Search Results (3,063)

In modern intelligent food processing, the unpredictable variability in pomelo orientation on high-speed conveyors poses a significant challenge to automated grading and precision peeling operations. To address this, a deep learning-based method is proposed for the real-time detection of pomelo posture. Firstly, a pomelo posture dataset was constructed to support model training and validation. Secondly, to balance the extraction of posture features from uniform fruits with the low-power constraints of edge deployment, a domain-specific architectural optimization is presented. Building on the YOLOv8n framework, the proposed model synergistically integrates specialized modules. A lightweight GhostHGNetV2 foundation is utilized to significantly reduce computational redundancy while maintaining the resolution required to detect key anatomical landmarks. To overcome spatial confusion and capture multi-scale global appearance information, a multi-path coordinate attention (MPCA) module is introduced. Furthermore, the SlimNeck architecture and VoVGSCSP module streamline multi-scale feature fusion via one-time aggregation, effectively preventing computational bottlenecks. This design optimizes the computational efficiency of the model while maintaining detection accuracy. Experimental results demonstrate that compared with the baseline YOLOv8n model, the proposed method increased the mAP50 accuracy by 3.67% while reducing parameter count and computational load by 17.5% and 23.3%, respectively. Additionally, it achieved a processing speed of 19.3 FPS on the Jetson Orin Nano 6G edge platform. This research provides a critical technical foundation for the recognition of pomelo posture, enabling subsequent orientation rectification and fostering the development of streamlined, automated pomelo processing lines. Full article

Indoor Environmental Quality (IEQ) strongly influences health, comfort, and learning performance in academic buildings, yet assessment practices remain fragmented and rarely aligned with sustainability goals. This study conducted a PRISMA 2020-guided systematic literature review to identify, screen, and map IEQ indicators for educational facilities and to develop a sustainability-aligned framework for classroom evaluation. Searches of Google Scholar, Scopus, and Web of Science (2010–2025) yielded 365 records; after de-duplication and eligibility screening, 142 peer-reviewed studies were included. From these, 118 unique IEQ indicators were extracted and classified into six domains: thermal comfort, indoor air quality, acoustic quality, visual comfort, environmental quality, and spatial quality. Using sustainability-oriented screening criteria (measurability, relevance, reliability, data accessibility, understandability, and long-term applicability), 50 indicators (42%) were retained as methodologically robust, while 68 (58%) were excluded due to weak standardization or limited practical applicability. The retained indicators were systematically mapped to the environmental, social, and economic pillars and aligned with key SDGs (3, 4, 7, 11, and 13). The resulting Sustainability-Aligned IEQ Indicator Framework integrates quality-screened indicators with pillar/SDG alignment and a mixed-method pathway that combines objective monitoring and occupant perception, supporting context-sensitive evaluation, particularly for naturally ventilated and tropical learning environments. Full article

Eye tracking (ET) provides process-level indices of how students sample task-relevant information during core academic activities. In school-age learners (6–18 years) with specific learning disorders (SLDs; dyslexia, dysgraphia, and dyscalculia), ET can complement behavioural assessment by quantifying oculomotor patterns linked to decoding, model–production coordination, and stepwise strategy execution. This narrative review synthesises ET findings in SLD across reading, handwriting/copying, and arithmetic and translates them into an applied framework for school-oriented use. We summarise key metrics and Areas of Interest (AOI)-based analyses, highlight technical and data-quality requirements for valid acquisition in educational settings, and outline compact functional assessment protocols integrated with standard academic and neuropsychological measures. Building on these foundations, we propose six hypothesis-driven gaze-contingent paradigms (H1–H6) as preliminary models for future experimental testing rather than as established interventions, and we map each to its current level of empirical support, specifying primary gaze outcomes and curriculum-relevant behavioural endpoints. We emphasise that eye-movement findings in specific learning disorders are heterogeneous and may vary as a function of age, task demands, and comorbidity. Accordingly, credible training effects require retention and transfer probes under standard, non-contingent display conditions, appropriate controls, and explicit developmental interpretation. Eye tracking is positioned as complementary functional evidence and as a platform for experimentally testable, mechanism-based interventions in school-age specific learning disorders. Full article

