Search Results (4,457)

Background/Objectives: Digital, remote, and ecological tools may complement clinic-based assessment in multiple sclerosis (MS), but the distribution of evidence across fatigue/fatigability, mobility, and real-world functional activity remains unclear. This scoping review mapped tools, metrics, constructs, contexts of use, and reported clinical utility in adults with MS, with attention given to whether the evidence was balanced across domains. Methods: Following Joanna Briggs Institute guidance and PRISMA-ScR/PRISMA-S reporting standards, five databases were searched on 14 March 2026. After deduplication, title/abstract screening, full-text assessment, and manual extraction and verification, the findings were synthesized descriptively without formal critical appraisal. Results: Of 3100 records identified, 1433 unique records were screened and 125 sources were included. Gait was the most frequently assessed domain (105/125), followed by fatigue/fatigability (33/125), physical activity (29/125), and sleep (2/125). The most frequent technologies were wearable devices (60/125), accelerometry (54/125), remote/home-based/telemonitoring modalities (52/125), and inertial measurement units (42/125). Conclusions: The evidence is predominantly gait- and mobility-focused, while fatigue/fatigability and broader real-world functional activity are less consistently represented. Reported clinical utility was usually framed around functional assessment, longitudinal/remote monitoring, rehabilitation planning, patient stratification, and decision support, but these characteristics were extracted as reported and were not independently appraised. Full article

Introduction: Freshwater habitats underpin global biodiversity and provide an array of essential ecosystem services to humans. However, threat hotspots like the Iberian Peninsula combine severe anthropogenic impacts (habitat degradation, climate change, and biological invasions, among others) with a high number of endemic range-restricted freshwater species. Despite the urgency, current conservation actions fall short of providing adequate protection. The irreplaceability index has been proposed as a useful assessment tool to focus limited efforts on areas that provide the highest benefit for threatened species. However, the transboundary nature of many rivers in the Iberian Peninsula can be a source of inefficiencies in protection if prioritisation efforts are conducted at a national rather than a peninsular scale. Objective: The aim of this study is to identify priority conservation basins for threatened native freshwater fish in the Iberian Peninsula and to evaluate the impact of national versus transboundary management strategies on the spatial protection afforded to these species. Methodology: The irreplaceability index was calculated for each basin by integrating basin richness, species rarity and their IUCN Red List conservation status. First, we modelled the species’ probability of presence using field observations recorded since 2000. Rarity was then calculated as the ratio between the modelled probability and the total number of basins within the species’ theoretical natural distribution. We then weighted each species’ rarity by its IUCN Red List conservation status, with higher weights to threatened species. We then calculated the basin irreplaceability index as the sum across all the species present in the basin of their conservation status-weighted rarity and ranked them according to this index. We replicated this approach considering Spain and Portugal independently, and both countries as one conservation planning unit. Results and Conclusions: The most irreplaceable basins were those harbouring a high density of threatened, narrow-range endemics. The priorities in each country differ depending on whether management strategies adopt a national or a broader geographical approach. Therefore, effective conservation requires transboundary planification to safeguard the shared biodiversity across countries. Full article

In this work, we present a neural network-based study capable of predicting faults in oil-insulated power transformers through the analysis of dissolved gases. The advantage of this study lies in using data already collected by electric power companies, which gather it to comply with international or regional standards; however, they sometimes act only after the equipment is already in a faulty condition. Therefore, the challenge in this work was data regularization, as collections typically occur at long intervals of 6 to 12 months. Furthermore, samples are often irregular, as data collection depends on factors such as weather and the availability of maintenance teams. As a result of this work, Multilayer Perceptron (MLP), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM) were used to predict failures with advanced forecasts ranging from 1 to 6 months, achieving accuracies of 97.5% and 85%, respectively. Thus, these models prove to be important tools for maintenance planning, enabling adequate predictability for organizing equipment shutdowns without the need for high investments in installing tools to capture this information online and adapting substations to send data to control rooms or other analysis centers. Full article

