Search Results (796)

Internet of Things (IoT) applications and services have transformed the way people interact with their environment, enhancing comfort and quality of life. Additionally, Machine Learning (ML) approaches show significant promise for detecting intrusions in IoT environments. However, the high dimensionality, class imbalance, and complexity of network traffic—combined with the dynamic nature of sensor networks—pose substantial challenges to the development of efficient and effective detection algorithms. In this study, a multi-objective metaheuristic optimization approach, referred to as MOOIDS-IoT, is integrated with ML techniques to develop an intelligent cybersecurity system for IoT environments. MOOIDS-IoT combines a Genetic Algorithm (GA)-based feature selection technique with a multi-objective Particle Swarm Optimization (PSO) algorithm. PSO optimizes convergence speed, model complexity, and classification accuracy by dynamically adjusting the weights and thresholds of the deployed classifiers. Furthermore, PSO integrates Pareto-based multi-objective optimization directly into the particle swarm framework, extending conventional swarm intelligence while preserving a diverse set of non-dominated solutions. In addition, the GA reduces training time and eliminates redundancy by identifying the most significant input characteristics. The MOOIDS-IoT framework is evaluated using two lightweight models—MOO-PSO-XGBoost and MOO-PSO-RF—across two benchmark datasets, namely the NSL-KDD and CICIoT2023 datasets. On CICIoT2023, MOO-PSO-RF obtains 91.42% accuracy, whereas MOO-PSO-XGBoost obtains 98.38% accuracy. In addition, both models perform well on NSL-KDD (MOO-PSO-RF: 99.66% accuracy, MOO-PSO-XGBoost: 98.46% accuracy). The proposed approach is particularly appropriate for IoT applications with limited resources, where scalability and model efficiency are crucial considerations. Full article

Understanding the utilization patterns of nuclear medicine (NM) services is essential for optimizing resource allocation and service provision. This study aimed to address the regional evidence gap by reporting the demand for NM services by sex and age at a public hospital in Jamaica. This was a non-experimental, retrospective study of NM scans that were completed at the University Hospital of the West Indies from 1 June 2022 to 31 May 2024. While all scans were reported in the descriptive totals, for patients with multiple scans during the study period, only the data from the first visit was used in the inferential statistical analysis. This was performed with the IBM SPSS (version 29.0) software and involved the use of chi-square goodness of fit and multinomial logistic regression. A total of 1135 NM scans for 1098 patients were completed (37 patients had more than one scan); 596 (54.3%) were female and 502 (45.7%) were male, with the ages ranging from 3 days to 94 years old. Among the female patients, there was a greater demand in the ≥60 years age group for cardiac amyloid scans (χ² = 6.40, p < 0.05), while females 18–59 years had a greater demand for thyroid scans (χ² = 7.714, p < 0.05) and bone scans (χ² = 3.904, p < 0.05). On the other hand, significantly more males in the ≥60 age group presented for cardiac amyloid (χ² = 4.167; p < 0.05) and bone scans (χ² = 145.79, p < 0.01). Males were significantly less likely to undergo a thyroid scan than females (p < 0.01, OR = 0.072, 95% CI: 0.021, 0.243) while individuals aged 18–59 years were more likely to undergo this scan than patients aged 60 or older (p = 0.02, OR = 3.565, 95% CI: 1.258, 10.104). Males were more likely to do a cardiac amyloid scan (p < 0.05, OR = 2.237, 95% CI: 1.023, 4.891) but less likely to undergo a cardiac rest/stress test than females (p = 0.02, OR = 0.307, 95% CI: 0.114, 0.828). Prolonged life expectancy and an aging population have the potential to impact NM utilization, thus requiring planning for infrastructure, equipment, work force, and supplies. Cancer-related and cardiovascular indications are a top priority at this facility; hence, age- and sex-specific analysis are useful in establishing models for policy makers with regard to the allocation of economic and human resources for the sustainability of this specialized service. Full article

