Search Results (564)

Improving the performance of computer networks using seamless Wi-Fi can be achieved by implementing a number of strategies and technologies. Strategies include, first of all, the optimal location of routers and access points, the use of a multi-band network or routers supporting different bands. Routers with support for beamforming technology, which directs the Wi-Fi signal directly to connected devices, allow you to improve the signal quality and data transfer speed. Increasing the performance of Wi-Fi computer networks is also provided by the use of network monitoring and management software, which allows you to monitor its performance and respond to possible problems in the network infrastructure. This is an important task, because it determines the quality and convenience of access to network resources. First of all, it allows you to achieve a high data transfer rate, which is especially important in conditions of high traffic necessary for demanding applications. Seamless Wi-Fi technologies also promote increased mobility and flexibility of users, allowing them to connect to the network in any place with a good signal without having to use wired connections. Network management becomes more efficient with automatic switching between access points and increased fault tolerance in the face of changing traffic usage scales. Quantitative results: Implementation of the Wi-Fi roaming mechanism using the IEEE 802.11 specification; Wi-Fi performance measurements obtained for various IEEE 802.11n HT20 and IEEE 802.11a client ratios; the original test environment included 50 laptops and netbooks from various manufacturers, equipped with various operating systems and wireless network adapters; seamless Wi-Fi technologies based on IEEE 802.11k, IEEE 802.11v, and IEEE 802.11r improve communication continuity during device mobility and support real-time AI-based decision making; Wi-Fi based on local communication standards (WLAN-Wireless Local Area Network). It allows data transmission speeds from 1 Mb∙s⁻¹ to 6.75 Gb∙s⁻¹. Indoors, the Wi-Fi range is 20 m, and outdoors 100 m; WiMax (Worldwide Interoperability for Microwave Access) is a built-in set of wireless broadband standards that provide a constant data rate of 1 Gb∙s⁻¹ and 100 Mb∙s⁻¹ in a cellular network; LR-WPANs (Low-Rate Wireless Personal Area Networks) are standards that are the basis for higher communication protocols, ZigBee. They offer data rates ranging from 40 kb to 250 kb∙s⁻¹. In devices with limited resources, these standards operate at 2.4 GHz at higher transmission speeds and 868/915 MHz at lower. The novelty in the article is the implementation of the Wi-Fi roaming mechanism, presentation of Wi-Fi scenarios, discussion of module generations, indication of integrated agriculture in terms of modern digitalization technologies, and characteristics of smart farming. Full article

Background: Non-group 1 pulmonary hypertension, also known as secondary pulmonary hypertension (SPH), is predominantly observed among females. However, there is a significant lack of data concerning factors associated with hospitalization among patients diagnosed with SPH. This study aims to provide clinicians with vital insights for the identification of high-risk groups and for the more effective management of contributory risk factors within the female population affected by SPH. Methods: Using the 2019 National Inpatient Sample, we identified female admissions with SPH (n = 648,190), accounting for 3.8% of the total 17,236,228 female admissions. An Artificial Neural Network (ANN) analysis was conducted to evaluate predictive factors. We randomly allocated 3,319,543 patients into training and testing datasets at a ratio of 70:30, comprising 2,323,696 (70%) for training and 995,847 (30%) for testing, to calibrate and validate the performance of the ANN algorithm. Model performance was assessed by comparing misclassification rates between training and testing sets and by the area under the receiver operating characteristic curve (AUC); only internal validation was performed. Results: Females hospitalized with SPH were generally of older age, with a median of 75 years compared to 58 years, and more frequently identified as White (67.7% versus 65.5%) or Black (20.5% versus 15.5%) relative to those without SPH. They also demonstrated a higher prevalence of most atherosclerotic cardiovascular disease (ASCVD) risk factors or their equivalents, including complicated hypertension (50.6% versus 17.8%), diabetes with chronic complications (30.6% versus 13.7%), and hyperlipidemia (50.8% versus 29.2%), as well as other comorbidities such as COPD (43.4% versus 20.2%) and CKD (43.3% versus 14.0%), and exhibited increased all-cause mortality (4.5% versus 1.8%) (p < 0.001). Our ANN model achieved an AUC of 0.823, indicating good predictive capability. The rates of incorrect predictions were comparable in both the testing and training cohorts, at 3.8% each. The factors most strongly associated with a coded SPH diagnosis included age at admission, complicated hypertension, chronic kidney disease, chronic obstructive pulmonary disease, uncomplicated hypertension, prior VTE, race, arthropathies, and AIDS. Conclusions: Our ANN model identified demographic and comorbidity factors associated with a coded SPH diagnosis among hospitalized females, with good discrimination (AUC = 0.823). Because the model classifies the presence of an existing diagnosis rather than predicting future hospitalization, and was validated only internally, external and prospective validation is required before clinical application. Once validated, these factors could support individualized, sex-specific risk stratification for high-risk female populations, consistent with the goals of personalized medicine. Full article