Industrial surface inspection is fundamental to advanced manufacturing, yet reliable robotic image acquisition in complex geometries remains challenging due to severe occlusions and the inherent trade-off between resolution and coverage. Inspired by human visual inspection behaviors and perception–action coordination mechanisms, this paper proposes a hierarchical trajectory optimization framework for robotic image acquisition based on measured point clouds. Specifically, a multi-constraint preprocessing model is developed to emulate human-like active perception strategies, enabling occlusion-aware viewpoint generation over complex concave and convex surfaces with adaptive camera orientation. Building upon this, a multi-objective trajectory optimization method is introduced to coordinate global coverage and local motion efficiency, jointly optimizing viewpoint sequencing, path length, and motion smoothness hierarchically. To further enhance flexibility in constrained environments, a Pose Reachability Augmented Generative Adversarial Network (PRAGAN) is proposed to learn feasible and adaptable imaging postures under kinematic constraints. Experimental results on an industrial robotic platform equipped with 2D and 3D vision systems demonstrate 100% coverage of key surface areas, a 47.0% reduction in path length, and a 37.5% decrease in solution time compared with the baseline in the physical experiments, while ensuring collision-free operation. Both simulation and real-world experiments validate that the proposed framework effectively captures human-inspired perception and motion coordination, providing a practical and scalable solution for complex industrial surface inspection. Full article

Building-Integrated Photovoltaics (BIPV) can contribute to decarbonisation, but its large-scale deployment requires accurate energy yield predictions that justify these systems during the decision-making process to ensure cost-effectiveness. In urban contexts, boundary conditions involve modelling strategies that can reliably represent the effect of shading from nearby elements. However, specific tools for proper modelling BIPV are not generally available and the workflow frequently requires the combination of different tools. Nowadays there is still no clear nor unique strategy for modelling BIPV, and expert groups are currently working on benchmarking analyses. This work compares energy yield estimations from two PV simulation software tools, System Advisor Model and PVsyst to seven years of experimental data (2017–2023) from five BIPV façade arrays distributed across three orientations (east, south and west). The main focus was twofold. Firstly, to analyse their management of shadows by following two different shading approaches: their built-in 3D modelling tools and a Digital Surface Model (DSM). Secondly, to evaluate the capability of these tools to simulate the performance of real BIPV systems. Results manifest that conventional and accessible PV software can be suitable for BIPV modelling as long as care is taken to properly assess the effect of shading, especially from urban tree canopies. The novel DSM strategy proposed is proven effective and can be a valid alternative in certain cases when the availability of in situ data is limited. Full article

Indoor environmental quality (IEQ) is increasingly recognized as a critical factor in shaping employee well-being, satisfaction, and work performance, particularly in hybrid workplace settings. This mixed-methods study examined how integrated IEQ conditions influence employee experience in a public-sector hybrid workplace through a case study of the WorkHub, a technology-enabled flexible workspace embedded within a large municipal utility. Quantitative data were collected from 93 valid survey responses using the Workplace Environment Satisfaction and Performance Questionnaire (WESP-Q™), and qualitative insights were obtained from a 90-min participatory think tank session with 24 employees. Results showed that WorkHub users reported significantly higher satisfaction across 15 of 18 environmental and spatial dimensions, including layout, thermal comfort, air quality, lighting, furnishings, cleanliness, and overall building experience. They also reported significantly stronger outcomes in collaboration access, work transition, focus support, work efficiency, workspace productivity, pride in work, and job satisfaction. Qualitative findings reinforced these results, highlighting technology integration, daylight, and spatial flexibility as key strengths, while identifying acoustics, thermal discomfort, and limited privacy as persistent challenges. These findings support a systems-oriented, human-centered approach to workplace design, demonstrating that integrated IEQ can enhance employee experience, collaboration, and organizational performance in hybrid public-sector environments. Full article

