bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidemiología quirúrgica de la obstrucción intestinal por adherencias en el servicio de cirugía general del Complejo Hospitalario Dr. Arnulfo Arias Madrid. 2015-2020, Panamá
Authors: Rodriguez Laura , You Ale , Perurena Joaquín , Orillac Alfredo , Rodríguez Sara
Published: May 2024

Introducción: La obstrucción intestinal supone un 20% de las consultas por dolor abdominal en urgencias y hasta un 75% se deben a adherencias por cirugías previas. A pesar de las altas tasas de resolución con el tratamiento conservador, es a menudo recurrente y amerita manejo quirúrgico. Objetivo: Determinar la epidemiología quirúrgica de la obstrucción intestinal por adherencias en el servicio de cirugía general del Complejo Hospitalario Dr. Arnulfo Arias Madrid en el período 2015-2020. Metodología: Se realizó un estudio observacional descriptivo, retrospectivo, transversal mediante revisión de expedientes de pacientes con diagnóstico de obstrucción intestinal por adherencias. Resultados: El 54% de los pacientes fueron mujeres y el 46% hombres. Con mayor frecuencia en >65 años y una edad media de 72,5 años. La mayoría de los pacientes presentaban al menos un antecedente quirúrgico abdominal previo (89%). El tiempo transcurrido desde la última cirugía fue más de 10 años (53%). La respuesta al tratamiento conservador fue del 75%. De los pacientes operados, al 77% se le realizó adherenciolisis, al 13% resección y anastomosis intestinal, al 3% ostomías y al 7% otros procedimientos. La moda del tiempo de hospitalización fue de <5 días para el manejo conservador y de 5-10 días para el manejo quirúrgico. Conclusiones: Este estudio marca el inicio de una serie de proyectos, encaminados a evaluar los riesgos y resultados del tratamiento, y decidir el momento óptimo para la intervención quirúrgica, con el objetivo primordial de disminuir la morbi-mortalidad y mejorar la calidad de vida de la población.
Factores de riesgo de progresión de la enfermedad renal crónica
Authors: Guzmán-López Ailen , Varona Jeanny , Zabalía Ricardo
Published: May 2024

Introducción: la enfermedad renal crónica constituye un grave problema de salud pública mundial; en este sentido se hace necesario estar actualizado sobre los factores que influyen en la progresión de la enfermedad. Objetivos: caracterizar los factores de riesgo de progresión de la enfermedad renal crónica. Resultado: existen diversos factores que influyen en la progresión de la enfermedad renal crónica, dentro de los cuales se encuentran los no modificables (etiología de la enfermedad renal crónica, grado de función renal inicial, edad, sexo, raza, peso al nacimiento) y modificables (proteinuria, factores metabólicos, tabaquismo, obesidad, síndrome metabólico/ resistencia a la insulina, dislipidemias, anemia, empleo de sustancias nefrotóxicas). Conclusiones: se logró caracterizar un grupo de factores de riesgo que poseen gran influencia en el desarrollo de la enfermedad renal, cuya identificación temprana en los pacientes disminuirá la progresión a la enfermedad renal crónica, por lo que pueden ser utilizados como instrumentos de vigilancia clínica y epidemiológica.
Prevalencia y características de adultos quemados del Servicio de Cirugía Reconstructiva del Hospital Dr. Rafael Hernández L., Chiriquí. 2016-2018
Authors: Della Sera Lasso María Gabriella
Published: May 2024

Introducción: Las quemaduras constituyen un problema de salud pública que afecta mayormente a países en desarrollo [1,2]. En Panamá, existe una unidad de quemados para el manejo de pacientes adultos, ubicada en la ciudad capital, y no contamos con datos estadísticos sobre estas lesiones en dicha población.  Objetivos: A través de este estudio descriptivo retrospectivo, buscamos generar la primera base de datos enfocada en la prevalencia y características de pacientes adultos quemados en Panamá. Métodos: Se incluyeron 110 expedientes de adultos ingresados por el Servicio de Cirugía Reconstructiva del Hospital “Dr. Rafael Hernández L.” (HRRH) en Chiriquí, Panamá con diagnóstico de “Quemadura” durante los años 2016 y 2018, haciendo énfasis en sus datos demográficos, mes de admisión, mecanismo de lesión, grado de quemadura, porcentaje de superficie corporal total quemada (SCTQ), estancia intrahospitalaria (EIH) y abordaje quirúrgico. Resultados: Se obtuvo una prevalencia de período del 16%. 39% de casos se reportaron en el 2018. Se registró una mediana de edad de 42.5 años y una razón hombre: mujer de 1.4:1. Se identificó mayor frecuencia de admisiones en enero, seguido de marzo y julio (p=0.242). El mecanismo de lesión más consignado fue energía térmica (82.7%), el grado de quemadura más común fue IIa (64.5%). En 70% de los expedientes se matriculó un porcentaje de SCTQ menor del 10%. La mayor cantidad de casos tuvo una EIH menor a 30 días, encontrando una relación estadísticamente significativa entre porcentajes altos de SCTQ y una EIH mayor a un mes (p=<0.001). El 60% de los pacientes no recibió manejo quirúrgico. Conclusiones: Las quemaduras en adultos representan un porcentaje importante del censo manejado por el servicio de Cirugía Reconstructiva del HRRH. Su frecuencia a través de los años va en ascenso, con predominio en el grupo etario de 41-50 años y género masculino. El perfil de quemaduras más frecuente fue grado IIa con menos del 10% de SCTQ. Porcentajes más altos de SCTQ se relacionaron con EIH igual o mayores al mes. La mayoría de los pacientes fueron manejados con curaciones en sala de hospitalización.
Un panorama actualizado de la dispepsia
Authors: Oliva Rodríguez Emylys , Santos Esquivel Pamela , Muñoz Triana Isaac
Published: May 2024