Permutation flow shop scheduling is an important production planning problem handled in different contexts. Just-in-time measures have been significant in the optimization of real problems and one is specifically addressed here: the total earliness and tardiness of jobs. The most used approach in the literature to mathematically express this measure is to sum them up using unit weights thus obtainning a mono-objective function. In this paper it is shown that this is a simplification of a problem that is inherently multi-objective, highlighting how a more comprehensive approach can better support decision-making. A bi-objective mathematical optimization model and tools capable of analyzing the mono-objective solution within the multi-objective perspective are proposed. A computational study to analyze the benefits and difficulties of the solution using the bi-objective approach is presented. The results show that for large-scale instances in which the tardiness factor is small, the conflict between the objectives of minimizing the total earliness and minimizing the total tardiness of jobs increases significantly. Specifically, the mono-objective solution is unbalanced in 50.00% of the analyzed instance structures. However, in 48.12% of the instances, alternative Pareto-optimal trade-offs can be achieved with zero increase to the mono-objective optimal value. Therefore, the multi-objective approach has a greater potential to support decision-makers. Furthermore, we show that the choice of the solution method must be carefully considered, since the Pareto frontier associated with most instances has many non-supported points, representing up to 66.71% of the non-dominated set. Full article

Background/Objectives: Adult patients supported with extracorporeal membrane oxygenation (ECMO) frequently require invasive diagnostic, therapeutic, surgical, or bedside procedures during ongoing extracorporeal support. These procedures are clinically challenging because ECMO-related anticoagulation, platelet dysfunction, acquired coagulopathy, and circuit-related coagulation activation may increase both bleeding and thrombotic risks. This systematic review evaluated the safety of invasive procedures performed during adult ECMO support, excluding tracheostomy/tracheotomy because this procedure has recently been addressed in a dedicated systematic review. Methods: A systematic search of PubMed/MEDLINE and Scopus was performed. The final bibliographic data collection was completed in April 2026. Studies were eligible if they included adult ECMO or extracorporeal life support patients undergoing invasive procedures during ongoing ECMO support, or with ECMO used as procedural support, and reported at least one procedure-specific safety outcome. Primary outcomes were procedure-related complications, bleeding, major bleeding, and transfusion requirements. Secondary outcomes included thrombotic and circuit-related complications, oxygenator exchange, reintervention, reoperation, procedural failure, ECMO duration, intensive care unit and hospital length of stay, and mortality. Results: The final qualitative synthesis included 46 studies, comprising 26 studies from PubMed/MEDLINE and 20 additional unique studies from Scopus. Included procedures were grouped into six domains: airway, bronchoscopic, and tracheobronchial procedures; thoracic surgery and lung resections; abdominal surgery, gastrointestinal endoscopy, and decompressive laparotomy; lung transplantation and perioperative extracorporeal life support; cardiovascular, vascular, pulmonary embolism-related, and mechanical circulatory support-related procedures; and mixed non-cardiac surgery. Airway and bronchoscopic procedures generally showed high procedural success in selected cohorts, although registry-level tracheal procedure data reported hemorrhagic complications in 26.0% and surgical-site bleeding in 13.0%. Emergency thoracic and abdominal procedures carried the highest bleeding, transfusion, reintervention, and mortality burden. Lung transplantation studies showed that ECMO can be integrated into perioperative pathways, but hemothorax, transfusion, thromboembolism, and anticoagulation strategy remained central safety issues. Conclusions: Invasive procedures during adult ECMO are feasible in selected patients and experienced centers, but procedural safety varies markedly by procedure type, urgency, baseline disease severity, and anticoagulation strategy. A procedure-centered, multidisciplinary approach with individualized anticoagulation management and careful planning is essential. Full article

