Search Results (8,527)

Machine Learning (ML) models developed for the Edge have seen a massive uptake in recent years, with many types of predictive analytics, condition monitoring and pre-emptive fault detection developed and in-use on Internet of Things (IoT) systems serving industrial power generators, environmental monitoring systems and more. At scale, these systems can be difficult to manage and keep upgraded, especially those devices that are deployed in far-Edge networks with unreliable networking. This paper presents a simple and novel platform architecture for deployment and management of ML at the Edge for increasing model and device reliability by reducing downtime and access to new model versions via the ability to manage models from both Cloud and Edge. This platform provides an Edge ML Operations “Mirror” that replicates and minimises cloud MLOps systems to provide reliable delivery and retraining of models at the network Edge, solving many problems associated with both Cloud-first and Edge networks. The paper explores and explains the architecture and components of the system, offering a prototype system that was evaluated by measuring time to deploy models with regard to differing network instabilities in a simulated environment to highlight the necessity for local management and federated training of models as a secondary function to Cloud model management. This architecture could be utilised by researchers to improve the deployment, recording and management of ML experiments on the Edge. Full article

This study explores the readiness of Micro and Small Enterprises (MSEs) in Mexico, specifically grocery stores, to implement the Virtual Value Chain (VVC) through Information and Communication Technologies for Development (ICT4D). A mixed-methods approach was used, combining diagnostic tools, structured surveys, and interviews. Quantitative data were analyzed using descriptive statistics, correlation analysis, and machine learning to identify digital adoption patterns. The results indicate that limited technology adoption remains the main obstacle to VVC integration. Significant associations were found between digital engagement and the age and educational level of store managers. Key digital gaps persist in inventory control, supplier coordination, and demand forecasting. Although machine learning models did not significantly outperform baseline predictions on willingness to adopt technology, the findings emphasize the potential of targeted training and accessible mobile solutions. The study proposes a new diagnostic and predictive framework to assess VVC readiness in low-resource contexts. It shows that ICT, when strategically aligned with business operations and paired with adequate training, can enhance sustainability and livelihoods. Although the study is limited to one geographic area and one business sector, it offers a foundation for scaling similar initiatives. The findings support context-sensitive strategies and capacity-building efforts tailored to the realities of MSEs in emerging economies. Full article

Public green spaces are vital to urban life, offering recreational opportunities, enhancing mental and physical well-being, and supporting environmental sustainability. This study presents a structured evaluation of ten public parks in Riyadh, categorized as neighborhood, local, and large parks, and compares their performance to two internationally recognized benchmark parks—Hyde Park and Regent’s Park in London. A partly original evaluation framework was developed to assess the design-related and environmental (nature-based) qualities of these parks. The framework integrates 50 criteria grouped into nine categories, combining quantitative scoring on a five-point scale with qualitative on-site observations. This method enables a comprehensive assessment of design quality, accessibility, and sustainability features. A city-wide map with a color-coded legend illustrates the distribution of the evaluated parks, while field observations and photographic documentation supported the data collection. Findings reveal notable variations in design quality, accessibility, and sustainability across the parks. The results highlight both strengths and gaps compared to international benchmarks, providing valuable insights for improving park design and management. This study contributes to ongoing efforts to enhance park usability and align with Riyadh’s Vision 2030 objectives, offering a practical decision-support tool for planners, managers, and policymakers seeking resilient and inclusive public green spaces. Full article

Museum building information modeling is an emerging research field that harnesses the potential of digitization applied to both architecture and artworks. This present work aims to innovate the current practices by integrating virtual tours and semantic-aware models while also fostering the uses of the informed models beyond management or professional use. The methodology consists of a 3D informed model able to manage the collection catalog, leveraging the BIM paradigm. Subsequently, a VR desktop tool is developed based on panoramic images fully interoperable with data enrichment and all the informative layers. The results demonstrate the feasibility of a workflow for a multilayer platform for museums that balances computational issues and ensures correct representation of various levels of geometry and information. The assessment in a real-world scenario through a fully operative prototype of museum BIM to VR also allows us to outline perspectives for dissemination purposes. Full article

