bluuebunny/crossref_metadata_2025 huggingface dataset:
Neurodiversity and Non-Verbal Norms in a World Designed for the Majority
Authors: Yin Jenny Jiaqian , Silveus Sarah
Published: December 2024

Neurodivergent people experience constant systemic oppression and discrimination that causes trauma. Our current neuro-normative society benefits those who are considered “normal” and harms those who are considered “abnormal.” Neurodivergent counselors also experience discrimination within the world of counselor education. This chapter highlights the importance of increasing neurodiversity-affirming counselor education and provides concrete strategies to do so. Actionable steps include counselor educators' self-reflection on biases, putting neurodiversity-affirming strategies into practice in the classroom, and reassessing the criteria used to evaluate counselor-in-training performance. Specific examples are demonstrated in a case study of a neurodivergent counselor-in-training providing services for a neurodivergent client. A paradigm shift to be neurodiversity-affirming in counselor education practices is crucial for promoting trauma-informed gatekeeping in the counseling world.
The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications
Authors: Das Pritam , Singh Hakam , Mishra Nilamadhab , Kumar Nagesh , Tripathy Ramamani , Nayak Rudra Kalyan , Rout Saroja Kumar
Published: December 2024

Deep learning (DL) is making a significant impact on the lives of human beings, either directly or indirectly; we benefit from Artificial Intelligence (AI), Machine Learning (ML), DL and other technologies/networks in our day-to-day lives. DL not only can mimic a human brain and carry out tasks like a human being but has also outworked the approaches of ML, making itself the most efficient technology used nowadays. Maybe this is the reason why various fields like Cybersecurity, Medical Treatments, Traffic Control, Weather Forecast, Bioinformatics, Fraud Detection, Robotics, Vocal AI, Computer Vision, Autonomous Vehicles, E-Commerce and so on are using DL techniques/algorithms rather than the traditional ML approach. This review will illuminate the History of DL, i.e. what DL is, how and why it has evolved so far, and what the various parts of DL are. Though DL is considered the most efficient, it has some limitations, and we will investigate them gradually. We will also study all pre-researched DL Techniques and their implications for contemporary real-world predictive applications.
Transitioning From Legacy Systems to AI
Authors: Raza Aamir , Malik Abdul , Maqsood Maida
Published: December 2024

Disaster detection has long been a challenge due to the complexity and dynamic nature of natural disasters. Traditional methods often lack real-time capabilities and struggle to account for these challenges. This chapter explores the transition from legacy systems to Artificial Intelligence (AI) and Machine Learning (ML) for a more holistic approach. AI and ML concepts, including supervised and unsupervised learning algorithms, can analyze vast amounts of data from various sources to identify patterns and anomalies indicative of impending disasters. The integration of plant science offers additional insights into ecosystem responses to environmental changes, further refining AI models. The chapter explores the business benefits of AI/ML in disaster detection, including cost savings, improved risk management, and enhanced resilience. It advocates for multidisciplinary collaboration among scientists, technologists, and business leaders to create a comprehensive, real-time disaster detection system.
AI and IoT Solutions for Food Security and Agriculture
Authors: Ali Aitzaz , Raza Aamir , Malik Abdul , Shabbir Muhammad , Sarwar Nimra , Muzammal Hafsa
Published: December 2024

Climate change and population growth pose significant challenges to food security and environmental sustainability, with traditional agricultural practices often struggling to adapt, resulting in inefficient resource use and negative environmental impacts.The chapter discusses the challenges of ensuring food security and environmental sustainability in a world characterized by climate change and population growth. Traditional agricultural practices often struggle to adapt, leading to inefficient resource use and negative environmental impacts. The Potential of integrating AI, IoT, and plant science for sustainable agricultural management is discussed in that chapter. AI algorithms can analyze vast data from IoT sensors, providing real-time insights and recommendations for farmers. Plant science enhances AI-driven decision-making, enhancing precision irrigation, disease prediction, and yield forecasting. However, challenges like data security, privacy, and infrastructure development need multidisciplinary integration.
Role of Multi-Agent System in Reducing Failure Probabilities in Production System
Authors: Singh Vikram , Sharma Somesh Kr.
Published: December 2024

The goal of this study is to reduce the possibility of failure and increase a manufacturing organization's performance. After a thorough analysis of the literature, 28 MAT variables. These variables were classified into six factor groups, which formed the conceptual domain. The factors and variables were prioritized using the Analytical Hierarchy Process (AHP). The structural model developed yield compelling results, indicating that the 'Manufacturing Process' is the most essential factor followed by others. For variables, AHP evolved “Process Planning Agent” most prioritized under factor 'Manufacturing Process', “Diagnosis” for factor ‘Fault Identification', “Shop Floor Monitoring” for factor ‘Control System', and so on. This indicates variables are not limited to work within their group. So, organizations must have to focus more on the factors and variables those obtained the top-ranking during implications of MAT. This study may help industrial businesses to minimize the possibility of failures, which may lead to lower costs, increased production, and improved overall efficiency.
The Impact of Deepfakes on Trust and Security in Islamic Banking
Authors: Kismawadi Early Ridho
Published: December 2024