This paper juxtaposes the katechontic political theology of modern sovereignty that sacrifices life in the name of its protection with a paradigm of mystical sovereignty whose purpose is to serve the power of life. Reclaiming the power and politicality not only of theology but also of an overlooked and denigrated discourse, such as mysticism, serves two purposes: it restores the true content of mystery and elucidates the political dimension of theology. Mysticism has been either unduly dismissed in secular modernity as obscurantist, or its meaning has been abused by modern sovereignty for the purpose of investing power with an air of transcendent legitimacy. The proper restoration of the meaning of mysticism may eventually help us reconstruct an alternative conception of sovereignty, one that inverses the attributes Schmitt associates with sovereign power: mastery, supreme potency, legitimate exercise of arbitrary violence. Such an alternative conception of sovereignty, as vulnerability, sacrifice, service, and potent powerlessness may then enable us to appreciate the resources mystical theology can contribute to rethinking the nature of the political and the political nature of theology. Full article

In response to the escalating climate crisis, reducing greenhouse gas emissions (GHG) has become a top priority for both the public and private sectors. The pavement industry plays a key role in this transition, offering innovative technologies that minimize environmental impacts without compromising performance. Among these, the incorporation of recycled tire rubber and warm-mix asphalt (WMA) additives represents a promising strategy to reduce energy consumption and resource depletion in road construction. This study conducts a comparative life cycle assessment (LCA) to evaluate the environmental performance of an asphalt pavement incorporating recycled rubber and a WMA additive—referred to as R-W asphalt—against a conventional hot-mix asphalt (HMA) pavement. The analysis follows the ISO 14040/44 standards, covering material production, transport, construction, and maintenance. Two service-life scenarios are considered: one assuming equivalent durability and another with a five-year extension for the R-W pavement. The results demonstrate environmental impact reductions of up to 57%, with average savings ranging from 32% to 52% across key impact categories such as climate change, land use, and resource use. These benefits are primarily attributed to lower production temperatures and extended maintenance intervals. The findings underscore the potential of R-W asphalt as a cleaner engineering solution aligned with circular economy principles and climate mitigation goals. Full article

This paper presents a case study of the Local Care Ecosystems developed by the provincial government of Gipuzkoa (Basque Country, Spain) to strengthen coordination between social services, health services, and community-based initiatives at the municipal level. The initiative seeks to personalize care, enhance service integration, and support community-based care with the overarching goal of improving the quality of life for older adults living at home. These ecosystems incorporate social, institutional, and technological innovations aimed at supporting individuals who are frail or vulnerable throughout the care cycle. At present, 18 Local Care Ecosystems are active, providing services to 1202 people over the age of 65 and 167 families. The model addresses a growing global challenge linked to population aging, which has led to increasing demand for care and support services that are often fragmented, under-resourced, and constrained by outdated regulatory frameworks. These structural issues can compromise both the quality and efficiency of care for dependent individuals. Based on the findings, the paper offers policy recommendations to support the transfer and adaptation of this model, with the aim of improving the well-being of older adults who wish to remain in their own homes. Full article

Multistage centrifugal pumps, owing to their high head characteristics, are commonly applied in domains like subsea resource exploitation and groundwater extraction. However, the wear of flow passage components caused by solid particles in the fluid severely threatens equipment lifespan and system safety. To investigate the influence of solid-liquid two-phase flow on pump performance and wear, this study conducted numerical simulations of the solid-liquid two-phase flow within multistage centrifugal pumps based on the Euler–Lagrange approach and the Tabakoff wear model. The simulation results showed good agreement with experimental data. Under the design operating condition, compared to the clear water condition, the efficiency under the solid-liquid two-phase flow condition decreased by 1.64%, and the head coefficient decreased by 0.13. As the flow rate increases, particle momentum increases, the particle Stokes number increases, inertial forces are enhanced, and the coupling effect with the fluid weakens, leading to an increased impact intensity on flow passage components. This results in a gradual increase in the wear area of the impeller front shroud, back shroud, pressure side, and the peripheral casing. Under the same flow rate condition, when particles enter the pump chamber of a subsequent stage from a preceding stage, the fluid, after being rectified by the return guide vane, exhibits a more uniform flow pattern and reduced turbulence intensity. The particle Stokes number in the subsequent stage is smaller than that in the preceding stage, weakening inertial effects and enhancing the coupling effect with the fluid. This leads to a reduced impact intensity on flow passage components, resulting in a smaller wear area of these components in the subsequent stage compared to the preceding stage. This research offers critical theoretical foundations and practical guidelines for developing wear-resistant multistage centrifugal pumps in solid-liquid two-phase flow applications, with direct implications for extending service life and optimizing hydraulic performance. Full article