Background and Objectives: Functional decline is a major determinant of disability, caregiver burden, and loss of independence in behavioral variant frontotemporal dementia (bvFTD). Although bvFTD is characterized by early and rapidly progressive deterioration in everyday functioning, the multimodal contributors associated with longitudinal functional change remain insufficiently understood. The present study aimed to identify the strongest cognitive, behavioral, personality, and neuroimaging correlates of longitudinal functional deterioration in bvFTD using an integrated multimodal framework over a 12-month follow-up period. Methods: Twenty-seven patients diagnosed with bvFTD were recruited from the 2nd Neurology Clinic of the “AHEPA” University Hospital in Thessaloniki, Greece, and underwent comprehensive face-to-face neuropsychological assessment for the evaluation of a wide range of cognitive domains, alongside caregiver-based evaluations of behavioral disturbances, personality changes, and functional abilities, at baseline, 6 months, and 12 months. Brain perfusion single-photon emission computed tomography (SPECT) was acquired only at baseline, with regional cerebral blood flow (rCBF) quantified using a Brodmann area (BA)-based approach. Functional status was assessed using the Disability Assessment for Dementia (DAD) as the primary outcome, while the Frontotemporal Dementia Rating Scale (FRS) served as a secondary measure. Repeated-measures analysis of variance (ANOVA) was used to characterize longitudinal changes across cognitive, behavioral, personality, and functional domains, while linear mixed-effects (LME) models were applied to identify longitudinal correlates of functional decline and sources of inter-individual variability in functional outcomes. Results: Significant progressive decline in functional abilities was observed over the 1-year follow-up period, consistent with an aggressive and rapidly deteriorating clinical course in bvFTD. Reductions in functional performance were evident across both basic and instrumental activities of daily living, with deterioration being more pronounced in instrumental activities. Based on the final LME model, greater apathy-related (negative) behavioral symptoms, global cognitive impairment, attentional and processing speed deficits, and impaired inhibitory control were independently associated with poorer longitudinal functional outcomes (p < 0.001). At the neuroimaging level, reduced baseline perfusion in the right BA 24 within the anterior cingulate cortex was also significantly associated with greater loss of functional independence over time (p < 0.001). Conclusions: Longitudinal functional decline in bvFTD reflects the combined disruption of behavioral regulation, global cognition, executive control, and frontal–cingulate network integrity. The findings provide a preliminary foundation for future research investigating factors associated with accelerated functional decline. Further validation in larger, multicenter longitudinal cohorts is needed to determine the prognostic relevance of these factors and their potential applicability to patient stratification and individualized care planning. Full article

Developing sustainable and scalable personal thermal management textiles that simultaneously provide radiative cooling, moisture comfort, and responsible end-of-life management remains challenging. Here, we report a sustainable, scalable, and recyclable bamboo dissolving pulp-derived cellulose/SiO₂ fiber (CSF), fabricated by a wet-spinning process involving the dissolution and regeneration of cellulose and nano-SiO₂. The resultant CSF exhibits a hierarchical interface-pore structure, which enhances solar scattering (up to 94.56% in 0.4–1.0 μm) by Mie scattering of nano-SiO₂ particles and multiple scattering at micro- and nanopore-induced air/cellulose/SiO₂ interfaces. By coupling high mid-infrared emissivity of 94.8% (8–13 μm), the CSF demonstrates average daytime sub-ambient cooling of 9.5 °C under hot and humid summer conditions. More importantly, the CSF presents a multiscale water-transport network that integrates molecular water capture (–OH groups), capillary infiltration (nanoscale interfaces between nano-SiO₂ and cellulose), and liquid spreading and evaporation (interconnected microchannels between fibers), which realizes larger liquid diffusion area and water-vapor transmission rate (7.55 cm² and 175.48 g m⁻² 24 h⁻¹), compared to commercial cotton and polyester. In addition, the CSF demonstrates desirable soil-biodegradation capability, while the feasibility of closed-loop reuse is demonstrated through a single recycling cycle, supporting environmentally friendly wearable cooling textiles. The wet-spinning strategy paves the way for the construction of sustainable, scalable and recyclable fiber for thermal- and moisture-comfort textiles. Full article