This research presents an important contribution to the development of digital security policies in the Islamic finance sector, with a particular focus on modern technological threats such as deepfakes. Through an in-depth threat analysis, this study identifies potential risks faced by the Islamic banking industry, especially in terms of security and customer trust. The proposed recommendations include strict regulation of the creation and distribution of synthetic media, the development of more advanced detection technologies, and effective regulatory enforcement. Collaboration between governments, research institutions, and industry is also emphasized as key in designing and implementing policies that are able to respond to technological threats in an adaptive manner. With this approach, the study assists policymakers and regulators in designing strategies that can protect integrity and trust in Islamic banking, as well as ensure sustainability and security in the ever-evolving digital era.
Shaping Consumer Perception Through Deepfake Marketing
Authors: Rani Sonam , Bohara Sailaja , Gupta Gaurav , Paruthi Mandakini , Ranjan Shiv
Published: December 2024

The advent of deepfake technology has introduced transformative possibilities in marketing, reshaping consumer perceptions and engagement through hyper-realistic digital content. This book chapter examines the ethical dimensions and potential implications of deepfake applications in marketing, specifically focusing on their power to shape consumer perception. With the ability to create synthetic yet believable visual and audio representations, deepfakes have provided brands with innovative tools to captivate audiences and personalize experiences. However, this comes with ethical concerns, including risks of deception, manipulation, and consumer mistrust. This chapter explores both the opportunities and challenges posed by deepfake marketing, emphasizing the need for responsible practices to maintain transparency, authenticity, and consumer trust. It also discusses regulatory and policy considerations, proposing ethical frameworks to guide marketers in the responsible use of deepfake technology.
Collaboration and Collective Action
Authors: Subrahmanyam Satya
Published: December 2024

This chapter explores the critical role of collaboration and collective action in addressing the deepfake challenge. As deepfake technology advances, it presents unprecedented risks to businesses, individuals, and society. This chapter examines cross-sector partnerships among governments, tech companies, businesses, academia, and nonprofits to combat deepfakes effectively. It emphasizes the need for legal frameworks, innovative detection technologies, public education, and digital literacy to build resilience. Through case studies, the chapter highlights successful strategies and identifies gaps in current approaches, advocating for proactive solutions to anticipate future technological developments. Ultimately, it calls for continuous, unified efforts to create a safer, more trustworthy digital ecosystem.
Bridging E-Governance and Sustainability
Authors: Singh Hardeep , Singh Bikram Pal
Published: December 2024

This chapter is about relationship between e-Governance and sustainability, highlighting digital governance initiatives for promoting sustainable development. As governments worldwide increasingly adopt e-Governance frameworks, there is a growing recognition of their potential to drive environmental, social, and economic sustainability. The chapter explores key aspects such as enhancing transparency and accountability, optimizing resource use, and reducing carbon footprint through digital processes. It examines case studies where e-Governance practices have contributed to sustainable outcomes, and analyzes challenges such as digital divide, data security and policy integration. By integrating sustainability into e-Governance strategies, the chapter argues that governments can foster more inclusive, efficient and resilient societies, creating a pathway toward achieving global sustainability goals. Findings underscore need for a holistic approach where digital innovation and sustainable governance go hand in hand, ensuring that e-Governance serves as a catalyst for sustainable growth.
Approaches of Deep Learning Used in Cyber Security and Cyber-Crime
Authors: Shukla Ratnesh Kumar , Tiwari Arvind Kumar , Bhardwaj Shivam
Published: December 2024

Deep Learning (DL) is an area of artificial intelligence (AI), wherein machine learning (ML) using convolutional neural networks to detect patterns in data and forecast its worth. It excels in tough settings like climate change and can handle sophisticated jobs such as image and speech recognition, natural language processing, and others. Deep learning models have found applications in a variety of fields due to their ability to reflect complicated patterns in data. Deep learning applications have the capacity to analyze and automatically classify large volumes of Internet traffic. Deep learning-based solutions that automate the detection of attacks and address complicated cybersecurity issues are gaining popularity. This study extensively describes the promising uses of deep learning, which is based on many layers of artificial neural networks, in a wide range of security challenges. Before critically and comparatively reviewing state-of-the-art solutions from the literature, we will highlight the main properties of typical deep learning architectures used in cybersecurity applications. Deep learning highlights developing concepts and provides an overview of required resources, such as a general framework and appropriate datasets. The limits of the evaluated works are highlighted, as well as a vision of the present challenges in the field, providing useful insights and best practices for researchers and developers working on related problems.
Blue-Green Infrastructure for Climate Resilience
Authors: Krishnakumar Sheeja
Published: December 2024

