Search Results (470)

(1) Background: Brain–computer interfaces (BCIs) enable direct communication between the brain and external devices using electroencephalography (EEG) signals, offering potential applications in assistive technology and neurorehabilitation. Code-modulated visual evoked potential (cVEP)-based BCIs employ code-pattern-based stimulation to evoke neural responses, which can then be classified to infer user intent. While increasing the number of EEG electrodes across the visual cortex enhances classification accuracy, it simultaneously reduces user comfort and increases setup complexity, duration, and hardware costs. (2) Methods: This online BCI study, involving thirty-eight able-bodied participants, investigated how reducing the electrode count from 16 to 6 affected performance. Three experimental conditions were tested: a baseline 16-electrode configuration, a reduced 6-electrode setup without retraining, and a reduced 6-electrode setup with retraining. (3) Results: Our results indicate that, on average, performance declines with fewer electrodes; nonetheless, retraining restored near-baseline mean Information Transfer Rate (ITR) and accuracy for those participants for whom the system remained functional. The results reveal that for a substantial number of participants, the classification pipeline fails after electrode removal, highlighting individual differences in the cVEP response characteristics or inherent limitations of the classification approach. (4) Conclusions: Ultimately, this suggests that minimal cVEP-BCI electrode setups capable of reliably functioning across all users might only be feasible through other, more flexible classification methods that can account for individual differences. These findings aim to serve as a guideline for what is currently achievable with this common cVEP paradigm and to highlight where future research should focus in order to move closer to a practical and user-friendly system. Full article

With the growing demand for personalized and flexible production, human–robot collaboration technology receives increasing attention. However, enabling robots to accurately perceive and align with human motion intentions remains a significant challenge. To address this, a novel human–robot collaborative control framework is proposed, which utilizes electromyography (EMG) signals as an interaction interface and integrates human skill imitation with reinforcement learning. Specifically, to manage the dynamic variation in muscle coordination patterns induced by joint angle changes, a temporal graph neural network enhanced with an Angle-Guided Attention mechanism is developed. This method adaptively models the topological relationships among muscle groups, enabling high-precision three-dimensional dynamic arm force estimation. Furthermore, an expert reward function and a fuzzy experience replay mechanism are introduced in the reinforcement learning model to guide the human skill learning process, thereby enhancing collaborative comfort and smoothness. The proposed approach is validated through a collaborative assembly task. Experimental results show that the proposed arm force estimation model reduces estimation errors by 10.38%, 8.33%, and 11.20% across three spatial directions compared to a conventional Deep Long Short-Term Memory (Deep-LSTM). Moreover, it significantly outperforms state-of-the-art methods, including traditional imitation learning and adaptive admittance control, in terms of collaborative comfort, smoothness, and assembly accuracy. Full article

The detection and quantification of fabric tactile sensations are crucial in textile production and marketing as they are closely linked to textile comfort and serve as key criteria for consumers when selecting fabrics. Previous studies have predominantly focused on measuring the physical properties of fabrics, often neglecting correlations between these parameters and tactile sensations. This oversight complicates customers’ ability to assess the tactile experience of fabrics during online purchasing. This study first obtained subjective evaluations of three types of fabric tactile sensations through experiments involving volunteer participants. Subsequently, five objective physical properties that characterize fabric tactile properties were proposed and experimentally tested on 15 fabric samples categorized by yarn weight, weave pattern, and material. A fabric tactile spider diagram was created by normalizing the values of the five physical properties across the 15 fabric samples. The grading of the physical properties was then performed based on the proposed evaluation index. These spider diagrams were compared with the subjective evaluation results to analyze the physical properties that most significantly influenced subjective perception, ultimately leading to the development of a highly reliable fabric touch prediction model. Full article

This study quantitatively analyzes the effects of various ventilation parameters on airflow stability in confined spaces ventilated by opposed jets, a common configuration in high-density settings. Using large eddy simulations (LES), we evaluate how changes in supply velocity, airflow configuration, enclosure geometry, and thermal gradients influence airflow dynamics. Findings show that higher supply velocities, up to 1.92 m/s, lead to a measurable increase in oscillation period (from 7.7 s to 11.3 s) and reduce small-scale flow disturbances. The free jet configuration exhibits higher oscillation amplitude and a more disordered structure compared to the attached jet, resulting in uneven airflow distribution. Aspect ratio has a pronounced effect, with increased ratios extending oscillation periods from 10.6 s to 18.1 s and intensifying turbulence. Thermal gradients, with floor temperatures rising from 15 °C to 35 °C, and the oscillation period are increased, further dispersing airflow and reducing stability. Phase space reconstruction and power spectral analysis provide quantitative benchmarks for oscillation frequencies and patterns, correlating velocity time series with airflow structural changes. The findings from this study can serve as a foundation for future research on thermal comfort and air quality management in enclosed environments. Full article

