapter also examines successful case studies, highlighting diverse approaches to innovation. Moreover, it tackles notable obstacles like regulatory barriers, financial shortfalls, cultural opposition, and the intricacies of ecosystem administration. Additionally, the chapter explains the critical role of AI in enhancing these ecosystems by enabling more efficient processes, predictive analytics, and data-driven decision-making.
Land Governance Requirements for Society 5.0
Authors: Chigbu Uchendu Eugene , Hayford Elvena
Published: July 2024

Literature alludes to Society 5.0 as the next generation of human society characterised technologically as a system of systems in which numerous systems create an extensive networked system. This chapter explores Society 5.0 beyond the futuristic but also experiential. It focuses on how a land governance system can support its functionality. The study is conceptually designed. It theoretically explores how land governance can contribute to Society 5.0 in the Industrial 5.0 age. It used a historical review of industry periods to examine the industrial transition from Industry 1.0 to 5.0 from a land governance perspective. It used artificial intelligence to produce visual depictions of Society 5.0. The key highlights of the study are that not achieving the global sustainable development goals could mean a non-human-centric Society 5.0. It produced a land governance requirement matrix that can enable the land sector functions align with Society 5.0 for sustainability, human-centricity and resilience.
Does Inflation Affect Emissions Reduction?
Authors: Nguyen Dat Duy , Huyen Mai Thanh
Published: July 2024

Inflation and sustainable development are two important factors in the economic development of most countries. This study will use empirical analysis to examine how macroeconomic variables, including the money supply (M2), economic growth rate (GRR), trade openness (TO), and inflation (INF), related to CO2 (the environment variable) in Vietnam from 1995 to 2022. The effect of detecting emitted CO2 can be considered both in the short and long term. This study uses the research analysis method of the self-healing distributed slow (ARDL) model. Several independent variations are proposed in the model, including M2 supply, economic growth rate, trade expansion rate, and issuance rate, to evaluate the influence of increasing emission waste. Research results show that the impacts are statistically significant in the short and long term. Finally, the study also offers some policy tips for Vietnam to adjust economic variables to achieve a better level of development and move towards sustainable economic development.
Application of Big Data Analysis and Cloud Computing Technology
Authors: Guo Dajun
Published: July 2024

While networks bring convenience to people, more attention must be paid to the security of the network platform. This study combines big-data technology and machine learning (ML) to investigate the application of big-data analysis and cloud-computing technology in network security. First, the data-collection technology of abnormal network behavior is introduced, and the Flume data-collection component and Kafka distributed technology are discussed. Second, the data-processing process of abnormal network behavior and the corresponding algorithm processing are analyzed. Finally, an abnormal network behavior detection model based on big data is constructed and compared with related models based on decision-tree and random-forest (RF) algorithms. The experimental results show that the big-data anomalous network behavior detection technology based on the ML framework can effectively improve the type and efficiency of anomalous network behavior detection, which is of some significance for improving the network security control capability.
Art Design of Non-Heritage Cultural and Creative Products Based on the Concept of Sustainability
Authors: Li Jing , Gao Min
Published: July 2024

With the continuous development of social economy and the gradual improvement of intangible culture protection system, the express train that integrates intangible culture into cultural and creative products to drive economic development has been on the highway. The integration of the two has become an important direction of traditional art protection and development in the industry and business of intangible cultural protection. From the perspective of sustainable development theory, this paper points out that the designers and developers of cultural and creative products need to take sustainable design as the core theory, organically combine the narrative of consumers with the intangible culture, and give full play to the social, cultural and commercial value of the current sustainable design theory in the visual design of intangible cultural and creative products. Taking the sustainability of ecological design and the sustainability of people-oriented design as the innovative ideas of visual design.
Fecal Microbial Dysbiosis Is Associated with Colorectal Cancer Risk in a Korean Population
Authors: Kim Jeongseon , Gunathilake Madhawa , Yeo Hyun Yang , Oh Jae Hwan , Kim Byung Chang , Han Nayoung , Kim Bun , Pyun Hyojin , Lim Mi Young , Nam Young-Do , Chang Hee Jin
Published: July 2024

