Search Results (423)

Research on educational virtual reality (VR) has focused on learning outcomes, but less on the design strategies that create those outcomes or whether benefits are consistent across different learners. This study created user experience (UX) design guidelines for educational VR by analyzing strategies from print, video, and digital media, then adapting their functions for immersive VR. A two-dimensional framework combined five instructional functions from Gagné’s events of instruction and Merrill’s four content types. Guided by cognitive load theory and multimedia learning theory, five guidelines were developed: Space-Centered Stimulus Presentation, Environment-Intrinsic Context Learning Guidance, Body-Tracking-Based Direct Performance Induction, Integrated Structural Real-Time Feedback, and Multi-Scenario Retention and Transfer Training. A CPR prototype focused on compression-only resuscitation was tested with 40 adults in experimental and comparison groups. The experimental group showed significantly larger gains in knowledge (r = 0.704, large), performance (r = 0.395, medium), and usability (r = 0.385, medium). An exploratory analysis found that all experimental participants improved, compared to 45% and 75% in the comparison group (Fisher’s exact p < 0.001 and p = 0.047). Semi-structured interviews with 22 participants revealed that both groups experienced hand-tracking errors; however, the comparison group also reported issues such as feedback separation, redundant presentation, and unclear flow, causing extraneous cognitive load, whereas the experimental group cited the spatially integrated guidance (heart character, sternum display) as beneficial for learning. These results suggest that VR design guided by these guidelines can lead to greater and more consistent learning improvements among users. Full article

Widespread antibiotic use in aquaculture has increased selective pressure on resident bacterial communities, accelerating the emergence of resistance in key pathogens and raising concerns for animal health, environmental microbiomes, and food-chain safety. Reducing dependence on therapeutic antimicrobials requires alternative strategies that remain effective under the processing and biosafety constraints of intensive production systems, where recurrent bacterial diseases continue to cause substantial economic losses. Live probiotics, currently the most extensively studied microbiome-based intervention, have practical limitations, including reduced viability during feed pelleting and extrusion, transient gut colonization, strain-specific host responses, biosafety concerns related to horizontal transfer of antimicrobial-resistance genes, and variable regulatory requirements across regions. Postbiotics, defined as preparations of non-viable microbial biomass, with or without metabolites, that confer a demonstrated health benefit in the target host, and paraprobiotics, which emphasize inactivated whole-cell preparations that preserve surface-associated microbial molecular patterns, may help address several of these constraints. These approaches offer improved compositional definition, greater feed-processing stability, and a potentially more favorable biosafety profile. Because they are non-viable, their anti-pathogen effects do not depend on growth or competitive colonization but may instead involve preformed antimicrobial compounds retained in some preparations, interference with pathogen attachment, modulation of the intestinal environment, reinforcement of barrier function, and stimulation of host immune responses. This review synthesizes current evidence on postbiotics and paraprobiotics in aquaculture, with emphasis on structural classification, pattern-recognition receptor signaling, intestinal barrier function, innate immune priming, encapsulation technologies, and translational readiness. Taken together, available evidence supports postbiotics and paraprobiotics as promising, but not yet fully characterized, alternatives to live probiotics within antibiotic-reduction strategies for aquaculture. Progress toward commercial application will depend on resolving key questions related to dose–response relationships, processing stability in formulated feeds, and species-specific efficacy. Full article

