Search Results (49,659)

Post-blast operations in tunnel construction represent a critical bottleneck due to mandatory downtime and hazardous environmental conditions. This study addresses these challenges by developing and validating an integrated cyber–physical architecture that coordinates an autonomous Unmanned Aerial Vehicle (UAV) and an Autonomous Wheel Loader (AWL) under the supervision of a Digital Twin acting as central operational digital interface. Specifically, this technology was designed to access the tunnel, evaluate post-blasting conditions, and initiate operations during mandatory exclusion periods for personnel. The system was validated in a realistic, Global Navigation Satellite System (GNSS)-denied tunnel environment emulating post-detonation visibility constraints. The results demonstrate that the aerial agent successfully navigated and mapped the excavation front in less than 8 min, establishing a shared coordinate system for the ground machinery. Through this collaborative workflow, the autonomous deployment enabled operations to commence 50% to 80% earlier than conventional manual procedures. Furthermore, the system reduced daily operational time by approximately 8%, with an estimated return on financial investment between one and seven months. Overall, the proposed framework eliminates human exposure during high-risk inspections and transforms the fragmented excavation cycle into a continuous, data-driven process. Full article

Mental fatigue (MF) has been hypothesized to contribute to injury risk in athletes, but observational studies have not directly investigated this relationship. Therefore, the current study evaluates potential relationships between mental fatigue and subsequent injury occurrence in basketball. Using an observational design, we monitored fourteen male semi-professional basketball players (age: 22 ± 4 years; stature: 192.6 ± 8.8 cm; body mass: 85.5 ± 9.1 kg; Tier 3) from a single team for 21 weeks throughout the competitive season. Each week, the players participated in 5 team-based training sessions, 2–4 individual training sessions, and 1–2 official games. Subjective MF ratings were collected using 100 mm visual analogue scales twice a week (the day before and after the official game) and then averaged. Time-loss injuries were registered, noting the body location, mechanism, and context (training and games). Generalized logistic mixed models were employed to evaluate whether MF levels were associated with injury occurrence in the subsequent 1, 3, and 5 days and 1, 2, 3, and 4 weeks of basketball activity. A total of 11 injuries were registered during the study (7.40 per 1000 h of basketball activity), with an average time loss of 12 ± 19 days. There were no associations between MF and injury occurrence in the following 1, 2, 3 or 4 weeks (all p > 0.05, odds ratios: 1.00–1.28). In male semi-professional basketball settings, preliminary evidence indicates that MF might not be associated with injury occurrence. However, due to the dearth of injury events, the statistical power of this study is insufficient to detect potential small–medium effects. Therefore, the current results should be considered exploratory as opposed to a definitive rejection of the hypothesis. Future studies should evaluate the relationship between MF and injury risk in larger samples and among professional athletes. Full article

The energy utilization of residual woody biomass is a relevant strategy for the decentralized energy transition and local waste management in rural areas. The objective of this study was to characterize (physically, chemically, and energetically) five types of residual biomass: pine branches, huinumo (this material refers to the long, thin pine needles that, after drying and falling, form a layer on the forest floor), cherry branches and leaves, and grass waste generated in the community of San Francisco Pichátaro, Michoacán, Mexico, in order to evaluate its viability for the production of densified solid biofuels. A comprehensive analysis was conducted, including moisture content, higher heating value, proximate characterization, structural chemical analysis (using the Van Soest method), elemental CHONS analysis, ash microanalysis (by ICP-OES), and a multicriteria analysis with normalized energy and compositional indicators. The results showed that huinumo and cherry leaves were the most outstanding biomasses, presenting the highest heating values (20.7 MJ/kg) and low moisture and ash contents. Pine branches obtained the most balanced results, characterized by their equilibrium in fixed carbon and lignin, as well as their low potassium content. The multicriteria analysis showed that there is no absolute optimal biomass; however, it indicates that pine branches and huinumo are the most robust feedstocks for the production of briquettes or pellets. The results confirm the significant technical and environmental potential of local lignocellulosic residues for the production of solid biofuels and for contributing to sustainable energy solutions at the local scale. Full article

While predictive accuracy is often prioritized in machine learning (ML) models, interpretability remains essential in scientific and high-stakes domains. However, diverse interpretability algorithms frequently yield conflicting explanations, highlighting the need for consensus to harmonize results. In this study, six ML models were trained on six synthetic datasets with known ground truths, utilizing various model-agnostic interpretability techniques, as well as gradient-based and counterfactual-based explainers. Consensus explanations were generated using established methods and a novel approach: WISCA (Weighted Scaled Consensus Attributions), which integrates class probability and normalized attributions. WISCA consistently aligned with the most reliable individual method, underscoring the value of robust consensus strategies in improving explanation reliability. Full article

