Search Results (1,588)

Accurate fine-scale forest mapping is fundamental for ecological monitoring and resource management. While deep learning semantic segmentation methods have advanced the interpretation of high-resolution UAV imagery, their generalization across diverse forest regions remains challenging due to high spatial heterogeneity. To address this, we propose two enhanced versions based on the PP-LiteSeg architecture for robust cross-regional forest segmentation. Version 01 (V01) integrates a multi-branch attention fusion module composed of parallel channel, spatial, and pixel attention branches. This design enables fine-grained feature enhancement and precise boundary delineation in structurally regular artificial forests, such as the Huayuan Forest Farm. As a result, V01 achieves a mIoU of 92.64% and an F1-score of 96.10%, representing an approximately 18 percentage-point mIoU improvement over PSPNet and DeepLabv3+. Building on this, Version 02 (V02) introduces a lightweight residual connection that directly shortcuts the fused features, thereby improving feature stability and robustness under complex textures and illumination, and demonstrates stronger performance in naturally heterogeneous forests (Longhai Township), attaining an mIoU of 91.87% and an F1-score of 95.77% (5.72 percentage-point mIoU gain over DeepLabv3+). We further conduct comprehensive comparisons against conventional CNN baselines as well as representative lightweight and transformer-based models (BiSeNetV2 and SegFormer-B0). In bidirectional cross-region transfer (train on one region and directly test on the other), V02 exhibits the most stable performance with minimal degradation, highlighting its robustness under domain shift. On a combined cross-regional dataset, V02 achieves a leading mIoU of 91.50%, outperforming U-Net, DeepLabv3+, and PSPNet. In summary, V01 excels in boundary delineation for regular plantation forests, whereas V02 shows more stable generalization across highly varied natural forest landscapes, providing practical solutions for region-adaptive UAV forest segmentation. Full article

This study presents a life cycle assessment of a low-cost pilot-scale wastewater treatment system that combines solar photocatalytic oxidation with Nature-based Solutions (NBSs) for a specially constructed wetland (CW). The prototype was designed and assessed for its efficiency in treating urban wastewater and its environmental impact on agricultural irrigation reuse. Evaluations were performed with the SimaPro software, applying the Impact ReCiPe Medpoint methodology, which includes characterization and selection of the relevant environmental issues steps. The results demonstrate the potential of this hybrid system for providing high-quality treated wastewater suitable for agricultural reuse in water-scarce regions. The analysis reveals that the operational phase, mainly driven by energy consumption for pumping, aeration, and photocatalytic processes, accounts for over 85–98% of the total global warming potential (GWP), primarily due to reliance on fossil-based electricity. Conversely, the construction phase significantly impacts land use and toxicity categories, with concrete and substrate production contributing around 95% to land occupation and 97% to human toxicity. The photocatalytic subsystem also contributes notably to embodied carbon at 42.4%, owing to energy-intensive manufacturing. The results underscore the importance of optimizing operational energy efficiency and selecting sustainable materials to mitigate environmental burdens. The integrated system demonstrates promising potential for producing high-quality treated effluent suitable for agricultural reuse in water-scarce regions, supporting sustainable water management. These findings provide important insights for reducing ecological impacts and advancing environmentally sustainable wastewater treatment solutions. Full article

Urban areas face rising risks from extreme heat due to climate change, intensifying thermal stress and exacerbating social inequalities. Urban climate refuges—cool, accessible indoor and outdoor public spaces that maintain their ordinary functions—are increasingly adopted as a local adaptation measure to protect vulnerable populations during heat events. This study aims to develop and test a SWOT–CAME analytical framework to evaluate and compare the maturity, equity, and implementation logic of urban climate refuge networks in three European cities with contrasting climates and governance traditions: Barcelona, Amsterdam, and Copenhagen. A qualitative multiple-case design is combined with a transparent indicator set (coverage, accessibility, and typology mix) derived from official municipal sources and planning documents. Results show differentiated pathways: Barcelona represents an institutionalized network model; Amsterdam illustrates an emerging coordinated public-health approach; and Copenhagen reflects an ecosystem-based orientation where green–blue infrastructure provides substantial passive cooling capacity but requires clearer heat-specific operational protocols. The discussion highlights the need for hybrid adaptation strategies that combine nature-based solutions with operational governance and targeted support for vulnerable groups. The paper concludes with a transferable framework for cities seeking to integrate climate refuges into resilience and climate-justice agendas. Full article

