Search Results (1,452)

Standard 16000-8 of the International Organization for Standardization (ISO 16000-8) specifies the assessment of ventilation performance using age-of-air concepts and tracer gas techniques. Since its publication in 2007, ventilation systems and assessment practices have evolved considerably, driven by increased use of mixed-mode and decentralized ventilation and advances in modeling and measurement technologies. This review examines how ISO 16000-8 can be modernized to harmonize with adjacent ventilation and indoor air quality standards while remaining applicable to contemporary systems and emerging approaches. A structured literature search of Web of Science and Google Scholar identified 76 studies (2007–2026) that engage with ISO 16000-8, age-of-air metrics, or tracer gas-based assessment. The literature was synthesized qualitatively using the framework of Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), classifying studies into performance assessment, measurement–simulation convergence, and standardization discourse. The synthesis shows that while the conceptual foundations of ISO 16000-8 remain valid, assumptions of homogeneous mixing and steady-state conditions are often violated in real buildings, leading to inconsistent application of age-of-air indicators. Field and laboratory studies under point-source conditions demonstrate reduced ventilation effectiveness of 0.73–0.82 in classrooms and 0.5–1.4 in various indoor environments, instead of ≈1 for perfect mixing. Spatial heterogeneity is also observed in mixed-mode systems, with an efficiency around 0.5. In decentralized and façade-integrated systems, air exchange effectiveness deviates from theoretical expectations, indicating inhomogeneous air renewal and short-circuiting. Field measurements show configuration-dependent discrepancies in air exchange rates (e.g., carbon dioxide vs. perfluorocarbon tracer methods under varying door positions), while wind induces time-varying infiltration. Collectively, the literature demonstrates systematic violations of well-mixed and steady-state assumptions underpinning ISO 16000-8. Fragmentation between ventilation performance standards and indoor air quality regulation limits practical uptake. Emerging experimental, numerical, and data-driven methods complement ISO 16000-8, provided applicability domains and uncertainties are addressed. The review concludes that ISO 16000-8 should be modernized toward a harmonized, performance-based framework integrating diverse ventilation systems and assessment technologies. Full article

Persistent post-endometrial ablation uterine bleeding indicates that no method of EA eliminates the entire endometrium, and post-EA hysteroscopy shows a distorted and scarred uterine cavity in the majority of patients. These observations raise concerns regarding presentation, assessment and stage of potential post-ablation endometrial cancer (PAEC), developing in residual endometrium pockets. To better understand these concerns, a literature search was conducted, from the introduction of EA in the 1980s through 2025, to capture reports of endometrial cancer (EC) associated with or following EA using multiple data bases, imputing search terms of EC following EA and possible combinations of first- and second-generation EA techniques associated with EC. Upon review of all publications, we identified 86 ECs associated with EA, described in 20 case reports (N = 20), four case series (N = 18), eleven cohort studies (N = 21), one registry (N = 27) and five reviews. Based on 12 relevant studies at a median follow-up of 8.5 years (range 1.9–25), 43 EC were identified in 39,795 women with a history of EA, with a summary incidence of 0.11% (range 0.0–1.59%). Although the studies and data are very heterogeneous, it appears that EA may afford a protective effect in reducing the risk of EC in the short term. The mechanistic effect is likely due to a quantitative reduction in the endometrium that can potentially become malignant, and/or due to the elimination of occult pre- or malignant endometrial elements which are vulnerable to EA. Moreover, based on 25 evaluable cases, the mode and time to presentation, the diagnostic work-up (including endometrial biopsy and hysteroscopy), and the stage of PAEC appear not to be altered by EA. Full article