Understanding the strain-dependent electronic response of carbon nanotubes is important for nanoelectronic applications in which mechanical deformation serves as a functional tuning mechanism. This study developed a physics-informed machine learning framework for modeling biaxial strain-induced band gap variation in zig-zag single-walled carbon nanotubes (SWCNTs). A traceable density functional theory/Perdew–Burke–Ernzerhof (DFT/PBE) dataset was reconstructed from published band gap curves and comprised 144 records representing 16 zig-zag SWCNT chirality groups, from (8,0) to (23,0), at nine nominal biaxial strain levels between −10% and +10%. The absolute band gap was reformulated as a baseline-relative target ($\mathsf{\Delta }{E}_g$) representing the strain-induced variation from the chirality-specific unstrained state; this formulation assumes that the corresponding unstrained band gap is available for each chirality before prediction. Physics-informed descriptors included the chirality-derived diameter, chirality family, nominal strain, squared strain, and family–strain interaction terms. Predefined linear and nonlinear regression models were evaluated using repeated shuffled five-fold cross-validation, while transfer to unseen chirality groups was assessed using leave-one-chirality-out (LOCO) validation. Sensitivity analyses were additionally conducted to evaluate baseline uncertainty and digitization confidence. Within the represented chirality–strain domain, the best nonlinear configuration—support vector regression using diameter, squared strain, and family–strain descriptors—achieved a mean cross-validated coefficient of determination ($R^2$) of 0.880 for $\mathsf{\Delta }{E}_g$, compared with 0.786 for absolute $E_g$. Ridge regression using family–strain descriptors achieved a mean $R^2$ of 0.527, demonstrating that the baseline-relative target also contained an interpretable linear response component. The benefit of target reformulation was most evident in explained variance and fold-level stability, whereas differences in absolute error metrics were comparatively small. The best $\mathsf{\Delta }{E}_g$ model achieved a mean LOCO $R^2$ of 0.636, although substantial fold-level variation indicated that transfer remained strongly dependent on the held-out chirality group. The findings remained stable under chirality-specific $E_{g0}$ perturbations of up to ±0.020 eV and after exclusion of three low-confidence digitized records. Overall, baseline-relative target formulation and chirality-aware descriptor design improved the modeling of strain-induced electronic responses under limited-data conditions. The results should nevertheless be interpreted as a proof of concept within the represented zig-zag SWCNT domain rather than as a universal predictor across the complete CNT design space. Full article

Gut microbial metabolism links intestinal ecology with systemic physiology and neural pathology, but its effects vary across disease stage, tissue compartment, and host background. This review uses Alzheimer’s disease (AD) as the principal model and compares selected features with Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). Across the AD continuum, fermentation-related changes appear in prodromal cohorts, whereas broader alterations in amino acid products, host–microbial co-metabolites, bile acids, and lipids accompany mild cognitive impairment and dementia. These group-level patterns do not constitute a fixed patient trajectory. Microbial production, intestinal absorption, hepatic conversion, renal clearance, barrier integrity, and tissue-specific receptors jointly determine biological exposure. Experimental studies connect short-chain fatty acids and indole derivatives with epithelial and neuroimmune homeostasis, while imidazole propionate, trimethylamine N-oxide, selected kynurenine products, and remodeled bile acid pools engage vascular, inflammatory, amyloid, or tau-related pathways. Cerebral pathology can also remodel the intestinal ecosystem, creating reciprocal feedback. Apolipoprotein E4 modifies lipid handling, vascular permeability, and immune responses, helping to explain why comparable metabolic profiles may carry different consequences among individuals. Translation therefore requires more than a change in community composition. Trials must verify microbial function, metabolite target engagement, AD biomarker response, and clinical benefit in appropriately stratified participants. Shared pathways in PD and ALS provide comparison points, but disease-specific cells, proteinopathies, and treatment exposures constrain direct transfer of AD-derived targets. Full article

Lithium–sulfur (Li–S) batteries are promising next-generation energy-storage systems but are severely hindered by polysulfide shuttling, sluggish sulfur redox kinetics, and unstable Li₂S nucleation/growth behavior. Herein, a multifunctional MXene/carbon nanotube/poly(ethylene oxide) (MX/CNT/PEO)-modified separator is developed to regulate polysulfide behavior and improve interfacial electrochemical stability. In this composite architecture, MXene provides polar sites for lithium polysulfide adsorption, while carbon nanotubes construct interconnected conductive networks and suppress MXene restacking. The incorporation of poly(ethylene oxide) improves interfacial continuity and introduces additional oxygen-containing functionalities within the composite framework. Benefiting from the integrated effects of polar adsorption, conductive pathways, and structural integration, the MX/CNT/PEO-modified separator effectively suppresses polysulfide diffusion, reduces charge-transfer resistance, and promotes more favorable Li₂S nucleation/growth behavior. Electrochemical analysis shows that the charge-transfer resistance decreases from 175.9 Ω for pristine PP to 15.7 Ω for the MX/CNT/PEO@PP separator, corresponding to a 91.1% reduction. Potentiostatic Li₂S deposition analysis further supports favorable Li₂S nucleation/growth behavior on the MX/CNT/PEO-modified interface, after background subtraction. As a result, the Li–S cell with the MX/CNT/PEO@PP separator delivers a high initial discharge capacity of 1613 mAh g⁻¹ at 0.1 C and maintains average capacities of 1331.1 and 803.1 mAh g⁻¹ at 0.1 and 2 C during rate testing, respectively. During long-term cycling at 2 C, the cell retains 319.3 mAh g⁻¹ after 1000 cycles, with an average capacity decay rate of 0.064% per cycle. This work provides a rational composite-interlayer design strategy for multifunctional separator materials in high-performance Li–S batteries. Full article