With the intensification of global climate change, buildings in hot climate zones face increasing challenges related to high energy consumption and thermal comfort. Building integrated photovoltaic (BIPV) façades, which combine power generation and energy saving potential, require further optimization in their climate-adaptive design. Most existing studies primarily focus on the photoelectric conversion efficiency of PV modules, yet there is a lack of systematic analysis of the coupled effects of temperature, humidity, and solar radiation intensity on PV performance. Moreover, the current literature rarely addresses the regional material degradation patterns, integrated cooling solutions, or intelligent control systems suitable for hot and humid climates. There is also a lack of practical, climate specific design guidelines that connect theoretical technologies with real world applications. This paper systematically reviews BIPV façade design strategies following a climate zoning framework, summarizing research progress from 2019 to 2025 in the areas of material innovation, thermal management, light regulation strategies, and parametric design. A climate responsive strategy is proposed to address the distinct challenges of humid hot and dry hot climates. Finally, this study discusses the barriers and challenges of BIPV system applications in hot climates and highlights future research directions. Unlike previous reviews, this paper offers a multi-dimensional synthesis that integrates climatic classification, material suitability, passive and active cooling strategies, and intelligent optimization technologies. It further provides regionally differentiated recommendations for façade design and outlines a unified framework to guide future research and practical deployment of BIPV systems in hot climates. Full article

This study uses generative AI to investigate the influence of building façade geometry on human physiological and psychological health. Employing Christopher Alexander’s fifteen fundamental properties of living geometry and a set of ten emotional descriptors {beauty, calmness, coherence, comfort, empathy, intimacy, reassurance, relaxation, visual pleasure, well-being} in separate tests, ChatGPT 4.5 evaluates simple, contrasting window designs. AI analyses strongly and consistently prefer traditional window geometries, characterized by symmetrical arrangements and coherent visual structure, over fragmented or minimalist–modernist alternatives. These results suggest human cognitive–emotional responses to architectural forms are hardwired through evolution, privileging specific geometric patterns. Finally, ChatGPT o3 formulates ten detailed geometric rules for empathetic window design and composition. It then applies these criteria to select contemporary window typologies that generate the highest anxiety. The seven most anxiety-inducing designs are the most favored today worldwide. The findings challenge contemporary architectural preferences and standard window archetypes by emphasizing the significance of empathetic and health-promoting façade designs. Given the general suspicion among many readers of the frequently manipulative and unreliable use of AI, its use in this experiment is not to validate design decisions directly, which would put into question what the AI is trained with, but to prove a correlation between two established methodologies for evaluating a design. AI is used as an analytical tool to show that Alexander’s geometric rules (the guidelines proposed beforehand) closely match emotional reactions (the desirable outcomes observed afterward). This novel use of AI suggests integrating neurodesign principles into architectural education and practice to prioritize urban vitality through psychological well-being. Full article

Streets, as critical public space nexuses, require synergistic quality–utilization alignment—where quality without use signifies institutional inefficiency, and use without quality denotes operational ineffectiveness. Focusing on high-frequency pedestrian commuting streets (HFPCSs) that not only crucially mediate metropolitan mobility patterns but also shape citizens’ daily urban experiences and satisfaction, this study proposes a data-driven diagnostic framework for street quality–utilization assessment, integrating multi-source urban big data through a case study of Shenzhen. By integrating multi-source urban big data, we identify HFPCSs using LBS data and develop a multi-dimensional evaluation system that incorporates 1.07 million Points of Interest (POIs) for assessing convenience, utilizes DeepLabv3+ for the semantic segmentation of street view imagery to evaluate comfort, and leverages 15,374 km of road network data for accessibility analysis. The results expose dual mismatches: merely 2.15% of HFPCSs achieve balanced comfort–convenience–accessibility benchmarks, while over 70% of these are clustered in northern districts, exhibiting systematically inferior quality metrics across dimensions. Diagnostic analysis reveals specific planning and spatial configurations contributing to these disparities, informing targeted retrofitting strategies for priority street typologies. This approach establishes a replicable model for megacity street renewal, deploying supply–demand diagnostics to synchronize infrastructure upgrades with pedestrian flow realities. By bridging data insights with human-centric urban improvements, this framework demonstrates how smart city technologies can concretely address the quality–utilization paradox—advancing sustainable urbanism through evidence-based street transformations. Full article