Background/Objectives: Foot and ankle presentations during Hajj occur in a dense mass-gathering environment where prolonged walking, heat exposure, crowding, variable footwear, and limited self-care can interact with chronic disease and wound vulnerability. Previous Hajj studies have described foot injuries and diabetes-related complications, but less is known about whether simple high-risk foot documentation flags identify presentation records with higher care-pathway intensity. The primary objective was to estimate the presentation-level burden of core high-risk foot profiles among pilgrims presenting with foot and ankle conditions during Hajj 2025. Secondary objectives were to evaluate associations with a surgery-coded care-intensity indicator, hospital referral, and component heterogeneity. Methods: This observational presentation-level analysis included 3957 foot and ankle presentation records. The unit of analysis was the presentation/case record, not a unique individual pilgrim. A core high-risk foot profile was defined as diabetes, neuropathy, diabetic foot ulcer, foot ulcer, complications of open wound, or osteomyelitis. The primary outcome was a surgery-coded care-intensity indicator, defined solely from treatment documentation containing “Surgery” and interpreted as a care-pathway proxy rather than confirmed operating-room surgery. Logistic regression estimated crude and adjusted odds ratios (ORs); exploratory risk-category analyses assessed heterogeneity within the composite profile. Results: Core high-risk foot profiles were identified in 1793/3957 presentations (45.3%). The primary outcome occurred in 239/1793 high-risk presentations (13.3%) and 201/2164 non-high-risk presentations (9.3%), an absolute difference of 4.0 percentage points. The crude OR was 1.50 (95% CI 1.23–1.83; p < 0.001). The association persisted in the primary adjusted model (adjusted OR 1.47; 95% CI 1.20–1.79; p < 0.001) and in the extended clinical sensitivity model (adjusted OR 1.47; 95% CI 1.20–1.80; p < 0.001). Care pathways and secondary outcomes are summarized was also more frequent in high-risk presentations (12.2% vs. 9.8%; crude OR 1.28; 95% CI 1.05–1.57; p = 0.017). Exploratory category analysis showed that chronic-risk-only presentations had a primary outcome rate similar to non-high-risk presentations (9.0% vs. 9.3%), whereas ulcer/wound/deep-infection presentations had a higher rate (17.3%; crude OR 2.04; 95% CI 1.63–2.55; p < 0.001). Model discrimination was modest (C-statistics 0.55–0.64). Conclusions: Core high-risk foot flags were common among Hajj foot and ankle presentation records and were associated with surgery-coded care-intensity and referral documentation. However, the composite was clinically heterogeneous, the outcome was not a validated surgery endpoint, and the models were not prediction tools. These findings support cautious use of high-risk foot flags as operational prompts for assessment and pathway planning rather than as standalone clinical risk estimates. Full article

Background/Objectives: The rising prevalence of multimorbid and complex chronically ill young and middle-aged adults necessitates the implementation of innovative care models and the creation of roles that can meet the complex healthcare needs of this patient group. Advanced Practice Nurses (APNs) can play a crucial role in the care of multimorbid and complex chronically ill young and middle-aged adults in APN-led clinics; however, in Switzerland, these roles are still evolving. The aim of this study was to explore APNs’ perspectives on the planned development of their roles in an APN-led clinic. Methods: To gain insights into the experiences of APNs in caring for this patient group, a qualitative study design was chosen. Data were collected through interviews with APNs from Switzerland, the USA, and Canada. In total, 19 APNs (12 from Switzerland and 7 from the United States and Canada) participated in the study. The data were collected through semi-structured online interviews. These data were analyzed using reflective thematic analysis in accordance with the approach presented by Braun and Clarke. Results: The analysis identified 10 themes that describe the competencies, components, and framework conditions required for the work of APNs in an APN-led clinic for multimorbid and complex chronically ill young and middle-aged adults within the Swiss clinical context. Required competencies include direct clinical practice, guidance and coaching, collaboration, and psychosocial support. Essential components include person-centered care, transitional care, and continuity of care. Key framework conditions include regulations of the legal and regulatory framework and eligibility for reimbursement of services, resources, and extended competencies and scope of practice. Conclusions: The perspectives of the APNs involved in this study show that multimorbid and complexly chronically ill young and middle-aged adults require complex and long-term care that extends beyond the hospital setting. The findings of this study show that Swiss APNs may be well positioned to contribute to this role. Full article