This study aims to explore the effectiveness of climate resilience measures in mitigating climate-related adversities, with a particular focus on the role of blue-green infrastructure. It investigates how blue-green infrastructure contributes to climate resilience and assesses its success in urban development both in India and globally. The study also examines the challenges and opportunities associated with implementing blue-green infrastructure in the Indian context, identifying key barriers and enablers for its adoption. The study highlights the alignment of blue-green infrastructure with Sustainable Development Goals, particularly those related to climate action and sustainable urbanization, offering insights into how such infrastructure can support broader sustainability objectives. Through these analyses, the research provides a comprehensive understanding of the potential of blue-green infrastructure as a climate-resilient solution for urban development.
Conceptualizing Sustainable Smart Country
Authors: Younus Muhammad , Nurmandi Achmad , Mutiarin Dyah , Prianto Andi Luhur , Manaf Halimah Abdul
Published: December 2024

The Sustainable Smart Country is a concept that explores the relationship between technological infrastructure and social structures, focusing on the role of a smart social framework in achieving sustainability on a country-wide scale.This research uses a comprehensive approach, combining urban planning, information technology, and social sciences to understand the complex web of dependencies between technological advancements and the underlying social fabric. The success of a Smart Country depends on the integration of cutting-edge technologies and the astute design and cultivation of a smart social structure.The research employs a multi-disciplinary lens, drawing from case studies, data analytics, and theoretical frameworks to understand the dynamics at play. The research aims to bridge the gap between sustainability, smart technology, and social structures, contributing to the ongoing discourse on urban development and creating intelligent, sustainable nations.
Harnessing Hybrid Solar Panels for Sustainable Urban Energy Solutions Into Blue-Green Infrastructure
Authors: K. B. Bommegowda , Shivaprakasha K. S.
Published: December 2024

Urban areas face increasing challenges in meeting energy demands while promoting environmental sustainability. This chapter explores the potential of hybrid solar panels as a key component in sustainable urban energy solutions, particularly within blue-green infrastructure. Hybrid solar panels, which combine photovoltaic cells and piezoelectric sensors, offer a dual approach to capturing renewable energy, enhancing their utility in urban settings. This integration emphasises their compatibility with blue-green infrastructure elements such as green roofs, water management systems, and public green spaces. By incorporating hybrid solar panels into blue-green infrastructure, cities can develop resilient, energy-efficient environments that promote sustainability and enhance the quality of urban life. Furthermore, the chapter provides valuable insights and practical recommendations for urban planners, policymakers, and stakeholders seeking to leverage renewable energy to develop sustainable urban ecosystems.
Innovative Technology Leadership and Program Management
Authors: Pathak Sonal , Duggal Sonia , Negi Neerja
Published: December 2024

Innovative technology leadership is crucial for driving the development and implementation of AI-powered solutions in blue-green infrastructure (BGI). This chapter explores how AI and emerging technologies can enhance the management of water and green spaces to create sustainable, resilient urban environments. By integrating AI into the planning, monitoring, and optimization of BGI, cities can better manage stormwater, reduce flooding, improve biodiversity, and enhance public spaces. The role of leadership in managing cross-disciplinary teams, fostering collaboration, and ensuring the alignment of technological innovation with environmental goals is highlighted. Case studies and best practices are provided to demonstrate the successful deployment of AI-powered BGI solutions. The Chapter also addresses the challenges in scaling these technologies and the need for effective program management to ensure sustainability, community engagement, and policy alignment.
Smart Cities and Blue-Green Infrastructure
Authors: Pathak Sonal , Negi Neerja , Dadhich Priyanka
Published: December 2024

Smart cities are increasingly adopting sustainable practices to improve urban living while addressing environmental concerns. One key component of this movement is blue-green infrastructure (BGI), which integrates water management (blue) and vegetation (green) systems to enhance urban resilience, biodiversity, and sustainability. In tandem with these efforts, machine learning (ML) plays a critical role in optimizing the design, implementation, and maintenance of BGI in smart cities. ML algorithms provide the ability to process large datasets from sensors, weather forecasts, and environmental variables to create predictive models that enhance decision-making in urban planning. This paper explores the convergence of smart city initiatives, blue-green infrastructure, and machine learning, examining how advanced data-driven technologies can support sustainable urban development. Key applications include real-time monitoring of water management systems, predicting environmental impacts, optimizing resource allocation, and automating the management of green spaces. The integration of machine learning with blue-green infrastructure offers cities a transformative pathway toward more sustainable, resilient, and efficient environments.
Comments on "Da la scheggia rotta usciva insieme parole e sangue: an unusual case of bleeding and the metaphor of a clinical trial"
Authors: Vermylen Jozef
Published: December 2024

Dear Editor,
I found very interesting the special article on Pier delle Vigne...
Exploring the perceived value-behavioural intention link: An Islamic banking perspective
Authors: Roberts-Lombard Mornay , Variava Aalia , Baig Irfaan , Chavoos Rahilca
Published: December 2024