La dispepsia es un conjunto de síntomas gastrointestinales superiores, como sensación de plenitud, saciedad temprana, náuseas, ardor o malestar abdominal que se presentan por un mínimo de 4 semanas. Se cree que los mecanismos subyacentes implican anomalías en la motilidad gastrointestinal, hipersensibilidad visceral, alteración del microbiota gastrointestinal, factores genéticos, factores psicológicos (estrés, ansiedad), así como factores dietéticos y ambientales. Se clasifica en dispepsia orgánica y funcional; en éstas existe asociación con la infección por Helicobacter pylori, uso crónico de medicamentos (antinflamatorios no esteroideos), consumo de tabaco y el sexo femenino.
Los criterios de Roma IV se utilizan para identificar y clasificar la dispepsia funcional en subtipos según los síntomas, serían: Síndrome de distrés posprandial que presenta plenitud posprandial molesta o saciedad posprandial 3 veces a la semana, y el Síndrome de dolor epigástrico que demuestra al menos dolor y/o ardor epigástrico al menos 1 vez a la semana.
Older Adults' Metaphorical Perceptions of Aging in Turkey
Authors: Şahan Ayşe Gülay , Kilavuz Asli
Published: May 2024

Purpose:

To determine older adults' metaphorical perceptions of the concept of aging.

Method:

Participants in this qualitative study comprised 57 older adults as determined using convenience and criterion sampling methods. Data were obtained using a personal data form and the metaphor form and analyzed with descriptive and content analysis techniques.

Results:

Fifty-seven metaphors were identified within three themes: 24 within
Mental Aspect
, 18 within
Physical Aspect
, and 15 within
Psychosocial Aspect
.

Conclusion:

The fact that most metaphors appeared within the
Mental Aspect
theme was interpreted as an indication that participants felt the effects of aging more in the mental dimension. Results of the research show that aging is perceived as experience and accumulation mentally, as inadequacy physically, and as the end or loneliness psychosocially. [
Journal of Gerontological Nursing, 50
(5), 27–34.]
Long-Term Effect of a Tablet-Based Cognitive Behavioral Group Intervention on Step Count, Fatigue, Self-Efficacy, and Quality of Life in Older Adults With Arthritis: A Pilot Study
Authors: Fiske Sarah , Choi Jeungok , Jacelon Cynthia , Martell Christopher R.
Published: May 2024

Purpose:

To evaluate the long-term effect of a tablet-based, cognitive-behavioral group intervention (Tab-G) to improve daily walking for older adults with arthritis.

Method:

Using an experimental pretest/posttest repeated measure design, long-term effects on step count, fatigue, self-efficacy, and quality of life (QOL) were investigated.

Results:

Results of repeated measures analysis of variance showed significant improvement in step counts (F[1, 37] = 4.18,
p
= 0.048), fatigue (F[1, 36] = 9.971,
p
= 0.003), self-efficacy (F[1,28] = 4.645,
p
= 0.04), and QOL (F[1, 29] = 6.147,
p
= 0.019) in the Tab-G group compared to the control group. There were significant time effects across four time points (baseline and Weeks 4, 8, and 10) in fatigue (F[3, 108] = 5.43,
p
= 0.002), self-efficacy (F[3, 84] = 5.433,
p
= 0.002), and QOL (F[3, 87] = 3.673,
p
= 0.015), but not in step counts (F[3, 111] = 0.611,
p
= 0.609).

Conclusion:

Findings demonstrate positive long-term effects on fatigue in older adults with arthritis. [
Journal of Gerontological Nursing, 50
(5), 35–42.]
Learning Through Metaphors With Adult Doctoral Students
Authors: Cosgrove Preston B.
Published: May 2024

With doctoral attrition rates at 50%, there is a need to better support and facilitate doctoral student success. Although multiple solutions are needed, addressing students' experience in the classroom is a vital component. This chapter argues that one method to do so is through the power of metaphors as an engaged pedagogical tool. The first part offers the theory and research on metaphors, teaching, and adult learning. Requiring competence and creativity from the teacher, metaphors can help facilitate effective learning because they are comprehensive ways of orientating a student's conceptual understanding around a topic. As the foundation of their research, all doctoral students complete a literature review. And the second part of the chapter presents a pedagogical illustration about how to teach argumentation, analysis, and synthesis in the literature review via an extended engaged metaphor around film popularity. This final section brings the theoretical rhetoric around metaphor and doctoral learning into tangible reality.
An Understand, Assess, Apply Instructional Approach
Authors: VanHorn Daniel R. , VanHorn Abigaile M.
Published: May 2024