The electronic judicial evidence preservation systems face various challenges including regulatory control, data exchange, poor credibility, etc. To address these issues, a blockchain-based judicial evidence preservation framework, JudicBlock, is proposed in the present study. It combines the scalability of the Interplanetary File System with the transparency and security of public blockchain. By decentralizing data management and using cryptographic integrity, the system ensures reliable chronological tracking of investigative changes. Unlike traditional approaches, JudicBlock incorporates smart contracts and advanced consensus mechanisms to enforce strict access controls with secure collaboration among the stakeholders. The simulation results show that JudicBlock provides better results over traditional ELR (electronic law records) storage schemes in terms of mining cost, query fetching time, block processing IPFS (Interplanetary file systems) throughput, etc. At a USD 6 mining cost, it appends an average of 23,601 transactions. For 25 blocks, the average query fetching time is 0.852 ms with the cache support of 32 KB. The proposed scheme achieves an average ELR uploading latency improvement of 6.79% over traditional schemes. The results indicate the efficacy of the proposed scheme over the conventional schemes. Full article

Shipping in complex marine environments requires a balance between navigational safety, minimising travel time and optimising logistics management, which is particularly challenging in areas with geometric obstructions and Offshore Wind Farms (OWFs). This study focuses on the maritime route networks in the Croatian ports of Pula and Rijeka, including the main access routes to OWFs and zones characterised by multiple navigational challenges. The aim of the research is to develop an empirically based and practically applicable framework for the optimisation of sea routes that combines analytical precision with operational efficiency. The parallel application of Dijkstra and A* algorithms enables a comparative analysis between deterministic and heuristic approaches in terms of reducing navigation risk, optimising route costs and ensuring fast logistical access to OWFs. The applied methods include the analysis of real and simulated route networks, the evaluation of statistical route parameters and the visualisation of the results for the evaluation of logistical and operational efficiency. Adaptive heuristic modifications of the A* algorithm, combined with the parallel implementation of Dijkstra’s algorithm, enable dynamic route planning that takes into account real-world conditions, including variations in wind speed and direction. The results obtained provide a comprehensive framework for safe, efficient and logistically optimised navigation in complex marine environments, with direct applications in the maintenance, inspection and operational management of OWFs. Full article

Remote First Nations communities in Australia experience ongoing energy insecurity due to geographic isolation, reliance on diesel, and uneven consumer protections relative to grid-connected households. This paper analyses evidence on electricity access, infrastructure and practical experience along with initiatives for improving existing infrastructure; highlights government policies, funding frameworks and regulation; demonstrates the benefits of community-led projects; provides geographic and demographic insights; and relevels key challenges along with pathways for effective solutions. Drawing on existing program experience, case studies and recent reforms (including First Nations–focused strategies and off-grid consumer-protection initiatives), this paper demonstrates that community energy systems featuring solar-battery systems can significantly improve reliability and affordability by reducing reliance on diesel generators and delivering tangible household benefits. The analyses reveal that there is an ongoing gap in protecting off-grid consumers. Hence, this work proposes a practical agenda to improve electricity supply systems for First Nations community energy systems through advanced community microgrids (including long-duration storage), intelligent energy management and monitoring systems, rights-aligned consumer mechanisms for customers with prepaid metering systems, fit-for-purpose regulation, innovative blended finance (e.g., Energy-as-a-Service and impact investment) and on-country workforce development. Overall, this paper contributes to a perspective for an integrated framework that couples technical performance with equity, cultural authority and energy sovereignty, offering a replicable pathway for reliable, affordable and clean electricity for remote First Nations communities. Full article

Background: Pain is a prevalent and distressing symptom for children with cancer, negatively affecting quality of life and family functioning. While most research focuses on hospital-based care, many pain episodes occur at home, where parents act as primary caregivers with limited access to evidence-based symptom management. Young children are particularly vulnerable due to limited self-reporting capacity and reliance on parental assessment. We aimed to explore parent experiences and pediatric oncology clinician perceptions of young children’s cancer pain at home, its impact on families, and recommended supports. Methods: Using an interpretive descriptive qualitative design, we conducted semi-structured interviews with parents of children aged 2–11 years undergoing outpatient cancer treatment and clinicians at two hospitals in Canada and the United States. Data were analyzed using thematic analysis. Results: In total, 21 parents and 21 clinicians participated. Three themes were developed: (1) the multifaceted experience of young children’s cancer pain at home, (2) the ripple effects of a young child’s cancer pain on the family unit, and (3) assessing and treating children’s cancer pain at home. Conclusion: Managing cancer pain at home places substantial emotional and practical demands on the families of young children. Our findings highlight that structured supports providing parents and clinicians with education, effective communication pathways, and collaboration opportunities may optimize home-based pain care, reduce caregiving burden, and improve outcomes for children and their families. Full article