The increasing demand for environmentally sustainable and efficient laundry detergents has prompted the exploration of innovative biotechnological solutions. This study aims to integrate solid fermentation and by-product valorization for high-quality proteases suitable for laundry detergents. Of 486 strains isolated from fruit by-products, 9 were selected for their proteolytic activity, but only 3 showed proteolytic activity in the presence of detergent components. Strain M17, identified as Yarrowia lipolytica (Yl), proved to be the most effective in producing proteolytic extracts with activity similar to that found in commercial detergents. The produced proteases were incorporated into laundry detergent formulations, and their enzyme activity was compared with that of commercial laundry detergents. The results showed that the proteolytic extracts have enzyme activity similar to that of commercial laundry detergents. Culture media were developed to enhance protease production using fruit by-products. The highest activity (43.71 U (g dm)⁻¹) was achieved at C/N = 20.04, while the best productivity (1.37 U (g dm·h)⁻¹) at pH 7.0 and 30 °C was observed. The results demonstrate that culture media based on fruits and vegetable by-products enhance protease yield and activity. This approach not only reduces waste but also adds value to natural resources through an environmentally friendly process. This study underscores the potential of combining solid-state fermentation with by-products. Using Yl in combination with fruit and vegetable by-products is a practical, eco-friendly method for producing high-quality proteases for laundry detergents. This green enzyme innovation offers significant promise for advancing the detergent proteolytic enzymes and promoting sustainable practices in by-product management. Full article

Bio-based, biodegradable, and renewable polymers offer a promising alternative to traditional synthetic polymers derived from petroleum or other non-renewable resources. However, their use is limited by suboptimal properties and high costs. Incorporating sustainable reinforcements into the polymer matrix significantly improves biopolymer performance while preserving key properties, sustainability, and cost-effectiveness. Bio-based polymeric composites have emerged as a crucial category of biopolymers, playing a key role in advancing a sustainable, circular economy. This review provides an updated overview of bio-based polymer composites and nanocomposites, focusing on reinforcement strategies using natural nanofillers and engineered nanoparticles. We summarize key synthesis and processing methods, discuss structure–property relationships, and highlight recent advances in applications such as food packaging, biomedical devices, energy systems, environmental remediation, 3D printing, and supercapacitors. Polymer nanocomposites are versatile, with their performance depending on the type, size, and interactions between the fillers and the polymer matrix. Progress in metallic, ceramic, carbon-based, natural, and hybrid fillers has improved their properties. Using bio-based polymers and renewable fillers supports sustainability. Natural nanofillers derived from renewable sources and industrial byproducts offer a sustainable approach to developing high-performance, biodegradable nanocomposites. Smart nanocomposites can react to external stimuli by integrating specialized fillers that enhance their mechanical and mobility properties. Shape memory nanocomposites can be remotely activated—using heat, electricity, magnets, or light—enabling advanced applications. Finally, we address major challenges and outline future directions for scalable, circular-material solutions, drawing on perspectives from the circular economy and life cycle assessment (LCA). Full article

Background/Objectives: Chronic diseases pose a major challenge for healthcare systems, requiring integrated, patient-centered approaches that combine clinical management, prevention, and self-care. Lifestyle Medicine (LM) and lifestyle in general offers complementary frameworks to address these needs. However, the potential integration of LM within community nursing—particularly through the role of Family and Community Nurse (FCN)—has not been comprehensively synthesized. This narrative review aimed to synthesize international evidence on the role of community nursing—particularly FCN—in integrating chronic care management and LM view. Methods: For quality assessment, a narrative review was conducted in accordance with the SANRA criteria to enable the integration of heterogeneous evidence and a comprehensive synthesis of this complex topic. Literature searches were performed in the PubMed–Medline database, and the final screening of references from included studies was used to identify relevant manuscripts. Primary studies published in English over the past ten years were screened and analyzed using the PICOS framework. Sixteen eligible studies were included in the final synthesis. Results: The included studies indicated that nurse-led community interventions in LM view were associated with improvements in self-management, treatment adherence, and selected clinical outcomes, such as blood pressure, glycated hemoglobin, and physical activity levels. Empowerment-based approaches and the use of digital or telehealth tools supported patient engagement and health literacy. At the organizational level, multidisciplinary collaboration, shared protocols, and professional leadership emerged as key factors in sustaining continuity and quality of care, while organizational fragmentation and limited training in behavioral counseling were commonly reported barriers. Conclusions: Community nursing, particularly through FCNs, plays a relevant role in integrating chronic care management and LM approaches, contributing to improved self-management, treatment adherence, and selected clinical outcomes. The evidence highlights the importance of empowerment-based interventions, digital support tools, and multidisciplinary collaboration in enhancing care continuity and patient engagement. Addressing organizational barriers and strengthening behavioral counseling training remain essential to support effective implementation in community settings. Full article