Cattle behavior constitutes important phenotypic information reflecting animals’ health status, activity level, and welfare condition, and is therefore of considerable significance for automated monitoring and precision management in smart livestock farming. However, under complex barn conditions, cattle behavior recognition is easily affected by factors such as illumination variation, partial occlusion, background interference, and individual differences, thereby reducing recognition stability and generalization capability. To address these challenges, this study proposes a pose-driven method for cattle behavior recognition in complex barn environments. First, a 16-keypoint annotation scheme suitable for describing bovine posture, termed cow16, was constructed. Based on this scheme, OpenPose was employed to extract heatmaps (HMs) and part affinity fields (PAFs), which were then used to build an intermediate HM/PAF posture representation. Subsequently, this representation was taken as the input to a lightweight convolutional neural network for classifying three behavioral categories: stand, walk, and lying. On this basis, class-imbalance correction during training and a multi-random-seed logits ensemble strategy during inference were further introduced. In addition, knowledge distillation was adopted to transfer knowledge from a high-performance teacher model to a lightweight student model. Experimental results demonstrate that training-stage class-imbalance correction and inference-stage multi-random-seed logits ensembling exhibit strong complementarity; when combined, the AB configuration improves the test-set Macro-F1 by 3.83 percentage points. Moreover, the distilled student model still achieves competitive recognition performance while maintaining 1× inference cost, indicating a favorable trade-off between accuracy and efficiency. This study provides a useful reference for deployment-oriented cattle behavior recognition in smart farming scenarios and offers a lightweight technical basis for subsequent practical applications. Full article

In this research paper, we introduce an improved multiple-component decomposition technique based on the refined volume scattering models (MCSMRV) for polarimetric interferometric synthetic aperture radar (PolInSAR) system. The primary objective of this methodology is to address the issue of overestimation in volume scattering (OVS) and to clarify the mixed ambiguities associated with scattering mechanisms. Our approach incorporates an innovative inversion technique for rotation angles in urban areas, alongside the newly proposed volume scattering models. Furthermore, a refined Wishart mixture model (RWMM) is proposed for distinguishing building regions from non-building regions, which can effectively support the rational selection of volume scattering models. Additionally, the polarimetric interferometric similarity parameter (PISP) is employed to modify the volume scattering models for buildings with diverse orientation angles. To validate the effectiveness of MCSMRV, we utilize ESAR PolInSAR data and the PolInSAR data collected by the Aerospace Information Research Institute. Various mathematical methods are applied to assess the performance of MCSMRV. The experimental results clearly demonstrate that MCSMRV represents a robust method for characterizing the scattering mechanisms across different terrain types. Full article

At the international level, heritage is widely recognised as a critical component of sustainable development. However, in South Asian countries such as Pakistan, India, and Bangladesh, historic cities continue to struggle to preserve and integrate built heritage amid rapid urbanisation, socio-economic transformation, and evolving contemporary urban demands. Heritage places in these contexts are shaped by complex interrelations between collective memory, the built environment, and socio-cultural identity. Yet, conservation practices have been mainly implemented through fragmented, building-by-building approaches that neglect urban-scale coherence and intangible cultural dimensions. This article addresses this gap by examining adaptive reuse as a value-based conservation strategy in historic urban quarters, where heritage serves as both a repository of cultural memory and a catalyst for sustainable, experience-based tourism. Drawing on qualitative fieldwork, heritage value assessment matrices, and doctoral research, this study uses the Saddar Bazaar Quarter in Karachi, Pakistan, as a case study to explore how tangible and intangible heritage values can be systematically integrated into conservation and regeneration processes. The findings demonstrate that heritage-led adaptive reuse, when embedded within a comprehensive urban-scale conservation framework, can sustain everyday socio-cultural practices, reinforce local identity, and enhance the legibility of historic urban environments. Rather than positioning tourism as a primary driver, the study shows that culturally sensitive and community-oriented tourism emerges as an outcome of successful heritage integration, grounded in lived urban experience rather than commodified representation. Based on these insights, the article proposes a value-based integration framework that aligns heritage conservation, adaptive reuse, and sustainable tourism within historic urban quarters. The framework offers transferable methodological guidance for revitalising heritage places and collective memories, while providing policy-relevant insights for heritage governance that support sustainability objectives, community resilience, and inclusive urban regeneration in post-colonial contexts. Full article

