Search Results (4,626)

To achieve autonomous ultrasound scanning skill transfer across different physical equipment instances and address the limitations of traditional imitation learning methods—which struggle with cross-instance generalization due to their reliance on specific manipulator parameters—this study proposes a physical-parameter-decoupled imitation learning method based on waypoint representation. This approach utilizes a greedy algorithm to automatically extract key nodes within the task space from expert demonstration trajectories, constructing a trajectory representation decoupled from low-level kinematic parameters and base calibration errors. Simultaneously, a velocity-aware adaptive error precision adjustment mechanism is introduced to dynamically modulate waypoint extraction thresholds, simulating the speed-accuracy strategies employed by sonographers across different scanning phases. Cross-validation across two mainstream generative architectures—Action Chunking Transformer (ACT) and Diffusion Policy—on an offline dataset confirms the plug-and-play capability of waypoint representation in suppressing long-horizon error accumulation, with both architectures achieving significant reductions in prediction errors. For physical deployment, a complete ACT-waypoint system featuring low-level triple safety redundancy was validated. In kidney long-axis standard plane scanning tasks, the system achieved a 92% success rate on the source domain manipulator and maintained an 84% success rate on the target deployment manipulator, despite incompatible low-level kinematic parameters and base coordinates. Force control accuracy remained stable around the target value of 12 N. The results demonstrate that the proposed method effectively overcomes base coordinate and D-H parameter discrepancies to achieve cross-instance zero-shot skill transfer, significantly enhancing the adaptability across physical instances and the scanning success rate of imitation learning models. Full article

Maintaining road infrastructure in underground mines is critical for ensuring efficient transportation, reducing fuel consumption, extending the lifespan of machines, and providing operator safety and comfort. At the same time, the operation of heavy machinery on uneven roads, and the presence of loose rock fragments make it impossible to keep roads in consistently good condition, necessitating continuous condition monitoring and appropriate maintenance planning. This paper proposes a framework based on a single inertial sensor mounted on a mining vehicle for road quality assessment and vehicle speed estimation. The developed methods have a hybrid character, combining the physical interpretability of inertial data with unsupervised AI-based techniques. The integrated analytical system, combining road surface quality assessment with vehicle speed analysis, serves as a decision-supporting tool for pinpointing road segments that are critical for maintenance, safety, transport efficiency, and machine wear. The proposed approach was validated using data collected from haul trucks operating under real-world conditions. The system has the potential to support more efficient and sustainable management of mine road maintenance by reducing unnecessary interventions, resource consumption, and the negative environmental and safety impacts associated with haulage operations. Full article

Food contamination by ochratoxin A (OTA) constitutes a significant threat to public health and global food safety and security, a challenge increasingly intensified by climate change. Due to the high thermal and chemical stability of OTA, traditional physical and chemical decontamination methods often prove insufficient or detrimental to food quality. Consequently, microbial detoxification has emerged as a sustainable alternative. This review delves into the two primary biological mechanisms for OTA detoxification: physical adsorption—predominantly mediated by yeast and bacterial cell walls—and enzymatic biotransformation. Among the documented metabolic pathways, the hydrolysis of the amide bond by carboxypeptidases and amidohydrolases is recognised as the most reliable detoxification pathway. Conversely, alternative pathways, such as lactone ring opening, are hindered by their potential toxicity and chemical reversibility under acidic conditions. While various lactic acid bacteria, yeast, and filamentous mould species demonstrate high efficacy in OTA decontamination, their industrial implementation is currently limited by the complexity of food matrices and the lack of in vivo validation. The integration of multi-omics (proteomics and metabolomics), alongside CRISPR/Cas9 genome editing, is essential for identifying novel biocontrol agents. These precision biotechnological tools are fundamental for translating laboratory findings into industrial-scale OTA detoxification strategies. Full article