Air pollution is one of the major environmental challenges threatening global sustainable development and human health. The World Health Organization identifies it as a critical factor contributing to non-communicable diseases and inequality, especially in vulnerable populations such as children. The findings highlight the negative effects of environmental degradation on physical health and underline the urgent need to incorporate health metrics, such as children’s fitness, into sustainability monitoring frameworks and public policies aiming at cleaner and healthier urban environments. The aim of this study was to examine the association between ambient particulate pollution and cardiorespiratory fitness in school-aged children from two rural villages in southern Spain characterised by relatively higher and lower levels of particulate matter. A total of 938 children (primary and secondary school levels) participated in a naturalistic pre–post study design. Cardiorespiratory fitness was assessed using the 6 min walk test, where maximal oxygen uptake (VO₂max) was estimated. Assessments were conducted before and after a period characterised by unfavourable air-quality conditions in the higher-pollution village. The students were assigned by convenience into an experimental [n = 476 (EG)] and a control group [n = 462 (CG)]. The t-test, repeated measures analysis and MANOVA test were used in order to report differences within and between groups, as well as time-points and academic levels. The significance level was set at p < 0.05. Significant differences between groups were reported within the pre-test period, showing elevated pre-test values in the CG compared to the EG. The EG showed a higher pre–post difference in estimated VO₂max compared to the CG for primary education level (16.19%, ES(d) = 0.91 vs. 3.07%, ES(d) = 0.26; p < 0.001, respectively); secondary education (EG: 12.29%, ES = 0.91 vs. CG: 1.69, ES(d) = 0.16); and the whole population (EG: 14.72%, ES = 0.91 vs. CG: 2.84, ES = 0.25). It seems that the environmental context, and specifically the air pollution in the area of residence, may be an important factor to consider in relation to the assessment of physical fitness in the school-aged youth population. Full article

As automated vehicles move from controlled environments to unpredictable real-world roads, scenario-based testing has become the cornerstone of safety validation. In recent years, substantial progress has been made in scenario representation standards and generation methodologies. However, integrating scenario generation, standards-aligned packaging, validation, curation, and structured querying into a reproducible end-to-end lifecycle remains challenging in practice. This work presents a reproducible reference architecture for Scenario Databases (SCDBs) that treats scenario collections as lifecycle-governed data systems rather than static repositories. The proposed architecture unifies the scenario lifecycle within a single workflow. It integrates scenario generation and ingestion, validation and curation, immutable storage, semantic and value-based querying, and reproducible export. Scenario semantics are represented using ASAM OpenX formats (OpenDRIVE and OpenSCENARIO), together with ASAM OpenLABEL metadata, enabling standards-aligned interoperability. Querying is performed over categorical and value-carrying metadata without requiring inspection of raw scenario artifacts at query time. The reference implementation is deployed using Infrastructure-as-Code, supporting reproducibility and low operational overhead. Execution-based metric enrichment is supported as an optional extension, enabling scenarios to be augmented with execution-derived measurements and trace metadata. The contribution is not a centralized database, but a reference architecture and deployment blueprint that supports interoperable and federated scenario ecosystems. By framing SCDBs as reproducible lifecycle systems, this work supports scalable scenario reuse and more transparent safety validation workflows. Full article

