Search Results (16,089)

In the context of Industry 5.0, human–robot collaboration increasingly demands intuitive, safe, and sensorless interaction for tasks such as hand-guided teaching and concurrent manipulation. However, conventional admittance control systems are prone to instability due to abrupt changes in human arm stiffness and their reliance on accurate dynamic models. To address these challenges, this paper proposes a sensorless external force estimation and variable admittance control method that models robot dynamic uncertainties and interaction forces as normally distributed stochastic quantities. An improved particle swarm optimization algorithm is introduced to calibrate the variance parameters, enhancing estimation accuracy and robustness. Furthermore, an energy-based variable admittance control strategy is developed, which preserves system passivity by adaptively adjusting inertia and damping gains based on real-time energy variations. The proposed method was validated on a redundant robot platform. Experimental results show that the external force and torque estimation errors remain below 3 N and 3 N.m, respectively, with lower detection delays and errors than those of a first-order generalized momentum observer in collision detection. Variable admittance experiments demonstrate that the system maintains passivity and stable interaction even under sudden arm stiffness changes. The approach is well-suited for industrial applications requiring safe, sensorless, and compliant human–robot collaboration. Full article

This paper presents an integrated techno–economic framework for coordinated grid-to-vehicle and vehicle-to-grid (G2V–V2G) operation in unbalanced distribution networks. A hardware-compatible bidirectional charger with nested AC/DC and DC/DC control loops, together with a rule-based energy management system (EMS), enables seamless mode transitions while enforcing state-of-charge (SoC) and network constraints. A probabilistic Monte Carlo study on the IEEE 13-bus feeder shows that uncoordinated G2V charging induces adverse grid impacts such as voltage stress, line-ampacity violations, and transformer overloading, whereas EMS-driven V2G support improves voltage by 2–4%, reduces line loading by 15–25%, and lowers transformer stress by up to 10%. To align these technical benefits with economic incentives, a bi-level Stackelberg model is formulated where the utility updates locational energy prices based on combined voltage, line ampacity, transformer loading stress indices and EVs choose profit-maximizing nodes, modes and power levels. The interaction converges to a Stackelberg equilibrium with a clear win–win situation; the feeder’s average locational energy price falls entirely within the win–win region, yielding positive per-session profits for both the EV (≈$0.80) and the utility (≈$0.48) while reducing feeder stress. These results demonstrate that stress-aware locational pricing, combined with detailed converter-level control provides a technically robust and economically sustainable pathway for large-scale EV integration. Full article

Background/Objectives: This secondary and exploratory meta-analysis re-evaluated 30 randomized controlled trials on free and added sugars (FS) detailed in the European Food Safety Authority’s (EFSA) report on the tolerable upper intake level for dietary sugars, focusing on the influence of food source (beverages, foods, or mixed) on cardiometabolic and anthropometric health. Methods: The EFSA’s method of analyzing the relative FS intake (difference between treatment and comparator arms, Δ%E^fs) was used, with further adjustment for the reported intake of all sources of FS and energy. The EFSA’s “high vs. low” random-effects meta-analysis comparing groups with the highest and lowest FS intake was replicated, and additional exploratory dose–response meta-regressions (linear and non-linear) were performed, stratified by food source. Given the secondary and observational nature of the analysis, all source-stratified findings should be interpreted as hypothesis-generating, rather than causal. Results: There were no interactions between Δ%E^fs and food source for any outcome, and within a source there were linearly positive and statistically significant regressions for body weight (mixed), low-density lipoprotein cholesterol (LDL-C, foods), and uric acid (beverages). Across 13 outcomes, Δ%E^fs was positively and linearly related to greater fasting glucose, high-density lipoprotein cholesterol (HDL-C), and LDL-C, and non-linearly to body weight. However, the data were limited in their representation of FS intake at typical population levels, and there were insufficient data to investigate the effect of FS from foods on most anthropometric outcomes. Conclusions: Meta-regressive dose–responses revealed little relationship between Δ%E^fs from specific food sources and health outcomes, but such effects might be masked by confounding factors. Future trials that test realistic intakes of FS across diverse food matrices and account for dietary compensation would help to overcome limitations in the body of evidence. Full article