Multi-objective optimization problems (MOPs) are ubiquitous in scientific research and engineering applications, where multiple conflicting objectives must be optimized simultaneously. Unlike traditional multi-objective evolutionary algorithms, which aim to approximate the entire Pareto front, preference-based multi-objective evolutionary algorithms (PBMOEAs) incorporate decision maker preferences to guide the search toward a region of interest (ROI). This paper presents a focused survey of PBMOEAs using a three-dimensional analytical framework consisting of preference articulation mode, preference modeling approach, and preference incorporation mechanism. Under this framework, the survey reviews major preference modeling approaches and preference incorporation mechanisms, and further discusses three practical issues critical to PBMOEA design: the effectiveness of preference incorporation, the practical limits of interactive methods, and the role of visualization in ROI-oriented decision support. Findings indicate that while PBMOEAs enhance decision-making efficiency, their performance hinges on preference quality, problem characteristics, cognitive load, and method suitability. Future directions include unified modeling, comprehensive evaluation, human-centered design, and integrating surrogate models, explainable learning, and LLM-assisted interfaces. Full article

For complex tasks such as search and recovery in uncharted maritime areas, the use of heterogeneous unmanned swarms (UAVs and USVs) is highly promising, yet effective cross-domain cooperative trajectory planning remains a key challenge, often leading to mission delays. This paper proposes a rapid Cooperative Cross-domain Path Planning framework (CCPP) and its associated algorithm for heterogeneous UAV–USV swarms. The framework first establishes a visual-fusion modeling pipeline, converting visual pose estimation, uncertainties, and semantic dynamic obstacles into a planning representation with robust safety margins and time-varying risk fields. A hybrid velocity-path co-optimization algorithm is then designed to simultaneously generate curvature-feasible trajectories and speed profiles under heterogeneous kinematics and explicit temporal constraints. In the end, an adaptive interpretable decision tree acts as a meta-strategy for online replanning and real-time adjustment of modes and weights. To address the critical issue of uneven arrival time distribution, this paper introduces, inspired by economic inequality analysis, a normalized Gini coefficient-based arrival time consistency index to quantify and optimize coordination timing. Comprehensive experiments validate the effectiveness of the proposed approach in enhancing cooperative efficiency and real-time adaptability. Full article

Background/Objectives: The objective of this scoping review was to map and critically describe emerging speech-in-noise assessment tools developed over the last decade for the evaluation of hearing loss beyond conventional audiological measures. Methods: This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A comprehensive literature search was performed in the PubMed/MEDLINE, Scopus, and Embase databases. A comprehensive review of studies describing novel or emerging SIN-based assessment tools was conducted, with a particular emphasis on those including adult participants with normal hearing and hearing loss. Results: Nine studies met the inclusion criteria and were included in the review. The identified tools cover a range of methodological innovations, including advanced digits-in-noise paradigms, antiphasic and binaural presentation modes, optimized adaptive procedures, and digital or automated testing platforms. Several studies also incorporated artificial intelligence-based approaches, such as machine learning, text-to-speech, and automatic speech recognition, to enhance test development, administration, and hearing loss classification. Across all studies, SIN measures demonstrated the ability to reliably differentiate between normal hearing listeners and individuals with hearing loss and to provide complementary information beyond pure-tone audiometry. Conclusions: Emerging speech-in-noise tools show considerable potential to improve the functional assessment of hearing loss and to support more sensitive, accessible, and scalable approaches for hearing evaluation. Further research is required to assess their clinical integration and long-term impact on hearing screening and diagnostic pathways. Full article

Dynamic response measurements support bridge monitoring and structural assessment because they are obtainable under operational loading and are sensitive to changes in stiffness, boundary conditions, and mass distribution. This article presents a structured scoping review of dynamic-response-based bridge monitoring and assessment. It covers damage-sensitive indicators, stiffness/capacity proxy inference, interpretation under operational and extreme loading, sensing with acquisition (contact, and indirect/drive-by), and data processing, machine learning and digital-twin integration for decision support. Evidence was identified through targeted searches in Scopus and The Lens with duplicate resolution in Zotero. The cited studies are compiled into a traceable evidence inventory linked to method families and decision objectives. The synthesis shows that global modal properties enable change screening but are highly confounded by environmental/operational variability. Localization and state characterization typically require denser or higher-fidelity sensing and signal conditioning. Finally, capacity-related inference using calibrated conversion models or machine learning (ML) surrogates remains context-bounded and validation-dependent. This review provides an end-to-end pipeline, evidence-maturity rubric, and conservative failure-mode checks with escalation logic that tie SHM outputs to inspection and analysis rather than direct condition declarations for bridge owners. This review is intentionally scoped and does not claim PRISMA-style comprehensiveness. Full article