Background/Objectives: Post-extubation stridor (PES) is common in pediatric critical care and may contribute to extubation failure, particularly in children with heart disease. Prophylactic corticosteroids are frequently used before extubation, but their benefit in pediatric cardiac patients remains uncertain. We evaluated the association of prophylactic corticosteroids with PES and extubation failure and explored whether PES mediated any association with failure. Methods: We performed a retrospective, single-center, observational cohort study of extubation events in a pediatric cardiac critical care unit from July 2016 to June 2024. Exposure was prophylactic intravenous corticosteroids before planned extubation, most commonly dexamethasone (0.15–0.5 mg/kg per dose) or methylprednisolone (1–2 mg/kg per dose), administered 6–24 h before extubation in single- or multi-dose regimens. The primary outcome was clinically defined PES; the secondary outcome was extubation failure, defined as reintubation within 48 h. Confounding was addressed using propensity scores with inverse-probability weighting after common-support restriction. Causal interpretation of the weighted and mediation estimates was considered conditional on the no-unmeasured-confounding (ignorability) assumption. Subgroup analyses were stratified by PES status, and exploratory mediation analysis used structural equation modeling. Results: Among 494 extubation events, prophylactic corticosteroid use was not associated with lower odds of PES after weighting (OR 1.06, 95% CI 0.53–2.10) or extubation failure (OR 0.49, 95% CI 0.19–1.24). Among patients with PES, corticosteroid use was associated with a non-significant reduction in extubation failure (OR 0.70, 95% CI 0.14–3.43). Exploratory mediation analysis, interpreted under the ignorability assumption, did not support PES as a meaningful mediator. Conclusions: In this single-center cohort, prophylactic corticosteroid use was not associated with reduced PES or extubation failure. The findings do not support clinically defined PES as a key mediator of any potential treatment effect. Prospective studies are required for confirmation. Full article

Estimation of rice crop yield at the village level is essential because village is the Insurance Unit (IU) for rice crop in many regions in India, and timely and accurate yield information at this scale supports timely and transparent claim settlements for farmers and supports local agricultural planning. To achieve this, a multi-source satellite data-based machine learning approach was used to estimate rice yield at the village level using optical and SAR data, climatic data and land surface model-derived parameters in Kakinada of Andhra Pradesh, India. The predictor dataset included seasonal cumulative rainfall, seasonal Normalized Difference Vegetation Index (NDVI)-Max, seasonal NDVI-Mean, seasonal Land Surface Water Index (LSWI)-Max, seasonal LSWI-Mean, season total Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) and season total Root Zone Soil Moisture (RZSM), and season total backscatter of the Sentinel-1 VH polarization were used to represent crop greenness, moisture status, photosynthetic activity, soil water availability, canopy structure, and seasonal water supply. For model development and validation, village-level rice yield data from 2017 to 2023 was used, which was collected through Crop Cutting Experiment (CCE) at the maturity stage of Kharif season. In this study, four machine learning models such as Random Forest (RF), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gradient Boosting (GB) were evaluated. The multi-source satellite data and yield data for the period 2017–2021 were used to train the models, which were independently tested on 2022 data and then applied to predict the rice yield in 2023. Leave-One-Year-Out (LOYO) cross-validation was also conducted on the 2017–2022 data to assess temporal robustness and generalization capability across years. Among the evaluated models, Random Forest exhibited the best overall performance. For the independent test year 2022, RF achieved an R² of 0.465, RMSE of 415.34 kg ha⁻¹, MAE of 322.22 kg ha⁻¹, and MAPE of 10.36%. For the prediction year 2023, RF achieved improved accuracy with an R² of 0.838, RMSE of 325.75 kg ha⁻¹, MAE of 262.21 kg ha⁻¹, and MAPE of 7.68%. Further, LOYO cross-validation also showed the robustness of RF, achieving the highest mean R² of 0.702 and mean RMSE of 384.73 kg ha⁻¹. The results illustrate that multi-source satellite data combined with machine learning can be a reliable and operationally useful tool in predicting village-level rice yield, which can be used for crop insurance claim settlement. Full article