Green roofs in Southern Europe are interest-growing nature-based solutions, capable of improving urban sustainability by positively impacting the water cycle, biodiversity, pollution, and, in some cases, energy consumption and carbon sequestration. Native plants adapted to Mediterranean climates exhibit drought-resistant traits, making them highly suitable for the challenging microclimate of green roofs. This microclimate features intense solar radiation, strong winds, and higher temperatures, in comparison to ground level, leading to increased atmospheric evaporative demand, driven by the interplay of radiation, wind, temperature, and humidity. Consequently, native plants from ecosystems resembling this microclimate are likely better suited for green roofs than local ground-level species. The current review synthesizes current knowledge on the use of native plants in Southern European green roofs, focusing on water management challenges given the region’s climate and scarce water resources. Out of roughly 12,500 native plant species in the Mediterranean basin, only about 124 have been examined in the past 20 years for green roof applications, with just 16% appearing in multiple scientific studies, highlighting a significant knowledge gap. The data indicate that ca. 85% of these species are perennials, valued for their low maintenance needs, a key consideration for green roof sustainability. Some of the studied species retain adequate aesthetic value when cultivated on green roofs with limited water availability. These species are mainly associated with four habitat types—rocky, coastal, dry, or well-drained environments—with a few linked to humid or adaptable conditions. This study aims to document the selection of drought-adapted native plant species best suited for green roof implementation in Southern Europe, contributing to enhancing sustainable urban design in the region, considering water management best practices and water use efficiency. Full article

As one of China’s “New Four Furnaces”, the city of Hangzhou faces significant heat challenges exacerbated by rapid urbanization. Urban parks offer effective nature-based solutions, but optimizing their multi-dimensional cooling performance—encompassing cooling area (PCA), efficiency (PCE), intensity (PCI), and gradient (PCG)—remains a key challenge. This study quantitatively analyzed the internal and external landscape features of 18 parks in Hangzhou, revealing that park cooling performance is not simply a case of “bigger is better.” We found that parks with more complex shapes and irregular boundaries exhibited higher cooling efficiency per unit area (PCE) compared to larger parks with smooth, simple shapes, though sometimes at the expense of peak PCI. Furthermore, the surrounding built environment is critical: high building density within a 300 m buffer zone was found to significantly impede the spatial extent of the cooling effect (PCA). Based on these findings, we propose that to effectively mitigate urban heat, cities should (1) shift focus away from creating large, isolated parks with smooth boundaries; (2) prioritize a network of smaller, morphologically diverse parks with irregular edges that extend into the community; and (3) enhance each park’s cooling reach through strategies like green streets and tree-lined paths. These approaches offer tangible, actionable guidance for designing high-performance cooling green infrastructure in dense urban environments. Full article

Most pediatric exoskeletons for cerebral palsy (CP) focus on lower-limb assistance and neglect trunk control, limiting rehabilitation outcomes. This study presents a self-aligning trunk–limb exoskeleton that integrates trunk stabilization with active lower-limb support. The design includes a hip–waist rapid adjustment mechanism, a bioinspired gear-rolling knee joint, modular thigh–shank structures, a trunk support module, and a body-weight support device. To enable transparent and coordinated assistance under pathological gait conditions, a continuous gait progress-based multi-joint control framework is developed. Joint motion is described as continuous gait progress over the full gait cycle (0–100%), and joint-specific progress estimates are fused into a unified system-level reference using observability-weighted circular statistics. Inter-joint coordination is achieved through phase-consistency-based temporal modulation implemented, enabling smooth synchronization while preserving joint-level autonomy and motion continuity. Technical evaluation—comprising kinematic misalignment analysis, simulation validation, and gait trials—demonstrated a 66.8% reduction in hip misalignment and an 87.4% reduction in knee misalignment. Gait parameters under exoskeleton-assisted walking closely matched baseline walking, confirming natural kinematic preservation without interference. These results indicate that the proposed trunk–limb exoskeleton improves human–robot synergy, enhances postural stability, and provides a promising solution for pediatric gait rehabilitation in CP. Full article

