Search Results (399)

The paper presents select in situ and numerical investigations related to improving the energy efficiency of historic buildings. Using the case study of a historic timber building as an example, the procedure of the in situ investigation of its existing condition is presented. This procedure included measuring the moisture of the timber elements, determining the presence of fungi, mold, and wood-destroying insects, infrared camera inspection, and measuring the microclimate of the rooms. According to the conclusions of the building survey report, conservation guidelines were proposed. On the basis of those proposed guidelines, thermal upgrades were suggested, including insulation on the inside of the envelope components. Detailed numerical calculations were provided for the proposed thermal insulation systems. Those included a hygrothermal performance evaluation in the context of the change in the moisture content of timber elements in the insulated envelope components. The risk of mold development on the surface of selected junctions was also estimated. The key outcome of this study is a proprietary procedure for improving the thermal protection quality of envelope components of historic timber buildings. Full article

Per- and polyfluoroalkyl substances (PFASs) have attracted global attention due to their persistence and biological toxicity, becoming critical emerging contaminants in river and lake environments worldwide. Building upon existing studies, this work aims to comprehensively understand the pollution patterns, environmental behaviors, and potential risks of PFASs in freshwater systems, thereby providing scientific evidence and technical support for precise pollution control, risk prevention, and the protection of aquatic ecosystems and human health. Based on publications from 2002 to 2025 indexed in the Web of Science (WoS), bibliometric analysis was used to explore the temporal evolution and research hotspots of PFASs, and to systematically review their input pathways, pollution characteristics, environmental behaviors, influencing factors, and ecological and health risks in river and lake environments. Results show that PFAS inputs originate from both direct and indirect pathways. Direct emissions mainly stem from industrial production, consumer product use, and waste disposal, while indirect emissions arise from precursor transformation, secondary releases from wastewater treatment plants (WWTPs), and long-range atmospheric transport (LRAT). Affected by source distribution, physicochemical properties, and environmental conditions, PFASs display pronounced spatial variability among environmental media. Their partitioning, degradation, and migration are jointly controlled by molecular properties, aquatic physicochemical conditions, and interactions with dissolved organic matter (DOM). Current risk assessments indicate that PFASs generally pose low risks in non-industrial areas, yet elevated ecological and health risks persist in industrial clusters and regions with intensive aqueous film-forming foam (AFFF) use. Quantitative evaluation of mixture toxicity and chronic low-dose exposure risks remains insufficient and warrants further investigation. This study reveals the complex, dynamic environmental behaviors of PFASs in river and lake systems. Considering the interactions between PFASs and coexisting components, future research should emphasize mechanisms, key influencing factors, and synergistic control strategies under multi-media co-pollution. Developing quantitative risk assessment frameworks capable of characterizing integrated mixture toxicity will provide a scientific basis for the precise identification and effective management of PFAS pollution in aquatic environments. Full article

Urbanization reshapes bird communities by filtering species according to their ecological traits, often reducing richness, altering relative abundances, and favoring a subset of functionally tolerant species that dominate urban assemblages. Some native taxa are able to inhabit cities, even using them as stepping stones for range expansion. We examined urban habitat use, microhabitat selection, and potential niche partitioning between two range-expanding thrushes (Austral Thrush [Turdus falcklandii] and Rufous-bellied Thrush [Turdus rufiventris]) in two urban settlements in the Pampas region, Argentina. Using 131 transects across green areas and urbanized zones, we related abundance patterns to habitat features at the transect scale and evaluated microhabitat selection at the individual level. Austral Thrush abundance increased with herbaceous cover, tree cover, and even concrete surfaces, suggesting a relatively high tolerance to fragmented green spaces within dense urban matrices. In contrast, Rufous-bellied Thrush showed a positive association with tree cover, avoided tall buildings, and reached higher abundance in the smaller city, consistent with its recent arrival in the region and preference for less intensively urbanized environments. Microhabitat data revealed marked vertical stratification: Austral Thrush foraged almost exclusively at ground level on grassy or bare substrates, while Rufous-bellied Thrush used trees, shrubs, and vines more frequently. These differences reflect fine-scale resource partitioning that may contribute to reducing niche overlap and favor the coexistence of both species in recently colonized urban areas, while recognizing that such dynamics occur within broader bird assemblages where multiple species interact and compete for space and resources. Our findings highlight that even closely related species can respond divergently to urban structure, and that maintaining structural and substrate heterogeneity within cities may help support native bird diversity. Full article