Orientation: Knowledge of the commitment behaviour (affective and calculative) of Islamic banking customers is central to an in-depth understanding of the perceived value-behavioural intention link in the competitive Islamic banking industry in South Africa.Research purpose: The study investigates the extent of the role of affective and calculative commitment on the perceived value-behavioural intention link within the Islamic banking industry of South Africa.Motivation for the study: To date, there is, however, no clear pathway in a Business-to-Consumer (B2C) setting, and further research is needed on how to strengthen this link.Research approach/design and method: A quantitative exploratory-descriptive research design was used to collect data from 350 Islamic banking customers in the Gauteng province of South Africa purposively through the use of self-administered questionnaires. Exploratory factor analysis, Pearson’s coefficient analysis and multiple regression analysis were applied to measure the proposed hypotheses developed for the study.Main findings: Service quality has a significant and positive impact on perceived value, while the latter has a favourable and considerable impact on affective and calculative commitment. In addition, calculative commitment has a beneficial impact on behavioural intention.Practical/managerial implications: The research informs Islamic banks of the importance of service engagement as a driver of perceived value, which stimulates the future affective and calculative commitment of Islamic bank customers in an emerging market context.Contribution/value-add: This study provides an enhanced understanding of the relevance of selected factors (service quality and calculative commitment) in strengthening the perceived value-behavioural intention link.
Protecting Her Health: A Position Paper on Breast and Cervical Cancer
Authors: Chitra Tomy , Menon Vishnu B , Haseena K. P. , Sarah Joy , Gauravi Mishra , Catherine Sauvaget , Satheeshan B. , Nina Linder , Francis Paul T.
Published: December 2024

Breast cancer and cervical cancer are the two most prevalent cancers in women that screening programs can identify early. This study explores the epidemiology and screening of breast cancer, and cervical cancer from an Indian perspective, human papillomavirus (HPV) screening and artificial intelligence (AI) in cervical cancer screening, as discussed in the “Protecting her Health” session of the 6th Amrita International Public Health Conference. The conference was organized by the Department of Community Medicine, Public Health and Oncology, Amrita Institute of Medical Sciences, Kochi, Kerala, India, in collaboration with iTMO University and the Eurasian Federation of Oncology on December 1, 2023 and December 2, 2023 with the theme “Advancing Public Health Strategies for Cancer Control.” The following conclusions were suggested during discussions under the subtheme “Protecting her Health”:

Even though mammography (MAM) is recommended by the World Health Organization (WHO) for screening breast cancer, clinical breast examination is a reasonable strategy in low- and middle-income countries with the lack of MAM-based screening.

There should be a robust commitment from the Government to implement the WHO’s 90-70-90 elimination strategy into practice to eradicate cervical cancer. Scientific evidence from India reported the effectiveness of screening for cervical cancer through Visual Inspection with Acetic acid or HPV test.

Adding HPV vaccination into the immunization program along with the screening activities can eradicate cervical cancer in the long run.

With the least infrastructure, AI may be used to screen for cervical cancer in environments with limited resources.
Evaluation of the antibacterial activity of some plant essential oils against Ralstonia solanacearum and the molecular diagnosis of the bacterium
Authors: Mikhail Maurice S. , Abd-Alim Ahmed I. , Balabel Naglaa M. , Abbas Ahmed M.
Published: December 2024

Background

Evaluation of the antibacterial activity of some essential oils for controlling potato bacterial wilt.

Objective

In vitro and planta trials, five essential oils, lemongrass, eucalyptus, thyme, ginger, and peppermint, were evaluated for their aptitude to impede the progress of Ralstonia solanacearum.

Materials and methods

Five essential oils were assessed for their activity to inhibit R. solanacearum growth using the disc diffusion method. Certain volumes of each tested plant essential oil were added on filter paper discs using tetrazolium chloride agar medium, which contained the tested bacterium to obtain the proposed concentrations used to evaluate the most efficient oil for controlling potato bacterial wilt. Serological and molecular identification was also conducted.

Results and conclusion

R. solanacearum was characterized using cultural characteristics on the selective medium South Africa, “which is the most effective in suppressing the growth of contaminating microorganisms, and the highest recovery rate of the tested bacterium,” immunofluorescence antibody staining tomato bioassay test and molecular identification via real-time PCR (Taq-man) assay. In-vitro studies showed that all tested plant essential oils (lemongrass, eucalyptus, thyme, ginger, and peppermint) significantly reduced R. solanacearum progress. Eucalyptus (Eucalyptus globulus) and peppermint (Mentha piperita) essential oils were the most efficient in suppressing R. solanacearum growth, where it showed the highest mean inhibition zone, followed by thyme oil (Thymus vulgaris), lemongrass oil (Comybogen citratus), and ginger oil (Zingiber officinale), respectively. Phenotypic variances in bacterial cell construction have been noticed via a transmission electron microscope. Eucalyptus oil led to cell wall lysis, cell laceration, bubble-like structures, and degraded cellular components in bacterial cells.
Characteristics and Visual Outcome of Ocular Trauma Patients in North Bihar, India
Authors: Patel Deepak , Kumar Nishant , Shahnawaz Asif
Published: December 2024

Aim:

To describe the epidemiology and visual outcome of patients with ocular trauma in North Bihar, India.

