Search Results (201,328)

Background/Objectives: While traditional sports nutrition emphasizes high carbohydrate intake for endurance athletes, trained athletes may achieve metabolic adaptation to low-carbohydrate and ketogenic diets with maintained or improved performance outcomes. This systematic review and meta-analysis synthesize evidence on the effects of low-carbohydrate (≤130 g·day⁻¹ or ≤25% total energy) and ketogenic (<50 g·day⁻¹ or <10% total energy) diets on aerobic performance variables in trained athletes. Methods: A comprehensive search of five electronic databases (PubMed, SCOPUS, Web of Science, SPORTDiscus, and Cochrane Central Register of Controlled Trials) identified 33 aerobic-focused studies meeting comprehensive inclusion criteria. Selected studies examined trained athletes (≥6 months structured training, age 18–45 years) randomized to low-carbohydrate, ketogenic, or high-carbohydrate control conditions with outcome data on aerobic performance variables (VO₂max, time trial performance, time to exhaustion, and exercise economy) and metabolic markers (fat oxidation and substrate utilization). Quality assessment employed Newcastle-Ottawa Scale methodology. Results: Maximal aerobic capacity (VO₂max) was preserved in 50.0% of studies, with 11.1% documenting improvements. Submaximal exercise economy showed the greatest sensitivity, with 50.0% documenting impaired efficiency. Time to exhaustion demonstrated context-dependent effects, with 69.2% maintaining performance. All 30 studies measuring fat oxidation demonstrated consistent increases (+28% to +200%). Critically, temporal analysis identified a 1-week adaptation threshold: studies measuring outcomes within ≤7 days documented performance impairment, while studies measuring at >1 week consistently demonstrated maintained or improved performance. Conclusions: Low-carbohydrate diets reliably induce metabolic adaptation characterized by dramatically increased fat oxidative capacity. However, aerobic performance responses are nuanced, with preserved maximal aerobic power, transient submaximal efficiency impairments, and context-dependent endurance effects. Adaptation involves initial acute-phase decrements (≤7 days) followed by recovery. Evidence supports periodized carbohydrate strategies balancing metabolic adaptation benefits from low-carbohydrate training phases with carbohydrate requirements during competition. Full article

A reassessment of the Trp requirements for brown laying hens using the Trp biomass source allows an update of the nutritional recommendation, in addition to assessing whether biomass has an adjuvant effect in the diet. This research was carried out with the aim of evaluating the efficiency utilization of Trp and determining the ideal Trp intake for aged brown laying hens using the L-Trp biomass 60%. A completely random design was used, with eight treatments and eleven replicates, totaling 264 hens. The diets were formulated by supplementation technique using one basal diet with 0.112% of digestible Trp, resulting in amino acid levels that ranged from 0.112 to 0.225% of digestible Trp. The variables analyzed were performance and egg quality. When the effect of Trp levels (p ≤ 0.05) was detected, the model’s linear–plateau (LP), quadratic–plateau (QP), and the first intercept of the QP in the plateau of LP were adjusted to determine the ideal Trp intake. The results obtained show an effect of the treatments (p < 0.05) only on the performance variables. The first intercept results obtained were 186.2, 174.7, 182.7, and 182.5 mg/hen per day for egg production, egg mass, feed conversion ratio, and feed efficiency, respectively. Dietary supplementation with L-Trp biomass 60% effectively meets the nutritional requirements of aged brown laying hens, supporting efficient nutrient utilization without impairing productive performance or egg quality. Full article

Underground mines’ complex environments with dim lighting and high dust and humidity hamper feature extraction and reduce detection accuracy. To address this, we propose a low-light image enhancement-based target detection algorithm. Firstly, LIENet enhances low-light image quality and brightness via a dual-gamma curve and non-reference loss function-guided iterations. Secondly, the hierarchical feature extraction (HFE) method with a dual-branch structure captures long-term and local correlations, focusing on critical corner regions. Finally, HFE is combined with a feature pyramid structure for comprehensive feature representation through a top-down global adjustment. Our method, validated on a self-built dataset, outperforms other algorithms with an mAP@0.5 of 96.96% and mAP@0.5:0.95 of 71.1%, proving excellent low-light detection performance in mines. Full article