Few-Shot Semantic Segmentation (FSS) faces significant challenges in modeling complex backgrounds and maintaining prediction consistency due to limited training samples. Existing methods oversimplify backgrounds as single negative classes and rely solely on pixel-level alignments. To address these issues, we propose a symmetry-aware superpixel-enhanced FSS framework with a symmetric dual-branch architecture that explicitly models the superpixel region-graph in both the support and query branches. First, top–down cross-layer fusion injects low-level edge and texture cues into high-level semantics to build a more complete representation of complex backgrounds, improving foreground–background separability and boundary quality. Second, images are partitioned into superpixels and aggregated into “superpixel tokens” to construct a Region Adjacency Graph (RAG). Support-set prototypes are used to initialize query-pixel predictions, which are then projected into the superpixel space for cross-image prototype alignment with support superpixels. We further perform message passing/energy minimization on the RAG to enhance intra-region consistency and boundary adherence, and finally back-project the predictions to the pixel space. Lastly, by aggregating homogeneous semantic information, we construct robust foreground and background prototype representations, enhancing the model’s ability to perceive both seen and novel targets. Extensive experiments on the PASCAL-$5^i$ and COCO-${20}^i$ benchmarks demonstrate that our proposed model achieves superior segmentation performance over the baseline and remains competitive with existing FSS methods. Full article

Background: Despite chemotherapy-related toxicities being more likely in older patients, no routine prediction tool has been validated for the UK population. Previous research within the TOASTIE (tolerance of anti-cancer systemic therapy in the elderly) study found a low predictive performance of the Cancer and Aging Research Group (CARG) score for severe chemotherapy-related toxicities. Building on this, the TOASTIE study dataset was used to assess the viability of developing a predictive model with baseline variables and frailty scores for severe chemotherapy-related toxicities in older patients. Methods: All patients from the TOASTIE dataset were included, with the inclusion/exclusion criteria detailed in the TOASTIE protocol. Demographic factors, self-assessment scores, Rockwood Clinical Frailty Score and researcher’s estimated risks of toxicity were assessed for their association with severe chemotherapy-related toxicities. After data partition into 70:15:15 train/validation/test, models were built on the training dataset using logistic regression (LR), LASSO and random forest (RF). Models were optimized with a validation set with LR and LASSO; cross-validation was used with RF. Model performance was assessed with balanced accuracy, NPV and AUC. Results: Of the 322 patients included, the incidence of severe toxicities was 22% (n = 71). Ten variables were statistically significant, albeit weakly associated with severe toxicities: primarily patient-reported factors, Performance Status and high baseline neutrophil count. LR models gave the best balanced accuracies of 0.6382 (AUC 0.6950, NPV 0.8696) and 0.6469 (AUC 0.6469, NPV 0.4286) with LASSO, and 0.6294 (AUC 0.6557, NPV 0.6557) with RF. Conclusions: Models lack sufficiently robust results for clinical utility. However, a high NPV in predicting no toxicity could help identify lower-risk patients who may not require dose reductions, potentially improving overall outcomes. Full article