Erectile dysfunction (ED) is a common multifactorial condition with significant physical, psychological and relational consequences. While historically associated with aging, its rising prevalence among younger men underscores the need for updated diagnostic and therapeutic frameworks. This narrative review synthesizes contemporary evidence on the pathophysiology, diagnostic workup and management of ED, with emphasis on guideline-directed care and emerging treatment modalities. A comprehensive literature search was conducted, with evidence synthesized from key clinical guidelines, landmark trials and recent peer-reviewed studies. Lifestyle optimization remains the foundational step, followed by first-line pharmacotherapy with phosphodiesterase type 5 inhibitors (PDE5is), which demonstrate high efficacy and safety across diverse patient populations. For patients with inadequate PDE5is response, second-line options include alprostadil (intracavernosal, with approximately 70% success rates or intraurethral), vacuum erection devices and penile prosthesis surgery, with patient and partner satisfaction exceeding 95% for the latter when performed in experienced centers. Psychosexual therapy is an integral adjunct, particularly in psychogenic or mixed etiologies. Regenerative approaches such as low-intensity extracorporeal shockwave therapy (Li-SWT) and platelet-rich plasma (PRP) injections are under investigation; current evidence supports their use only in experimental settings due to limited long-term data. A multidisciplinary, individualized strategy—incorporating pharmacologic, surgical and psychosocial interventions—remains the cornerstone of modern ED management. This review critically distinguishes well-established evidence from ongoing clinical debates and translates findings into practical guidance for daily practice. Ongoing technological advances may further refine diagnostic accuracy and treatment personalization, but high-quality studies are needed to establish the role of regenerative and digital tools. Full article

Forest and grassland fires have become increasingly severe under climate change, posing significant threats to ecosystems and human safety. Accurate wildfire prediction using remote sensing data remains challenging due to complex spatiotemporal dynamics and heterogeneous data sources. To address this issue, this study proposes a hybrid deep learning framework integrating U-Net and an attention-enhanced bidirectional long short-term memory network (AUBLSTM) for spatiotemporal wildfire prediction using multi-source remote sensing and meteorological data. The U-Net is employed for spatial feature extraction, while AUBLSTM captures temporal dependencies and improves fire spread modeling with attention mechanisms. An encoder–decoder architecture is adopted to enhance multi-scale feature representation, and meteorological constraints are incorporated to improve physical consistency. Experimental results demonstrate that the proposed model outperforms baseline methods, including convolutional long short-term memory (ConvLSTM) and fully connected networks, achieving superior performance in terms of MSE, RRMSE, PSNR, SSIM, IoU, and F1-Score. The framework is efficient, scalable, and suitable for deployment in electronic monitoring and early warning systems, providing a practical solution for integrating multi-source data into wildfire surveillance applications. Full article

Weeds represent a major constraint in the cultivation of medicinal and aromatic plants (MAPs), causing significant reductions in yield, biomass, and essential oil quality while increasing labor and production costs. Effective weed management is particularly critical during early crop growth, when young plants are most vulnerable to competition. Non-chemical strategies, including cultural practices, mechanical and thermal weeding, mulching, and crop diversification, have proven effective in suppressing weeds, enhancing crop competitiveness, and maintaining yield and quality, especially in organic or low-input systems. Mulching and optimized cultivation strategies consistently provide reliable weed control, improve soil moisture and nutrient use efficiency, and can influence secondary metabolite accumulation. Chemical weed control, including selective pre- and post-emergence herbicides, remains important in slow-growing MAPs but is increasingly constrained by regulatory restrictions and concerns over residues in raw plant material and essential oils. Integrated weed management combining cultural, physical, and reduced chemical approaches offers the most effective solution, balancing efficacy, crop safety, and product quality. Emerging strategies such as bioherbicides, precision agriculture, and robotic systems hold promise but require further research. Advancing weed management in MAPs will depend on interdisciplinary studies, field-scale validation, and technology-driven innovations to support sustainable, high-quality production. Full article