Physical and competitive environments play an important role in shaping athletes’ psychological development, motivation, and long-term engagement in sport. Guided by the Personal Assets Framework, this study examined basketball athletes’ perceptions of the quality of facilities and material resources across developmental stages and explored how these environments influenced developmental experiences and continuity in youth sport. A mixed-methods sequential explanatory design was employed. Quantitative data were collected from Brazilian basketball athletes aged 18–19 years (n = 141), followed by semi-structured interviews with 24 athletes. Distributional differences were explored using Kruskal–Wallis tests and associations using chi-square tests, while qualitative data were analysed through thematic analysis. Results indicated that both public and private gyms were commonly used practice settings; however, private facilities were consistently perceived as offering superior structural conditions and material resources, particularly from early adolescence onward. Although physical environments were largely perceived as non-limiting during childhood, their influence on psychological development, motivation, and perceived developmental opportunities became progressively more salient with age. Overall, the findings highlight the importance of adequate physical and competitive environments as key contextual components of athlete development, suggesting that long-term participation in youth sport is strongly influenced by the contexts in which athletes are embedded. Full article

This paper investigates the joint scheduling problem of battery electric bus fleets and plug-in charging infrastructure in an urban transit system. The operation of an electric bus network is inherently a multi-component system, where vehicle assignment, battery energy management, and charger capacity decisions interact and jointly determine system performance and cost efficiency. To capture these interdependencies, we propose a system-level integrated scheduling framework that simultaneously determines bus trip assignments, charging event timing and duration, and charger utilization plans. The problem is formulated as a continuous-time mixed-integer linear programming model that minimizes the total system cost, subject to operational feasibility, battery state-of-charge dynamics, and charger capacity constraints. To enhance computational tractability, a Lagrangian relaxation-based decomposition approach is developed, coupled with a linear programming-based diving heuristic. Computational experiments on benchmark instances demonstrate that the proposed framework produces high-quality system-level schedules with substantially reduced solution time compared with directly using a commercial solver. A real-world case study based on a large charging station in Beijing shows that the optimized joint schedules reduce the required fleet size from 22 to 13 buses and the number of chargers from five to two, leading to a 38.3% reduction in total system cost. These results highlight the effectiveness and practical value of the proposed approach for the planning and operation of urban electric bus transit systems. Full article

Multiple sclerosis (MS) is characterized by progressive mitochondrial dysfunction affecting complexes I, III, and IV of the electron transport chain, contributing to axonal energy failure and neurodegeneration. This review examines the potential of combining β-hydroxybutyrate (βHB), epigallocatechin-3-gallate (EGCG), and ellagic acid (EA) as a multi-target therapeutic strategy to restore mitochondrial function in patients with MS. Experimental and clinical studies demonstrate that each compound exerts complementary mechanisms. Ketone bodies provide an alternative energy substrate and restore complex I activity via sirtuin-dependent pathways. EGCG acts predominantly at the peripheral level by reducing systemic inflammation and oxidative stress. EA-derived urolithins effectively cross the blood–brain barrier to directly enhance mitochondrial biogenesis and respiratory chain function in the central nervous system. Clinical trials have reported improvements in fatigue, cognition, mood, and muscle function following supplementation with these compounds. The convergence of their actions on energy restoration, reactive oxygen species reduction, and epigenetic modulation of protective pathways suggests their synergistic potential. Optimized delivery strategies, including exogenous ketone salts, liposomal EGCG, and microencapsulated EA, may overcome bioavailability limitations and interindividual variability in the gut microbiota metabolism. Full article