Softness-Weakness constitutes a core category in Laozi’s philosophy, while in Yan Zun’s Laozi zhigui of the Western Han dynasty, Harmony-Weakness becomes the key concept for interpreting Laozi’s thought. This conceptual transformation from Softness-Weakness to Harmony-Weakness both reflects the intellectual background of Confucian–Daoist synthesis in the Han dynasty and marks the creative development of Daoist philosophy during this period. Building upon complete inheritance of Laozi’s Softness-Weakness thought, Yan Zun achieved a theoretical reconstruction of Daoist philosophy through introducing Harmony—this Confucian core category. At the cosmological level, Yan Zun creatively incorporated Supreme-Harmony into the sequence of the Dao’s generation, establishing its ontological position as the “progenitor” of the myriad things. Through the proposition “Harmony is its destination, Weakness is its function”, Yan Zun endowed Harmony-Weakness with a clear teleological dimension and value orientation, elevating Harmony-Weakness from a survival strategy to a fundamental principle of cosmic generation. At the practical level, through the Harmony-Weakness concept, Yan Zun constructs a complete system integrating self-cultivation and politics, developing Daoist thought from relatively dispersed wisdom discourse into systematic theory. This conceptual transformation transcends the simple opposition between Softness-Weakness and hardness-strength, achieving a unity in which hardness and Softness mutually assist each other under Harmony’s regulation. However, while the introduction of Harmony deepened the theory, it may also have somewhat weakened the critical edge of Softness-Weakness thought, and the substantialization of Supreme-Harmony may have departed from Laozi’s nihilistic spirit. This theoretical tension precisely demonstrates the theoretical dilemmas and historical choices that Daoist thought faced in its Han dynasty development. Full article

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

This article advances a critical rethinking of digital transformation in craft-based and socially embedded production systems by examining ateliers of social integration as community-led solidarity spaces where sewing and embroidery practices intersect with relational, care-oriented, and collective dimensions. Existing debates on digitalisation remain largely centred on automation, scale, and efficiency, overlooking how technology operates within care-based and territorially embedded economies. To address this gap, the article develops an alternative analytical framework grounded in relational economies and the ethics of care. While the phenomenon is transnational, the empirical analysis focuses on the Italian context and draws on data from CreAbility, an ongoing action-research project aimed at building a digital community of micro and small fashion enterprises, associations, and designers characterized by social and cultural impact. Against dominant, scale-oriented models of innovation, the article conceptualises ateliers of social integration as relational ecosystems in which value is co-produced through social ties, inclusion practices, and localized knowledge. From this perspective, digital technologies serve as situated mediators that extend and amplify proximity-based relations. This reframing challenges linear and growth-centred accounts of digital innovation, instead proposing a non-linear, care-centred, and place-based model of digital transformation. Methodologically, the study adopts a mixed-methods design combining quantitative and qualitative techniques. Data were collected between June and July 2025 through an online questionnaire distributed to a broader population of Italian ateliers of social integration and were complemented by participatory focus groups involving organisational representatives. The findings show that these ateliers operate as infrastructures of proximity in which production, care, and community are co-constitutive, and where digital practices support forms of extended embeddedness rather than substitution. In doing so, the article contributes to debates on digitalisation, social innovation, and the care economy by showing how alternative, relational, and non-scalable models of production can reshape the meaning and the trajectories of innovation. Full article