Core physics multigroup cross-section libraries provide essential cross-section and burnup data for reactor neutron physics calculations, serving as a fundamental prerequisite for reactor physics analysis. The China Nuclear Data Center has developed the TPEX multigroup cross-section library for pressurized water reactors (PWRs) based on the Chinese Evaluated Nuclear Data Library CENDL-3.2. A systematic critical benchmark validation of the newly developed TPEX library has been performed. To verify its applicability and accuracy, the validation has been conducted against 131 critical benchmark experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP 2006) and the WIMS-D library update project. The calculated effective multiplication factors $\left(k_{eff}\right)$ are compared with the experimental values, results from equivalent multigroup libraries, and reference solutions from Monte Carlo code. The results indicate that the absolute average deviations between the calculated $k_{eff}$ values using the TPEX library and the experimental measurements are 280 pcm for the uranium solution experiments, 410 pcm for the plutonium solution experiments, 10 pcm for the uranium metal lattice experiments, 20 pcm for the uranium dioxide lattice experiments, 22 pcm for the MOX fuel lattice experiments, and 150 pcm for the LCT001 uranium oxide assembly experiments. Accordingly, the TPEX library demonstrates excellent performance in reactivity predictions for PWRs. Full article

Background and aims: Lactiplantibacillus plantarum is a widely studied probiotic species with well-documented benefits for gastrointestinal function and immune modulation. However, probiotic effects are strain-specific, and the safety of newly identified strains must be clinically established. L. plantarum K014, isolated from traditionally fermented vegetables, has not previously been evaluated in human subjects. This study aimed to evaluate the safety and tolerability of L. plantarum K014 in healthy Malaysian adults by assessing its effects on anthropometric measures, hematological indices, liver and renal function, gastrointestinal health, and selected immune-related outcomes, including the incidence and severity of common cold symptoms. Methods: This single-center, randomized, double-blind, placebo-controlled trial was conducted over a 6-month period. Of 304 healthy adults screened, 152 were enrolled and randomized in a 1:1 ratio to receive either L. plantarum K014 (≥1 × 10⁹ CFU/day) or placebo (maltodextrin), administered daily in sachet form; 125 participants completed the study. Clinical assessments, including physical examination, anthropometric measurements, and blood analyses, were performed at baseline, Month 4, and Month 6. Gastrointestinal symptoms, stool characteristics, and immune-related outcomes were monitored weekly using structured online questionnaires. Results: L. plantarum K014 was well tolerated, with no probiotic-related adverse events reported. No clinically significant changes were observed in body weight, BMI, hematological indices, or renal function in either group. Exploratory analyses indicated that participants receiving L. plantarum K014 exhibited statistically significant differences in several liver function markers, as well as lower severity of diarrhea and abdominal pain compared with placebo, though these findings were not prespecified efficacy endpoints and should be interpreted cautiously. Similarly, lower weekly ratings of common cold symptoms interfering with work or study were observed in the probiotic group as an exploratory observation. Conclusions: Daily consumption of L. plantarum K014 at a dose of ≥1 × 10⁹ CFU for six months was safe and well tolerated in healthy adults. The absence of adverse effects, together with observed trends toward lower gastrointestinal discomfort and immune-related symptoms, supports the suitability of L. plantarum K014 for further investigation in efficacy-driven clinical studies. Full article

Reliable detection of internal defects in pressure vessel structures remains essential for structural safety and condition-based maintenance. This study presents a low-complexity structural health monitoring framework based on fiber Bragg grating (FBG) sensing and multiresolution wavelet analysis for void detection in curved pressure vessel structures under guided wave excitation. Guided waves are introduced using piezoelectric actuators, while the FBG sensors capture the resulting strain-induced wavelength variations. Due to the limited bandwidth of the optical interrogator, the recorded signals represent the strain envelope response associated with guided wave interaction rather than the resolved ultrasonic carrier waveform. To characterize defect-induced changes, the acquired signals are analyzed using continuous wavelet transform (CWT) for time–frequency interpretation, and discrete wavelet transform (DWT) and wavelet packet transform (WPT) for energy-based multiresolution feature extraction. Experimental results show that void defects lead to consistent redistribution of wavelet-domain energy and increased non-stationarity in the measured strain responses. These trends are further supported by finite-element simulations, which reproduce similar energy redistribution patterns between intact and damaged cases. The proposed framework provides a physically interpretable and computationally efficient approach for defect detection using low-bandwidth FBG sensing, without reliance on high-speed acquisition or data-intensive learning models. The results demonstrate the feasibility of using energy-based multiresolution analysis of FBG strain signals for practical and scalable structural health monitoring of pressure vessel systems. Full article