Materials and Methods:

A prospective observational study was undertaken from October 2023 to March 2024. Data on sociodemographic features, etiology of trauma, type of ocular injury, and treatment of ocular trauma were collected as the exposure variables. The main outcome variable was best corrected visual acuity at 8 weeks following the initial visit.

Results:

A total of 212 patients (212 eyes) with ocular trauma were recruited with follow-up at 8 weeks following recruitment, the most affected age group was below 20 years (67.92%), followed by young adults of age between 21 and 30 years (22.16%). The male-to-female ratio for ocular injury was 4.3:1. Most participants had closed globe injuries (n = 182, 85.84%), with over half the population injured by blunt objects (n = 124, 58.49%). Furthermore, among the adult populations, the majority of the patients (n = 31, 44.28%) were injured during manual work, whereas, most pediatric injuries occurred while playing, (n=112, 52.83%). The incidence of monocular blindness was 13.2% at 8 weeks after the first presentation.

Conclusion:

Ocular trauma led to monocular blindness in a quarter of the study population. There is a need for preventive education on ocular injuries at both family and community levels.
Updates on Gene Therapy for Neovascular Age-related Macular Degeneration: A Review
Authors: Sharma Ashish , Kumar Nilesh
Published: December 2024

Age-related macular degeneration (AMD) remains a leading cause of irreversible vision loss worldwide, with neovascular AMD accounting for the majority of severe vision loss cases. Current treatments, primarily anti-vascular endothelial growth factor (anti-VEGF) therapies, have revolutionized AMD management but are limited by the need for frequent intravitreal injections. Gene therapy has emerged as a promising approach to address these limitations, offering the potential for long-term therapeutic effects from a single administration. This review examines the latest advancements in gene therapy for neovascular AMD, focusing on current approaches, delivery systems, and clinical progress. Anti-angiogenic strategies, including VEGF trap and anti-VEGF antibody gene therapies, are at the forefront of clinical development. Promising candidates like RGX-314 and ADVM-022 have demonstrated sustained VEGF suppression and reduced treatment burden in early-phase trials. Neuroprotective, anti-inflammatory, and complement modulation approaches are also being explored to address the multifaceted nature of AMD pathogenesis. Advancements in vector engineering, particularly with adeno-associated virus variants, have improved gene delivery efficiency and specificity. Novel administration routes, such as suprachoroidal delivery, are being investigated to optimize safety and efficacy. While early clinical data show encouraging safety profiles and potential for long-term efficacy, challenges remain, including immune responses to vectors and transgenes, and the need for precise dosing and administration techniques. As gene therapy for neovascular AMD progresses, key areas for future research include optimizing vector design for enhanced retinal penetration, developing combinatorial approaches targeting multiple disease pathways, and exploring personalized treatment strategies based on genetic risk profiles. The potential of gene therapy to provide durable therapeutic effects with a single administration holds promise for transforming AMD management, potentially improving patient outcomes and quality of life while reducing healthcare burden.
Computed tomography–guided percutaneous transthoracic core needle biopsy for the diagnosis of mediastinal masses
Authors: Kodali Sukanta , Banerjee Sourindra Nath , Deb Jaydip , Jana Pulak Kumar
Published: December 2024

Mediastinal masses encompass a wide spectrum of diseases; therefore, histopathological diagnosis is crucial for adequate surgical or medical treatments. Herein, we report six cases of mediastinal tumors that were definitively diagnosed by computed tomography (CT)-guided core needle biopsy. Case 1: A 35-year-old woman was found to have an anterior mediastinal mass on both a chest X-ray and a CT thorax. A CT-guided core needle biopsy of the mediastinal mass revealed type A thymoma. The patient underwent surgery and remained well 1 year of post-surgery. Case 2: A 47-year-old man was found to have a solid and cystic mass with areas of calcifications on a CT scan. A CT-guided core needle biopsy of the mediastinal mass revealed an immature teratoma. The patient is now under chemotherapy. Case 3: An 18-year-old boy was found to have a tumor in the anterior mediastinum on both a chest x-ray and CT scan. A CT-guided core needle biopsy of the mediastinal mass revealed a yolk sac tumor. The patient received only two cycles of chemotherapy and died. Case 4: A 26-year-old man was found to have a left anterior mediastinal mass with internal necrosis and calcification on a CT scan. A CT-guided core needle biopsy of the mediastinal mass revealed a malignant germ cell tumor. The patient is now under chemotherapy. Case 5: A 17-year-old boy was found to have an anterior mediastinal mass on both a chest X-ray and a CT scan. A CT-guided core needle biopsy of the mediastinal mass showed non-Hodgkin lymphoma. The patient received chemotherapy and remained well 6 months after the treatment. Case 6: An 8-year-old child was found to have an anterior mediastinal mass on a chest C-ray and a CT scan. A CT-guided core needle biopsy of the mediastinal mass revealed neuroblastoma. After six courses of chemotherapy the patient passed away. Percutaneous CT-guided core needle biopsy of mediastinal mass lesions is a safe, accurate, and cost-effective procedure.
Intervention package on stress management: Improving comprehensive well-being among nurses
Authors: Phuke Manda Jaywant , Zagade Tukaram , Mohite Vaishali Rajsinh , Salunkhe Jyoti , Ingale Swati , Choudhari Samir Kasam
Published: December 2024