Human T-cell leukemia virus type 1 (HTLV-1), the first identified human retrovirus, is associated with adult T-cell leukemia (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). The lack of effective antiviral therapies or vaccines highlights the critical importance of early diagnosis in managing HTLV-1-associated diseases. However, current commercial immunoassays, including enzyme immunoassays, line immunoassays, particle agglutination tests, and Western blots, are often limited by the need for specialized equipment and high costs, which restrict their accessibility in resource-poor regions. To address these challenges, we developed a novel dot-blot immunoassay using HTLV-1 P19 and GP46 synthetic peptides in combination with a precipitating tetramethylbenzidine (TMB) substrate. This innovative approach enables instrument-free visual detection through the formation of distinct blue-brown precipitates. Validation of this immunoassay with 179 clinical serum samples demonstrated 100% specificity and 91% sensitivity. Our assay offers a simple, cost-effective, and field-applicable diagnostic solution for HTLV-1 screening in resource-limited settings, potentially enhancing global surveillance of this neglected pathogen. Full article

Progressive climate change and the increasing concentration of carbon dioxide in the atmosphere represent one of the most serious challenges facing modern energy systems. At the same time, the global overproduction of plastics, particularly polyethylene terephthalate (PET), places a significant burden on the natural environment and waste management infrastructure. Electrochemical reactors offer a promising solution by enabling the simultaneous conversion of CO₂ and EG into valuable products such as carbon monoxide and glycolic acid, using electricity derived from renewable energy sources. Carbon monoxide can be further processed into high-energy synthetic fuels, such as propanol, while glycolic acid holds substantial importance in the pharmaceutical and plastics industries. An economic analysis was conducted to estimate the capital expenditures required for an electrochemical reactor and to assess the investment’s profitability based on the net present value (NPV) indicator. In addition, a Life Cycle Assessment (LCA) was carried out to evaluate the environmental impact of the proposed technology, with particular attention to its carbon footprint. The results indicate that the profitability of the system strongly depends on the market price and purity of glycolic acid, as well as on access to low-cost renewable electricity. The LCA confirms a significantly lower carbon footprint compared to conventional CO production, though further technological advancements are required for industrial deployment. Full article

Acute pulmonary embolism (APE) remains a significant cause of mortality and morbidity despite increasing prophylaxis for deep venous thrombosis (DVT). The IVC filter is a temporary or permanent intravascular device that traps migrating thrombi from their origin in the pelvis or a lower limb into the pulmonary vasculature, thereby preventing significant APE. The current and longstanding indications for placing an IVC filter are in patients with documented lower extremity DVT and acute APE who also have absolute contraindications to anticoagulation or have experienced an acute, hemodynamically unstable APE requiring ventilatory and vasoactive support, with limited cardiovascular reserve. Updated guidelines have led to a significant rise in IVC filter placements for specific therapeutic indications of venous thromboembolism compared to prophylactic use. Meta-analyses show that IVC filter placement is associated with a lower risk of subsequent APE but an increased risk of DVT. However, there appears to be no significant reduction in APE-related mortality and no change in all-cause mortality. Early complications after IVC filter placement typically relate to procedural issues and include bleeding or infection at the venous access site, development of arteriovenous fistulas, accidental arterial puncture, and post-procedural access site hematoma or thrombosis. Additional early complications include IVC filter malposition, incomplete expansion, IVC penetration, or guidewire entrapment. Delayed complications may involve DVT below the filter, IVC occlusion due to the filter, IVC filter migration, fracture of one of the IVC filter components, IVC rupture, or IVC thrombosis. Retrieval of IVC filters by simple, advanced, or open techniques should be considered after weighing the risk-to-benefit for the individual patient. Deployment of the IVC filter remains an important component of interventional APE management within the narrow indications currently proposed. Current guidance recommends that an untethered temporary IVC filter should be placed and retrieved once the contraindication to anticoagulation is resolved. Full article

Traditional road asset management relies on periodic, often inefficient, inspections. Digital Twins offer a paradigm shift towards proactive, data-driven maintenance by creating a real-time virtual replica of physical infrastructure. This paper proposes a comprehensive, formalized framework for a highway Digital Twin, structured into three integrated components: a Physical Space, which defines key performance indicators through mathematical state vectors; a Data Interconnection layer for real-time data processing; and a Virtual Space equipped with hybrid models. We provide a formal definition of these state vectors and a dynamic synchronization mechanism between the physical and virtual spaces. In this study, we focused on pavement condition assessment by using a data-driven component using accessible technology. This study show the synergy between the Digital Twin and deep learning, specifically by integrating advanced analytical models within the Virtual Space for intelligent pavement condition assessment. To validate this approach, a case study was conducted to classify road surface anomalies using low-cost Inertial Measurement Unit (IMU) data. We evaluated several machine learning classifiers and introduced a novel parallel Gated Recurrent Unit network. The results demonstrate that our proposed architecture achieved superior performance, with an accuracy of 89.5% and an F1-score of 0.875, significantly outperforming traditional methods. The findings validate the viability of the proposed Digital Twin framework and highlight its potential to achieve high-precision pavement monitoring using low-cost sensor data, a critical step towards intelligent road infrastructure management. Full article