Industry 5.0 is no longer understood merely as an extension of automation; it reflects a broader shift toward integrating technological advancement with human well-being, sustainability, and resilience. However, the literature reveals a fragmented landscape in which technological, industrial, and ecological dimensions are often treated separately, hindering a cohesive understanding of the paradigm. To address this gap, this study conducts a PRISMA-ScR-based review of 52 peer-reviewed studies (January 2021–March 2026), structured around ten research questions that examine technologies, sectors, methods, human-centered design, sustainability alignment, and implementation barriers. The review demonstrates high reliability (Cohen’s κ = 0.981). Findings highlight artificial intelligence (86%), collaborative robotics (80%), IoT (71%), and digital twins (63%) as core technologies, typically integrated within human-in-the-loop systems. Manufacturing and healthcare lead adoption, reporting reduced physical workload and improved safety. Nonetheless, only 63% of studies explicitly align with sustainability frameworks, revealing a persistent gap. Thus, inclusive Industry 5.0 remains a promising yet still insufficiently consolidated concept. Full article

Street soundscapes significantly shape communities’ environmental perceptions, behaviour and urban sustainability. Previous research has mainly focused on physical and acoustic aspects, while limited attention has been given to emotional and behavioural dimensions. This study explores how expert participants perceive street soundscapes through personal, physical, behavioural, and emotional dimensions, using international online focus groups with soundscape experts, urban planners, and policymakers (n = 12). Analysis followed a deductive thematic approach establishing four main a priori themes, with additional inductive coding used to refine these themes. The findings reveal that perception is shaped by contextual, cultural, temporal, multisensory, and environmental affordance factors. Notably, silence was found to carry a dilemma—perceived as either safe or unsafe depending on pedestrian density—and religious and cultural soundmarks were identified as evoking place attachment and belonging, areas largely overlooked in existing literature. These soundscapes were associated with emotional responses, including comfort, safety, restoration, and belonging, and with pedestrian behaviour encompassing mobility choices, coping strategies, and social interactions. Furthermore, seven out of ten Healthy Streets metrics were directly referenced by participants, highlighting the close relationship between acoustic environments and healthy streets design. Future studies should examine cultural, temporal, and spatial street characteristics and their effects on human behaviour and emotional responses. Full article

Turmeric has a long history of use as a colorant and flavoring agent. Turmeric extract (TE) is a feed additive containing at least 90% total curcuminoids, comprising mainly curcumin, desmethoxycurcumin and bisdemethoxycurcumin. The published antioxidant effects of TE in humans have sparked interest and feeding studies in companion animals. Studies describing the feeding of TE to cats are scarce and do not provide adequate toxicology data; regulatory approval is required to allow use of TE as a nutritional antioxidant in pet food. The current study describes a safety test of TE in cats. Control cats were fed a standard extruded dry diet whilst two groups of test cats were fed the same diet supplemented with two different levels of TE for four months. Physical examination, body weight, body condition score, food intake, fecal score, monitoring of adverse effects (vomiting, diarrhea, clinical signs), complete blood count, and blood biochemistry (particularly liver enzymes) were used to monitor toxicity signs. The lack of statistically significant effects of clinical or toxicological concern concludes that feeding TE to cats at a dietary level providing up to 1040 ppm total curcuminoids is safe. This allows future application of this ingredient in cat food as a nutritional antioxidant. Full article

Rock bursts remain among the most destructive and unpredictable disasters in mining operations, yet existing deep learning methods face significant challenges in engineering practicality, noise robustness, and representing complex inter-event relationships for accurate prediction. To address these limitations, this paper proposes DynamiXFormer, a novel Transformer-based rock burst prediction model. Unlike traditional temporal prediction paradigms, DynamiXFormer establishes a direct mapping from working face advancement to rock burst risk, thereby linking predictions to mining-induced disturbances. The model integrates three innovative modules: an Adaptive Frequency Denoising module that suppresses noise while enhancing salient information from a frequency-domain perspective; a Relative Event Encoding module that constructs inter-event correlation graphs to capture physical attribute correlations and spatio-temporal dependencies; and a Dynamic Sparse Attention mechanism that introduces a strong inductive bias, enabling attention to focus on both local precursory patterns and global critical shifts. Experiments on real-world microseismic monitoring data demonstrate that DynamiXFormer significantly outperforms six baseline models across all prediction horizons and evaluation metrics. In short-term prediction tasks, it achieves a Mean Squared Error as low as 0.000518 and a Recall of up to 97.85%. Ablation studies further validate the individual effectiveness and synergistic effects of the proposed modules. This research provides a new methodology for rock burst early warning, with strong potential to enhance mine safety monitoring and engineering applications. Full article