Extracting periodic fault pulses caused by gear surface fatigue in reducers is often hindered by transmission path interference and strong background noise. Moreover, the traditional Variational Mode Decomposition (VMD) and Maximum Correlation Kurtosis Decomposition (MCKD) method rely on manual parameter selection, which limits its practicality. To address these issues, this paper proposes a parameter-adaptive VMD-MCKD method based on vibration signals for extracting gear surface fatigue fault features. Using the reciprocal of the peak indicator squared of decomposed signals as fitness functions, the method employs the global search capability of the Sparrow Search Algorithm to adaptively select optimal VMD-MCKD configurations. The optimized VMD-MCKD method is applied to decompose gear surface fatigue fault signals, effectively filtering out noise while highlighting periodic fault pulses caused by gear fatigue. Envelope demodulation is then performed to extract characteristic frequency components of gear surface fatigue faults. Experimental results demonstrate that the proposed method can adaptively extract periodic fault pulse components from strong noise environments, achieving a 2-fold improvement in signal kurtosis and enhanced robustness. Full article

Urban logistics systems face growing delivery demand and complex traffic and operational constraints, which make unmanned delivery carriers, including unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), a promising solution. Existing studies typically focus on a single delivery carrier type and rely on idealized assumptions, overlooking heterogeneous cooperation under multiple stations, multiple time windows, and real-world transport conditions. To address these gaps, we propose the Multi-Station UAV–UGV Cooperative Delivery Scheduling Problem with Temporally Discontinuous Service Availability (MSUUCDSP) to minimize the total travel and waiting time of UAVs and UGVs. To solve the problem, we propose a mixed-integer linear programming (MILP) model with a novel mathematical approach and a Hybrid Large Neighborhood Search (HLNS) algorithm. Additionally, we adopt a Hidden Markov Model (HMM)-based map-matching method and big data techniques to capture realistic operational characteristics. Computational experiments are conducted on various realistic instances under four diverse scenarios. Results show that UAV–UGV cooperation significantly improves efficiency, reducing total time cost by 17.12% compared with single-mode delivery, and they reveal substantial discrepancies between idealized assumptions and realistic scenarios. We further develop an ArcGIS-based simulation to support practical implementation. The findings provide valuable insights for decision-making and engineering applications for logistics operators. Full article

Aging and obesity accompanied with hormonal disequilibrium represent critical, inter-related risk factors for breast cancer, significantly influencing disease incidence, progression, and therapeutic outcomes. This review aims to elucidate the multifaceted biological mechanisms linking obesity and aging to breast carcinogenesis, with a particular focus on the emerging therapeutic and preventive potential of postbiotics as molecules targeting cellular events important for cancer growth and responsiveness. Despite continuous advancement, breast cancer therapy still poses several challenges, such as treatment-induced acquired resistance, which is boosted by the inflammatory phenotype of senescent cancerous cells, as well as undesired side effects resulting from the destruction of normal cells. Such a complex background of breast carcinogenesis and oncotherapy resistance opens avenues to search for new preventive approaches and adjunctive treatment regimens. Postbiotics demonstrate a variety of benefits due to their selective antineoplastic activity, as well as the cytoprotective potential associated with antioxidant, anti-inflammatory and anti-senescent properties. Pleiotropic effects of postbiotics make them a promising tool for counteracting cellular and physiological disturbances that favor breast cancer development, including age- and obesity-related factors. They are prospective adjunctive agents in oncotherapy, albeit their efficacy and safety need to be thoroughly evaluated in clinical studies prior to implementation in routine treatment modes. Full article