Several studies have proven the impact of the quality of indoor environmental conditions on human professional and cognitive performances. Additionally, building energy efficiency and indoor comfort have attracted increasing interest, encouraging the implementation of advanced digital technologies and platforms for a more efficient management of buildings. In this context, this study proposes a new framework for an effective BIM-IoT integration leading to a nearly Digital Twin (DT) relying on a BIM model equipped with regularly-generated IEQ reports summarizing statistics from real-time collected data to support facility managers’ decision-making. Despite the relevant literature on the subject, the proposed methodology introduces some novelties, as monthly results of Indoor Air Quality (IAQ) and thermal comfort evaluation are provided by open HTML reports automatically generated through a Python 3.10 code from sensor data. These reports are easily readable without needing any external platform to be visualized and are directly accessible through BIM models. The proposed methodology has been validated on a pilot case study, thus proving its efficiency, effectiveness, and robustness in terms of automation level, interoperability, adaptability, reliability, accuracy in data visualization, and management. The study shows promising results but also some issues that could be addressed through further development of the research. Full article

Background: Family caregivers of patients with chronic diseases face high levels of burden, anxiety, and burnout, which may negatively affect both their well-being and patient outcomes. Low-cost, accessible telemedicine approaches may provide practical support in resource-limited settings. Methods: We conducted a prospective, parallel-group controlled study in Timisoara, Romania, between April 2024 and March 2025 and included 161 caregivers of older adults with chronic diseases, allocated 1:1 to receive either structured low-cost telemedicine support (weekly phone calls and SMS reminders; n = 82) or usual care (n = 79). Data were collected at baseline, three months, and six months through structured interviews. The primary outcome was caregiver burden measured by the Zarit Burden Interview (ZBI). Secondary outcomes included caregiver anxiety, burnout, satisfaction, and patient-related outcomes such as emergency room (ER) visits, hospital readmissions, and medication adherence. Analyses were performed using ANCOVA and logistic regression, adjusting for baseline values and relevant covariates. Results: At three months, caregivers in the intervention group had significantly lower burden scores compared to controls (adjusted mean difference −2.9; 95% CI −4.7 to −1.1; p = 0.002). Reductions in anxiety (−1.4; p = 0.02) and burnout (−1.6; p = 0.01) were also observed. These effects persisted at six months, though slightly attenuated. Patient outcomes favored the intervention: ER visits were lower at six months (27.50% vs. 41.02%; aOR 0.55, 95% CI 0.30–0.99; p = 0.047), while medication adherence and readmissions showed consistent but non-significant improvements. No adverse effects were reported. Conclusions: A simple, low-tech telemedicine program reduced caregiver burden, anxiety, and burnout and decreased ER visits. Improvements in medication adherence and readmissions were observed, but did not reach statistical significance. This pragmatic intervention can easily be integrated into primary care follow-up or community-based caregiver support programs, providing an affordable and low-cost technique to promote chronic disease management and caregiver well-being, especially in resource-limited health systems. Full article

In Mexico, 95% of the population has access to drinking water sources, but only about 65% of domestic waste water is treated to safe levels. This study analyzes forty years of Mexican scientific production on water and waste water treatment through a bibliometric and conceptual approach, evaluating its contribution Sustainable Development Goal (SDG) 6. The analysis identified three major research clusters: (1) biological processes for water treatment, (2) development and optimization of physical–chemical processes, and (3) water quality and management. These themes reflect the evolution of biological approaches for identifying and removing organic contaminants, the application of advanced techniques for improving water quality, and the promotion of sustainable water use. The study also highlights the growing attention to emerging contaminants, nanotechnology, integrated water resource management, and persistent challenges in sanitation. With respect to SDG 6, Mexican research has mainly focused on targets 6.1 (universal and equitable access to drinking water), 6.3 (water quality), and 6.5 (water resources management), while targets 6.2 (sanitation), 6.a (international cooperation), and 6.b (community participation) remain underrepresented compared with the international benchmarks, where the research trend is on water management, resources, and the water–food–energy nexus. Finally, the findings also show synergies with SDGs 11 (sustainable cities and communities), 9 (industry, innovation, and infrastructure), and 3 (good health and well-being), although gaps persist in addressing equitable access to water and society participation. Full article