The growing demand for low-carbon, resource-efficient, and multifunctional construction materials has intensified interest in solutions that can support both circular economy strategies and sustainable urban development. Expanded perlite—a lightweight volcanic material with low embodied energy and multiple functional properties—is increasingly considered a potential component of circular and nature-based material systems. This paper critically examines whether expanded perlite can serve as a sustainable alternative in civil engineering applications, contributing to reduced material consumption, improved thermal performance, and lower environmental impact across the life cycle. The review provides an overview of current applications of expanded perlite in lightweight concretes, insulation systems, green roofs, water-retention substrates, and other technologies relevant to resilient and net-zero cities. It also identifies key research gaps related to long-term durability, large-scale implementation, and life-cycle assessment, while emphasizing the need for proper handling procedures due to health concerns associated with dust exposure. By situating expanded perlite within the context of circular design and low-carbon construction, the paper highlights its potential role in decarbonizing the built environment and advancing the transition toward climate-resilient and regenerative urban systems. Full article

The study examines the relationship between entrepreneurial education and society’s approach to green energy. The findings highlight the crucial importance of this process for promoting an ecological and responsible economy. The starting point is the assumption that entrepreneurial competencies, particularly innovation and communication competencies and learning ability, can foster the perception of RES technologies as solutions that combine economic profitability with environmental benefits. Based on a literature review, a research gap was identified regarding the insufficient number of empirical analyses demonstrating the relationship between entrepreneurship education, key competencies, and attitudes toward renewable energy technologies. The study is quantitative in nature and is based on the analysis of survey data collected among high school and university students. The obtained results indicate that the effectiveness of entrepreneurship education is determined by the interaction of individual competencies and environmental conditions. Innovation and communication competencies and learning ability enhance educational outcomes, while technological barriers can significantly limit their positive impact. The analysis highlights the importance of a supportive institutional environment for the effective utilization of educational potential. On this basis, recommendations were formulated for the design of entrepreneurial education programs, emphasizing the need to integrate content related to renewable energy sources, the development of future competences and the reduction in technological barriers as elements supporting the transformation towards sustainable development. Full article

In marine hot–humid and salt spray environments, shipborne snap-action limit switches operating under micro-current loads are prone to triggering failures caused by the accumulation of heterogeneous films on electrical contact interfaces, which can induce abnormal behavior in electromechanical systems. To address this issue, this study systematically investigates the failure mechanisms of micro-current limit switches using multimodal diagnostic approaches. The results demonstrate that the migration and accumulation of corrosion products and foreign contaminants within the microswitch unit promote the formation of high-resistance heterogeneous films at the electrical contact interfaces, severely impairing reliable electrical conduction. Electrical contact experiments further reveal that the contact behavior is strongly dependent on the current magnitude. When the current exceeds 2A, arc discharge generated during contact closure can effectively disrupt and remove the heterogeneous films, thereby restoring the electrical functionality of previously failed switches under subsequent micro-current operating conditions. Based on the identified failure mechanism, and inspired by the natural eye-cleaning behavior of crabs, a biomimetic press-and-wipe self-cleaning dual-redundant limit switch design is proposed. The design enables autonomous surface cleaning through controlled reciprocal wiping between the moving and stationary electrical contacts, effectively suppressing the formation and accumulation of high-resistance films at the source. Comparative salt spray and damp heat storage tests demonstrate that the proposed self-cleaning limit switch maintains stable and reliable electrical contact performance in simulated marine environments, significantly improving operational reliability and service life under micro-current loads. This work provides both mechanistic insights and a practical structural solution for enhancing the reliability of electrical contact components operating under low-current conditions in harsh marine environments. Full article

This study presents the design, fabrication, and performance evaluation of a solar dryer capsule cabinet equipped with a parabola reflector, developed to enhance drying efficiency through the reflection of sunlight onto both the upper and lower surfaces of the product. Conventional solar drying exposes only the upper surface, resulting in uneven heating and the need for manual turning. The proposed system integrates a parabolic reflector and IoT-based monitoring sensors (BH1750 light sensor and DHT22 temperature-humidity sensor) to optimize heat distribution and record real-time environmental parameters. Dry experiments were conducted using Citrus hystrix DC. (Makrut lime) peels under natural sunlight from 9:00 a.m. to 5:00 p.m. The moisture loss achieved with the proposed dryer (P-DSD) was 45.66%, compared with 6.79% for direct solar drying (DSD). The drying rate increased from 3.05 g h⁻¹ (DSD) to 20.50 g h⁻¹ (P-DSD), while the specific energy consumption (SEC) decreased from 3519.75 kWh kg⁻¹ to 523.67 kWh kg⁻¹, representing an 85.13% energy reduction. Economic analysis showed a system cost of $1384 and a return on investment of 30.0%. These results demonstrate that the proposed solar dryer capsule cabinet with a parabola reflector offers a low-cost, eco-friendly, and high-efficiency solution for drying agricultural and herbal products, significantly shortening the drying time and improving product quality. Full article