As the face of higher education continues to change, instructors must develop effective strategies and innovative pedagogical techniques to engage an increasingly diverse set of learners. Specifically, instruction should provide opportunities for connection between disparate concepts as well as between disparate learners. How can teachers effectively leverage the unique qualities and experiences of non-traditional students to enhance adult learning and increase the value of the classroom experience for all students? This chapter offers instructors a unique perspective not only on the cognitive processes of non-traditional students but also research-based personality and behavioral assessments, transforming them into innovative pedagogical tools with immediate practical application. By understanding the strengths that adult learners bring to the classroom as well as the cognitive processes that support learning and skills acquisition, instructors can devise teaching strategies that enhance the learning and development of all students within their classroom.
Strengthening Learning and Quality Outcomes for Adult Learning and Teaching Through Trust and Motivation
Authors: Baran Mette L.
Published: May 2024

Higher education institutions in the United States are under constant scrutiny for failing to adequately develop many students' critical thinking, complex reasoning, and writing skills during the first two years of college. This begets the question: what can faculty do to better prepare students for future careers through developing deeper learning and increased skill sets? It is imperative that higher education institutions find renewed confidence from their public constituents. Seeking answers to these challenges, the emphasis on this chapter will be on what faculty members can do to strengthen the learning and quality outcomes of instruction by developing trusting relationships with students and enhanced student motivation.
Connecting With the Adult Learner's Worldview
Authors: Steuber Julie A. , Jones Janice Elizabeth
Published: May 2024

Today's complex and fast-moving environment places the need for higher education educators to use flexible approaches in their teaching. Teaching may appear easy; the work is highly complex with many causes impacting the learning environment both internal and external. Every human being holds a worldview, and that worldview influences how students learn and how they present themselves. Learning how to navigate a student's worldview and helping the students themselves navigate their own worldview and those around them becomes an important task for teachers.
Reaching the Military Veteran Learner
Authors: Moscardini Robert Anthony
Published: May 2024

Military veterans face several difficulties when leaving their regimented lifestyle in uniform to transition to a chaotic civilian population. Reintegration into society often requires veterans to learn new skills or return to college. Veteran students are nontraditional and at times do not fit the mold traditional student retention programs are designed to address. The author traces the evolution of student retention theory from Spady to the present, with respect to the veteran population as nontraditional students, and examines new ideas based not on what colleges are doing, but rather on what students are considering when making the decision to continue their college education.
Teaching Adult Students in the Middle East
Authors: Saleh Rami , Baran Mette L.
Published: May 2024

The practice of adult education is that adult students have a great impetus to develop life skills and improve their knowledge. The purpose of this chapter is to critically analyze adult education in the Middle East by assessing its trend, differences, and similarities with the West, instructional practices and strategies, and challenges facing lecturers in teaching adult education. The increase in the number of foreign students in US universities is attributed primarily to the quality of education offered. At the higher education level, Smail and Silvera, argue that 21st-century educators should shift from authority and control in the universities to critical thinking, creativity, and project-based learning. With the world being interconnected, higher education and teaching in the Middle East will be streamlined with Western education. As such, there is expected change in the curriculum and teaching style in MENA regions with the western education system considered to be superior.
Generative Artificial Intelligence Policy for Academic Literacy in South African Higher Education
Authors: Kruger-Roux Helena , Alberts Retha
Published: May 2024

As artificial intelligence (AI) models become widespread, South African universities need policies that balance access and uphold standards. Literature shows generative AI offers opportunities like personalised support, but risks like plagiarism require addressing. Current university guidance focuses narrowly on misconduct, not innovation. Principles proposed for policies include recognising AI's value if governed well; developing inclusive policies through participation; regular updating as AI advances rapidly; effectively communicating policies; anticipating AI's impact across teaching, learning, research, and assessment; and partnering between universities and AI companies. Case studies show involving stakeholders is vital. Comprehensive policies outlining ethical use across contexts are lacking. Guidance tends to emphasise constraints, not possibilities. However, responsible leveraging can expand access without compromising literacy development. This needs evidence-based governance upholding enduring educational values amid emerging tools.
The Impact of AI Requires Integration Across K-12 and Tertiary Learning
Authors: Wiggill Charles , Batchelor Jacqueline
Published: May 2024

This chapter explores the integration of artificial intelligence (AI) in South African K-12 education and its influence on literacy, especially as students progress to higher education. It addresses the varying levels of school development in South Africa and the challenges teachers face, including infrastructure issues and differing attitudes towards AI. Using Rogers' diffusion of innovations model, teachers are categorised into five groups, from innovators to laggards, to assess their openness to AI in education. The study emphasises the crucial role of early adopters in successfully implementing AI technologies. It suggests that by supporting innovators and early adopters, significant improvements in literacy levels in schools could be achieved, potentially elevating literacy in higher education. The chapter discusses AI's potential to transform traditional educational models and its role in literacy enhancement within South Africa's K-12 sector.
Application of ChatGPT in Doctoral Education and Programming
Authors: Long Kelly Burmeister , Adams Katherine Rose
Published: May 2024