This article presents the results of studies of the degradation of the structure and mechanical properties of the core materials BN-350 fast neutron and research WWR-K reactors required to justify the service life extension of early-generation power and research reactors. Extending the service life of nuclear reactors is a modern problem, since most operating reactors are early-generation reactors that have exhausted their design lifespan. The possibility of extending the service life is largely determined by the condition of the structural materials of the nuclear facility, i.e., their residual resources must ensure safe operation of the reactor. For the SAV-1 alloy, the structural material of the WWR-K reactor, studies were conducted on witness samples which were in the active zone during its operation for 56 years. It was found that yield strength and tensile strength of the irradiated SAV-1 alloy decreased by 24–48%, and relative elongation decreased by ~2% compared to the unirradiated alloy. Inside the grains and along their boundaries, there were particles of secondary phases enriched with silicon, which is typical for aged aluminum alloys. For irradiated structural steels of power reactors, studied at 350–450 C, hardening and a damping nature of creep were revealed, caused by dispersion hardening and the Hall–Petch effect. Full article

Background/Objectives: Childhood cancer leads to significant physical, cognitive, and psychosocial consequences that adversely affect the development and quality of life. Occupational Therapy (OT) has the potential to mitigate these effects. However, its integration into pediatric oncology care in Spain remains limited and underexplored. This study aims to examine the availability, characteristics, and perceived impact of OT services within pediatric oncology units across Spain and to identify key barriers to their implementation. Methods: A descriptive, cross-sectional study using a mixed-methods approach was conducted. An online questionnaire was distributed to healthcare professionals working in pediatric oncology units nationwide. Quantitative data were analyzed using descriptive statistics, Fisher’s exact test, and odds ratios with 95% confidence intervals to explore associations. Effect sizes were calculated using Cramér’s V where applicable. Qualitative responses underwent inductive thematic analysis. Results: A total of 42 hospital centers from 12 autonomous communities participated. Only 16 reported having OT services in pediatric oncology, with notable regional disparities. A significant proportion of respondents were unaware of the integration of OT in their institutions. Identified barriers included lack of resources, insufficient specialized training, and limited institutional recognition of OT. Nonetheless, professionals familiar with OT interventions reported positive outcomes, particularly in improving patients’ functional autonomy, emotional well-being, and social participation. Conclusions: OT remains insufficiently integrated into pediatric oncology care in Spain. To optimize the quality of care, it is essential to address educational, structural, and institutional challenges and promote OT as a key component of multidisciplinary teams. Full article

Smart cities use advanced infrastructure and technology to improve the quality of life for their citizens. Collaborative services in smart cities are making the smart city ecosystem more reliable. These services are required to enhance the operation of interoperable systems, such as smart transportation services that share their data with smart safety services to execute emergency response, surveillance, and criminal prevention measures. However, an important issue in this ecosystem is data security, which involves the protection of sensitive data exchange during the interoperability of heterogeneous smart services. Researchers have addressed these issues through blockchain integration and the implementation of smart contracts, where collaborative applications can enhance both the efficiency and security of the smart city ecosystem. Despite these facts, complexity is an issue in smart contracts since complex coding associated with their deployment might influence the performance and scalability of collaborative applications in interconnected systems. These challenges underscore the need to optimize smart contract code to ensure efficient and scalable solutions in the smart city ecosystem. In this article, we propose a new framework that integrates generative AI with blockchain in order to eliminate the limitations of smart contracts. We make use of models such as GPT-2, GPT-3, and GPT4, which natively can write and optimize code in an efficient manner and support multiple programming languages, including Python 3.12.x and Solidity. To validate our proposed framework, we integrate these models with already existing frameworks for collaborative smart services to optimize smart contract code, reducing resource-intensive processes while maintaining security and efficiency. Our findings demonstrate that GPT-4-based optimized smart contracts outperform other optimized and non-optimized approaches. This integration reduces smart contract execution overhead, enhances security, and improves scalability, paving the way for a more robust and efficient smart contract ecosystem in smart city applications. Full article