Objective:

The main objective of this study is to investigate the effectiveness of the stress management intervention package in improving stress-related burnout.

Materials and Methods:

An experimental study was done on 300 nurses selected by a nonprobability convenience sampling technique and a quasi-experimental one-group pre- and posttest research design was utilized. Modified expanded nurses stress scale and self-structured three-point Likert scale on the challenges that nurses may face following stressful life events utilized to collect information. The nurses signed up for six interactive sessions on various stress-coping methods by utilizing a variety of teaching strategies such as lecture cum discussion, video slides, group work, and direct interaction with the experts to explore stress-related issues.

Results:

Continuous stress affects both the body and the mind, causing psychosomatic symptoms. Data found that 2% to 10% of nurses frequently suffered with physical symptoms such as exhaustion, backache, acidity, headache, shoulder stiffness, and insomnia. Following the intervention, the number of nurses who had these symptoms frequently and sometimes decreased. Previously, 10% of nurses experienced emotional symptoms frequently; however, after intervention, this figure was reduced to < 2%. The greatest proportion of nurses (18%) reported frequently worrying, while 1.3% expressed frequent worrying after intervention. Maximum (5%) of nurses had a tendency to eat too little or too much; this has been reduced to 0.3% after the intervention. The intervention package on stress management significantly improved nurses’ comprehensive well-being (P < 0.0001).

Conclusion:

An intervention package for stress management was helpful in lowering physical, emotional, psychological, and behavioral stress-related symptoms among nurses.
Examining the impact of Buerger-Allen exercises on alleviating muscle cramps in extubated patients
Authors: Rashmita Sahoo , Mamata Swain , Pravati Tripathy
Published: December 2024

Objective:

This study aimed to evaluate the effectiveness of Buerger-Allen exercise (BAE) in reducing muscle cramps among recently extubated patients in the intensive care unit (ICU).

Materials and Methods:

A quantitative, quasi-experimental design was employed, involving 92 recently extubated ICU patients randomly assigned to either an experimental or control group. The experimental group underwent BAE, a three-step intervention targeting lower extremity circulation and muscle cramp reduction. The exercises included the elevation of lower extremities, foot and leg exercises, and a rest and recovery phase, administered twice daily for 10 days. The control group received standard nursing care without any specific exercise regimen. Muscle cramp severity was assessed using the modified Penn Spasm Frequency Scale before and after the intervention.

Results:

The experimental group showed a significant reduction in muscle cramp severity score postintervention, with the mean scores decreasing from 6.83 ± 1.66 to 4.22 ± 1.45 (t = 10.21, P = 0.001). The control group experienced a smaller reduction, with scores decreasing from 6.98 ± 1.57 to 6.43 ± 1.37 (t = 2.810, P = 0.007). Between-group analysis confirmed a significant difference postintervention, with the experimental group improving more (t = 8.242, P = 0.001). The Mann–Whitney U test also highlighted a significant difference between groups after the intervention (U = 494.5, P = 0.001), validating the effectiveness of BAE.

Conclusion:

BAE significantly reduces muscle cramp severity in recently extubated ICU patients, suggesting that this nonpharmacological intervention can effectively improve patient outcomes and aid in postextubation recovery.
Aortic Aneurysm: Dissection from the Root to Pelvis
Authors: Jhang Lan-Sin , Chao An-Shine , Chien Chih-Wei
Published: December 2024

Isolated pelvic pain caused by aortic dissection is a very uncommon clinical presentation. This life-threatening cardiovascular lesion needs prompt diagnosis and intervention to prevent rupture. We report the case of a 45-year-old woman with Marfan syndrome who presented to our gynecologic clinic with low abdominal pain. Bedside point-of-care ultrasound revealed the bilocular echo lucent cystic lesion indicating the dissection of common iliac artery in her pelvis.
Evaluation of referral documentation in pediatrics emergency transfers: A cross-sectional observational study
Authors: Agrawal Nitika , Kumar Rakesh , Pandey Savita , Gupta Alpa , Das Kunal , Simalti Ashish
Published: December 2024

Background:

Inadequate handover documentation may result in delay and adverse outcomes during continuity of care. This is much more important in interfacility transfers where improper or missing documentation of prior events from a referring point may result in a break in the continuity of care.