The efficient recovery of platinum group metals (PGMs) from decoppered anode slimes is essential for sustainable resource management, yet the atomic-level mechanisms underlying their capture remain unclear. Herein, first-principles calculations were employed to elucidate the microscopic interactions by which bismuth acts as a trapping agent for PGMs (Ru, Ir, Pt, Rh, Os, Pd) and to determine the effects of four representative impurities (As, Sb, Pb, Si). The results demonstrate that pristine Bi(001) exhibits strong chemisorption toward all six PGMs, as proved by the large charge transfer, significant electron sharing and pronounced p-d orbital hybridization. Furthermore, these impurities spontaneously incorporate into the Bi(001) surface due to the large binding energy. Crucially, some impurities such as As and Si function as potent surface activators rather than detrimental contaminants. These dopants significantly enhance the PGM binding strength by inducing intense localized charge redistribution and establishing strong orbital hybridizations among the Bi-5d, PGM-d and p orbitals of dopants. Overall, this work provides a theoretical foundation for strategically utilizing the impurities to optimize the recovery of PGMs in complex smelting systems. Full article

Constructed wetlands (CWs) are a low-energy alternative for treating dye-containing wastewater; however, the mechanisms enabling azo dye removal without external carbon supplementation remain unclear. This study demonstrates that azo dye reduction can proceed under oxic bulk conditions in CWs through vegetation-induced microscale redox heterogeneity. Lab-scale CWs planted with cattail and papyrus were evaluated for the removal of Reactive Orange 16 (RO16, monoazo) and Reactive Black 5 (RB5, diazo) at influent concentrations of 10–50 mg/L under varying ambient temperature (2–36 °C) and hydraulic retention time (1–15 days). Vegetated CWs consistently outperformed the unplanted system, achieving 60–95% removal for RO16 and up to 98% removal for RB5, whereas the unplanted CW showed substantially inferior performance, with removal efficiencies below 54% for RO16 and below 37% for RB5. Dye-decolorizing bacteria, including Priestia megaterium and Clostridium spp., were isolated exclusively under anaerobic conditions from vegetated CWs despite oxic bulk dissolved oxygen levels. The isolates did not decolorize dyes under aerobic conditions or when dyes were provided as sole carbon sources, indicating that azo dyes functioned as electron acceptors and required additional electron donors. These results suggest that vegetation promotes localized reductive microenvironments and supplies endogenous organic carbon, enabling anaerobic azo bond reduction within otherwise oxic systems. The findings indicate a mechanistic basis for plant–microbe interactions in CWs and support the design of sustainable treatment systems for dye-containing wastewater without external carbon input, particularly in warm regions. This study resolves a long-standing question of how azo dye reduction proceeds in CWs without external carbon input. Full article

Emergency locator transmitters (ELTs) are key safety systems for post-crash aircraft localization and search-and-rescue operations. In more electric aircraft (MEA), however, their design and operation are increasingly influenced by complex electrical architectures, tighter equipment integration, and more demanding electromagnetic environments. This paper presents a narrative literature review of ELT technology from a MEA-oriented perspective. A practice-oriented narrative approach is adopted, examining ELTs through a dual lens: the evolution of the search and rescue (SAR) ecosystem and the progressive electrification of aircraft systems. The review addresses ELT fundamentals, classifications, operating principles, and interaction with the Cospas-Sarsat infrastructure, and examines the transition from legacy analog beacons to modern 406 MHz digital systems incorporating GNSS positioning, MEOSAR capabilities, second-generation beacon functionalities, and distress tracking features. Particular attention is given to integration challenges in MEA platforms, including autonomous energy supply, battery endurance, power quality disturbances, electromagnetic compatibility, installation robustness, antenna survivability, and certification constraints. The analysis highlights that ELT performance in MEA depends not only on the beacon itself, but also on the coupled interaction among device design, installation conditions, and the electrical environment. Finally, the review outlines research priorities for next-generation ELTs, including improved survivability assessment, energy-aware architectures, integration strategies based on electromagnetic compatibility, and certification-ready solutions compatible with future aircraft platforms. Full article