Commercial carbon-based electrodes such as graphite felt and carbon felt in all-vanadium redox flow batteries suffer from inherent drawbacks, including slow vanadium ion redox kinetics, insufficient intrinsic catalytic activity, fiber corrosion, and functional group loss under strong acidic oxidative conditions, significantly limiting battery energy efficiency and long-term operational reliability. Rare-earth elements, with their unique 4f electron shell structure, tunable electronic levels, abundant surface oxygen vacancy defects, and strong coordination ability, offer a dual pathway—electronic and microstructural modulation—to optimize the interfacial electrocatalytic behavior of carbon electrodes, providing a novel materials system to overcome electrode performance bottlenecks in vanadium batteries. This review systematically summarizes recent advances in rare-earth-functionalized carbon electrodes and electrocatalysts for vanadium redox flow batteries, elaborating on core modification strategies, performance enhancement trends, and synergistic catalytic mechanisms. It also presents quantitative experimental results from the literature to clearly demonstrate the benefits: CeO₂-modified graphite felt at 0.2 wt% shows a 10.8% increase in energy efficiency compared to pristine graphite felt at a current density of 200 mA·cm⁻², while multi-rare-earth co-doped carbon electrodes achieve a 65% reduction in charge transfer resistance relative to unmodified electrodes. The review systematically categorizes two dominant modification routes—surface nano-decoration with rare-earth oxides and lattice bulk doping with rare-earth elements—and summarizes design principles and enhancement mechanisms of diverse composite catalytic systems, including rare-earth–carbon nanocomposites, rare-earth-based heterojunctions, and porous rare-earth catalysts. It further analyzes critical challenges in current research, such as unclear long-term stability mechanisms, high costs of high-purity rare-earth raw materials, immature large-scale fabrication processes, and limited in situ dynamic characterization techniques. Compared with existing reviews, this work clearly distinguishes between surface loading and lattice doping as two distinct rare-earth modification approaches, clarifying their differences in active site formation, electronic regulation logic, and cycling stability. It establishes a comprehensive theoretical framework for the coupled electronic–geometric effects in rare-earth-modified carbon electrodes, linking the intrinsic physicochemical properties of rare earths, material microstructure design, and battery electrochemical performance. Moreover, it innovatively proposes a pathway toward full-lifecycle recycling and reuse of rare-earth-based catalytic electrodes for industrial implementation. This review provides a complete theoretical foundation for developing high-performance, long-cycle, low-cost vanadium redox flow battery electrode materials and supports their engineering scale-up, contributing to the development of large-scale, long-duration energy storage technologies. Full article