As urbanization accelerates, the increasing density of urban buildings and the prevalence of multi-unit high-rise residential areas have emerged as significant factors affecting residents’ comfort. Effective green space planning within residential areas can mitigate residents’ thermal discomfort. This study utilizes methods including the construction of two-dimensional and three-dimensional landscape indices and meteorological data simulation to examine the relationship between residents’ comfort levels at various heights in residential buildings and the 3D landscape patterns of residential areas, based on semantic three-dimensional grid data from a residential complex in Wuhan. The results indicate that (1) The characteristics of 3D landscape patterns vary across different regions within multi-unit high-rise residential areas. The landscape patches in the central and southern regions are more balanced compared to other areas, while there is minimal height variation in residential buildings in the northeastern region. (2) There are notable differences in comfort levels at varying heights across different areas of the residential district. In summer, residents expressing satisfaction with environmental comfort are primarily located in high-rise buildings in the central-southern region, whereas in winter, satisfaction is concentrated among residents in lower and mid-rise buildings in both the northern center and southern areas. (3) The degree of landscape fragmentation, the dominance of certain patches, and the distribution of buildings and vegetation at different heights significantly influence residents’ comfort. Achieving a balanced distribution of green spaces, reducing building density, and ensuring a uniform arrangement of trees of varied heights can effectively enhance the living environment for residents on lower floors, providing practical strategies for the planning of green spaces and built environments that improve overall resident quality of life. This research provides a theoretical foundation and reference for evaluating thermal comfort in high-rise residential areas and optimizing green space configurations. Full article

With the intensification of climate challenges driven by rapid urbanization, the microclimate and thermal comfort of residential blocks have attracted increasing attention. Current research predominantly focuses on isolated morphological factors—such as building orientation, layout patterns, and height-to-width ratios—while neglecting the synergistic effects of multifactorial spatial configurations on outdoor thermal comfort. This study addresses this gap by analyzing 36 residential block samples in Wuhan, a representative city in a hot-summer and cold-winter (HSCW) region. Utilizing the Honeybee plugin in Grasshopper (GH) alongside the Universal Thermal Climate Index (UTCI), we simulate outdoor thermal environments to identify critical influencing elements. The results reveal how multifactor interactions shape thermal performance, providing evidence-based design strategies to optimize microclimate resilience in high-density urban contexts. This work advances the understanding of spatial morphology–thermal dynamics and offers practical insights for sustainable residential planning. This study systematically investigates the thermal performance of residential blocks through parametric prototyping and seasonal simulations. Sixteen morphological prototypes were developed by combining four building layout typologies (arrayed, staggered, enclosed, and hybrid) with three critical variables: the height-to-width ratio (HWR), building orientation deviation angle (θ), and sky visibility factor (SVF). Key findings reveal the following: (1) the hybrid layout demonstrates superior annual thermal adaptability when integrating fixed orientation (θ = 0°), moderate H/W = 1, and SVF = 0.4; (2) increased H/W ratios enhance thermal comfort levels across all layout configurations, particularly in winter wind protection; and (3) moderate orientation deviations (15° < θ < 30°) significantly improve microclimate performance in modular layouts by optimizing solar penetration and aerodynamic patterns. These evidence-based insights provide actionable guidelines for climate-responsive residential design in transitional climate zones, effectively balancing summer heat mitigation and winter cold prevention through spatial configuration optimization. Full article

Women exhibit unique vulnerabilities in health, especially regarding mental health and neurodegenerative diseases. Biological, hormonal, and metabolic differences contribute to sex-specific risks that remain underrepresented in clinical studies. Diseases such as major depressive disorder (MDD) and Alzheimer’s disease (AD) are more prevalent in women and may be influenced by hormonal transitions, particularly during menopause. Chronic low-grade inflammation is emerging as a shared mechanism underlying both conditions, and this inflammatory state can be worsened by dietary habits. During menopause, mood and sleep disturbances can influence dietary behavior, leading to enhanced snacking and consumption of high-glycemic and comfort foods. Such foods, low in nutritional value, promote weight gain and elevated inflammatory markers. Their consumption combined (or not) with a preexisting Western diet pattern—already linked to inflammation—could reinforce systemic inflammation involving the gut–brain axis. Moreover, the symptoms “per se” could act on inflammation as well. Peripheral inflammation may cross the blood–brain barrier, sustaining mood disorders and promoting neurodegenerative changes. Finally, MDD and AD are both associated with conditions such as obesity and diabetes, which occur more frequently in women. The review highlights how menopause-related changes in mood, sleep, and diet may heighten susceptibility to mental and neurodegenerative diseases. Full article