Agrivoltaics (AV) has emerged as an integrated land-use innovation capable of simultaneously addressing food, energy, and water challenges, yet its systemic implications for farming system sustainability remain insufficiently synthesized. This review adopts a farming system dynamics perspective to examine how AV systems reorganize biophysical, ecological, and socio-economic interactions across agroecosystems. Drawing upon agroecological principles, pathways of sustainable intensification and ecological intensification, and resource-loop strategies in circular economy, we identify the key elements and cause-and-effect relationships that shape AV system performance. Evidence indicates that the co-location of photovoltaics (PV) structures and crop cultivation generates new system properties, altered light distribution, moderated microclimates, redistributed soil moisture, and diversified production functions that influence productivity, resource-use efficiency, ecological services, and farm resilience. Using causal loop analysis, we conceptualize four central feedback dynamics: (i) PV–crop trade-offs and spatial-sharing relationships; (ii) microclimate modifications and crop physiological responses; (iii) ecological performance and landscape-level interactions; and (iv) circularity loops connecting resource conservation, renewable-energy substitution, soil processes, and material flows. This feedback collectively determines eco-efficiency outcomes, including enhanced land-equivalent productivity, improved water-use efficiency, strengthened regulating services, and reductions in external energy dependence. At the farming-system scale, AV diversifies income streams and stabilizes yields under climatic variability, whereas at the landscape scale, it fosters multifunctionality by supporting regenerative resource flows and ecological resilience. Building on these insights, we propose an integrated framework that links agroecological elements with dynamic feedback structures to guide context-specific AV design, management, and governance. This system-oriented synthesis provides a foundation for future research and policy efforts aimed at optimizing AV as a circular, resilient, and sustainable farming system innovation. Full article

This study was conducted to evaluate the effect of varying dietary energy levels on milk production, feed intake, nutrient digestion and metabolism, and antioxidation function of lactating donkeys, and integrating 16S rRNA gene sequencing, metabolomics, and proteomics to comprehensively reveal the underlying regulatory networks. A single-factor, completely randomized design was used in this study. Twenty-four Dezhou donkeys with similar milk yield (3.25 ± 0.46 kg/d), lactation days (29 ± 4.34 d), parities (4.17 ± 1.17), and body weight (256 ± 34 kg) were randomly divided into three dietary treatments (n = 8), and either a fed high-energy diet (DE = 13.1 MJ/kg, HED), medium-energy diet (DE = 12.4 MJ/kg, MED), and low-energy diet (DE = 11.7 MJ/kg, LED). The experiment period included 2 weeks for adaptation and 8 weeks for data and sample collection. Orthogonal polynomial contrasts were used to evaluate the linear and quadratic effects of increasing dietary energy. There were no significant interaction effects between dietary energy level and lactation week on any milk production and quality variables (p > 0.05). Increasing dietary energy level increased DMI, milk production, milk production efficiency, and milk components (linear and quadratic; p < 0.05). Increasing dietary energy improved the digestibility of DM and neutral detergent fiber (linear; p < 0.05), and crude protein digestibility, energy digestibility and metabolism, and nitrogen metabolism (quadratic; p < 0.05). However, it decreased BHBA and NEFA concentrations (linear; p < 0.05). Furthermore, increasing dietary energy first increased then decreased the activities of GSH-PX, SOD, and T-AOC (linear and quadratic; p < 0.05), while increasing the MDA content (linear; p < 0.05). Compared with HED and MED, LED increased the relative abundance of the genera unclassified_f_Syntrophomonadaceae, Christensenellaceae_R-7_group and Treponema_2. Compared with HED, MED increased the relative abundance of the genera Ruminiclostridium_5, Ruminiclostridium_1, Family_XIII_UCG-001, unclassified_o__Clostridiales and norank_f__PL-11B10. Thyroid hormone synthesis, tyrosine metabolism, and glutathione metabolism pathways are critical metabolic routes; these pathways can enhance energy metabolism and antioxidant function, thereby improving the milk production performance of lactating donkeys. In conclusion, the digestible energy of 12.40 MJ/kg was optimal for the milk performance of lactating donkeys, whereas excessively high dietary energy (13.1 MJ/kg) may reduce milk performance. Full article

Background/Objectives: Multiple sclerosis (MS) is a chronic, demyelinating and neurodegenerative disease frequently associated with dysphagia, nutritional imbalances, and alterations in body composition. This study aims to describe the anthropometric profile and body composition in people with MS, estimate the risk and type of dysphagia, analyse dietary intake and habits, and evaluate the evolution of these parameters over six months. Methods: This descriptive analytical longitudinal study included 30 patients with MS (20 women, 10 men), with a median age of 53.3 years at baseline and 54.0 years at final assessment. The prevalence of dysphagia risk was determined, dietary patterns and body composition were characterised, and their interactions were explored through two assessments conducted six months apart. Results: Overall, 90% of the sample had relapsing–remitting MS (RRMS). At both the initial and final assessments, the median BMI was above 25 kg/m² and a high prevalence of dysphagia risk (63.3% and 76.7%), particularly for liquids. Frequent inadequacies were observed in the intake of certain macronutrients and micronutrients, including energy, fibre, potassium and magnesium. Likewise, the analysis by food groups revealed low adherence to recommendations, particularly for fruits, cereals, legumes, fish and lean meats. No significant differences were detected between the two time points. Conclusions: Dysphagia, dietary intake, habits, and body composition are interconnected dimensions in MS; systematically integrating nutritional assessment and dysphagia screening into clinical practice would contribute to a more comprehensive management and to improvements in swallowing disorders and nutritional status in people with MS. Full article