The seamless integration of real-time operational technology (OT) with big data architectures remains a critical bottleneck in developing robust robotic Digital Twins. Furthermore, evaluating stochastic motion planners strictly within pristine simulations obscures vital real-world challenges such as sensor noise, communication latency, and mechanical stress. This study presents a high-throughput, real-time Hardware-in-the-Loop (HIL) pipeline integrating ROS 2, Apache Kafka, and Functional Mock-up Units (FMUs). Using a UR10e manipulator in a constrained industrial environment, we conducted extensive physical benchmarking of 11 Open Motion Planning Library (OMPL) algorithms across 10 repetitions, generating a comprehensive dataset of 785,192 samples. The proposed IT/OT architecture achieved deterministic millisecond-level synchronization, bounding end-to-end communication latency between 0.09 and 15.51 ms. Physical executions revealed a macroscopic “topological divergence” between simulation and reality, with spatial deviations peaking at 457.65 mm due to real-world point-cloud noise. While algorithms like EST and KPIECE demonstrated optimal geometric efficiency (e.g., a mean path length of 14.57 m) and hardware-friendly dynamics, traditional planners like RRT generated severe inertial spikes of up to 100 N, demonstrating substantial unsuitability for continuous industrial deployment. The primary contribution is a methodologically novel, rigorously validated big data pipeline and the release of an open-source, 50 Hz multimodal dataset (spatial, temporal, and dynamic forces), bridging the sim-to-real gap and providing a foundational benchmark for future data-driven robotic applications. Full article

Proactive disease transmission pathway analyses break complex transmission routes into simpler steps, making risks and uncertainties easier to identify. This approach is especially valuable for African Swine Fever (ASF), a difficult-to-control disease in low-biosecurity settings or when biosecurity practices are inconsistently applied. To support targeted biosecurity planning, a pathway analysis was conducted that is specific to pork harvest facilities in the United States. The analysis focused on two federally inspected plants that slaughter market hogs and produce primal cuts. Inputs, outputs, and potential transmission pathways were identified through a literature review, site visits, and facility personnel interviews. Because ASF virus remains stable at low temperatures and in many pork products, particular attention was given to pathways involving storage conditions, waste materials, and processing steps such as heating or pH modification. Processing steps were evaluated against existing process control plans and ASF inactivation thresholds to determine mitigation status. Of 42 identified pathways, 39 were classified as unmitigated or of unknown mitigation status. These unmitigated or unknown pathways—broadly involving pigs, people, vehicles, and waste—represent the highest priorities for further risk assessment work and for exploring ways to develop or strengthen biosecurity protocols that reduce ASF transmission. Full article

Sustainable fresh food supply chains depend heavily on effective coordination under uncertain market conditions. Citrus export systems are particularly sensitive to perishability, seasonality, and cold-chain constraints. Under these conditions, reliable price forecasts are important for export planning, logistics efficiency, and sustainable supply-chain management. This study examines the relationship between orange and mandarin export prices in Türkiye using monthly data from 2016 to 2025. Export prices are proxied by real unit values derived from official trade statistics. The analysis applies Augmented Dickey–Fuller tests, Johansen cointegration analysis, and Vector Error Correction Models (VECMs). Forecast performance is evaluated using a rolling-origin framework and compared with ETS, SARIMA, XGBoost, and a seasonal naïve benchmark. The results identify one cointegrating relationship between the two export markets. The estimated long-run coefficient is 0.92, indicating near one-to-one price co-movement. Adjustment toward equilibrium is asymmetric, with orange prices responding faster (ECT = −0.44) than mandarin prices (ECT = −0.21). Forecasting results show that VECM-based models outperform all alternative specifications. The robust VECM achieves the lowest forecast errors (MAPE = 8.3%), compared with 9.8% for XGBoost, 10.6% for SARIMA, 11.5% for ETS, and 14.1% for the seasonal naïve benchmark. Diebold–Mariano tests confirm that these improvements are statistically significant. The findings indicate that orange and mandarin export prices should be analyzed jointly rather than separately. In closely connected citrus supply chains, cointegration-based forecasting models provide more reliable forecasts and a stronger analytical basis for sustainable market coordination. Full article