This collaborative autoethnographic study explores the integration of AI tools in doctoral education, focusing on instructional methods, program planning, and curriculum development. Drawing on faculty experiences, strengths such as content speed and organization are identified alongside weaknesses like trustworthiness issues and limited critical thinking abilities. Implications highlight the need for quality assurance, AI literacy training, and clear policies. Recommendations include establishing guidelines, proper AI tool attribution, and continued research to understand AI's impact. The study underscores the importance of thoughtful integration of AI to maximize benefits while addressing limitations effectively.
A GenAI Ontology for Academic Literacies Teaching and Learning Practices
Authors: Eybers Oscar Oliver
Published: May 2024

In the ever-evolving higher education landscape, the integration of AI, particularly Generative AI (GenAI), is causing a profound shift. This chapter explores how GenAI is reshaping teaching, learning, and academic literacies. Academic literacies facilitators now navigate a diverse terrain, bridging traditional materials, digital resources, and AI-enhanced texts. They cultivate scholars' proficiency in GenAI tools and pioneer innovative teaching methods. This chapter introduces a GenAI ontology to support this transformative journey. It equips facilitators and students to use GenAI effectively, fostering tailored teaching methods and personalised literacies assessments. In summary, this chapter presents GenAI's potential to innovate, enhance accessibility, and elevate academic prowess in higher education.
Trends and Difficulties in Research and Applications of Renewable Energy
Authors: Das Himadri Sekhar
Published: May 2024

The chapter compiles the existing landscape of research and uses in energy from undepletable sources, highlighting arising flows and determined challenges. It explores the vital type of renewable energy sciences, stressing the increasing unification of leading fabrics, storage answers, and smart gridiron technologies. Despite notable progress, barriers to a degree intermittency, scalability, and business-related viability persevere. The chapter determines a concise survey of the developing research landscape and the complicatedness guide the extensive adoption of energy from undepletable source beginnings.
A Comprehensive Study of Machine Learning Models and Computer Vision Techniques for Renewable Energy Forecasting
Authors: Prasad G. , Raja Joe Arun
Published: May 2024

This project aims to develop a method for wind turbine blade (WTB) inspection using machine learning and computer vision that would allow early detection and diagnosis of structural faults in WTBs, aiding in condition-based maintenance in the industry. At present, the industry relies on the use of manual inspections of blades for fault detection and diagnosis. The use of drones for inspection has been proven for bridges and dams and is in the process of being implemented in the OSW industry. However, current methods of inspection require huge volumes of data and labour-intensive pre-processing. This project aims to utilise machine learning methods, to reduce human input required in the detection and diagnosis of faults in WTBs. This will consist of developing a set of novel computer vision algorithms that can achieve high accuracies of fault detection and classification from limited datasets to introduce prior knowledge into the learning process.
A Study of Computer Vision, Deep Learning, and Machine Learning Techniques for Forecasting Solar Power and Renewable Energy
Authors: Majumder Jayeeta , Acharjya Pinaki Pratim , Barman Subhabrata , Koley Santanu
Published: May 2024

Utilising renewable energy sources is becoming more popular as a way to mitigate the effects of climate change and global warming. In an effort to make renewable energy more predictable, numerous prediction techniques have been developed. The objectives of this study are best illustrated by this chapter, which aims to provide a review and analysis of machine-learning and computer vision techniques in renewable solar energy projections. In addition to machine-learning and computer vision techniques for renewable solar energy projections, this chapter also focuses on the objective to deliver an optimized academic outcome, potentially necessary for the development of new solar energy fields. This could significantly contribute to the amplified usage of solar energy, which is a sustainable and cleaner energy source.
AI Approach Towards Optimal Finding of Renewable Sources of Energy and Their Classification
Authors: Saha Pampa , Mukherjee Anshit , Mukherjee Gunjan
Published: May 2024

The smart energy domain poses substantial challenges in future research, necessitating advanced investigation into optimizing smart customizable networks using artificial intelligence (AI) and machine learning (ML). With renewable energy (RE) being pivotal for global development amid climate change, AI introduces new paradigms to reshape activities, demanding revamped energy infrastructure and RE deployment strategies. The chapter explores the adoption of AI in future smart cities research with considerable economic benefits. Moreover, in the field of environmental science and engineering (ESE), the ML's potential in revolutionizing ESE by addressing complex problems and outlining crucial components for successful ML implementation in ESE, correct model development, proper interpretation, and applicability analysis has been done. The renewable source of energy like solar and wind energy can be generated in place where they are found in plenty. The ML application of energy source tracing and the prediction of energy type with multiple models of efficiencies has been highlighted.
Anti-Poaching of Tree Monitoring and Forest Fire Detection System Using Renewable Energy
Authors: Pal Palash , Dey Dilip , Pandey Anushka , Chakraborty Monishita , Kumari Deepti , Kumari Komal , Kumari Priya
Published: May 2024