Bioenergy production from agro-industrial waste has the potential to contribute to climate change mitigation. In Brazil, the pequi (Caryocar brasiliense Camb.) production chain makes an economic, environmental, and social contribution. However, the collection and processing of the fruit produce large amounts of waste, such as the peel, whose improper disposal leads to significant environmental impacts. This study evaluated how moisture and carbonization temperature influence the energy properties of charcoal briquettes made from pequi peel waste. Carbonization was performed at two final temperatures (360 °C/480 °C) with a heating rate of 1.5 °C min⁻¹ and residence times of 4 h and 5 h 20 min, respectively. Carbonization yields were calculated based on dry mass. Briquettes were produced from pequi peel at moisture contents of 5%, 7.5%, and 10% (wet basis). After carbonization, the charcoal briquette samples were characterized by proximate analysis, higher heating value (HHV), bulk density, energy density, and mechanical durability. Carbonization temperature exerted a more pronounced effect on the properties of the carbonized briquettes than the initial moisture content. Carbonization at 480 °C increased the fixed carbon content (76.38%, 74.25%, and 75.10% for treatments 1, 2, and 3) and the HHV (25.10–25.31 MJ kg⁻¹), while reducing the gravimetric yield (32.84–33.25%). The influence of moisture content was more evident in carbonizations carried out at 360 °C, indicating a temperature-dependent interaction. The use of pequi peel for solid biofuel production promotes the valorization of agro-industrial residues and supports strategies aimed at the circular bioeconomy and the decarbonization of the energy matrix. Full article

Cardiovascular and cerebrovascular diseases are serious threats to human health and impose a significant burden on individuals and society. As the two critical and complex organs with the highest metabolic demands, the brain and the heart form an interactive relationship through metabolic networks. As a core prerequisite for maintaining the normal physiological functions of the body, metabolic homeostasis is also a crucial foundation for ensuring the brain–heart synergy. When the human metabolism is in a stable state, the energy supply and material exchange of the brain and the heart can accurately match demand, the neural signal transmission is smooth, and the myocardial contraction is strong and regular—thus ensuring the coordinated and unified functions of these two vital organs. However, once metabolic homeostasis is disrupted, problems such as energy metabolism disorders will arise, which will then become a core inducing mechanism for cardiovascular and cerebrovascular comorbidities. This article presents a review of the research progress on the potential mechanisms of brain-heart interactions based on metabolic regulation from three aspects: neurometabolic, endocrino-metabolic and immune–metabolic regulation, the impact of cardiac function on brain metabolism, and the bidirectional regulation of brain-heart metabolism. Full article

Metal-functionalized boron nitride nanostructures represent promising platforms for lightweight solid-state hydrogen storage. In this work, we perform a comprehensive density functional theory (DFT) investigation of pristine and metal-decorated B₄N₄ quantum dots (M = Li, Ti) to evaluate their structural stability, adsorption energetics, and near-ambient storage performance. Pristine B₄N₄ is highly stable but interacts weakly with H₂ (E_ads ≈ −0.12 eV), leading to negligible uptake under operating conditions. Li decoration moderately enhances adsorption through charge-induced polarization (E_ads ≈ −0.15 eV) but offers limited stabilization beyond the first few molecules. In contrast, Ti decoration fundamentally reshapes the interaction landscape, strengthening electrostatic, polarization, and dispersion contributions and enabling significantly stronger yet reversible H₂ binding (E_ads ≈ −0.36 eV). Sequential adsorption calculations predict maximum theoretical capacities of 14, 18, and 20 H₂ molecules for pristine, Li-, and Ti-decorated systems, respectively. Grand canonical thermodynamics show that Ti–B₄N₄ retains nearly its full loading at 30 bar and 298 K, while pristine and Li-decorated clusters store only negligible amounts. Under desorption conditions (3 bar, 373 K), Ti–B₄N₄ releases most of its stored hydrogen, yielding an exceptional reversible capacity of 15.1 wt%. Energy decomposition analysis attributes this performance to cooperative electrostatic, polarization, and dispersion enhancements. Ti–B₄N₄ emerges as a highly promising theoretical candidate, warranting future experimental validation. Full article