Purpose The association between the fecal microbiota and colorectal cancer (CRC) risk has been suggested in epidemiologic studies. However, data from large-scale population-based studies are lacking.Materials and Methods In this case-control study, we recruited 283 CRC patients from the Center for Colorectal Cancer, National Cancer Center Hospital, Korea to perform 16S rRNA gene sequencing of fecal samples. A total of 283 age- and sex-matched healthy participants were selected from 890 cohort of healthy Koreans that are publicly available (PRJEB33905). The microbial dysbiosis index (MDI) was calculated based on the differentially abundant species. The association between MDI and CRC risk was observed using conditional logistic regression. Sparse Canonical Correlation Analysis was performed to integrate species data with microbial pathways obtained by PICRUSt2.Results There is a significant divergence of the microbial composition between CRC patients and controls (permutational multivariate analysis of variance p=0.001). Those who were in third tertile of the MDI showed a significantly increased risk of CRC in the total population (odds ratio [OR], 6.93; 95% confidence interval [CI], 3.98 to 12.06; p-trend < 0.001) compared to those in the lowest tertile. Similar results were found for men (OR, 6.28; 95% CI, 3.04 to 12.98; p-trend < 0.001) and women (OR, 7.39; 95% CI, 3.10 to 17.63; p-trend < 0.001). Bacteroides coprocola and Bacteroides plebeius species and 12 metabolic pathways were interrelated in healthy controls that explain 91% covariation across samples.Conclusion Dysbiosis in the fecal microbiota may be associated with an increased risk of CRC. Due to the potentially modifiable nature of the gut microbiota, our findings may have implications for CRC prevention among Koreans.
Immunoprophylaxis failure and vaccine response in infants born to mothers with chronic hepatitis B infection in Djibouti
Authors: Darar Dirir Sahal , Ahouidi Ambroise D , Drame Aboubacry , Osman Abdi Warsama , Youssouf Kayad Guelleh , Houmed Aboubakar Mohamed , Camara Makhtar , Kane Toure Coumba , Diop Ndiaye Halimatou
Published: July 2024

BACKGROUND

In endemic areas, vertical transmission of hepatitis B virus (HBV) remains a major source of the global reservoir of infected people. Eliminating mother-to-child transmission (MTCT) of HBV is at the heart of World Health Organization’s goal of reducing the incidence of HBV in children to less than 0.1% by 2030. Universal screening for hepatitis B during pregnancy and neonatal vaccination are the main preventive measures.

AIM

To evaluate the efficacy of HBV vaccination combined with one dose of immunoglobulin in children born to hepatitis B surface antigen (HBsAg)-positive mothers in Djibouti city.

METHODS

We conducted a study in a prospective cohort of HBsAg-positive pregnant women and their infants. The study ran from January 2021 to May 2022, and infants were followed up to 7 mo of age. HBV serological markers and viral load in pregnant women were measured using aVidas microparticle enzyme-linked immunosorbent assay (Biomérieux, Paris, France) and the automated Amplix platform (Biosynex, Strasbourg, France). All infants received hepatitis B immunoglobulin and were vaccinated against HBV at birth. These infants were closely monitored to assess their seroprotective response and for failure of immunoprophylaxis. Simple logistic regression was also used to identify risk factors associated with immunoprophylaxis failure and poor vaccine response. All statistical analyses were performed with version 4.0.1 of the R software.