In geo-distributed deployments, sensor data are collected under the coordination of smart terminals and relayed on-chain via decentralized oracles. A motivating scenario involves healthcare networks where regional hospitals submit aggregated medical data to blockchain systems while maintaining strict information security—often designating one gateway per region for external communication. Long geographical distances between smart terminals stress traditional consensus with excessive network overhead and limited efficiency. To address this, we propose a layered BFT consensus method, 2-layer EaZy BFT (2EZBFT). The system forms multiple independent groups of smart terminals and builds a two-layer consensus architecture—“intra-group synchronization, inter-group consensus”—to complete cross-group data aggregation and final on-chain consensus. This layered design reduces intra-group communication complexity by lowering the number of nodes per group and reduces cross-group interactions via leader-side aggregation, thereby lowering overall network overhead. Compared with other BFT algorithms, the proposed scheme improves the efficiency of data collection and on-chain reporting while ensuring consensus security and consistency. Experiments show improvements in metrics such as network overhead and consensus latency. In a discrete-event simulation with an asymmetric WAN latency matrix and geo-partitioned groups, 2EZBFT achieves up to $45\%$ higher throughput than flat BFT algorithms such as PBFT and HotStuff under high load. It provides a practical path for efficient data interaction in decentralized oracles and offers guidance for improving the performance of blockchain–real-world data exchange. Full article

Multi-modal image segmentation is a key task in various fields such as urban planning, infrastructure monitoring, and environmental analysis. However, it remains challenging due to complex scenes, varying object scales, and the integration of heterogeneous data sources (such as RGB, depth maps, and infrared). To address these challenges, we proposed a novel multi-modal segmentation framework, DyFuseNet, which features dynamic adaptive windows and cross-scale feature fusion capabilities. This framework consists of three key components: (1) Dynamic Window Module (DWM), which uses dynamic partitioning and continuous position bias to adaptively adjust window sizes, thereby improving the representation of irregular and fine-grained objects; (2) Scale Context Attention (SCA), a hierarchical mechanism that associates local details with global semantics in a coarse-to-fine manner, enhancing segmentation accuracy in low-texture or occluded regions; and (3) Hierarchical Adaptive Fusion Architecture (HAFA), which aligns and fuses features from multiple modalities through shallow synchronization and deep channel attention, effectively balancing complementarity and redundancy. Evaluated on benchmark datasets (such as ISPRS Vaihingen and Potsdam), DyFuseNet achieved state-of-the-art performance, with mean Intersection over Union (mIoU) scores of 80.40% and 80.85%, surpassing MFTransNet by 1.91% and 1.77%, respectively. The model also demonstrated strong robustness in challenging scenes (such as building edges and shadowed objects), achieving an average F1 score of 85% while maintaining high efficiency (26.19 GFLOPs, 30.09 FPS), making it suitable for real-time deployment. This work presents a practical, versatile, and computationally efficient solution for multi-modal image analysis, with potential applications beyond remote sensing, including smart monitoring, industrial inspection, and multi-source data fusion tasks. Full article

The subject of this paper is an analysis of the use of wall heating and cooling modules with heat pipes for efficient space heating and cooling. The modules under consideration constitute a structural element installed in the room’s partition structure and consist of heat pipes embedded in a several-centimeter layer of concrete. Water-based central heating and chilled water systems were used as the heat and cooling source. The heat pipes are filled with a thermodynamic medium that changes state in repeated gas–liquid cycles. The advantage of this solution is the use of heat pipes as a heating and cooling element built into the wall, instead of a traditional water system. This solution offers many operational benefits, such as reduced costs for pumping the heat medium. This paper presents an analysis of the potential of using heat pipe modules for heating and cooling in real-world buildings in Poland. Taking into account the structural characteristics of the rooms under consideration (i.e., internal wall area, window area), an analysis was conducted to determine the potential use of the modules for space heating and cooling. The analysis was based on rooms where, according to the authors, the largest possible use of internal and external wall surfaces is possible, such as hotels and schools. Based on the simulations and calculations, it can be concluded that the modules can be effectively used in Poland as a real heating and cooling element: standalone, covering the entire heating and cooling demand of a room, e.g., a hotel room, or as a component working with an additional system, e.g., air cooling and heating in school buildings. The changes in outdoor air temperature, during the year analyzed in the article, were in the range of −24/+32 °C. Full article