The transition toward transportation electrification has accelerated significantly in the United States through the implementation of the National Electric Vehicle Infrastructure (NEVI) program under the Bipartisan Infrastructure Law. This study examines the evolution of NEVI implementation across the six New England states from 2022 to 2026 within a shared federal policy framework. Using a qualitative comparative longitudinal document analysis approach, the research analyzed state NEVI plans, annual implementation updates, transportation electrification strategies, and policy documents through thematic comparative analysis. The findings revealed that NEVI implementation evolved beyond compliance-oriented charging deployment toward broader adaptive governance and sustainability-oriented transportation processes. States demonstrated varying implementation trajectories shaped by institutional coordination, utility collaboration, operational adaptation, equity priorities, and infrastructure planning strategies. The results further indicated increasing emphasis on resilient infrastructure planning, interoperability, cybersecurity, operational continuity, and equitable charging accessibility throughout the implementation period. The study concludes that EV infrastructure implementation should be understood not only as a technical deployment initiative but also as an evolving socio-technical sustainability transition process influenced by adaptive governance and institutional maturation. This research contributes to the sustainability governance literature by providing a comparative regional analysis of the evolution of transportation electrification implementation across multiple jurisdictions under a shared federal policy framework. Full article

Background: The integration of internationally educated nurses (IENs) into healthcare workforces is expanding globally, yet organization-led support models remain understudied. Successful IEN integration requires ethical recruitment, structured onboarding, workforce support, and stakeholder engagement in policy discussions related to transition and retention. Objective: To examine the conceptualization, implementation, and policy implications of the Philippine Nurses Association of America Cy Pres Task Force’s national initiative to support IEN onboarding and transition into U.S. healthcare. Methods: This descriptive program evaluation utilized governance documents, program planning records, policy summit materials, aggregated survey findings, PNAA Human Rights Committee resources, and the Handbook for Filipino Nurses Immigrating to the United States to examine initiative development, implementation processes, and program outputs. A descriptive narrative synthesis was used to characterize program structure, stakeholder engagement, and policy priorities. Findings: The PNAA Cy Pres governance model was built around ethical recruiting, workforce integration, and advocacy. The work began with policy summits with nurse leaders, health care organizations, recruitment agencies, and policy experts, focusing on hiring, onboarding, legal issues, and staff retention. Stakeholder engagement, interdisciplinary collaboration, and appreciative inquiry were used to identify best practices and goals. Key outputs included the establishment of a national governance structure, implementation of national and regional policy summits, and identification of policy priorities related to ethical recruitment, onboarding, workforce integration, and governance. Conclusions: The PNAA Cy Pres initiative provides an implementation-informed approach that may help guide future workforce integration efforts. The study illustrates how ethical recruitment, workforce integration, and stakeholder engagement can help translate workforce policy principles into practice. Policy & Practice Implications: Healthcare institutions, policymakers, and professional organizations need to work together to standardize onboarding, ethical recruitment, and support mechanisms to facilitate the integration and sustainability of the IEN workforce. Full article

To achieve scientific cost forecasting, this study investigates structural changes in mining cost driven by the widespread adoption of mechanized mining, increased mining depths, and significant operational variations. Based on the backpropagation (BP) neural network, this study systematically analyzes the cost-composition characteristics of modern mining operations and applies activity-based costing to achieve refined cost accounting for each mining operation unit. Ten key influencing factors, including working space, stope temperature, stope depth, haulage distance, worker seniority and work efficiency, scraper efficiency, equipment service life, fuel and lubricant consumption rates, are identified by analyzing cost variation patterns. Principal component analysis (PCA) is used to reduce the dimensionality of the ten factors to simplify this model and enhance prediction accuracy. The PCA-BP neural network mining cost forecasting model is built with the principal components extracted as input variables. Actual cost data from an underground metal mine in Shandong Province is used for our model training and validation, with adopting linear regression, eXtreme Gradient Boosting (XGBoost), and a traditional BP neural network as the comparison models for performance evaluation. Our prediction results indicate that the PCA-BP model achieves an average relative error of 3.80% and a root mean square error of 1.43, both significantly outperforming the comparison models. The results demonstrate superior predictive accuracy and stability of our model. Validated with data from a typical deep mechanized gold mine in eastern China, the PCA-BP cost forecasting model requires parameter retraining based on local production conditions for applications in other regions. This study confirms that the model aligns well with the cost characteristics of modern underground metal mines and produces effective predictions, offering reliable quantitative support for the development of cost control strategies and optimization of cost planning in mining enterprises. Full article