Background and Objectives: Estimating the need for palliative care for children is a crucial step in addressing the needs of children facing life-threatening conditions, while providing a powerful argument to combat unacceptably wide disparities in access to care. The need for palliative care for children in Romania remains insufficiently quantified. More accurate estimates are indispensable to assess the true extent of need and to support adequate policy responses. Materials and Methods: This retrospective cross-sectional study aimed to estimate the need for pediatric palliative care in Romania for 2022–2023. We analyzed secondary data obtained from the General Directorates of Social Assistance and Child Protection (DGASPC) in 41 counties and the six sectors of Bucharest. The analysis focused on life-limiting conditions as defined by the WHO Annex 3, Order no. 253/2018. Results: The study identified 14,499 pediatric cases with palliative care needs, showing a highly uneven national distribution, especially across diagnostic groups and age categories. We observed a higher number of cases in rural areas (7553) compared with urban areas (6946). Our own data do not include resource estimates; however, prior reports indicate only 50 palliative care beds for children in Romania. Conclusions: This study reveals a substantial and unevenly distributed need for pediatric palliative care in Romania, with notable disparities across age groups, diagnostic categories, and urban-rural areas. The identification of 14,499 eligible cases underscores the urgency of developing targeted policies and allocating adequate resources to ensure equitable access to specialized palliative services for all children in need. Full article

Background and aims: Rheumatic diseases are chronic, progressive conditions associated with severe pain, joint damage, disability, and even death. Healthcare interventions play a critical role in symptom management, patient education, and adherence to treatment plans. This study evaluates the role of healthcare interventions in the management of patients with rheumatic diseases, focusing on pain management, functional rehabilitation, patient education, and multidisciplinary collaboration. In addition, barriers to optimal care and potential solutions, including digital health technologies, are explored. Materials and methods: We conducted a narrative review of the scientific literature. Studies published between 2014 and 2025 were selected from PubMed, Scopus, Web of Science, Elsevier, Springer, Frontiers, and Wiley Online Library. Key areas of review included nurse-led pain management, education programs, and the impact of interdisciplinary care on patient outcomes. Results: Nursing interventions significantly improve pain control, treatment adherence, and self-management skills in patients with rheumatic diseases. Multidisciplinary approaches improve functional rehabilitation and increase quality of life in patients with rheumatic conditions. However, barriers such as insufficient health care resources, lack of patient awareness, and disparities in the availability of services hinder effective care delivery. Conclusions: A structured, multidisciplinary approach integrating healthcare interventions, digital health solutions, and patient-centered education is essential to optimize the management of rheumatic diseases. Future research should focus on improving access to non-pharmacological therapies and standardizing healthcare protocols for better patient outcomes. Full article

Introduction: Visual impairment impacts millions of people around the world, with the vast majority of problems being treatable. Disadvantaged communities are unable to utilize the same resources to treat these problems due to a lack of knowledge or resources, in addition to the presence of barriers preventing access. The objective of this paper is to assess eye health awareness and evaluate the barriers for individuals from disadvantaged communities in order to inform future interventions and increase access to care. Methods: This is a pilot study utilizing an online anonymous questionnaire designed to assess the demographics, eye health awareness, and access to eye care of community-based patients. A comprehensive literature review was also conducted using PubMed, Scopus, and Google Scholar to evaluate barriers to eye care and methods to improve community health outcomes. The primary goal was to improve understanding of eye health awareness and access in order to inform future strategies that can help in improving eye health awareness and service availability. Results: The results indicated that 61.2% of respondents believed that eye exams are very important, and only 7.7% of participants believed that regular eye exams are not important. The majority of participants (75%) agree that regular eye exams help prevent serious eye conditions and 84.5% believe that eye health can affect quality of life. 35.6% of participants reported they had their eyes checked by a healthcare professional within the last year, while 21.2% reported never having an eye exam. Although the majority of participants found access to eye care services in their community somewhat or very easy, 8.6% and 9.5% of participants found access difficult and very difficult, respectively. Even though 45.6% of participants reported not facing any barriers regarding access to eye care, the cost of services, long waiting times, and lack of nearby eye care providers were often cited as barriers from the remainder of the participants. Moving forward, local interventions such as mobile eye clinics, public health workshops, and telehealth are viable options to obtain an understanding of the community’s health status in addition to creating opportunities to educate and provide health screenings. Conclusion: The results indicate that although there is awareness of the importance of eye health for the majority of participants, there is still a sizable minority who have insufficient understanding. Barriers to healthcare such as cost, waiting times, and proximity to providers are common problems that are preventing many from seeking eye care. Future interventions should be created to increase access and literacy amongst the community through telehealth, mobile eye clinics, and public health workshops. Additional efforts should be taken by healthcare stakeholders to enhance care delivery, implement policies, and improve awareness. Full article