Social sustainability remains the least operationalised dimension of sustainability research in tourism, particularly with regard to employment quality. Tourism growth is often assumed to generate positive social outcomes through job creation, yet limited empirical attention has been paid to whether tourism employment meets basic standards of decent work. The main objective of this study is to assess whether sustained employment growth in the Portuguese tourism sector has been accompanied by measurable improvements in employment quality, and to examine the implications of this relationship for the social sustainability of tourism development. Drawing on the International Labour Organization’s Decent Work Agenda, the study operationalises decent work as a core, though partial, dimension of social sustainability and develops a Social Sustainability Index in Tourism (SSIT). The index is constructed using longitudinal administrative labour data from the Portuguese tourism sector covering the period of 2010–2022 and integrates indicators related to employment stability, remuneration, working conditions, gender equality, and social protection through a transparent, theory-informed weighting scheme complemented by sensitivity analysis. The empirical results show that, despite substantial expansion in tourism employment, gains in job quantity were not matched by commensurate improvements in decent work outcomes. Persistent employment insecurity, low wage adequacy, and enduring gender inequalities continue to characterise the sector, indicating a structurally constrained pattern of social sustainability. The main contribution of the study lies in providing a replicable, employment-based composite indicator that enables systematic monitoring of social sustainability in tourism and empirically challenges growth-centred narratives that implicitly equate employment expansion with socially sustainable development. The SSIT is intended as a diagnostic and monitoring tool rather than a comprehensive evaluation of social sustainability, as it captures only formal employment and those dimensions of decent work observable in administrative data. Full article

Cooling curve analysis enables accurate determination of aluminum alloy solidification parameters while capturing important non-equilibrium phenomena that are difficult to resolve using thermodynamic models alone. Modern casting simulation tools such as MAGMASOFT and ProCAST provide advanced capabilities, including user-defined material databases and microstructure models, but their predictive accuracy depends strongly on the quality of alloy-specific input data. In particular, the effects of trace element variations and chemical modification treatments, such as strontium-induced depression of the Al–Si eutectic temperature, are not always quantitatively represented in generic databases. This study demonstrates that thermal analysis provides experimentally based solidification data under controlled cooling conditions representative of foundry practice. Cooling curve analysis directly records undercooling, recalescence, and modification-induced temperature shifts, including eutectic temperature changes of ~10 °C after strontium treatment, which significantly influence solidification kinetics and defect formation. A short industrial thermal analysis test enables the extraction of key parameters, including liquidus, eutectic, coherency, rigidity, and solidus temperatures; fraction-solid evolution; and latent heat release. When integrated into casting simulation databases, these experimentally derived parameters support improved modeling of feeding behavior, shrinkage porosity risk, hot tearing tendency, and microstructure development. The proposed approach positions cooling curve analysis as a practical complementary tool for calibrating and enhancing simulation input data under real alloy and process conditions. Full article

Despite the promising exploration potential of the tight bioclastic limestone in the Carboniferous Shiqiantan Formation (Shiqiantan Sag, Junggar Basin), its reservoir characteristics remain poorly constrained. In particular, the macro and microscopic features and the key factors controlling reservoir development are still not well understood. We combined core observation, cast thin-section analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), high-pressure mercury intrusion, nitrogen adsorption, and nuclear magnetic resonance (NMR) to systematically characterize the Carboniferous bioclastic limestone reservoirs and identify the factors controlling their development in the Shiqiantan Sag. This study develops a multi-scale quantitative framework that integrates mercury intrusion–withdrawal behavior, nitrogen adsorption, and NMR T₂ spectra to constrain pore connectivity and the contribution of microfractures in tight carbonate reservoirs, providing a transferable approach for reservoir evaluation beyond the study area. The results categorize three rock microfacies in the study area: Bioclastic micrite, Micritic bioclastic limestone, and Sparry Bioclastic Limestone. The reservoir space is predominantly composed of secondary pores, including intragranular dissolution pores, intercrystalline clay pores, and microfractures. The pore structures exhibit a marked contrast across the lithofacies: the sparry bioclastic limestone develops the most optimal pore-fracture composite system, The pore structures exhibit a marked contrast across the lithofacies, directly correlating with hydrocarbon accumulation. Specifically, the sparry bioclastic limestone develops a pore-fracture composite system characterized by 25–100 nm pore throats, corresponding to the primary oil-bearing intervals observed in drilling. In contrast, the bioclastic micrite limestone and micritic bioclastic limestone, despite exhibiting localized nanoscale pores, lack effective connectivity (pore throats < 25 nm) and predominantly act as tight, dry layers with poor or no oil and gas shows, which endow them with the anomalous characteristic of relatively low porosity yet high permeability. This study reveals an integrated control on the development of tight bioclastic limestone reservoirs, in which sedimentary microenvironment and paleogeomorphology jointly determine the initial reservoir framework, while subsequent structural fractures and associated diagenetic dissolution play a critical role in modifying pore structures and enhancing reservoir quality. Sedimentary microfacies distribution, controlled by paleogeomorphologic variations, dictated the initial reservoir fabric. Subsequently, fracture systems generated by tectonic uplift, coupled with dissolution from meteoric freshwater leaching and organic acids, facilitated the development of secondary pores. Ultimately, the resulting optimization of the pore structure governs the final reservoir quality. The sparry bioclastic limestone is identified as the most promising exploration target in the study area. Its favorable reservoir quality is mainly attributed to its development on palaeogeomorphic and structural highs, where enhanced hydrodynamic energy and subsequent fracture-related dissolution significantly improved pore connectivity. These high-quality reservoirs are widely developed on gentle slope profiles and similar high-quality reservoirs may also locally occur at isolated palaeogeomorphic highs within steep-slope settings, as demonstrated by individual wells. Full article