Wireless sensor networks (WSN) have emerged as an effective solution for monitoring and recording physical conditions of the environment. Forests, being an important part of the ecosystem, are prone to several challenges including forest fires and tree poaching. Uncontrolled anthropogenic activities, abnormal natural conditions, and tree smuggling are some of the factors that contribute to these problems. To address these issues, the authors propose a WSN-based system for preventing tree poaching and forest fires. The system will consist of spatially distributed sensors that will continuously monitor the physical conditions of the forest, including temperature, humidity, and presence of human activity. The data collected from these sensors will be processed in a central location to detect any abnormal changes in the environment. In case of a potential forest fire or tree poaching activity, the system will send alerts to the relevant authorities, allowing them to take timely action. By leveraging the power of WSN, the proposed system aims to prevent and monitor forest fires and tree poaching.
Biomass-Based Biohydrogen Production Metabolic Pathway, Challenge, Future Economy, and AIML Implication
Authors: Chatterjee Shamba , Das Sucheta
Published: May 2024

The urgent need for a cleaner, more sustainable energy source has been sparked by the fast-dwindling supply of fossil fuels and the catastrophic consequences of climate change. The thriving market of hydrogen as a fruitful alternative is experiencing as an important environmentally friendly industrial feedstock. There are significant techno-financial and environmental obstacles to the commercialization of hydrogen as a fuel. Microalgal biohydrogen generation has drawn increasing attention as a means of overcoming these difficulties. Different metabolic pathways can be used to make microalgal biohydrogen, but a concise explanation of the economics and technical aspects of improving microalgae-driven biohydrogen generation is highly needed. Thus, assured prolonged sustainability can be achieved by improvising economical hydrogen generation technologies through the amendment of vital trial and error factors, possible gene-level, metabolic engineering modification and AIML employment.
A Deep Dive Into Cybersecurity Risk Assessment and Countermeasures in Online Social Networks
Authors: Zineddine Abdelhadi , Belfaik Yousra , Sadqi Yassine
Published: May 2024

In the evolving realm of online social networks (OSNs), assessing cybersecurity risks and implementing effective countermeasures are crucial for practitioners. This chapter confronts this challenge, beginning with an extensive literature review that explores the range of threats, vulnerabilities, and attacks prevalent in OSNs. It differentiates between general cybersecurity risks and those unique to OSNs, with a special focus on user-side vulnerabilities. The chapter critically analyzes risk assessment and security assessment, highlighting their distinct yet interconnected roles in cybersecurity. Various risk assessment methods are evaluated for their applicability to OSNs, alongside a discussion of both technical and non-technical countermeasures for risk mitigation. Concluding with key findings and future research directions, this chapter offers a comprehensive guide for understanding and tackling the complex cybersecurity challenges in online social networks.
Strategies to Combat Cyberattacks
Authors: Letchumanan Malathi , Kamaruddin Rohaidah
Published: May 2024

Many consider the internet a safe environment for sharing information and performing online transactions. However, they are unaware of the cyberattacks that occur in the cyber environment. People are vulnerable to cyberattacks such as stealing of data and identity theft that cause financial loss and mental distress. Thus, cybersecurity that protects computer systems is considered vital to combat cyberattacks. This chapter aims to review strategies that can combat cyberattacks systematically. The results of this chapter showed an overview of the reviewed literature about authorship, geographical distribution of the studies, applied methods, types of respondents involved, types of strategies used to combat cyberattacks, and main study findings. Twenty-one studies met the authors' inclusion criteria. The findings highlighted that good governance, strategic partnership, perceived threat, coping appraisal, perceived cultural values, attitude, and technology efficacy are the strategies adopted by organisations and individuals to combat cyberattacks.
An Approach for Safe Network Image Communication Using Hybrid Cloud and Half Tensor Product Compression Perception
Authors: K. Madhura , Baa Roshan , Naaz Rohaila , Chhajer Siddth Kumar , Kant Kamal , Pramanik Sabyasachi , Gupta Ankur
Published: May 2024

Since the beginning of the digital era, there has been an increasing focus on picture security since it is a crucial medium for the transfer of information. In this regard, the study develops a hybrid cloud and half-tensor compression-aware technology network image security transmission technique. Following an introduction to the fundamentals of cryptography and its use in the encryption of images, the relevant compression perception methods are expounded upon. In order to further secure the security of network pictures during transmission, the research then suggests the half-tensor product compression perception approach and integrates this technique with the hybrid cloud idea to build a new image encryption and decryption algorithm. According to the findings, the suggested method obtains the greatest peak signal-to-noise ratio value of 31.89 and structural similarity index value of 0.97, respectively. In addition, the lowest values for the times spent on encryption and decryption are 2.128 and 0.288, respectively, indicating that these techniques need less time than others.
AI-Driven Energy Forecasting, Optimization, and Demand Side Management for Consumer Engagement
Authors: Suresh Chalumuru , Nyemeesha V. , Prasath R. , Lokeshwaran K. , Raju K. Ramachandra , Boopathi Sampath
Published: May 2024