The aim of this scoping review is to categorize and examine the relationships between school neighbourhood built environment categories and the physical health of children and adolescents worldwide. The search strategy initially found 8837 studies in four databases (Web of Science, PubMed, SportDiscus and Transportation Research Board) and after applying the inclusion and exclusion criteria 55 articles were included. The findings report on seven school neighbourhood built environment categories: building, connectivity and network, food environment, greenness, land use, safety and other variables. Interestingly, the connectivity and network category comprises 32 variables. Likewise, this category, together with the food environment, shows a clear predominance, with both categories accounting for 71.04% of all significant associations. The greenness category stands out due to its association density similarly to the predominant categories. The physical health categories were body composition, mode of commuting, physical activity, sedentary behaviour and weight status. Complementary weighted cross-tabulation analyses showed that when associations were weighted by participant sample size and school sample size, the food environment–weight status relationship became the most prominent, whereas connectivity-related associations became less dominant. The findings indicate preferential links between school neighbourhood built environment and physical health domains, with the connectivity and network category mainly associated with commuting mode and physical activity, and the food environment was primarily linked to weight status and dietary intake. Consequently, special attention must be given to urban planning and policies in the school neighbourhood built environment. Full article

Nature-inspired metaheuristic algorithms are commonly applied to complex combinatorial optimization problems where exact methods are computationally impractical. Tourist route optimization is a representative multi-objective problem characterized by realistic constraints such as travel time, cost, opening hours, and transportation modes. Although Mushroom Reproduction Optimization is computationally efficient, it often experiences premature convergence in complex search spaces. This paper proposes a novel hybrid algorithm, Mushroom–Weed Hybrid Reproduction Optimization (MWHRO), which integrates the colony-based local search of the Mushroom Reproduction algorithm with the fitness-proportional reproduction and competitive elimination mechanisms of Invasive Weed Optimization. Hybridization enhances population diversity and global exploration while preserving fast convergence. The proposed algorithm is evaluated based on a realistic tourist route optimization problem using real-world data from Zagreb, Croatia, across multiple transportation modes and objective-weight scenarios. Performance is compared against Ant Colony Optimization, Invasive Weed Optimization, Particle Swarm Optimization, and standard Mushroom Reproduction Optimization under equal evaluation budgets. Experimental results demonstrate that the proposed MWHRO algorithm consistently achieves high-quality solutions with significantly lower execution times, particularly in constrained and multimodal scenarios. Statistical analysis confirms the robustness and practical suitability of the proposed approach for real-world route optimization. Full article

A novel hydraulic circuit, the Modular Hydraulic Servo Booster (MHSB) is applied to redundant hydraulic manipulators. The MHSB uses multiple pumps and valves to drive multiple actuators to significantly improve energy efficiency compared with conventional servo-valve systems. Our previous work has proposed a control strategy that incorporates energy-optimal trajectory planning and operation mode switching using a graph search algorithm to perform point-to-point (PTP) tasks for manipulators. This paper extends our previous study by constructing an optimal-posture table that incorporates manipulability. By using this table to evaluate the cost in graph search, we achieve real-time optimal trajectory planning and operation mode switching for redundant manipulators. Numerical simulation from different PTP tasks on a three-link manipulator (1-m length, 10-kg weight) validate the proposed method. Full article

Aiming at the problems of microseismic signals from rock mass fracture in deep-buried tunnels with low signal-to-noise ratio (SNR) suffering from coupled interference of multi-source noise, and traditional filtering methods having fixed parameters and poor processing effects on spectral aliasing, this study proposes a ternary coupled adaptive filtering method integrating the Sparrow Search Algorithm, Variational Mode Decomposition and Wavelet Threshold Denoising (SSA-VMD-DWT). First, the noise intrusion characteristics of low-SNR microseismic signals in deep-buried tunnels were analyzed, and the filtering difficulties of white noise, low-frequency noise, high-frequency noise and non-stationary noise were clarified. Subsequently, a parameter optimization framework with the Sparrow Search Algorithm (SSA) as the core was constructed to optimize the key parameters, including the penalty factor α and modal number K of Variational Mode Decomposition (VMD), as well as the wavelet basis and decomposition layers of Wavelet Threshold Denoising (DWT), respectively. A dual-index threshold decision function based on kurtosis and correlation coefficient, and a wavelet packet entropy weighted reconstruction algorithm were designed to realize the collaborative adaptive adjustment of decomposition depth and threshold rules. Finally, the performance of the algorithm was verified through simulation signal experiments and an engineering case of a deep-buried tunnel in Southwest China. The results show that for the simulated signal with a low SNR of 2 dB, the SNR is increased to 12.43 dB, and the root mean square error is reduced to 2.36 × 10⁻⁷ after denoising by this algorithm, which is significantly superior to the Empirical Mode Decomposition (EMD) and traditional DWT methods. In the engineering case, the information entropy of the filtered signal is the lowest among all methods, which can effectively suppress multi-band noise and retain the core characteristics of microseismic signals from rock mass fracture, solving the problems of spectral aliasing, detail loss and empirical parameter setting of traditional methods. This method provides a new technical paradigm for the processing of low-quality microseismic signals in deep tunnel engineering and can improve the accuracy of monitoring and early warning for rock mass dynamic disasters. Full article