The Arctic Puffin Optimization (APO) Algorithm is a recently proposed metaheuristic algorithm that has been widely applied to solve optimization problems in continuous spaces. However, it cannot be directly used to solve combinatorial optimization problems in discrete spaces. To address these limitations, a Binary Arctic Puffin Optimization (BAPO) Algorithm is proposed, focusing on developing transfer functions to convert the algorithm’s continuous solutions into discrete binary solutions. Two primary transfer function types, S-shaped and V-shaped, are commonly employed. Experimental analysis identifies optimal functions for different algorithmic stages. These are then integrated with a conversion factor to propose a hybrid transfer function for the binarization of the Puffin Optimization Algorithm. To address the issue of slow particle convergence in the later stages of the exploration phase and the tendency to overlook high-quality solutions during the exploitation phase in the binary algorithm, logarithmic inertia weight and the golden sine strategy are incorporated, respectively, for improvement. Simulation experiments were conducted to solve both single-dimensional and multidimensional 0–1 knapsack problems. Experimental data and convergence curves, including mean values and standard deviations, were analyzed. The results demonstrate that the binary Arctic puffin optimization algorithm exhibits excellent convergence, stability, and fast search speed. Full article

The surface quality and production efficiency of continuous-casting steel slabs are predominantly determined by the performance of the mold. To address slab corner defects and enhance operational stability, this study systematically optimized two key components: the broad-face clamping mechanism and the narrow-face copper plate. A disk spring–hydraulic composite clamping mechanism was designed and subjected to mechanical analysis to ensure sufficient and reliable clamping force under high-load casting conditions. Meanwhile, based on the principle of solidification shrinkage, an external chamfer structure for the narrow-face copper plate was proposed to improve heat transfer uniformity at the slab corner. Engineering design calculations and practical application in an export-oriented wide-and-heavy slab continuous-casting project (specification: 250 mm × 2500 mm) demonstrated that the optimized clamping mechanism provides enhanced structural rigidity, while the new narrow-face copper plate effectively mitigates corner cracks and reduces wear. This integrated design approach significantly improves slab surface quality and extends component service life, yielding substantial economic benefits. Full article

High-precision thermal regulation in semiconductor process equipment is critical for product quality, yet it is challenged by actuator transport delays, limited actuator bandwidth due to hardware dynamics, and broadband inlet disturbances in temperature-controlled process fluids. This paper presents a systematic solution integrating architecture optimization with a physics-informed hybrid prediction model to enable effective feedforward compensation. Frequency-domain analysis justifies placing the temperature fluctuation attenuator (TFA) upstream of the heater to filter mid-to-high-frequency disturbances without compromising feedback stability. To address actuation delays, a Physics-CNN-LSTM predictor is developed using a residual learning strategy. This framework employs a mechanism model for baseline estimation and a deep learning network to correct persistent low-frequency residuals caused by unmodeled dynamics. Comparative experiments on industrial data demonstrate that the model achieves a Root Mean Square Error (RMSE) of $3.56\times {10}^{-5}$ K under low-to-mid-frequency inlet disturbances, reducing error by approximately 51.8% compared to a standard LSTM. The model also exhibits strong robustness against disturbance frequency shifts ($R^2>0.996$ on unseen data). Furthermore, closed-loop simulations confirm that the proposed feedforward compensation enhances temperature stability in high-precision thermal control. Full article