This chapter explores the role of artificial intelligence (AI) in the energy sector, focusing on energy forecasting, optimization, and demand management. It highlights the importance of AI technologies in utilities, grid operators, and consumers. AI-driven models accurately predict energy consumption patterns and demand, and how machine learning algorithms, data analytics, and IoT devices can improve forecasting precision. AI also optimizes energy production and distribution processes, reducing costs, enhancing reliability, and promoting sustainability. It also emphasizes its role in demand side management, focusing on consumer engagement strategies and AI-driven demand response programs.
Review on Artificial Intelligence-Based Sustainable System for Autonomous Vehicles
Authors: Ganesh Sundaram Sankar , Murugan K. Bala , Rajan G. Pandiya , Muthukumar M. , Karthick Alagar
Published: May 2024

Artificial intelligence (AI) has played a pivotal role in developing autonomous vehicles and revolutionizing the automotive industry. AI is at the forefront of the autonomous vehicle revolution, with the potential to transform transportation, enhance safety, and reduce environmental impact. While there are challenges and concerns to overcome, ongoing research, technological advancements, and regulatory efforts are helping to pave the way for a future where autonomous vehicles are an integral part of our transportation landscape. The successful integration of AI in autonomous vehicles will depend on a collaborative effort between the automotive industry, regulators, and the public to ensure the safe and responsible deployment of this transformative technology.
Improved Performance of Active Suspension System Using COA Optimized FLC for Full Car With Driver Model
Authors: Fahira Haseen S. , Lakshmi P.
Published: May 2024

Suspension in a vehicle is provided primarily to improve the passenger comfort and vehicle handling for the automobiles moving under any road conditions. Because of the non-linear characteristics of the vehicle, fuzzy logic controller (FLC) fed active suspension system is proposed for a full car with driver vehicle model. This controller dynamics are optimized by meta-heuristic optimization algorithm namely big bang–big crunch (BBBC) optimization and coyote optimization algorithm (COA). The passive system dynamics are compared with controller fed and optimized controller fed system under bump and random road inputs. The passive and active model is simulated in MATLAB/Simulink environment. The results are compared based upon root mean square values of head acceleration, body acceleration, pitch acceleration, roll acceleration, and power spectrum density of head acceleration. The results indicate that implementation of COA optimized FLC is effective in improving ride quality and road handling of the vehicle.
Development of Communication Networks in Industrial Sectors to Enhance Privacy and Security in the Cyber Physical System Through Internet of Things
Authors: Jayalakshmi M. , Malarselvi G. , Ali Mohammed , Kaliappan S.
Published: May 2024

This research study focuses on the development of a communication network for industrial sectors using internet of things (IoT) technology in order to enhance privacy and security in the cyber-physical system. The increasing reliance on cyber-physical systems in industrial sectors has highlighted the need for secure and private communication networks. The proposed network utilizes advanced encryption techniques and secure communication protocols to protect sensitive data and critical infrastructure. The network architecture is designed to detect and prevent cyber-attacks in real-time and also implements secure communication protocols to prevent unauthorized access. In case of any failures, the proposed communication network has self-healing mechanisms to automatically restore normal operation. The findings of the research show that the proposed communication network is able to effectively protect against cyber-attacks and unauthorized access while maintaining the availability and integrity of the system.
Failure Rate Examination for Liability Tree-Based Analysis for Clamped Double Subsystem With DC Short Voltage Protective Functionality
Authors: Rajkamal M. D. , Mothilal T. , Shanmugapriya M. , Saravanan M.
Published: May 2024

This study presents a comprehensive failure rate examination for implantable antennas, employing a liability tree-based analysis focused on a clamped double subsystem (CDSM) equipped with DC short voltage protective functionality. The enhanced protective feature of the CDSM aims to improve the security and safety of implantable antennas used in critical applications. However, this subsystem's design necessitates the use of additional IGBTs, diodes, and capacitors compared to standard configurations, consequently increasing the complexity and potential failure rate. Given that demanding converter operation in implantable antennas can escalate the failure rate, conducting a precise reliability analysis becomes vital for the deployment of CDSM in these devices. A failure durability analysis is undertaken to address the operational characteristics of CDSM in implantable antennas. Fault Tree Analysis (FTA) is utilized to evaluate the risk with greater precision than previous methods, which mainly considered component types, quantities, and network connectivity states.
Blockchain Technology to Detect Fake Products
Authors: Farhan  , Sulaiman Rejwan Bin , Nur Abdullah Hafez
Published: May 2024

Consumer confidence, business credibility, and economic development are all negatively impacted by the prevalence of counterfeit items in circulation. The potential role of blockchain technology in finding a solution to this issue is explored in this chapter. For product authentication, it employs Ethereum, smart contracts, and QR codes to create a transparent and secure system. A permanent record of a product's origin, ownership, and authenticity can be created using the proposed method by utilising the immutability and traceability of blockchain technology. By streamlining and automating the verification process, smart contracts guarantee fast and accurate validation. Conversely, quick response (QR) codes facilitate consumers' ability to verify the authenticity of a product and acquire more information about it. This chapter details the system's design, implementation, and testing findings, demonstrating that it effectively detects counterfeit items and opens up the supply chain.
Securing the Internet of Things in Logistics
Authors: Din Syed Nizam Ud , Muzammal Syeda Mariam , Bibi Ruqia , Tayyab Muhammad , Jhanjhi Noor Zaman , Habib Muhammad
Published: May 2024