Condensation assessment of a residential building in Changsha, China-located in the hot summer and cold winter climate zone-was conducted during the Plum Rain Season (PRS) using Energy Plus simulations and field measurements. Window-opening behaviour significantly influences indoor air quality and thermal comfort. This study specifically examines how window-opening patterns, including opening duration and opening degree, affect interior surface condensation risk in a rural residential building during PRS. Results indicate that window operational status (open/closed) exerts a dominant influence on condensation risk, while varying window opening degrees during identical opening duration showed negligible differential impacts. Critical temporal patterns emerged: morning window openings during PRS should be avoided, whereas afternoon (15:00–18:00) and nighttime (18:00–06:00) ventilation proves advantageous. Optimisation analysis revealed that implementing combined afternoon and nighttime ventilation windows (15:00–18:00 + 18:00–06:00) achieved the lowest condensation risk of 0.112 among evaluated scenarios. Furthermore, monthly-adjusted window operation strategies yielded eight recommended ventilation modes, maintaining condensation risks below 0.11 and providing occupant-tailored solutions for Changsha’s PRS conditions. These findings establish evidence-based guidelines for moisture control through optimised window operation in climate-responsive building management. Full article

A study was designed to explore the possibility of using herbal supplementation to sustain growth performance during heat stress exposure in Kenguri sheep. This 60-day study was conducted on 24 Kenguri ewes (1–2 years old), randomly assigned to four treatment groups (n = 6 per group) as follows: KC (n = 6; Kenguri Control), KHS (n = 6; Kenguri Heat Stress), KCS (n = 6; Kenguri Control and herbal supplement), and KHSS (n = 6; Kenguri Heat Stress and herbal supplement). The herbal mixture of Ocimum sanctum (Tulsi), Emblica officinalis (Amla), Morinda citrifolia (Noni), Withania somnifera (Ashwagandha), and Phyllostachys edulis (Bamboo) was used in this study. The herbal supplement used in the present study was given to the KCS and KHSS groups’ animals in dry powder form at a dose of 0.8 g/Kg BW/Day. All variables were recorded fortnightly, and gene expression analysis was performed at the end of the experiment. The results indicated that the recorded temperature–humidity index (THI) provided thermal comfort for KC and KCS while inducing extremely severe heat stress to the KHS and KHSS groups. Heat stress did not alter the feed intake, while the herbal supplement during heat stress increased the feed intake from day 30 onwards. Furthermore, heat stress significantly (p < 0.001) increased the water intake, while the herbal supplement did not alter the heat stress-induced water intake. In addition, neither heat stress nor herbal supplements influenced the body weight and allometric measurements studied. Furthermore, heat stress significantly (p < 0.01) decreased the level of plasma tri-iodo-thyronine (T₃) and thyroxin (T₄) and had a non-significant effect on plasma growth hormone (GH), insulin-like growth factor-1 (IGF-1), while the herbal supplements significantly (p < 0.01) increased the levels of all these hormones studied. Likewise, in peripheral blood mononuclear cells (PBMCs) the expression patterns of growth hormone receptor (GHR), Insulin-like growth factor 1 (IGF1) and prolactin receptor (PRLR) were significantly (p < 0.001) downregulated during heat stress (0.25, 0.3, and 0.48-fold change, respectively). However, the herbal supplement significantly (p < 0.01) increased the heat stress-induced reduction in the expression pattern of these three genes (0.65, 0.61, and 0.61-fold change, respectively). Therefore, from this study, it could be concluded that although the herbal supplements did not bring positive changes in body weight and allometric measurements, it still had a beneficial impact on the endocrinology and genes governing growth performance in Kenguri ewes. Thus, the herbal feed additive used in the study shows promise for relieving heat stress in Kenguri ewes. Full article