Low-frequency acoustic fields—common in ventilation ducts, building façades, and industrial infrastructure—remain an underutilized source for ambient energy harvesting, particularly in humid environments where conventional contact-based or mechanically resonant harvesters may degrade over time. This study introduces a theoretical framework for converting acoustic pressure oscillations into electrical power through acoustic–electrokinetic coupling and proposes the Acoustic Baroionic Harvester (ABH) as a solid-state concept combining a Helmholtz resonator with a charged nanoporous membrane. The model is derived from coupled electrokinetic and fluid-mechanical governing relations, leading to closed-form expressions for the open-circuit voltage, internal electrokinetic resistance, and maximum deliverable power as functions of membrane surface charge, electrolyte properties, pore geometry, and resonance-induced pressure amplification. Numerical simulations are performed to validate the analytical scaling laws and to determine operating regimes that maximize power transfer to an external load. Under representative low-frequency acoustic excitation, the ABH predicts open-circuit voltages on the order of tens of millivolts and maximum power densities in the sub-microwatt-per-square-centimeter range. A compact CAD conceptual design tuned to approximately 120 Hz with a moderate resonance quality factor supports the feasibility of practical integration. The proposed approach enables micro-power generation from persistent low-frequency acoustic sources and provides a physically grounded pathway for self-powered sensing applications in built and industrial environments. Full article

This study assesses whether the mainstreaming hypothesis, derived from cultivation frameworks developed during the mass audience era, remains operative in a digital media environment characterized by fragmenting media and cultural taste publics. In particular, we consider evolving conceptions of mainstreaming that stimulated our research questions and hypotheses in four surveys conducted from 2015 to 2024. We broaden our view of media to see if entertainment content—especially film genres—can provide common ground in attracting people with little else in common. Results suggest that such “cultural mainstreaming” may occur by providing common gratifications and impact global indictors of our lives—happiness, community attachment, feelings about our quality of life, and perceived cosmopoliteness. But the results are limited to a general adult population, not the younger students studied. The findings apply only to the general adult population and not to the younger student sample examined. Overall, the results indicate that the cultivation effect is relatively weak; the small number of significant relationships observed does not appear to exceed what might be expected by chance. Taken together, these findings suggest that mainstreaming and media influence operate as more complex processes in the digital era. Full article

This paper proposes a hybrid quantum–classical framework for distribution network reconfiguration (DNR) under high distributed generation (DG) penetration, integrating nonlinear AC power-flow validation with the Quantum Approximate Optimization Algorithm (QAOA). Unlike prior quantum-assisted studies that rely on simplified DC or surrogate models, the proposed approach embeds AC-feasible loss evaluation directly within the combinatorial optimization loop. The methodology first evaluates all admissible switching configurations of the IEEE 33-bus system under DG integration using full AC power flow. The resulting loss landscape is compressed into a Quadratic Unconstrained Binary Optimization (QUBO) representation and mapped to an Ising Hamiltonian, enabling variational optimization via QAOA. The dominant configuration suggested by the quantum layer is subsequently validated through AC feasibility analysis. Simulation results show that the coordinated DG + QAOA strategy reduces active power losses from 282.938 kW (baseline) to 95.773 kW, corresponding to a 66.15% reduction relative to the original topology and an additional 20.62% improvement beyond DG-only operation. The minimum bus voltage increases from 0.8828 p.u. to 0.9531 p.u., satisfying IEEE 1547 limits, while requiring only two switching operations. These results demonstrate that embedding AC-consistent validation within a hybrid QAOA framework enhances physical realism, scalability, and solution quality for combinatorial optimization in active distribution networks. Full article