Internet of things (IoT), a network of interconnected devices capable of collecting, storing, analyzing, and transmitting data, has garnered significant attention. Its widespread adoption has transformed various industries, including healthcare, transportation, manufacturing, and agriculture, owing to its numerous benefits and innovative potential. However, the rapid expansion of IoT has raised concerns about its security, presenting unique challenges compared to traditional information technology (IT) platforms. Securing the IoT environment is particularly challenging due to inherent constraints in IoT devices, such as limited resources, as well as the diverse range of devices with varying capabilities and communication protocols. The decentralized nature of the IoT network adds complexity to ensuring its security. Consequently, employing conventional host-based security techniques like anti-virus and anti-malware software in IoT is deemed impractical and inefficient.
The Moderating Role of Technological Orientation Between the Relationship of Blockchain Technology and Supply Chain Operational Performance
Authors: Shahbaz Saeed , Iqbal Maimoona , Shabbir Shahzaib
Published: May 2024

This research proposes a model that shows the impact of blockchain technology on supply chain operational performance and has a significant influence by the help of environmental orientation as a mediator and technological orientation as a moderator. The approach used in this research is quantitative and used to support the theoretical model with the help of online survey. The results of all the items used in the questionnaire are analyzed with the SPSS methodology. The results drawn from 250 respondents present that blockchain technology influences the supply chain operational performance significantly having environmental orientation as a mediator and technological orientation as a moderator. Furthermore, the research implies that the textile manufacturing sector for Pakistan can make use of the organizations by the analysts by considering the block chain technology that are joint to obtain the affective outputs.
Intravenous Regional Anaesthesia on Comparative Effects of Fentanyl and Magnesium Sulphate as Ropivacaine Adjuvants for Upper Limb Surgeries
Authors: Mulla R. M. , Dhulkhed Vithal K. , Gandhi Soudamini , Sudaryanto Agus
Published: May 2024

An established method for managing pain during upper limb procedures is intravenous regional anaesthesia or IVRA. The adjuvants are chosen for IVRA significantly impact the duration and effectiveness of regional anaesthesia. This study was piloted to compare the effects of two adjuvants given to ropivacaine in IVRA for upper limb surgeries: magnesium sulphate and fentanyl. A cohort of sixty patients scheduled for hand surgery participated in this prospective study. Two separate groups of subjects were assigned to these subjects: Cluster RF (n = 30) received 0.2% ropivacaine mixed with fentanyl, and Cluster RM (n = 30) received 0.2% ropivacaine mixed with magnesium sulphate. The study evaluated the need for postoperative analgesia at the outset and the duration and start of sensory and motor blockage.
A Comprehensive Clinico-Epidemiological Study on Pruritic Dermatoses in the Elderly
Authors: Nagare Neha , Varsha Jamale , Deokar Neha Prahlad , Jawd Saher Mahmood
Published: May 2024

This observational study, conducted at Krishna Hospital in Karad, aimed to comprehensively explore pruritic disorders' clinical and epidemiological aspects in individuals aged 60 years and above. The primary focus was on understanding the effects of pruritus on quality of life and investigating the prevalence, distribution, and predictors of pruritic conditions in the elderly population. Executed between February 2021 and July 2022, the study included 200 participants meeting specific inclusion criteria, with ethical standards upheld through written consent. Exclusion criteria were applied to refine the study population. The research adopted a hospital-based clinical-epidemiological observational cross-sectional design within the dermatology department, providing a realistic healthcare setting. Participants underwent comprehensive systemic and cutaneous examinations, completing a locally designed questionnaire.
Geotechnical Properties of Subglacial Till at Baltic Sea Offshore Wind Farm Sites
Authors: Solhjell E. , Moellenbeck D. , Yang S. , Lakeman J. W.
Published: May 2024

Detailed geotechnical soil investigation surveys have been performed with onshore laboratory testing and interpretation to support the development of two wind farm sites, herein denoted Sites 1 and 2, in the Baltic Sea, offshore Poland. The two wind farms are planned to have about 50 wind turbines each with a total combined capacity of about 1.4 GW. Large diameter monopiles have been selected as the foundation concept with a target embedment length ranging from 25 m to 40 m.

The presence of an overconsolidated, high to ultra-high strength subglacial till layer, located at a depth of about 20 m to 40 m below seabed, is critical for the monopile foundation design. This layer presents significant challenges in terms of pile drivability, while also providing support to the monopile foundation design, both for the foundation capacity as well as the overall structural stability and integrity. The onshore laboratory testing included classification testing, static and cyclic strength testing, and testing to determine in-situ stress history and deformation properties. The interpretation included the integration of the geophysical data, geological, in-situ testing, and geotechnical laboratory testing to derive representative soil parameters for the subglacial till. X-ray scans showed signs of a complex geological process having taken place.