This study investigates the development of high-strength biofiber cement boards with enhanced thermal insulation properties by utilizing recycled biofibers derived from cement packaging bags, combined with a water-based adhesive to enhance the curing efficiency of Portland cement through a cementation–curing process. This approach reduces waste from cement packaging and other biofiber residues through recycling, thereby promoting environmental sustainability. Moreover, it does not require the use of additional chemicals for the disposal or treatment of fiber waste, nor does it require the incineration of biofiber waste. Recycled biofiber from cement bags, composed primarily of cellulose (60 wt%), lignin (15 wt%), and hemicellulose (10 wt%), serves as a reinforcing phase, while the cement and adhesive mixture functions as a strong binding matrix. The fabrication of composite materials using undamaged cement bag fibers preserves fiber integrity and enables a well-ordered one-dimensional (1D) fiber alignment, which promotes more effective reinforcement than two-dimensional (2D) or three-dimensional (3D) orientations, in accordance with the rule of mixtures. In addition, the incorporation of a water-based PVAc adhesive accelerates the curing rate of the cement phase, promoting the formation of a strong interconnected network structure, and facilitates a more complete curing process. The physical, mechanical, chemical, and thermal properties of the biofiber cement boards were evaluated in accordance with relevant industrial standards, including TISI 878:2023, BS 874, ASTM C1185, ASTM D570, ASTM C518, ISO 8301, and JIS A1412. The results indicate that an optimal cement mortar to water-based adhesive ratio of 1:2, combined with an increased number of biofiber sheet layers, significantly enhances material performance, particularly in Formulas (7)–(9). Among these, Formula (9) exhibits the lowest water absorption (0.0835 ± 0.0102%), the highest tensile strength (19.489 ± 0.670 MPa), the highest flexural strength (20.867 ± 2.505 MPa), the highest Young’s modulus (5735.068 ± 387.032 MPa), and low thermal conductivity (0.152 W/m.K). The resulting boards demonstrate strong bonding ability, enhanced resistance to fire, moisture, and weathering, and a longer service life compared to lower cement-to-adhesive ratios (1:1 and 1:0). These findings demonstrate the potential of recycled biofiber composites, combined with water-based adhesives, as sustainable alternative materials for thermal insulation and structural applications, including ceilings and walls in building construction. Full article

Thermochromic materials (TCMs) have attracted increasing attention as passive adaptive materials for solar regulation in buildings because they can reversibly change their optical properties in response to temperature without external energy input. Owing to this temperature-triggered optical modulation, they have been widely investigated for smart windows, temperature indicators, anti-counterfeiting labels, and flexible devices. In recent years, representative systems such as VO₂-based materials, polymers, hydrogels, and organic–inorganic hybrids have shown steady progress, especially in transition-temperature tuning, spectral selectivity, and cycling stability. This review summarizes the main classes of TCMs as well as their color-changing mechanisms, preparation methods, and performance-regulation strategies, with an emphasis on building energy efficiency and passive solar regulation. Typical applications and current bottlenecks are also discussed, including response speed, durability, environmental compatibility, and large-scale manufacturing. Finally, several practical directions for future work are highlighted, particularly low-cost synthesis, multifunctional integration, and application-oriented material design. Full article

Identifying primary ceramic forming techniques is often problematic when surface traces are altered or erased by secondary shaping on the potter’s wheel, particularly in vessels combining hand-building and wheel use. This study aims to develop a quantitative, non-destructive method to distinguish wheel-throwing and wheel-coiling techniques by analyzing internal fabric features. Experimental replicas of Middle Minoan handleless conical cups (18th cent. BC), produced using wheel-throwing-off-the-hump and wheel-coiling techniques, were investigated using X-ray micro-computed tomography (µCT). Macropores were segmented from complete 3D µCT datasets and their shape preferred orientation was quantitatively assessed through ellipsoid fitting, orientation distribution functions, and pole figure analysis. The results reveal systematic and reproducible differences between the two forming techniques: wheel-coiled vessels show predominantly horizontal pore elongation, expressed as equatorial girdle textures and vertically clustered short axes, whereas wheel-thrown vessels display inclined pore orientations, forming displaced girdles and ring-like short-axis distributions. These contrasting orientation patterns reflect distinct deformation fields imposed during vessel shaping. The study demonstrates that quantitative 3D analysis of pore orientation in whole vessels provides reliable criteria for identifying ceramic forming techniques and confirms previous qualitative observations. This approach offers a robust framework for technological analysis of ceramics and can be applied to both complete vessels and suitably oriented fragments. Full article