Quantum computing has emerged as a powerful tool for solving complex problems in various fields. Personalized medicine, tailoring medical treatment to patients based on their genetic and health data, is one area where predictive analytics can be useful. This work explores the application of quantum algorithms for predictive analytics, specifically in the context of predicting outcomes of cardiovascular disease based on patient data. This research is focused on the quantum-based predictive models for the case study of cardiovascular disease. The models are based on Quantum Support Vector Machines, Quantum Neural Networks, and Variational Quantum Eigensolver algorithms. The software implementation is based on the Python programming language, including an integrated quantum algorithm. A dataset of cardiovascular disease from an online platform is used to train and evaluate the models. Full article

Real-time road accident prediction under dynamic climatic conditions remains a critical challenge for intelligent transportation systems, especially in peripheral and rural regions with limited communication infrastructure. This study proposes and evaluates a comprehensive five-layer cyber–physical architecture based on Federated Edge Intelligence to enable climate-aware spatiotemporal road accident prediction across the 24 provinces of Ecuador. The framework integrates low-power IoT sensing nodes equipped with TinyML capabilities (ESP32-S3), long-range LoRaWAN (Long-Range Wide-Area Network) communication networks, containerized edge–cloud orchestration via OpenNebula and K3s, a decentralized Federated Learning ecosystem using the FedAvg algorithm, and a geospatial decision intelligence backend. Leveraging a nationwide multi-source dataset spanning the 2014–2025 period with 27,620 processed records, the architecture successfully handles highly skewed historical accident profiles optimized through a Box–Cox transformation. Empirical results demonstrate that the centralized Stacking ensemble achieves the highest overall baseline performance ($R^2=0.2460,\mathrm{MAE}=0.4748$) in the Box–Cox transformed space. In the decentralized environment, the federated Gradient Boosting implementation establishes a resilient and viable accuracy trade-off ($14.51\%$ increase in MAE) while strictly maintaining localized data sovereignty and compliance with personal data protection legislation. Operationally, the edge nodes achieve a localized inference latency of only $78\mathrm{ms}$, well below the critical $200\mathrm{ms}$ safety threshold, while the global aggregation engine exhibits rapid convergence within just three communication rounds. This cyber–physical ecosystem proves that combining localized TinyML inference with federated aggregation provides a scalable, low-latency, and privacy-preserving foundation for next-generation climate-aware road safety infrastructures in connectivity-constrained environments. Full article

Hemophilia is an X-linked inherited bleeding disorder, classified as type A or type B. Therapeutic advances offer new treatment options that improve disease control and reduce associated complications, including inhibitor development and hemophilic arthropathy. This document aims to update the Mexican hemophilia consensus, reviewing current evidence on diagnosis and management, and addressing gaps in the treatment and follow-up of patients in Mexico, aligning local needs with international recommendations. A PubMed literature search covering the last five years (up to September 2025) was conducted, prioritizing consensus statements, guidelines, and systematic reviews. Using the Delphi methodology, a structured questionnaire was submitted electronically to forty-four experts. Aspects without initial agreement were discussed at an in-person meeting. Consensus was defined as at least 80% of votes in favor. Recommendations were issued across six domains: laboratory diagnosis, genetic testing, management of hemophilia A and B without and with inhibitors, adjuvant treatments, and gene therapy. The recommendations address prophylaxis with coagulation factor concentrates, non-factor therapies, immune tolerance induction, perioperative management, pain management, and eligibility criteria and follow-up protocols for gene therapy with adeno-associated viral vectors. This consensus provides updated, evidence-based recommendations adapted to the Mexican healthcare context, identifying priority areas, including timely access to non-factor therapies and gene therapy, development of a national referral network for complex cases, and inclusion of novel therapeutic agents in the institutional essential medicines list, with the aim of improving the quality of life of people with hemophilia in Mexico. Full article

Marine macroplastics (MMP) generation is rising faster than existing management capacity, posing major ecological and governance challenges, particularly in developing coastal regions. This study applied bibliometric, social network, and S-curve analyses to evaluate 4870 publications on MMP pollution indexed in Scopus SCI and SSCI databases from 2001 to 2025 to achieve a systematic research evaluation, thematic focus, and future research direction. The results demonstrate that publication outputs have increased sharply from 20 in 2001 to 905 in 2025, with increasing focus on developing and optimizing recycling methods. Leading countries, including China, the U.S.A., and the U.K., with 577, 395, and 339 publications, respectively, reflect potential research activities and international collaboration. Keyword analysis identified marine pollution (475), macroplastic (frequency = 460), recycling technologies (frequency = 435), plastic recycling (403), and rivers (frequency = 326) as dominant research themes. Rivers remain the primary pathway for transporting macroplastics to marine environments, with the 20 largest rivers contributing the majority of global inputs, while smaller rivers in rapidly industrializing regions are becoming increasingly important. Per capita MMP generation was generally higher in high-income countries, including the U.S.A., Italy, Spain, France (0.5–0.75 kg/person), while lower in China and India (0.4–0.5 kg/person). S-curve analysis shows that physical and chemical recycling technologies, particularly open loop and pyrolysis, have reached a mature stage of development, whereas biological recycling remains an emerging research area with considerable future potential. Scenario analysis further suggests that targeted intervention strategies could reduce single-use plastic from 18.3 to 0.79 MMt by 2060, achieving up to 90% mitigation. Overall, findings demonstrate the urgent need for combined monitoring, technological innovations, and policy action to control marine plastic pollution to protect the marine ecosystem. Full article