In rapidly urbanizing metropolitan areas, children increasingly face risks to their physical and mental health, largely due to constrained access to suitable outdoor spaces that support regular physical activity. The uneven distribution and varying quality of these urban outdoor environments further intensify such risks by limiting children’s opportunities for safe, stimulating, and health-promoting activities. However, the existing research often lacks a systematic framework to quantify these spatial inequities across multiple dimensions. This study aims to fill this gap by constructing a robust analytical framework for evaluating outdoor environmental quality. It quantifies spatial distribution and determinants of these inequalities. The framework is structured around four core dimensions: Safety, Facility Variety, Fun, and Greenness. Taking Beijing as a case study, data from 1598 primary and secondary schools were analyzed. The Gini coefficient and Moran’s I were used to evaluate the equality and spatial clustering of environmental indicators, while the Geographically Weighted Regression model explored how Spatial Construction, Social Development, and Economic Level shape environmental quality. The results reveal the following findings: (1) the quality of children’s outdoor physical activity environments in Beijing is notably unequal, especially regarding Greenness and Fun; (2) these disparities correspond closely to the city’s “core–periphery” metropolitan structure; and (3) the relationships between metropolitan-level factors and environmental quality exhibit strong spatial heterogeneity. This study provides a comprehensive framework for evaluating and visualizing inequalities in children’s outdoor environments, offering empirical support for inclusive and health-oriented urban governance. Full article

Biodegradable metals represent a paradigm shift in orthopedic fixation by providing temporary mechanical support synchronized with bone healing while eliminating long-term complications associated with permanent implants. Conventional bioinert alloys, including stainless steels, Ti-based alloys, and Co-Cr alloys, exhibit high elastic moduli that induce stress shielding and often require secondary removal surgeries. In response, resorbable metallic systems based on Mg, Zn, and Fe have emerged as promising alternatives. Among these, Fe-Mn-C alloys stand out for load-bearing applications due to their exceptional strength-ductility balance governed by twinning-induced plasticity mechanisms, tunable degradation behavior, and intrinsic magnetic resonance imaging compatibility through austenitic phase stabilization. Focusing on Fe-Mn-C alloys, this review critically examines the metallurgical design principles underlying stacking fault energy optimization, phase stability, and Mn-controlled electrochemical behavior. Processing innovations, such as additive manufacturing, are discussed as tools to architecture porosity, refine microstructure, and accelerate degradation by graded designs while preserving mechanical structural support during healing. Hybrid metallic-bioactive systems, surface functionalization strategies, and functionally graded porous architectures were evaluated as advanced approaches to enhance osteointegration and modulate degradability. Despite these advances, significant barriers remain for clinical translation. Persistent discrepancies between in vitro and in vivo degradation rates, often attributed to biological encapsulation and degradation product accumulation, complicate lifetime prediction. Localized corrosion at microstructural heterogeneities such as twin boundaries and phase interfaces can undermine structural reliability under load-bearing conditions. Moreover, predictive multi-physics modeling frameworks capable of coupling electrochemical kinetics, mechanical loading, microstructural evolution, and bone remodeling remain underdeveloped, limiting reliable safety-margin estimation. Regulatory progress is further hindered by the absence of standardized testing protocols specifically tailored to Fe-based biodegradable alloys, including harmonized degradation rate windows, validated corrosion-mechanics coupling methodologies, and clinically defined Mn ion release thresholds. This review aims to discuss whether Fe-based alloys, especially Fe-Mn-C alloys, can transition from promising laboratory materials to clinically viable next-generation orthopedic implants capable of delivering patient-specific, mechanically compatible, and biologically synchronized temporary fixation. Full article