Background: Childhood and adolescent overweight and obesity are major global public health concerns. High-intensity interval training (HIIT) has been increasingly investigated as a time-efficient intervention; however, evidence regarding its effects on multiple health-related outcomes and the influence of intervention characteristics remains inconsistent. Objective: The objective of this study was to evaluate the effects of HIIT on body composition, metabolic health, and cardiorespiratory fitness in children and adolescents with overweight or obesity. Methods: Systematic literature searches were conducted in PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, and VIP databases. Randomized controlled trials were included. Risk of bias was assessed using the Cochrane Risk of Bias tool. Meta-analyses were conducted using random-effects models, and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated. Heterogeneity, sensitivity analyses, publication bias, and certainty of evidence (GRADE) were also evaluated. Results: A total of 21 randomized controlled trials involving 652 participants (325 in the intervention groups and 327 in the control groups) were included. Compared with control conditions, HIIT significantly improved multiple outcomes related to body composition, metabolic health, and cardiorespiratory fitness, including BMI (SMD = −1.05), body fat percentage (SMD = −0.69), total cholesterol (SMD = −0.42), HOMA-IR (SMD = −1.00), and VO₂peak (SMD = 0.91), while no significant effect was observed on lean body mass. Subgroup analyses suggested that HIIT protocols with a load duration of less than 1 min were associated with greater improvements in several outcomes, particularly body fat percentage, total cholesterol, HOMA-IR, and VO₂peak. Conclusions: HIIT may improve body composition, metabolic health, and cardiorespiratory fitness in children and adolescents with overweight or obesity. However, the certainty of evidence varied across outcomes and was limited for some findings by heterogeneity, small sample sizes, and potential risk of bias. Further high-quality, large-scale randomized controlled trials with standardized HIIT protocols are needed to confirm these findings and clarify the influence of different training characteristics (e.g., exercise mode and interval structure). Full article

Listening to music is a well-established strategy to enhance exercise capacity, yet the specific mechanisms linking music choice to performance enhancement remain fragmented. This scoping review systematically summarizes the existing literature on the effects of music choice (i.e., self-selected, preferred music) on performance and psychophysiological determinants of exercise capacity to establish an updated rationale for the use of personalized music interventions in training. Following PRISMA-ScR guidelines, a systematic search of five databases (PubMed, Web of Science, Embase, Scopus, CINAHL) was performed for studies published between January 2000 and April 2025. Peer-reviewed articles investigating the ergogenic effects of self-selected or preferred music with psychophysiological outcomes were included. Thirty-two studies met inclusion criteria. Overall, evidence supports consistent performance enhancement from choice music (CM) across modes of exercise including aerobic endurance, anaerobic power, and muscular endurance activities while maximal strength was largely unaffected. The most robust and consistent mechanisms underpinning the benefits of CM during exercise were psychological in nature, including improvements in affect, arousal, motivation, and perception of exertion. Notable physiologic benefits were also identified, including altered cortical excitability, autonomic modulation, and improvements in neuromuscular efficiency. Herein, this review provides a psychophysiological framework whereby CM acts as a primary mediator to induce psychological and physiological cascades which synergistically contribute to ergogenic benefits. Evidence heavily supports the superiority of CM to improve exercise performance across various modalities. Full article