Urban regeneration has become a central focus in global urban studies, increasingly linked to the dual imperatives of sustainability and urban resilience. According to Christopher Alexander’s theories of living structure and pattern language, traditional built environments emerge through progressive adaptation rather than top-down design. Moreover, historic urban fabrics evolve through continuous refinement of spatial solutions that simultaneously respond to environmental, functional, and social needs. Therefore, this study situates urban regeneration within a theoretical framework that recognizes traditional settlements as complex adaptive systems rather than static heritage. Chinese urban villages (Chengzhongcun) and Spanish Suelo Urbano no Consolidado (SUNC, Unconsolidated Urban Land) areas represent two contrasting forms of urban socio-spatial systems engulfed by urban expansion, both characterized by dense, historically rooted morphologies and incomplete infrastructure. As Chinese urban villages shift from a demolition–reconstruction model toward more sustainable regeneration approaches, this study compares Beijing’s Cuigezhuang and Málaga’s El Perchel through spatial analysis and stakeholder surveys. Alexander would argue that the demolition–reconstruction model disrupts the evolutionary processes that generate coherent urban fabrics. The research evaluates how differing planning systems foster or constrain sustainable development and social-spatial resilience in regeneration processes. Urban resilience is explicitly defined here as the capacity of urban communities and spatial structures to adapt to change, withstand pressures, and maintain social cohesion, accessibility, and local identity, while ecological and economic resilience are not measured in this study. Findings demonstrate that Spain’s incremental, participatory approach—anchored in Planes Especiales de Reforma Interior (PERI, special plans for inner urban renewal) and land readjustment (equitable distribution of costs and benefits) mechanisms—significantly outperforms China’s state-led demolition-based model in supporting long-term sustainability, heritage integrity, community cohesion, and spatial continuity. Spain’s legally embedded participation and in situ rehabilitation strategies offer transferable lessons for China’s evolving sustainable and resilience-oriented regeneration paradigm. Full article

Parametric insurance products for tropical cyclone risk transfer typically rely on maximum wind speed (MWS) as the only trigger parameter. While interpretable and widely used, it nevertheless leaves a substantial portion of loss variance unexplained. This paper proposes and evaluates two dual-parameter extensions of the cat-in-a-grid parametric framework, combining MWS with either the radius of maximum wind speed (RMW) or minimum central pressure (MCP). Two integration strategies are examined: a stratified approach, in which events are partitioned by the secondary parameter and separate MWS-based loss functions are fitted within each stratum, and a multivariable approach, in which both parameters enter a bivariate polynomial loss function directly without event partitioning. Four dual-parameter configurations are evaluated against a single-metric MWS baseline using 5-fold cross-validation (CV) on a large stochastic catalog for Jamaica, across four training data strategies. Results show that RMW improves predictive accuracy over the MWS baseline under most training strategies, although the multivariable extension underperforms the baseline under binned training. MCP, by contrast, offers only a marginal benefit that disappears under binned training, consistent with its strong correlation with MWS. In addition, results also show that multivariable models require IQR-filtered raw training to realize their potential, while stratified models perform best with binned training. Full article

A collision-free path is not sufficient for visibility-dependent mobile robot tasks: a moving obstacle can block the camera–target line of sight and cause inspection or visual-servoing failure even when the robot remains physically safe. Maintaining visual contact with targets is therefore important in Industry 4.0 environments, yet visibility-preserving maneuvers can conflict with navigation progress and collision avoidance. This work presents the Visibility-Informed Safety and Target Awareness framework with control barrier function filtering and occlusion-evasive local replanning (VISTA-CBF+ELR). The architecture combines visibility-risk planning, target-bearing control, an ELR supervisor, and a CBF quadratic program that keeps collision constraints hard while relaxing field-of-view and occlusion requirements through slack. Counterproductive interventions are limited through persistence, benefit–cost and feasibility gates, progress protection, bounded dwell, recovery, and cooldown. In locked factory simulations, redesigned VISTA achieved 67% and 73% strict-goal success under clean and nominal sensing, whereas Visibility-CEM-2D achieved 87% and 86% but with lower clearance. In matched Gazebo trials, strict success was 19/30 for redesigned VISTA, 26/30 without ELR, and 16/30 for Nav2 Smac+MPPI; zero-clearance collisions were 8/30, 3/30, and 14/30, with no difference surviving multiplicity correction. A separate CEM stress test sustained 6.875 Hz optimization, missed 26.31% of 100 ms deadlines, and held commands on 31.35% of ticks. The results demonstrate repair of the ELR pathology and conditional visibility-risk reduction while exposing safety–visibility trade-offs, transfer limitations, and real-time constraints. Full article