RESULTS

Of the 50 pregnant women recruited, the median age was 31 years, ranging from 18 years to 41 years. The MTCT rate in this cohort was 4% (2/50) in HBsAg-positive women and 67% (2/3) in hepatitis B e antigen-positive women with a viral load > 200000 IU/mL. Of the 48 infants who did not fail immunoprophylaxis, 8 (16%) became poor responders (anti-HB < 100 mIU/mL) after HBV vaccination and hepatitis B immunoglobulin, while 40 (84%) infants achieved a good level of seroprotection (anti-HB > 100 mIU/mL). Factors associated with this failure of immunoprophylaxis were maternal HBV DNA levels (> 200000 IU/mL) and hepatitis B e antigen-positive status (odds ratio = 158, 95% confidence interval: 5.05-4958, P < 0.01). Birth weight < 2500 g was associated with a poor immune response to vaccination (odds ratio = 34, 95% confidence interval: 3.01-383.86, P < 0.01).

CONCLUSION

Despite a failure rate of immunoprophylaxis higher than the World Health Organization target, this study showed that the combination of immunoglobulin and HBV vaccine was effective in preventing MTCT of HBV. Therefore, further studies are needed to better understand the challenges associated with immunoprophylaxis failure in infants in Djibouti city.
Acute liver failure: A clinically severe syndrome characterized by intricate mechanisms
Authors: An Ran , Wang Jing-Lin
Published: July 2024

Acute liver failure presents as a clinical syndrome characterized by swift deterioration and significant mortality rates. Its underlying mechanisms are intricate, involving intricate interplays between various cells. Given the current scarcity of treatment options, there's a pressing need to diligently uncover the disease's core mechanisms and administer targeted therapies accordingly.
Roles of transforming growth factor-β signaling in liver disease
Authors: Wang Xiao-Ling , Yang Meng , Wang Ying
Published: July 2024

In this editorial we expand the discussion on the article by Zhang et al published in the recent issue of the World Journal of Hepatology . We focus on the diagnostic and therapeutic targets identified on the basis of the current understanding of the molecular mechanisms of liver disease. Transforming growth factor-β (TGF-β) belongs to a structurally related cytokine super family. The family members display different time- and tissue-specific expression patterns associated with autoimmunity, inflammation, fibrosis, and tumorigenesis; and, they participate in the pathogenesis of many diseases. TGF-β and its related signaling pathways have been shown to participate in the progression of liver diseases, such as injury, inflammation, fibrosis, cirrhosis, and cancer. The often studied TGF-β/Smad signaling pathway has been shown to promote or inhibit liver fibrosis under different circumstances. Similarly, the early immature TGF-β molecule functions as a tumor suppressor, inducing apoptosis; but, its interaction with the mitogenic molecule epidermal growth factor alters this effect, activating anti-apoptotic signals that promote liver cancer development. Overall, TGF-β signaling displays contradictory effects in different liver disease stages. Therefore, the use of TGF-β and related signaling pathway molecules for diagnosis and treatment of liver diseases remains a challenge and needs further study. In this editorial, we aim to review the evidence for the use of TGF-β signaling pathway molecules as diagnostic or therapeutic targets for different liver disease stages.
Chronic hepatitis B virus infection in Eastern Ethiopia: Clinical characteristics and determinants of cirrhosis
Authors: Ismael Nejib Y , Usmael Semir A , Belay Nega B , Mekonen Hailemichael Desalegn , Johannessen Asgeir , Orlien Stian MS
Published: July 2024

BACKGROUND

Chronic hepatitis B (CHB) virus infection is a major cause of liver-associated morbidity and mortality, particularly in low-income countries. A better understanding of the epidemiological, clinical, and virological characteristics of CHB will guide appropriate treatment strategies and improve the control and management of CHB in Ethiopia.

AIM

To investigate the characteristics of CHB in Eastern Ethiopia and assess the efficacy and safety of antiviral treatment.

METHODS

This cohort study included 193 adults who were human immunodeficiency virus-negative with CHB between June 2016 and December 2019. Baseline assessments included chemistry, serologic, and viral markers. χ 2 tests, Mann-Whitney U tests, and logistic regression analyses were used to identify the determinants of cirrhosis. Tenofovir disoproxil fumarate (TDF) was initiated using treatment criteria from the Ethiopian CHB pilot program.