Accurate genotyping of small insertions and deletions (InDels; <5 bp) remains technically challenging in routine molecular breeding, largely due to the limited resolution of agarose gel electrophoresis and the labor-intensive nature of polyacrylamide-based assays. Here, we present the Tri-Primer Amplification Refractory Mutation System (TP-ARMS), a simple and cost-effective PCR-based strategy that enables high-resolution genotyping of small InDels using standard agarose gels. The TP-ARMS employs a universal reverse primer in combination with two allele-specific forward primers targeting insertion and deletion alleles, respectively. This design allows clear discrimination of homozygous and heterozygous genotypes using a two-tube PCR workflow. The method showed complete concordance with Sanger sequencing in detecting 1–5 bp InDels across multiple crop species, including rice (Oryza sativa) and quinoa (Chenopodium quinoa). In addition, using a TP-ARMS reduced experimental time by approximately 90% compared with PAGE-based approaches and avoided the high equipment and DNA quality requirements of fluorescence-based assays. The practical applicability of the TP-ARMS was demonstrated in breeding populations, including efficient genotyping of a 3-bp InDel in OsNRAMP5 associated with cadmium accumulation and a 6-bp promoter InDel in OsSPL10 underlying natural variation in rice trichome density across 370 accessions. Collectively, the TP-ARMS provides a robust, scalable, and low-cost solution for precise small InDel genotyping, with broad applicability in marker-assisted breeding and functional genetic studies. Full article

The conceptual foundation of this research is the idea of convergence between such development directions of modern production systems as digital design tools and sustainable development. The problem lies in searching for the most effective tools, sources of knowledge, and solutions that contribute to improving ecological well-being, including through the adoption of nature-like technologies. The research aim is to substantiate the role of digital engineering in ensuring sustainable development and to identify priority directions for the development of production systems in the context of Russian realities. Research methods: systems analysis, formalization, comparison, statistical analysis, mathematical modeling were employed. Results: the influence of digital engineering on the sustainable development of production systems and the role of nature-like technologies are substantiated; the convergence of digitalization processes and the concept of sustainable development in the form of the «digital engineering–nature-like technologies» dyad is revealed; patterns of development of Russian production systems in the «design and engineering–environmental aspects of sustainable development» plane are identified; and alternative models for managing the technological development of production systems with a focus on ecological well-being are developed. Scientific novelty of the research: based on multidimensional nonlinear analysis, the importance of the convergence of digital engineering and nature-like technologies is proven, and priority directions for the development of production systems that contribute to achieving sustainable development goals under the policy of import substitution and technological leadership implemented in Russia are identified. The formulated theoretical and methodological provisions advance the field of knowledge in industrial economics and sustainable development and are applicable within the planning and programming of activities for production systems at various levels. Full article

Deep reinforcement learning (DRL)-based algorithms for solving the Traveling Salesman Problem (TSP) have demonstrated competitive potential compared to traditional heuristic algorithms on small-scale TSP instances. However, as the problem size increases, the NP-hard nature of the TSP leads to exponential growth in the combinatorial search space, state–action space explosion, and sharply increased sample complexity, which together cause significant performance degradation for most existing DRL-based models when directly applied to large-scale instances. This research proposes a two-stage reinforcement learning framework, termed GCRL-TSP (Graph Convolutional Reinforcement Learning for the TSP), which consists of a heatmap generation stage based on a graph convolutional neural network, and a heatmap-assisted Proximal Policy Optimization (PPO) training stage, where the generated heatmaps are used as auxiliary guidance for policy optimization. First, we design a divide-and-conquer heatmap generation strategy: a graph convolutional network infers m-node sub-heatmaps, which are then merged into a global edge-probability heatmap. Second, we integrate the heatmap into PPO by augmenting the state representation and restricting the action space toward high-probability edges, improving training efficiency. On standard instances with 200/500/1000 nodes, GCRL-TSP achieves a Gap% of 4.81/4.36/13.20 (relative to Concorde) with runtimes of 36 s/1.12 min/4.65 min. Experimental results show that GCRL-TSP achieves more than twice the solving speed compared to other TSP solving algorithms, while obtaining solution quality comparable to other algorithms on TSPs ranging from 200 to 1000 nodes. Full article