Subjects and Methods:

This was a cross-sectional observational study done to evaluate the quality of referral documentation available with the patients who were referred to a tertiary care center after consultation in a peripheral center between March 2024 and May 2024. A semi-structured pro forma was used to collect transfer characteristics and quality of transfer documents at the time of admission.

Results:

A total of 156 children were enrolled in the study. The mean age of children was 6.81 ± 5.79 years. 68 (43.6%) were referred from a private nursing home. Healthcare workers accompanied only 19 (12.2%) children. Referral documentation was available in 121 (77.6%). 96/121 (61.5%) had handwritten referral papers. Pretransport communication was received only in one patient. Patients being referred by private physicians (70.8%) and smaller hospitals (80.9%) have better documentation than medical colleges (40.9%) (P = 0.03), patients being transported in an ambulance (87.23% vs. 73.4%, P = 0.05) have higher chances of having referral documentation.

Conclusions:

There is a lack of pretransfer referral communication and quality referral documents. Pediatric referral services in the region are fragmented and nonuniform. There is a need to improve pediatric referral documentation and transfer services.
Incidence of excess oxygen use in critically ill children and its impact on clinical outcomes: A single-center, retrospective study from Pakistan
Authors: Naz Rubab , Ahmed Sahira , Irfan Muhammad , Alam Safa , Haque Anwarul
Published: December 2024

Background:

Oxygen therapy is crucial yet costly, with limited research on hyperoxemia in children, often relying on invasive PaO2 measurements. This study aims to assess the prevalence of excessive oxygen use in critically ill children using noninvasive SpO2 as a substitute for invasive arterial blood gases and explores its association to morbidity and mortality outcomes.

Subjects and Methods:

We conducted a retrospective study at the pediatric intensive care unit (PICU) of a tertiary care hospital in Pakistan between January 2022 and July 2023. Critically ill children between the age of 1 month and 15 years receiving oxygen therapy through high-flow nasal cannula (HFNC) or mechanical ventilation (MV) for over 24 h were studied. Cumulative excess oxygen exposure (CEOE) was quantified as the mean hourly FiO2 exceeding 0.21, while SpO2 was ≥95% during the first 24 h of ventilation and categorized into quartiles.

Results:

Of the 191 children, 126 (66%) were ventilated using MV, while 65 (34%) received HFNC. Common diagnoses included respiratory illnesses (48.2%), neurological disorders (18.3%), sepsis (12%), and surgical cases (10.5%). The median CEOE was 32.46 (interquartile range = 21.08–42.75). 50.3% were in higher CEOE quartiles (>32.46). No statistically significant differences were observed in multiorgan dysfunction syndrome (MODS) and mortality rates between the lower quartiles (first and second) and the higher quartiles (third and fourth).

Conclusions:

Fifty percent of the critically ill children were exposed to excess oxygen. There was no significant difference in the incidence of MODS and mortality across the lower and higher quartiles of CEOE.
Fact-checking en procesos electorales y campaña permanente. Un análisis comparado entre España y Portugal
Authors: Poch-Butler Santana Lois , Gelado-Marcos Roberto , Ventura-Salom Borja , De la Calle Velasco Guillermo
Published: December 2024

Introducción: La presente investigación propone estudiar el fact-checking desde una doble perspectiva comparada: de un lado, geográfica, con España y Portugal como marcos de análisis; y, del otro, temática, analizando patrones verificadores —y, por extensión, desinformadores— en periodos electorales y fuera de ellos. Metodología: Se propone, a tal efecto, un estudio que triangula entre el análisis estadístico y de discurso de una población de estudio compuesta por más de 2.500 verificaciones (N=2.635), y las cinco entrevistas en profundidad a verificadores de todas las agencias de fact-checking integradas en el hub IBERIFIER, que financia la Comisión Europea a través del European Digital Media Observatory (EDMO). Resultados: La política es el eje temático predominante en los contenidos verificados en España (el periodo electoral acentúa, además, esta tendencia), no así en Portugal. La tipología de desinformación verificada más frecuente es el contexto falso y tanto redes sociales (principalmente Facebook en Portugal y Twitter/X y Facebook en España) como plataformas de mensajería (WhatsApp) son los canales de donde más extraen los fact-checkers los contenidos verificados. Discusión: Se observan similitudes en los patrones discursivos (narrativas importadas, recurrencia de grupos como los inmigrantes o el colectivo LGTBI entre los sujetos pasivos de la desinformación). Conclusiones: Los procesos electorales incrementan la vulnerabilidad de los públicos a la desinformación y pueden, además, copar la actividad de las agencias de fact-checking hasta el punto de que éstas se queden sin recursos suficientes para dar cobertura a otras áreas sobre las que sí trabajarían en campaña permanente.
Impact of Time Aligned Measurement Parameters on Brake Specific Emissions
Authors: Patil Rahul Chandrakant , Rajoapdhye Sunil , Mudassir Mohammed , Mokhadkar Rahul , Phadke Abhijit Narahari , Bharambe Niraj , Dhuri Santosh
Published: December 2024

As per global emissions legislation requirements running test cycles and reporting brake specific emissions is the key requirement. Engine gaseous emissions measurement is mandatory requirement for ON Highway and OFF Highway applications for transient duty cycles during testing at test cells. To meet the stringent emission limits is one of the challenging tasks considering the nature of transient duty cycles with accurate measurement of lower emission values.