Healthcare cost acceleration and resource allocation issues have worsened across European health systems, where a small group of patients drives excessive healthcare spending. The prediction of high-cost utilization patterns is important for the sustainable management of healthcare and focused intervention measures. The aim of our study was to derive and validate machine learning algorithms for high-cost healthcare utilization prediction based on detailed administrative data and by comparing three algorithmic methods for the best risk stratification performance. The research analyzed extensive insurance beneficiary records which compile data from health group collective funds operated by non-life insurers across EU countries, across multiple service classes. The definition of high utilization was equivalent to the upper quintile of overall health expenditure using a moderate cost threshold. The research applied three machine learning algorithms, namely logistic regression using elastic net regularization, the random forest, and support vector machines. The models used a comprehensive set of predictor variables including demographics, policy profiles, and patterns of service utilization across multiple domains of healthcare. The performance of the models was evaluated using the standard train–test methodology and rigorous cross-validation procedures. All three models demonstrated outstanding discriminative ability by achieving area under the curve values at near-perfect levels. The random forest achieved the best test performance with exceptional metrics, closely followed by logistic regression with comparable exceptional performance. Service diversity proved to be the strongest predictor across all models, while dentistry services produced an extraordinarily high odds ratio with robust confidence intervals. The group of high utilizers comprised approximately one-fifth of the sample but demonstrated significantly higher utilization across all service classes. Machine learning algorithms are capable of classifying patients eligible for the high utilization of healthcare services with nearly perfect discriminative ability. The findings justify the application of predictive analytics for proactive case management, resource planning, and focused intervention measures across private group health insurance providers in EU countries. Full article

This paper presents a hybrid fast charging strategy for static wireless power transfer (WPT) systems that synergistically combines pulsed current and multi-stage current (MCM) modes to enable rapid yet battery-health-conscious electric vehicle (EV) charging, thereby promoting sustainable transportation. The proposed approach employs a memetic algorithm (MA) to dynamically optimize the charging parameters, achieving an optimal balance between speed and battery longevity while maintaining 90.78% system efficiency at the SAE J2954-standard 85 kHz operating frequency. A neural-network-based state of charge (SOC) estimator provides accurate real-time monitoring, complemented by MA-tuned PI control for enhanced resonance stability and adaptive pulsed current–MCM profiles for the optimal energy transfer. Simulations and experimental validation demonstrate faster charging compared to that using the conventional constant current–constant voltage (CC-CV) methods while effectively preserving the battery’s state of health (SOH)—a critical advantage that reduces the environmental impact of frequent battery replacements and minimizes the carbon footprint associated with raw material extraction and battery manufacturing. By addressing both the technical challenges of high-power WPT systems and the ecological imperative of battery preservation, this research bridges the gap between fast charging requirements and sustainable EV adoption, offering a practical solution that aligns with global decarbonization goals through optimized resource utilization and an extended battery service life. Full article

Efficient logistics and transport infrastructure are critical in contemporary urban and interurban scenarios due to their impact on economic development, environmental sustainability, and quality of life. This study explores the use of the Ant Colony Optimization (ACO) metaheuristic applied to the Vehicle Routing Problem (VRP) and the strategic positioning of service stations along major highways. Through a systematic mapping of the literature and practical application to a real-world scenario—specifically, a case study on the Bandeirantes Highway (SP348), connecting Limeira to São Paulo, Brazil—the effectiveness of ACO is demonstrated in addressing complex logistical challenges, including capacity constraints, route optimization, and resource allocation. The proposed method integrates graph theory principles, entropy concepts from information theory, and economic analyses into a unified computational model implemented using Python (version 3.12), showcasing its accessibility for educational and practical business contexts. The results highlight significant improvements in operational efficiency, cost reductions, and optimized service station placement, emphasizing the algorithm’s robustness and versatility. Ultimately, this research provides valuable insights for policymakers, engineers, and logistics managers seeking sustainable and cost-effective solutions in transport infrastructure planning and management. Full article