Estimating lithium-ion battery state of health (SOH) across operating conditions is challenging because operating profiles, measurement characteristics, and degradation trajectories differ among domains. This study proposes a physics-informed transfer learning (PITL) framework that combines a common health descriptor space, parameter function decomposition, and PINN–DeepHPM regularization. Open-circuit voltage reconstruction is used before feature extraction for dynamic profiles, whereas constant-current data are processed directly in the same descriptor space. During target-domain adaptation, selected shared-representation layers are frozen and the predictor and dynamic constraint parameters remain trainable. In the predefined Cell_1# tests, the resulting feature transfer configuration reduced RMSE relative to full fine-tuning by 23.53% for 21700_Dynamics and 61.78% for CEPREI. In leave-one-cell-out validation, PITL and full fine-tuning had comparable mean RMSEs on 21700_Dynamics, whereas full fine-tuning was more accurate on CEPREI. Freezing approximately 48% of the parameters reduced adaptation time and peak GPU memory. Thus, partial freezing can lower adaptation cost, but its accuracy benefit is target dependent. Full article

Individuals with lower-limb mobility impairment often experience fear of falling and difficulty coordinating with caregivers during transfer tasks. Therefore, safe, stable, and easy-to-operate collaborative transfer assistive equipment is urgently needed. This study proposes a Health Belief Model-driven design method for transfer assistive equipment, aiming to translate users’ risk perceptions and behavioral needs into implementable structural design strategies. First, transfer-related behavioral characteristics were analyzed according to the six constructs of the Health Belief Model. Second, the KJ method was used to classify original user requirements and establish a hierarchical requirement model, while the Fuzzy Analytic Hierarchy Process was applied to calculate requirement weights. Third, Quality Function Deployment and the House of Quality were used to transform user requirements into technical characteristics, through which four key technical contradictions were identified: anti-tipping stability versus lightweight design, status feedback versus process simplification, assistance and effort reduction versus lightweight design, and support-bearing capacity versus human–machine adaptability. Finally, structural optimization strategies were generated using TRIZ, and the proposed concept was preliminarily assessed through JACK digital human simulation and multi-stakeholder assessment at the conceptual design stage. The multi-stakeholder assessment further indicated that the proposed concept responded to requirements related to fall risk mitigation, injury protection, and perceived benefits, while adaptability for small-sized users, distal lower-limb support, and status-feedback mechanisms require further optimization. This study provides a traceable design process for incorporating users’ psychological and behavioral factors into structural innovation for assistive devices, thereby offering a methodological reference for the design of transfer assistive equipment. Full article

Anaerobic digestion (AD) is widely used for organic waste stabilization and bio-energy recovery, but its performance is often constrained by process instability, slow syntrophic metabolism, and sensitivity to acidification, ammonia, organic overloading, and inhibitory contaminants. Biochar has emerged as a promising strategy to enhance AD, with benefits extending beyond increased methane yield. This review examines how biochar properties, including pore structure, surface functional groups, alkalinity, and electrical conductivity, regulate different AD stages and improve process stability. Biochar provides microbial habitats, buffers pH, adsorbs inhibitors, accelerates volatile fatty acid conversion, and facilitates interspecies electron transfer. The effects of biochar dosage, feedstock type, reactor configuration, and operational conditions on digestion performance and resource recovery are critically evaluated. Broader contributions to organic waste valorization are also discussed. Future research should prioritize tailored biochar design, standardized characterization, long-term validation in continuous reactors, techno-economic analysis, and life-cycle assessment. These efforts are essential for translating laboratory findings into reliable and sustainable applications for organic solid waste treatment and resource recovery. Full article