RESULTS

A total of 132 patients (68.4%) were men, with a median age of 30 years [interquartile range (IQR): 24-38]. At enrollment, 60 (31.1%) patients had cirrhosis, of whom 35 (58.3%) had decompensated cirrhosis. Khat use, hepatitis B envelope antigen positivity, and a high viral load were independently associated with cirrhosis. Additionally, 66 patients (33.4%) fulfilled the treatment criteria and 59 (30.6%) started TDF. Among 29 patients who completed 24 months of treatment, the median aspartate aminotransferase to platelet ratio index declined from 1.54 (IQR: 0.66-2.91) to 1.10 (IQR: 0.75-2.53) (P = 0.002), and viral suppression was achieved in 80.9% and 100% of patients after 12 months and 24 months of treatment, respectively. Among the treated patients, 12 (20.3%) died within the first 6 months of treatment, of whom 8 had decompensated cirrhosis.

CONCLUSION

This study highlights the high prevalence of cirrhosis, initial mortality, and the efficacy of TDF treatment. Scaling up measures to prevent and control CHB infections in Ethiopia is crucial.
Peening Media Conditioned Carbon Steel Cut Wire Shot, Regular Hardness (45 to 52 HRC) (AWCR)
Authors:   AMS B Finishes Processes and Fluids Committee
Published: July 2024

This specification, in conjunction with the general requirements for peening media covered in AMS2431, establishes the requirements for the procurement of conditioned carbon steel cut wire shot with a hardness of 45 to 52 HRC.
Peening Media Conditioned Carbon Steel Cut Wire Shot, High Hardness (55 to 62 HRC) (AWCH)
Authors:   AMS B Finishes Processes and Fluids Committee
Published: July 2024

This specification, in conjunction with the general requirements for peening media covered in AMS2431, establishes the requirements for the procurement of conditioned carbon steel cut wire shot with a hardness of 55 to 62 HRC.
Aluminum Alloy Extrusions, 7.9Zn - 1.6Cu - 2.2Mg - 0.16Cr (7249-T76511), Solution Heat Treated, Stress-Relieved, Straightened, and Overaged
Authors:   AMS D Nonferrous Alloys Committee
Published: July 2024

This specification covers an aluminum alloy procured in the form of extruded bars, rods, wire, profiles (shapes), and tubing up to 1.499 inches (38.07 mm), inclusive, in nominal diameter or least thickness (bars, rods, wire, or profiles) or nominal wall thickness (tubing) (see 8.6).
Clinical, Demographic Characteristics and Short-Term Prognosis of Cancer Patients Presenting to the Emergency Department
Authors: Çelik Şimşek , Çelik Pelin
Published: July 2024

Aim: The aim of this study was to determine the demographic findings, clinical features, short-term mortality/ factors affecting mortality in cancer patients admitted to the emergency department.
Material and Method: This is a cross-sectional and retrospective study. This study was carried out with 204 patients with a diagnosis of cancer who presented to the emergency department. Clinical and demographic characteristics and short-term mortality status of the patients were analysed.
Results: The study was conducted with a total of 204 patients, 111 (54.4%) males and 93 (45.6%) females, with a mean age of 62.63 ± 14.16 years. Six patients presented with hematologic malignancy and 198 patients (97.1%) presented with solid malignancy. The number of patients with ≥3 comorbidities was 28 (13.7%) and the most common presenting complaint was gastrointestinal problems (26%). The most common performance score was 3 in 85 (41.7%) patients, while only 20 patients with a performance score of 4 were identified. Eighty-five (41.7%) of the patients were hospitalized. Mortality was observed in 9 patients (4.4%) in the emergency department, 22 patients (10.8%) within 1 week and 33 patients (16.2%) within 28 days. In cancer patients with a performance score of 4, the mortality rate was 75% at the end of week 1 and 90% at the end of 28 days. Multiple admissions, performance score 4, ≥3 comorbidities and metastasis were found to be significant predictors of 1-week and 28-day survival.
Conclusion: Mortality of cancer patients is high, and factors affecting mortality have been identified. These conclusions may provide significant pieces of information regarding the development of algorithms designed to determine the care needs of cancer patients in the Emergency Department.
Türk Sağlık Sisteminin Sorunlarının Hizmet Alıcı Rolündeki Sağlık Yönetimi Öğrencileri Tarafından Değerlendirilmesi
Authors: Gedikli Erman
Published: July 2024