In recent years, the rapid development of wireless personal, local, and cellular networks has fundamentally changed our daily lives, allowing for ubiquitous connectivity and access to new services. This technological evolution is accompanied by changes in the exposure to radio-frequency electromagnetic fields (RF-EMFs) in urban areas, raising important questions about potential health risks. This paper presents results for the temporal variation in RF-EMF exposure in urban areas in Bulgaria. Measurements of the electric field (E-field) were performed across multiple locations, on different days of the week, and at selected time periods to capture variations related to human activity and network usage. The results reveal temporal variation in E-field values, while all measured values remain significantly below established international exposure limits. Full article

We present a review on the application of the mathematical models for research on social processes, social structures, and actors in social systems. The scope of the review is not restricted to the classical applications of mathematics such as theory of probability, statistics, stochastic processes, differential equations, and game theory. We also discuss applications of the theory of networks for social network analysis and the numerical research on dynamics of social systems. The number of these applications has increased very fast in recent years. Special attention is given to the results from the area of sociophysics, where mathematical methodology is used to analyze social systems in cooperation with the models and concepts of physics. Another special topic in his review is connected to the results from econophysics, where the mathematical methodology and theories and methods of physics are used in the studies on the dynamics of economic systems. In addition, we give several examples for the application of mathematical methods to social systems: (a) application of difference equations to model the flow of substances in channels of networks; (b) analytical solution of nonlinear equations connected to the model of waves of popularity; (c) numerical results of the waves of popularity in a model that accounts for the change in the opinion of the supporters of the ideas for positive or negative popularity of a person, material item, or a piece of information (idea, theory, ideology, etc.) In the last case, we illustrate the effectiveness of the numerical analysis to discover new effects on the studied social system. The review ends with a large list of references. These references can be used as a guide of the way of new researchers to the large field of mathematical social dynamics. Full article

The increasing use of wireless personal networks in educational institutions has created significant challenges in ensuring network security and the reliable testing of communication infrastructure. The selection of appropriate software tools for network security testing is a complex decision-making problem due to multiple software quality criteria and operational requirements. This paper proposes a multi-criteria model for evaluating approaches to wireless personal network security testing in educational institutions through the analysis of representative software tools. The evaluation framework is based on the ISO/IEC 25010 software quality criteria: reliability, functional suitability, interoperability, performance efficiency and scalability, compatibility and maintainability. Five widely used tools (Nmap, OpenVAS, Nessus, Wireshark and Wazuh) were analyzed using a structured multi-criteria approach. Criteria weights were determined using the PIPRECIA-S method, while the ranking was verified using the TOPSIS method. The results show that Wazuh achieved the highest overall score (0.3051), followed by Wireshark (0.2315) and Nessus (0.1954), while OpenVAS (0.1443) and Nmap (0.1225) achieved lower ranks. The stability and reliability of the model were confirmed by sensitivity analysis, Pareto analysis, Spearman’s rank correlation and scenario analysis. The model provides a reliable decision-support framework for selecting network security testing approaches in educational and similar organizational environments. Full article

Shoes are increasingly being bought online without being put on in person as internet shopping gains popularity. As a result, returns have increased significantly, which has had negative effects on the economy and the environment. Numerous technologies are available to measure foot size precisely at home or in-store in order to address this problem. People can identify their perfect shoe size and avoid needless returns by taking accurate foot measurements. A single image should be enough to measure the foot in order to make the system as easy as feasible for the user. This is accomplished by using point clouds from one side of the foot, which are produced by capturing a depth image. In order to optimise the reconstruction of partial data, this study investigates the impact of the acquisition position of a single partial foot scan on reconstruction quality and measurement accuracy when a state-of-the-art network is employed for completion. To this end, task-specific partial foot datasets were created with varying camera positions and foot orientations to determine the optimal conditions for depth map acquisition. Utilising the foot dataset that has been introduced for the purposes of training and evaluation, the network was able to generate accurate reconstructions. These reconstructions allowed for the estimation of shoe size in accordance with the European sizing system. The method is accurate enough in all tested positions to reconstruct a foot with sufficient precision. However, we also identified position 5 in our multi-view setup, which is viewed from a lower angle, as the position that leads to the best reconstruction results. Additionally, advantages were found with input data that show more of the forefoot than the heel area. Therefore, the forefoot provides more information on the overall geometry and should be the focus of single-shot procedures. Full article