Unmanned aerial vehicles (UAVs) increasingly share low-altitude airspace with birds, making early distinguishing between drones and biological targets critical for safety and security. This work addresses long-range scenarios where objects occupy only a few pixels and appearance-based recognition becomes unreliable. We develop a model-driven simulation pipeline that generates synthetic data with a controlled camera model, atmospheric background and realistic motion of three aerial target types: multicopter, fixed-wing UAV and bird. From these sequences, each track is encoded as a time series of image-plane coordinates and apparent size, and a bidirectional long short-term memory (LSTM) network is trained to classify trajectories as drone-like or bird-like. The model learns characteristic differences in smoothness, turning behavior and velocity fluctuations, and to achieve reliable separation between drone and bird motion patterns on synthetic test data. Motion-trajectory cues alone can support early distinguishing of drones from birds when visual details are scarce, providing a complementary signal to conventional image-based detection. The proposed synthetic data and sequence classification pipeline forms a reproducible testbed that can be extended with real trajectories from radar or video tracking systems and used to prototype and benchmark trajectory-based recognizers for integrated surveillance solutions. The proposed method is designed to generalize naturally to real surveillance systems, as it relies on trajectory-level motion patterns rather than appearance-based features that are sensitive to sensor quality, illumination, or weather conditions. Full article

Background: Solid organ transplantation (SOT) is a life-saving treatment for patients with end-stage diseases and/or organ failure. However, access to healthy organs is often limited by challenges in organ preservation. Furthermore, upon transplantation, ischemia–reperfusion injury (IRI) can lead to increased organ rejection or graft failures. The work presented aims to address both challenges using an innovative nanomedicine platform for simultaneous drug and oxygen delivery. In recent studies, resveratrol (RSV), a natural antioxidant, anti-inflammatory, and reactive oxygen species (ROS) scavenging agent, has been reported to protect against IRI by inhibiting ferroptosis. Here, we report the design, development, and scalable manufacturing of the first-in-class dual-function perfluorocarbon-nanoemulsion (PFC-NE) perfusate for simultaneous oxygen and antioxidant delivery, equipped with a near-infrared fluorescence (NIRF) reporter, longitudinal, non-invasive NIRF imaging of perfusate flow through organs/tissues during machine perfusion. Methods: A Quality-by-Design (QbD)-guided optimization was used to formulate a triphasic PFC-NE with 30% w/v perfluorooctyl bromide (PFOB). Drug-free perfluorocarbon nanoemulsions (DF-NEs) and RSV-loaded nanoemulsions (RSV-NEs) were produced at 250–1000 mL scales using M110S, LM20, and M110P microfluidizers. Colloidal attributes, fluorescence stability, drug loading, and RSV release were evaluated using DLS, NIRF imaging, and HPLC, respectively. PFC-NE oxygen loading and release kinetics were evaluated during perfusion through the BMI OrganBank^® machine with the MEDOS HILITE^® oxygenator and by controlled flow of oxygen. The in vitro antioxidant activity of RSV-NE was measured using the oxygen radical scavenging antioxidant capacity (ORAC) assay. The cytotoxicity and ferroptosis inhibition of RSV-NE were evaluated in RAW 264.7 macrophages. Results: PFC-NE batches maintained a consistent droplet size (90–110 nm) and low polydispersity index (<0.3) across all scales, with high reproducibility and >80% PFOB loading. Both DF-NE and RSV-NE maintained colloidal and fluorescence stability under centrifugation, serum exposure at body temperature, filtration, 3-month storage, and oxygenation. Furthermore, RSV-NE showed high drug loading and sustained release (63.37 ± 2.48% at day 5) compared with the rapid release observed in free RSV solution. In perfusion studies, the oxygenation capacity of PFC-NE consistently exceeded that of University of Wisconsin (UW) solution and demonstrated stable, linear gas responsiveness across flow rates and FiO₂ (fraction of inspired oxygen) inputs. RSV-NE displayed strong antioxidant activity and concentration-dependent inhibition of free radicals. RSV-NE maintained higher cell viability and prevented RAS-selective lethal compound 3 (RSL3)-induced ferroptosis in murine macrophages (macrophage cell line RAW 264.7), compared to the free RSV solution. Morphological and functional protection against RSL3-induced ferroptosis was confirmed microscopically. Conclusions: This study establishes a robust and scalable PFC-NE platform integrating antioxidant and oxygen delivery, along with NIRF-based non-invasive live monitoring of organ perfusion during machine-supported preservation. These combined features position PFC-NE as a promising next-generation acellular perfusate for preventing IRI and improving graft viability during ex vivo machine perfusion. Full article