The subglacial till is heterogeneous, with sandy, gravelly clay alternating with homogenized deformed clay layers. It exhibits poor sorting, including intermittent sand layers and erosive contacts at various depths. Seismic reflections display varying amplitudes and facies characteristics, reflecting its intricate geological history linked to the last glaciation event. The presence of inclined layers, deformed laminations, and fractures help to confirm glaciotectonic origins. Key parameters for strength assessment are presented. The cyclic strength properties are compared to experience from literature offering insights into its cyclic loading behavior. The thorough investigation provides essential insights into the geotechnical properties of subglacial till at the two offshore wind farm sites, crucial for designing reliable monopile foundations in challenging marine environments.
CO2 SEQUESTRATION AND O2 PRODUCTION IN URBAN PARKS: THE CASE OF AN INTRODUCED SPECIES IN TROPICAL SOUTH AMERICA
Authors: Aguilar-Tello Alisson , Aponte Héctor , Alegre Julio
Published: May 2024

Urban parks make up the most significant proportion of green areas in cities and significantly help to mitigate climate change and improve the physical and mental well-being of the city inhabitants. In Latin America, one of the predominant species within the vegetation in these parks is Ficus benjamina (F. benjamina). However, this species has a questionable history due to the damage it produces to public infrastructures and its invasive non-native origin has biased its potential to provide ecosystem services. This study quantifies the capacity F. benjamina has for storing carbon (C) and producing oxygen (O2) in seven parks of one of the most affected districts of Lima, the Peruvian capital. The average C captured ranged from 2.31 ± 0.27 to 8.19 ± 1.88 t C ha-1, ranging from 8.48 ± 0.99 to 30.04 ± 6.91 t CO2 ha-1 and producing between 6.17 ± 0.72 and 21.85 ± 5.01 t O2 ha-1. These results show the benefits of these species in urban areas and should be considered for conserving these trees. Further research on ornamental plants, management policies implementation based on an ecological approach and good arboricultural practices will guarantee urban center purification in this global context.
South Africa's Labour Empire. A History of Black Migrancy to the Gold Mines
Authors: Verhoef Grietjie
Published: May 2024

No abstract available.
South Africa’s AMRITSAR: Responsibility and the significance of the Port Elizabeth shootings of 23 October 1920
Authors: Baines Gary
Published: May 2024

No abstract available.
Role of PON1 L55M Gene Polymorphism in Parkinson’s Disease among North Indian Population
Authors: Kumar Brijesh , Saluja Alvee , Juneja Abhishek , Anand Kuljeet S , Saraswathy Kallur N , Longkumer Imnameren , Dhamija Rajinder K
Published: May 2024

Background and Objectives:

The role of various genetic markers including alpha synuclein, Parkin, etc., is known in the pathogenesis of Parkinson’s disease (PD). Novel genetic markers including paraoxonase 1 (PON1) have also been linked to PD pathogenesis in recent studies. The PON1 L55M allele carriers may have defective clearance of environmental toxins and may result in increased susceptibility to PD. Hence, we studied the role of PON1 L55M polymorphism in PD among a North Indian population.

Materials and Method:

Seventy-four PD patients and 74 age- and sex-matched controls were recruited in this hospital-based case–control study. Baseline characteristics were recorded using structured questionnaire. DNA was extracted from 3–4 ml of venous blood, followed by PCR and restriction digestion. PON1 L55M genotypes were visualized as bands: LL (177 bp), LM (177, 140 bp) and MM (140,44 bp) on 3% agarose gel. Mann–Whitney U test and Chi-squared test were used for comparing two groups of skewed and categorical variables, respectively. Measures of strength of association were calculated by binary regression analysis. P value < 0.05 was considered as significant.

Results:

Parkinson’s disease patients had significantly higher exposure to pesticides (12.2%; P (organophosphate exposure) < 0.001) and well water drinking (28.4%; P = 0.006) compared to controls. Frequency distribution of LL, LM, MM genotypes was 67.5% (50/74), 28.4% (21/74), and 4.1% (3/74), respectively, for cases and 72.6% (54/74), 26% (19/74) and 1.4% (1/74), respectively, for controls. PON1 L55M genotype distribution between Parkinson’s disease cases and controls was not significant (P = 0.53). PON1 L55M polymorphism was not associated with PD after adjusting for confounders by binary regression analysis.

Conclusion:

There was no significant association between PON1 L55M polymorphism and PD. Larger population-based studies would be required from India before drawing any definite conclusions.
Case of Hallervorden–Spatz Syndrome: A Tale of Twin Sisters
Authors: Reddy Naveen , Sharma Jitender , Sharma Anmol
Published: May 2024

Hallervorden–Spatz syndrome, now known as pantothenate kinase–associated neurodegeneration (PKAN), is a rare autosomal recessive disorder that is characterized by cerebral iron deposition and leads to progressive extrapyramidal dysfunction and dementia. Most commonly seen in the first two decades of a person’s life, it is a differential for patients presenting with atypical progressive extrapyramidal disorder and cognitive impairment. It is characterized by progressive degeneration of the basal ganglia, globus pallidus, and the reticular part of the substantia nigra due to iron accumulation. The characteristic MRI brain pattern of the disease shows the eye-of-the-tiger sign. We report cases of early onset PKAN in two sisters of the same family, in which diagnosis was based on clinical features, lab parameters, and MRI imaging findings. This report aims to differentiate PKAN from other static and progressive neurological illnesses.