Background: Major depressive disorder (MDD) is increasingly recognized as a highly heterogeneous disorder. Although the person-based similarity index (PBSI) provides a useful framework for characterizing individualized brain structural similarity, existing studies in MDD remain limited by either small samples or a lack of integration across different morphological features. Methods: We used structural MRI data from 1442 patients with MDD and 1277 healthy controls to calculate PBSI scores of cortical morphology measures based on cortical thickness (CT), cortical volume (CV), cortical surface area (SA), and sulcal depth (SD). Group comparisons of whole-brain PBSI and regional contributions to PBSI scores were then performed, and a subgroup analysis in 243 first-episode, drug-naive (FEDN) patients with MDD was further conducted. Results: Patients with MDD showed significant alterations in PBSI. Specifically, PBSI scores were significantly reduced for CT, CV, and SD, whereas no significant group difference was observed for SA in the main analysis. Analyses of regional contributions to PBSI further revealed significant between-group differences across multiple cortical regions. These alterations were mainly distributed in the default mode, ventral attention, and visual networks for CT; in the default mode, ventral attention, sensorimotor, and visual networks for CV; and in the default mode, dorsal attention, frontoparietal, and sensorimotor networks for SD. Similar patterns were also observed in the FEDN MDD subgroup. Conclusions: These findings provide neurobiological evidence for the marked structural heterogeneity of MDD and highlight the potential of PBSI as an individualized neuroimaging marker for more precise diagnosis and personalized intervention. Full article

Tooth segmentation from dental meshes is a fundamental step in clinical applications such as computer-aided orthodontics and dental implantation. Compared with mature image segmentation, deep learning-based mesh segmentation research is currently in a high-speed development stage. This study follows a dual-flow personalized feature learning scheme based on meshes and researches high-resolution mesh segmentation problems for clinical needs, proposing a dual-flow deep learning architecture called Position Shape Network (PSNet). Its basic idea includes continuously adjusting the feature map size in the network layer to enhance the model’s generalization ability and designing a reasonable branch structure to personalize the learning of position attributes represented by coordinates and shape attributes represented by surface perimeter area. In addition, it is proposed that the resolution of the validation set should be determined by comprehensively analyzing and simplifying errors to ensure the credibility of the model evaluation. Under this evaluation system, PSNet was compared with relevant authoritative methods in experiments, and the results verified the rationality and efficiency of the method and viewpoint proposed in this paper. Full article

Background: Gender discrimination in sport remains a persistent global issue, reflected in women’s limited participation, leadership representation, media visibility, salary equity, and personal safety. These forms of discrimination also negatively affect athletes’ psychological well-being, mental health, and overall sports experience. Despite growing scholarly attention over the past three decades, a comprehensive quantitative synthesis of this research area has been lacking. Methodology: A bibliometric analysis of 397 peer-reviewed documents published between 1995 and 2026 was conducted using the Scopus database. Data were analysed through the Bibliometric R package 4.2.1 and Biblioshiny interface. Science-mapping techniques including keyword co-occurrence, thematic clustering, thematic evolution, and collaboration network analysis were combined with performance indicators such as annual publication output, leading sources, author productivity, and citation impact. Results: Scientific production increased markedly after the mid-2010s, involving 187 sources and 1106 authors, with rising collaboration and citation influence. Core research themes included gender inequality, leadership exclusion, media representation, harassment and abuse, and structural discrimination in sports systems. Importantly, many of these themes are directly linked to reduced athlete well-being, including increased stress, anxiety, and decreased participation. Recent thematic developments highlighted intersectionality, safeguarding, inclusion, governance, and athlete welfare. Conclusion: Research on discrimination against women in sport has evolved into a multidisciplinary, policy-relevant field. Addressing gender discrimination is essential not only to achieving equity but also to improving athletes’ subjective well-being and long-term participation in sport. However, significant gaps remain, particularly in Global South contexts and intervention-based studies, indicating the need for stronger evidence-driven strategies to advance gender equity, inclusion, and ethical governance in sport. Full article