This study evaluated the iron-chelating capacity (ICC) of Lupinus mutabilis protein hydrolysate (LMPH) and its peptide fractions obtained through ultrafiltration and purification by immobilized metal ion affinity chromatography (IMAC) and gel filtration chromatography (GFC). Peptides were identified by LC-MS/MS, and their interactions with Fe²⁺ were analysed using molecular docking. LMPH was produced by enzymatic hydrolysis with Alcalase and subsequently subjected to ultrafiltration to concentrate peptides smaller than 2 kDa. This fraction exhibited higher ICC (35.1 mg Fe²⁺·g⁻¹) than the hydrolysate (22.75 mg Fe²⁺·g⁻¹). Sequential purification by IMAC and GFC yielded peptide fractions with enhanced ICC values (45.20 and 13.51 mg Fe²⁺·g⁻¹). A total of 176 peptides were identified by de novo LC-MS/MS sequencing, from which nine were selected based on favourable structure–ICC relationships and absence of predicted toxicity. Molecular docking analysis suggested spatial proximity between Fe²⁺ and the selected peptides. Although stable multi-site binding was not predicted under the applied computational model, the results support the potential of these sequences to interact with Fe²⁺. These findings provide molecular and chemical insights supporting the iron-binding potential of LMPH-derived peptides and highlight their future potential as functional ingredients for preventing and managing iron deficiency. Full article

Increasing water demand and the rising complexity of wastewater matrices, driven by pharmaceuticals, personal care products, and recalcitrant industrial contaminants, require advanced catalytic solutions capable of efficient mineralization under sustainable conditions. Solar-driven processes have attracted growing attention; however, ultraviolet disinfection, heterogeneous photocatalysis, and photo-Fenton systems are commonly treated as independent approaches without mechanistic integration. This review presents a unified photonic–thermal catalytic framework for solar-driven wastewater treatment, emphasizing the interplay between photon absorption, charge-carrier separation, reactive oxygen species generation, and radical-mediated oxidation pathways. The contributions of ultraviolet, visible, and infrared radiation are analyzed in terms of catalyst activation, persulfate and ozone activation mechanisms, and temperature-enhanced reaction kinetics governed by Arrhenius behavior. Particular attention is given to photothermal effects that modulate surface reaction rates, mass transfer, and catalyst stability. By integrating mechanistic insights with reactor-level considerations, this work provides a rational basis for the design of robust solar catalytic systems with enhanced activity, selectivity, and scalability for real wastewater applications. Full article

The persistence of azo dyes in industrial effluents poses significant environmental risks; therefore, there is a need to develop effective adsorbents. This study investigates the efficiency of a Cu₂O/CuO nanocomposite as an adsorbent for the removal of a model dye, methyl orange (MO), from aqueous solutions. The material was characterized by XRD, SEM and BET analyses, revealing a dominant Cu₂O phase (96 wt%) with CuO fractions, and an average particle size of ~18 nm paired with a specific surface area of 19.54 m² g⁻¹. FTIR and TOC assays revealed the adsorption and degradation of MO by action of the nanocomposite. Operational parameters such as adsorbent dosage, initial dye concentration, pH, and the point of zero charge (PZC) were investigated. Under the optimized conditions, the nanocomposite achieved a dye removal efficiency of 97.0%. The kinetic results showed a strong correlation with the pseudo-second-order model. Furthermore, isotherm analysis revealed that the adsorption process is best described by the Langmuir–Freundlich model, demonstrating an outstanding maximum theoretical adsorption capacity (q_max) of 254.76 mg g⁻¹, which closely aligns with the experimental value (249.48 mg g⁻¹). The findings demonstrated that the synthesized Cu₂O/CuO nanocomposite acts as an efficient and promising adsorbent for the remediation of dye-contaminated waters. Full article

This study investigated whether cooked green beans, a discarded agro-industrial material, can partially replace commercial chicken feed to improve the performance of the edible cricket Gryllus madagascarensis, while accounting for the strong effects of rearing density. A two-by-two factorial experiment was conducted in which crickets were reared at low (500 individuals per box) or high density (2500 individuals per box) and fed either standard chicken feed or the same feed supplemented with cooked green beans, with twenty replicates per treatment. Survival, chicken feed consumption, biomass yield, frass production, efficiency of conversion of ingested feed, and approximate digestibility were measured over the rearing period. Survival increased from 30.0% to 32.9% at low density and from 11.7% to 13.2% at high density, while biomass yield increased from 117.2 g to 129.7 g and from 194.4 g to 231.2 g, respectively. Frass production also increased under supplementation. In contrast, individual body weight was not improved, indicating that higher biomass production resulted mainly from increased survival rather than faster growth. Rearing density remained a major determinant of performance, with low density favoring individual size and survival, and high density maximizing total biomass. Overall, partial replacement of commercial feed with cooked green beans improved survival, biomass yield, and frass production, supporting the use of plant-based wastes to enhance the sustainability of cricket farming. Full article