Background: Recent advancements in enabling technologies, including artificial intelligence and telemedicine, alongside robust clinical study outcomes, have led to significant progress in upper limb and hand exoskeletons utilised for post-stroke rehabilitation. Objectives: This review aims to synthesize the recent scientific literature (2010–2025) on post-stroke upper-limb and hand exoskeletons, with particular attention to the sensing architectures—sensing modalities, signal processing, sensor fusion, and sensor-driven control—that integrate technical and biomedical domains to examine device architecture, clinical context, and outcome selection. Methods: A search of PubMed and Scopus was conducted on 10 November 2025, cross-checked against IEEE Xplore, Web of Science, Embase, and ACM Digital Library. We included studies evaluating wearable exoskeletons or robotic orthoses for the upper limb/hand in post-stroke rehabilitation. Two independent reviewers screened records and extracted data, with disagreements resolved by consensus. Data were synthesised using a predefined label-based taxonomy. The review protocol was not registered. Results: From 1889 identified records, 219 studies met the inclusion criteria. The synthesis reveals a transition from rigid, laboratory-centered systems to lighter, soft, and home-oriented solutions. Available evidence suggests potential impairment-level benefits, particularly for proximal motor control, but certainty remains limited due to heterogeneity, small samples, blinding limitations, inconsistent dosing, and limited long-term follow-up; gains in hand/finger dexterity appear even more variable. Discussion: While exoskeleton-assisted therapy appears associated with impairment-level gains, transfer to activities of daily living (ADLs) and real-world function remains inconsistently documented and insufficiently powered to support firm conclusions. Full article

Power conversion systems (PCSs) connect dc energy sources to the grid, but background grid-voltage disturbances can degrade grid-current quality. This paper presents a unified derivation and implementation-oriented assessment of proportional grid-voltage feedforward in the abc, αβ, and dq reference frames for an LCL-filtered three-level PCS. The derived disturbance transfer function retains the feedforward term, and attenuation is quantified at the fundamental and selected harmonics. Tests cover gain tuning and voltage harmonics, 10% voltage unbalance, 49–51 Hz operation, SCRs from 10 to 2, ±20% LCL-parameter variation, a 25–50 kW reference ramp, common-mode voltage, and a sixth-harmonic resonant benchmark. With Kff = 0.6, grid-current THD falls from 10.65% to 7.19% in the strong-grid harmonic test; the resonant benchmark reaches 7.05%. At SCR = 3, retuned resonant control gives 20.33% THD versus 11.68% for proportional feedforward, while transferring the strong-grid resonant gain gives 123.02%. The delay-inclusive loop model retains positive stability margins, whereas the switching-model results reveal that the benefit of a fixed feedforward gain is condition-dependent and may diminish or reverse under clean-grid, frequency-deviation, parameter-variation, and weak-grid conditions. Archived 100 kVA waveforms verify stable implementation in all three reference frames. The results clarify the operating conditions under which proportional feedforward is effective, together with its digital implementation requirements and limitations. Full article

Background: Fetal programming, conceptualized within the Developmental Origins of Health and Disease framework, describes how intrauterine exposures may shape long-term offspring physiology and disease susceptibility. Metformin is increasingly used during pregnancy for gestational diabetes mellitus, type 2 diabetes mellitus, and selected cases of polycystic ovary syndrome. Its developmental interpretation is complex because the drug improves the maternal metabolic environment but also crosses the placenta and directly exposes the fetus. Methods: This focused narrative review used iterative, targeted searches of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar to identify pharmacological, placental, mechanistic, clinical, guideline-based, and offspring follow-up evidence. The literature search covered publications available through 31 May 2026. The manuscript was subsequently revised during the editorial submission and peer-review process, and the evidence synthesis was re-evaluated against this final literature cut-off date. Earlier landmark studies were retained where necessary for historical, pharmacological, or methodological context. Results: Metformin reduces hepatic glucose production and maternal insulin resistance and may limit gestational weight gain, insulin requirements, neonatal hypoglycemia, and excessive fetal growth in selected pregnancies. Placental transfer creates biological plausibility for direct effects on AMPK, mitochondrial, mTOR, nutrient-sensing, and epigenetic pathways. Long-term studies are broadly reassuring regarding neurodevelopment and major metabolic disease, but findings on growth trajectory, adiposity, and small-for-gestational-age risk remain heterogeneous and indication-dependent. Conclusions: Metformin should be interpreted neither as uniformly beneficial nor as developmentally neutral. Its use should be individualized according to maternal phenotype, indication, glycemic benefit, placental function, fetal growth, dose, timing, and the limitations of long-term offspring evidence. Full article