Amaç: Bu çalışmanın amacı İstanbul’da ikamet eden ve bir vakıf üniversitesinin sağlık yönetimi bölümü öğrencilerinden oluşturulan iki farklı kohort grubunun hizmet alıcı rolü perspektifinde Türk sağlık sisteminin sorunlarını değerlendirmektir.
Gereç ve Yöntem: 2022-2023 akademik yılından 30 katılımcının yer aldığı ilk kohort ve 2023-2024 akademik yılından 32 katılımcının yer aldığı ikinci kohort çalışmaya dahil edilmiştir. Veriler Delphi tekniği kullanılarak toplanmış ve analiz edilmiştir. Bu yöntemle, öğrencilerin görüşleri sistematik bir şekilde toplanarak sağlık sisteminin mevcut durumu ve iyileştirilmesi gereken alanlar belirlenmiştir.
Bulgular: Birinci kohort grubunda maddelerin (8 madde) %30,3'ünden fazlasında; ikinci kohort grubunda ise (11 madde) %40,8’inde uzlaşma olduğu tespit edilmiştir. Birinci kohort grubunun bulgularında, randevu sürelerinin uzunluğu, sağlık çalışanlarına uygulanan şiddet, özel hastanelerdeki ücretlendirme politikalarının yanlışlığı, bilgi yönetim sistemlerinin yetersizliği; ikinci kohort grubunda ise, özel hastanelerde gereksiz tetkik talepleri, sağlık personelinin aşırı iş yükü ve alanı dışında görevlendirilmesi, sağlık okuryazarlığının düşüklüğü gibi sorunlar belirtilmiştir.
Sonuç: Bu çalışma, Türk Sağlık Sisteminde üstesinden gelinmesi için sistematik iyileştirmelere ihtiyaç duyulan önemli zorlukları ortaya koymaktadır ve bunlar gelecekteki politika ve uygulamaların şekillendirilmesi için önemli kaynaklardır.
Denuncia maliciosa y ausencia de declaratoria judicial en el nuevo procedimiento expedito para delitos de violencia contra la mujer y miembros del núcleo familiar
Authors: Dávila Tapia César Rodrigo , Flores Idrovo Luis Manuel
Published: July 2024

En 2019, se reformó el Código Orgánico Integral Penal, introduciendo un nuevo procedimiento para casos de violencia contra la mujer y miembros del núcleo familiar, con reglas específicas que generan problemas de indefensión, especialmente en su regla sexta. Esta norma impide que las denuncias presentadas por personas obligadas a hacerlo sean calificadas como maliciosas, lo que es un requisito preprocesal esencial para proteger a quienes son víctimas de denuncias falsas o simuladas. En este artículo, se utilizó un análisis cualitativo de la dogmática y la normativa ecuatoriana para examinar cómo la figura de la malicia está concebida y regulada en el Código Orgánico Integral Penal, y cómo se limita en el nuevo procedimiento para juzgar delitos de violencia contra la mujer o miembros del núcleo familiar. Se analizó a fondo esta figura y su capacidad de responder a los derechos de los perjudicados, identificando una confusión dogmática con la temeridad. Con el apoyo de expertos, se constató esta situación jurídica sui generis, concluyendo que la norma provoca indefensión debido a una regulación deficiente y falta de criterio legislativo.
Derecho de no discriminación: Análisis de la Desigualdad salarial y acceso al campo laboral por condición de género
Authors: Rivera Franco Karla Solange , Ramírez Velásquez Joanna Carolina
Published: July 2024