This study examines how digital trade contributes to decarbonization within global value chains (GVCs), focusing on the roles of AI-enabled logistics, carbon pricing, and renewable energy policy. Using a monthly panel of 38 OECD economies from 2000 to 2024, we combine econometric models with machine-learning techniques to identify threshold effects and conditional relationships. The empirical specification includes fixed effects, interaction terms for AI-enhanced logistics, and carbon-pricing threshold analysis. At the same time, structural equation modelling (SEM) is used to assess mediation through renewable energy and regulatory stringency. The results indicate that GVC participation is significantly associated with lower CO₂ emissions (β = −0.064, p < 0.01). Digital trade alone is not statistically significant (β = −0.030), but its environmental effect becomes stronger when combined with AI-enhanced logistics. We identify a carbon-pricing threshold of USD 40 per tonne, above which emissions decline significantly (Δ = −15%, p < 0.01). Renewable energy adoption further reinforces the beneficial effect of digital trade under stronger regulatory conditions. These findings suggest that the emissions effects of digital trade are conditional rather than uniform and depend on complementary policy, technological, and energy factors. While the analysis is limited to OECD economies and monthly aggregate data, the study helps explain mixed findings in the literature by identifying the conditions under which digital trade is more likely to support emissions reduction. Full article

The human gut microbiota represents a complex and dynamic ecosystem of trillions of microorganisms that play a fundamental role in maintaining physiological homeostasis, regulating metabolism, and modulating the immune system. This narrative review explores the biochemical intricacies of the gut microbiome, focusing on the dominant phyla (Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Verrucomicrobia, Fusobacteria) and their specific contributions to host health. A critical emphasis is placed on the metabolic outputs of these microorganisms, such as short-chain fatty acids (SCFAs) like butyrate, which serve as vital energy sources and anti-inflammatory signaling molecules. Conversely, the review examines how dysbiosis, the disruption of microbial balance, is mechanistically linked to the pathogenesis of diverse conditions, including obesity, diabetes mellitus, inflammatory bowel disease (IBD), and gout. Furthermore, it highlights the profound impact of dietary interventions on microbial architecture, notably, how non-digestible carbohydrates promote beneficial taxa and eubiosis, while high-fat and high-sugar diets drive metabolic endotoxemia and systemic inflammation. By synthesizing current knowledge on microbial biotransformations of proteins and polyphenols, this work underscores the bidirectional relationship between nutrition and the microbiome. Ultimately, understanding these biochemical interactions is essential for developing targeted probiotic, prebiotic, and nutritional strategies to prevent and manage chronic metabolic and inflammatory disorders. Full article

Aflatoxin B1 (AFB1) is a potent mycotoxin threatening food and feed safety. Here, we report the identification and characterization of a Bacillus safensis-derived multicopper oxidase (BsaMCO) capable of efficient AFB1 detoxification. Recombinant BsaMCO exhibited robust in vitro activity, achieving >78% degradation of AFB1 under 24 h incubation at 37 °C. Optimization experiments revealed that enzyme concentration, pH, temperature, metal ions, and electron acceptors significantly influenced degradation efficiency, defining an operational window suitable for practical applications. LC–MS profiling suggested the presence of transformation products tentatively consistent with oxidative demethylation to aflatoxin P1 (AFP1) and with the formation of AFG2a-like products through subsequent hydration- and oxidation-related transformations. Molecular docking and 100 ns all-atom molecular dynamics (MD) simulations demonstrated stable binding of AFB1 in the T1 copper pocket. Van der Waals and electrostatic interactions, together with a persistent hydrogen bond at Gly323, facilitated single-electron transfer through the intramolecular T2/T3 copper cluster. Principal component and Gibbs free energy analyses confirmed a low-energy, stable conformational ensemble. HepG2 cell assays indicated that BsaMCO-degraded products substantially reduced cytotoxicity and apoptosis compared with native AFB1. Simulated feed experiments further validated enzymatic AFB1 degradation, with approximately 53% reduction after 24 h. Collectively, these findings establish BsaMCO as a safe and effective biocatalyst for AFB1 detoxification, providing mechanistic, structural, and cellular evidence supporting its application in food and feed safety. Full article