This manuscript is aimed at analyzing how operating factors may affect the durability of thermal insulation in building partitions located underground. It examines the durability of inverted insulation systems where thermal insulation is installed above the waterproofing layer and used in residential foundation slabs. The article demonstrates that, despite their popularity due to cost efficiency, the long-term success of these systems depends on thorough investigations of thermal isolation, especially considering different climate conditions. The analysis was based on an extensive literature review (2016–2024), supplemented with laboratory test results on extruded (XPS) and expanded (EPS) polystyrene boards. Additional tests examined the water penetration mechanism into insulation layers that are in direct contact with groundwater, revealing that cyclic freezing and thawing significantly increase moisture levels. The findings highlight the need for updated region-specific guidelines for the underground insulation in Central and Eastern Europe. Full article

This research investigates the integration of green cores as central biophilic elements in residential architecture, proposing a climate-responsive design methodology grounded in architectural optimization. The study begins with the full-scale refurbishment of a compact urban apartment, wherein interior partitions, fenestration and material systems were reconfigured to embed vegetated zones within the architectural core. Light exposure, ventilation potential and spatial coherence were maximized through data-driven design strategies and structural modifications. Integrated planting modules equipped with PAR-specific LED systems ensure sustained vegetation growth, while embedded environmental infrastructure supports automated irrigation and continuous microclimate monitoring. This plant-centered spatial model is evaluated using quantifiable performance metrics, establishing a replicable framework for optimized indoor ecosystems. Photosynthetically active radiation (PAR)-specific LED systems and embedded environmental infrastructure were incorporated to maintain vegetation viability and enable microclimate regulation. A programmable irrigation system linked to environmental sensors allows automated resource management, ensuring efficient plant sustenance. The configuration is assessed using measurable indicators such as daylight factor, solar exposure, passive thermal behavior and similar elements. Additionally, a post-occupancy expert assessment was conducted with several architects evaluating different aspects confirming the architectural and spatial improvements achieved through the refurbishment. This study not only demonstrates a viable architectural prototype but also opens future avenues for the development of metabolically active buildings, integration with decentralized energy and water systems, and the computational optimization of living infrastructure across varying climatic zones. Full article

Hakka traditional vernacular dwellings embody regionally specific climatic adaptation strategies. This study takes the Meizhou Guangludi enclosed house as a case study to evaluate its climate adaptability with longevity and passive survivability factors of the Hakka three-hall enclosed house under subtropical climatic conditions. A mixed research method is employed, integrating visualized parametric modeling analysis and on-site measurement comparisons to quantify wind, temperature, solar radiation/illuminance, and humidity, along with human comfort zone limits and building environment. The results reveal that nature erosion in the Guangludi enclosed house is the most pronounced during winter and spring, particularly on exterior walls below 2.8 m. Key issues include bulging, spalling, molding, and fractured purlins caused by wind-driven rain, exacerbated by low wind speeds and limited solar exposure, especially at test spots like the E8–E10 and N1–N16 southeast and southern walls below 1.5 m. Fungal growth and plant intrusion are severe where surrounding trees and fengshui forests restrict wind flow and lighting. In terms of passive survivability, the Guangludi enclosed house has strong thermal insulation and buffering, aided by the Huatai mound; however, humidity and day illuminance deficiencies persist in the interstitial spaces between lateral rooms and the central hall. To address these issues, this study proposes strategies such as adding ventilation shafts and flexible partitions, optimizing patio dimensions and window-to-wall ratios, retaining the spatial layout and Fengshui pond to enhance wind airflow, and reinforcing the identified easily eroded spots with waterproofing, antimicrobial coatings, and extended eaves. Through parametric simulation and empirical validation, this study presents a climate-responsive retrofit framework that supports the sustainability and conservation of the subtropical Hakka enclosed house. Full article

Taking Renhezhuang in Yongtai, Fujian, as a case study, this paper explores a research framework that integrates historical records with architectural remains under technological support. Renhezhuang not only preserves relatively complete partition documents but also retains a clear spatial configuration, providing ideal conditions for comparative analysis between textual records and physical structures. By employing space syntax, daylighting simulation, and ventilation modeling, this study links the logic of property allocation recorded in documents with the spatial organization of the building. The results reveal that the distribution of living units in Renhezhuang did not pursue strict equality; rather, it achieved balance through differentiated allocation, reflecting the coordination mechanisms of a traditional lineage society under limited resources. This study not only proposes a methodological framework that integrates textual evidence, spatial remains, and technical tools, but also underscores the sociological significance of built heritage as an entry point for understanding social order. The findings offer valuable insights for both heritage conservation and the study of socio-spatial dynamics. Full article