Calculating accurate results is critical since there are several factors which impacts the accuracy of calculated results especially for transient tests measurement as various engine measurement parameters are involved in calculating the brake specific emission results and time alignment of the various parameters are needed. As per latest regulatory test methods (Euro VI, BS VI, EPA), there is guidance on measuring the time lag through an experiment method and accounting the same during the results calculation, however during dynamic conditions as well as measurement equipment set up locations, the time lags will vary and influence the calculated results.

This paper focuses on understanding critical parameters which leads to variations in dynamic condition of time lag of measured emissions parameters. It also discusses through experimental observations, impact of static and dynamic time lag of measured emissions parameter on results calculations & sensitivity analysis. The paper finally summarizes the list of variables which can impact the brake specific emission results calculation and carbon balance error calculations.
Performance Evaluation of Battery Cooling System for Electric Bus Applications Using MATLAB
Authors: Suman Saurabh , Kushwah Yogendra Singh , Shukla Ankit
Published: December 2024

As the electrification of transportation continues to gain momentum, the thermal management of onboard batteries remains a critical aspect to ensure optimal performance, efficiency, and longevity. To address this challenge, a standalone cooling system with a cooling capacity has been developed, specifically tailored for electric buses. This paper presents a comprehensive analysis of the performance comparison between simulation and testing data for a standalone battery cooling system designed for electric bus applications.

The study encompasses two primary components: numerical simulation using MATLAB Simulink and experimental testing. In the experimental phase, rigorous tests were conducted in a laboratory environment to evaluate the system's cooling performance under various operating conditions. Key metrics such as cooling capacity, temperature profile, and power consumption were measured and recorded to assess the system's effectiveness. A detailed numerical simulation model was developed using MATLAB to simulate the thermal dynamics of the standalone battery cooling system. The simulation model was validated by comparing its results with the actual test data obtained from the experimental testing phase. Through this comparative analysis, the accuracy and reliability of the simulation model were assessed, and its ability to predict the system's performance was evaluated.

The results of the study indicate a high degree of correlation between the simulation and testing data, demonstrating the effectiveness of the simulation model in accurately capturing the thermal behavior of the standalone battery cooling system. The close agreement between the simulated and experimental results validates the accuracy of the simulation model and underscores its utility as a predictive tool for system design and optimization. This paper contributes to advancing the understanding of thermal management systems for electric buses and provides valuable insights into the integration of experimental testing and numerical simulation in the design and evaluation process. The findings facilitate the development of more efficient and reliable battery cooling solutions, thereby enhancing the performance and sustainability of electric bus fleets.
UWB Based Communication for Electric Vehicle Battery Management System
Authors: Dannana Arun Kumar , Subbiah Subbulakshmi Nallaperumal , Chandirasekaran Ramachandran , Beemarajan Mutharasu
Published: December 2024

The Battery Management System (BMS) plays a vital role in managing the energy present in the high voltage battery pack of electric vehicles. The wired battery management system is commonly used in automotive applications. The known difficulties with the wired battery management system includes the intricate wiring harness, wiring failures, system scalability and high implementation costs. To mitigate the above challenges, the wireless battery management system is proposed. Several wireless protocols, including BLE, Zigbee, and 2.4GHz proprietary protocol, are being examined for wireless BMS. However, there are technical difficulties with these protocols to be applied in the battery pack environment. This research paper looks at the Ultra-Wide Band (UWB) communication protocol for wireless BMS, considering UWB’s efficiency low latency and robust Radio Frequency (RF) performance. The UWB protocol is used to communicate between the Cell Supervisory Circuit (CSC) and the Battery Management Controller (BMC). The recent advancement has led this research to assess how UWB-based wireless BMS can be adapted to the Cell to Chassis / Pack / Module type of battery architectures. Among the primary challenges in the wireless BMS are the performance (range, packet loss, speed), cybersecurity due to the sophisticated environment and the different architectures implemented in the vehicle. The performance of wireless communication can be addressed by the Time-of-Flight (ToF) concept of UWB Protocol, and the security architecture of the UWB facilitates secure and high-priority communication. The RF front-end circuit’s simulated results and design considerations of UWB protocol in the wireless BMS are analyzed. The merits and limitations are summarized in this research paper.