La discriminación laboral por sexo o género es un problema que afecta a la mayoría de los Estados donde la mujer, así como, el colectivo LGBTI son grupos históricamente excluidos, debido a pensamientos falócratas que han normalizado conductas que menoscaban el derecho a la igualdad formal y material creando ideologías preconcebidas que se transfieren de generación en generación. El presente estudio tuvo como objetivo analizar los factores que influyen en la discriminación laboral salarial y de acceso al mercado de trabajo por condición de género, para lo cual se llevó a cabo una  revisión bibliográfica, exploratoria y descriptiva de la literatura científica reportada en las bases de datos científicas y académicas como son: Dialnet, Scopus, Web of Sciences, Redalyc, ErihPlus, DOAJ, Scielo y Google Académico, así como el estudio del marco legal nacional e Instrumentos Internacionales relacionados con el problema de investigación. Además de ello, se aplicó para el análisis de los resultados el método analítico-sintético en donde se ha identificado a la segregación laboral como multifactorial. De igual forma, se pudo constatar que el régimen jurídico que precautela los derechos de las mujeres ha tenido un avance vertiginoso. Sin embargo, en la actualidad los procedimientos y políticas vigentes en Ecuador no han sido suficientes para prevenir la exclusión en los tratamientos de ascenso y elección dentro del ámbito laboral.
Estudio del régimen semiabierto y su incidencia en la rehabilitación social de la persona privada de libertad
Authors: García Román Valeria Alexandra , Monsalve Robalino Bernardo Xavier
Published: July 2024

Este artículo aborda la relevancia del régimen semiabierto en el contexto del sistema penitenciario ecuatoriano y su influencia en la reintegración social de individuos privados de libertad. tiene como objetivo analizar el impacto del régimen semiabierto en la reintegración social de individuos privados de libertad en el Centro de Rehabilitación Social-Zona 1 de Ibarra, Ecuador. La metodología empleada se basa en un enfoque descriptivo y utiliza el método analítico-sintético para evaluar el régimen semiabierto en relación con la progresividad de derechos, el sistema de rehabilitación social y los fines de la pena. Se recolectaron datos a través de entrevistas y cuestionarios. Los resultados obtenidos revelan la importancia de un enfoque individualizado en la ejecución de penas para facilitar la reintegración progresiva de los condenados a la sociedad. Se evidencia la crisis estructural y organizativa en el sistema penitenciario ecuatoriano, así como la escasez de oportunidades para acceder a beneficios educativos y tratamientos psicológicos adecuados. En conclusión, se destaca la necesidad de reformas significativas en el sistema penitenciario para mejorar la efectividad de la rehabilitación social y la reinserción de los individuos en la sociedad una vez cumplida su condena.
Innovación en la contabilización de costos de investigación y desarrollo en industrias tecnológicas del Ecuador
Authors: Saavedra Jaramillo Milena Maylen , Solís Muñoz Juan Bautista
Published: July 2024

Este estudio se centra en la gestión de costos de investigación y desarrollo (I+D) en empresas tecnológicas del Ecuador. Se empleó un enfoque mixto, analizando cómo las empresas contabilizan los costos de I+D y cómo esto influye en la toma de decisiones estratégicas. Se recopilaron datos cualitativos y cuantitativos de 26 empresas mediante encuestas y revisión documental. Los resultados revelaron que la mayoría de las empresas prefieren contabilizar los costos de I+D como gasto completo en el período actual. Además, se destacó la importancia de una contabilización precisa de los costos de I+D para mejorar la toma de decisiones estratégicas, especialmente en micro y pequeñas empresas. Las conclusiones destacan la evolución de la contabilidad de costos, su papel en la gestión de proyectos de I+D, y la necesidad de abordar desafíos específicos, como la identificación precisa de costos, para mejorar la competitividad y la sostenibilidad empresarial.