Advancements in material technologies and increasingly stringent thermal insulation requirements are driving the search for innovative solutions to serve as an alternative to traditional insulating materials. Using 3D printing techniques to produce thermal insulation opens up new possibilities for creating structures, geometries, and shapes from a variety of raw materials, ranging from synthetic polymers to biodegradable composites. This study aimed to develop a modern thermal insulation barrier with a comparable thermal conductivity to conventional materials to enhance the energy efficiency of buildings. Cellular materials based on the Kelvin cell were fabricated using additive manufacturing via 3D SLS printing from a composite consisting of a biodegradable material (TPS) and a recyclable polymer (PA12). The printed cellular structural partitions were tested for their thermal insulation properties, including thermal conductivity coefficient, thermal transmittance (U-value), and thermal resistance. The best thermal insulation performance was demonstrated by a double-layer partition made from TPS + PA12 at a mass ratio of 5:5 and with a thickness of 60 mm. This sample achieved a thermal conductivity of λ = 0.026 W/(m·K), a thermal resistance of R = 2.4 (m²·K)/W, and a thermal transmittance of U = 0.42 W/(m²·K). Cellular partition variants with the most favorable properties were incorporated into building thermal balance software and an energy simulation was conducted for a single-family house using prototype insulating materials. This enabled an assessment of their energy efficiency and cost-effectiveness. Full article

The extraction of architectural structural line features can simplify the 3D spatial representation of built environments, reduce the storage and processing burden of large-scale point clouds, and provide essential geometric primitives for downstream modeling tasks. However, existing 3D line extraction methods suffer from incomplete and fragmented contours, with missing or misaligned intersections. To overcome these limitations, this study proposes a patch-level framework for 3D line extraction and structural optimization from building point clouds. The proposed method first partitions point clouds into planar patches and establishes local image planes for each patch, enabling a structured 2D representation of unstructured 3D data. Then, graph-cut segmentation is proposed to extract compact boundary contours, which are vectorized into closed lines and back-projected into 3D space to form the initial line segments. To improve geometric consistency, regularized geometric constraints, including adjacency, collinearity, and orthogonality constraints, are further designed to merge homogeneous segments, refine topology, and strengthen structural outlines. Finally, we evaluated the approach on three indoor building environments and four outdoor scenes, and experimental results show that it reduces noise and redundancy while significantly improving the completeness, closure, and alignment of 3D line features in various complex architectural structures. Full article

Weather routing is a critical guarantee for the safe and economical navigation of ships. Existing methods for weather routing still face challenges in selecting the appropriate planning granularity. A granularity that is overly coarse may result in routes passing through coastal and island-rich waters, such as coastal zones and reefs, thus compromising navigational safety. Conversely, a granularity that is excessively fine leads to an exponential increase in computational complexity, rendering the problem intractable. To address this issue, this paper proposes an efficient method for weather routing in coastal and island-rich waters, guided by ship trajectory big data: First, an adaptive quadtree is used to partition the navigable space into an adaptive grid, based on which a route network is constructed using ship trajectory big data. Next, a ship motion model is introduced to build both static and dynamic marine environmental fields, which are used to dynamically update the time weights of the route network. Finally, using the updated route network as a guide, the method aims to minimize voyage time and employs an improved time-varying A* algorithm for weather routing. Experimental results show that the proposed method effectively adapts to coastal and island-rich waters, outperforming the baseline SIMROUTE in safety, optimization, and efficiency. Unlike SIMROUTE, which crosses restricted areas, it avoids such risks entirely. It achieves average reductions of 6.8% in route length and 4.3% in navigation time and is 5.8 times faster than SIMROUTE for fine-grained planning. This balances voyage time, safety, and efficiency, offering a practical weather routing solution. Full article