This study explores the challenges faced by traditional dwellings amid modernization and urbanization, with a particular focus on Huizhou dwellings, which struggle with issues such as inefficient space use and suboptimal spatial quality. This study employs UWB (ultra-wideband) indoor positioning technology to examine differences in residents’ production/living behaviors and their spatial usage preferences between two Huizhou traditional dwellings with distinct preservation statuses during both the summer and winter seasons. The study reveals the following findings: (1) The hall, courtyard, and kitchen spaces are the most frequently used living areas, followed by wing rooms and patio spaces. Differences in spatial organization patterns significantly influence residents’ preferences for alternating between various functional spaces. Residents tend to favor functional spaces centered around or adjacent to key circulation areas; (2) In summer, the patio space provides shade and ventilation, creating a cool and comfortable environment that supports a variety of living activities, resulting in high utilization rates. In winter, however, the patio space hinders heat retention for the inner facade, leading to lower temperatures and reduced usage; (3) The utilization rate of wing room spaces has significantly improved after simple renovations, whereas unrenovated wing rooms and side rooms exhibit relatively low utilization rates; (4) During fine weather in winter, the courtyard space maintains a relatively comfortable temperature, making it highly utilized. In contrast, the courtyard becomes excessively hot in summer, leading to significantly lower utilization rates compared with winter. By analyzing residents’ behavioral trajectories, the study explores the differences in living behaviors and their correlation with residential spaces across the different seasons and preservation states of traditional dwellings. These results offer important perspectives for the sustainable development of residential conservation and renewal efforts. Full article

Background/Objectives: The objective of this study was to evaluate practice patterns among pediatric dentists for the management of permanent teeth needing endodontic treatment. Methods: An electronic nationwide survey was sent to all members of the American Academy of Pediatric Dentistry (AAPD). The survey assessed provider training on and confidence (0–100, with 100 = “most confident”) in treating pediatric patients needing endodontic treatment on permanent teeth, referral patterns, and preferred educational resources. A logistic regression identified significant predictors of confidence levels. Results: The final sample included 259 respondents, with 71% having over 10 years of experience in practice. A total of 47% of respondents reported performing endodontic treatments on permanent teeth in pediatric patients, with direct pulp capping (70%) and partial or full pulpotomy (62%) being the most common procedures. Although the respondents moderately agreed (53 ± 32) that they received sufficient training during their residency to perform endodontic treatment on permanent teeth, their reported comfort levels with performing these procedures were low (0.001 ± 33). The adequacy of the training received during their residency was identified as a significant predictor of a higher level of confidence (p < 0.001, 95% CI 0.437, 0.667). The respondents highlighted additional continuing education courses and training, dedicated lectures at the AAPD Annual Session, and annual joint symposia or meetings between the AAPD and the American Association of Endodontists as the most valuable educational resources for the endodontic management of permanent teeth in pediatric patients. Conclusions: The findings suggest that enhancing residency training and expanding access to targeted continuing education opportunities are critical for improving pediatric dentists’ confidence and competence in the endodontic management of permanent teeth in pediatric patients. Full article

The accuracy of identifying dynamic characteristics of super-tall buildings under typhoon conditions, as well as their correlation with the vibration amplitude, remains unclear, limiting the effective assessment of the structural performance and optimization of wind-resistant designs. To address this issue, the measured wind-generated vibration responses of Shanghai World Finance Center during the passage of Typhoon “Rumbia” were derived using data obtained from the health monitoring system of a super-tall building in Shanghai. The first and second inherent frequencies, as well as the damping ratio of the structure, were ascertained through the employment of the curve method and the standard deviation method. Based on this, a comparison and analysis were carried out regarding the variation patterns of the first and second inherent frequencies and the damping ratio with reference to the vibration amplitude. Vibration modes were identified using frequency domain analysis. The results of the natural frequency identification were compared to those from the Peak Picking method to see how well the curve method and the standard deviation method worked at finding modal parameters. Ultimately, an assessment of the super-tall building’s performance during the impact of the typhoon was conducted. The results demonstrate that the curve method and the standard deviation method can accurately identify the inherent frequency and damping ratio of the structure, with the curve method revealing a more pronounced regularity of the modal parameters. For the structure, in the horizontal and longitudinal directions, the first and second inherent frequencies exhibit a negative correlation with amplitude, while the damping ratio shows a positive correlation with amplitude. Moreover, as the floor level rises, the vibration modes in both directions of the structure steadily increase. During the impact of Typhoon “Rumbia”, the building’s performance complied with the requirements set by comfort standards. These analytical results not only provide valuable references for the wind-resistant design and vibration control of super-tall buildings but also offer critical support for condition assessment and damage identification within structural health monitoring systems. Full article