Search Results (7,762)

Panting is one of the earliest and most prominent behavioral responses of chickens under heat stress. More importantly, panting is inherently a temporally continuous state rather than an instantaneous event. However, existing vision-based methods usually determine panting from beak opening in individual frames, which contradicts the nature of panting and therefore cannot provide reliable assessment. To address this limitation, this study proposes a Cumulative Panting Ratio (CPR), which quantifies sustained open-beak behavior associated with panting by tracking and accumulating instantaneous open-beak events within a temporal sliding window. To support consistent estimation of sustained open-beak behavior and CPR, a cascaded Detection–Tracking–Classification pipeline is constructed to explicitly decouple body-level tracking from fine-grained beak behavior inference, thereby reducing the conflict between global localization and local feature extraction. In addition, a Near-Online Trajectory Stitcher is proposed to reconnect fragmented tracklets using unified temporal, spatial, scale, and directional constraints induced by platform movement. Experiments on practical inspection datasets demonstrated robust tracking continuity and stable quantification performance. Compared with state-of-the-art frameworks, the proposed method reduced identity switches from 10 to 4 and improved IDF1 by 2.43%, while minimizing counting errors across diverse detector architectures. With TensorRT acceleration and multi-stream parallel processing on the Jetson Orin NX, system throughput increased from 7.89 FPS to 51.43 FPS without compromising accuracy. Overall, this work provides a practical solution for quantitative heat stress assessment and supports the deployment of physiological state monitoring systems for precision livestock farming. Full article

Smartphone-based pedestrian dead reckoning (PDR) provides an infrastructure-free solution for two-dimensional (2D) planar localization in GPS-denied environments, but its open-loop nature makes it sensitive to accumulated step-length and heading errors. These errors grow when pedestrian actions and phone carrying modes change, because conventional methods use a fixed step-length model with a constant Weinberg coefficient. This paper proposes a motion-state-aware PDR method with two key designs. First, a joint motion state defined by action type and carrying mode is recognized from smartphone sensor data using a random-forest classifier. Second, the Weinberg coefficient is modeled through two adaptive variants: a state-wise linear model as the main lightweight adaptation mechanism, and a Transformer-enhanced extension that uses historical step-feature sequences to provide additional temporal smoothing for the per-step coefficient K. Both variants keep the predicted coefficient inside the Weinberg equation to preserve the physical structure of step-length estimation, with offline training minimizing the distance error over each calibrated segment. Heading is estimated by fusing gyroscope increments and magnetometer observations to improve continuity under magnetic disturbance. Experiments on routes with frequent motion-state transitions, including a representative indoor corridor with magnetic disturbance and turns, compare a fixed-parameter baseline and two established adaptive step-length baselines against the proposed variants using coefficient-modeling diagnostics and trajectory-level metrics. More challenging deployments such as underground or multi-floor environments are left for future work. Full article

Cherry tomatoes are highly susceptible to Salmonella contamination during pre- and post-harvest handling, leading to foodborne illness outbreaks and significant economic losses. Edible coatings incorporating natural antimicrobials offer a promising alternative to conventional chemical treatments for enhancing food safety while maintaining produce quality. This study developed and evaluated a pectin-based edible coating enriched with zinc nanohydroxide-thymol nanohybrids (ZnNH-T) for controlling Salmonella contamination and extending shelf-life of cherry tomatoes. ZnNH-T nanohybrids were synthesized via precipitation, followed by thymol intercalation, and characterized by SEM. Four coating formulations were prepared: pectin alone (P), pectin-thymol (PT), pectin-ZnNH (PNH), and pectin-ZnNH-T (PNHT). Antibacterial activity of the four coatings was first screened in vitro by disc diffusion against six S. enterica serovars; three serovars (Typhimurium, Enteritidis, and Montevideo) showing a statistically significant, coating-dependent inhibition response were selected for the postharvest assay. Cherry tomatoes were coated and dip-inoculated with three Salmonella serotypes (Typhimurium, Enteritidis, and Montevideo) at approximately 10⁵ CFU/mL and stored at 25 °C for 12 days. Antimicrobial efficacy, antioxidant activity (ABTS assay), and physicochemical quality parameters (weight loss, color, pH, and total soluble solids) were evaluated. Zinc nanohydroxides were successfully synthesized, as observed in SEM morphology. ABTS radical scavenging activity of filmogenic solutions was highest for PT (92.4%) and moderate for PNHT (65.9%), while P and PNH showed minimal activity (20.1% and 17.8%, respectively). PNHT coating achieved an approximately 2-log CFU/g reduction in Salmonella populations compared to uncoated controls over 12 days of storage, demonstrating sustained antimicrobial efficacy. Coated tomatoes exhibited significantly reduced weight loss (8% for PNHT vs. 13% for control), better color retention, lycopene content, maintained firmness, and stable pH and TSS values compared to uncoated controls. The pectin-ZnNH-T coating system represents a novel multifunctional approach for enhancing cherry tomato safety and quality. The use of thymol from the layered hydroxide structure, combined with zinc ion antimicrobial effects, provides sustained pathogen reduction while maintaining desirable physicochemical properties. This natural, biodegradable coating technology has potential for commercial application in fresh produce preservation. Full article

This study experimentally investigated the wave transmission and setup characteristics of biomimetic submerged structures as Nature-based Solutions (NbSs) for coastal protection. A non-porous monolithic pillar and a highly porous, multi-branched staghorn coral replica were tested in a 2D flume featuring a 1:20 foreshore slope representative of Kuta Beach, Bali. The results revealed a highly divergent, period-dependent hydrodynamic response. Under short-period waves (T = 0.8 s), attenuation was density dependent; the porous replica gradually dissipates energy through canopy micro-turbulence, yielding transmission coefficients (Kt) ranging from 0.25 to 1.18. Conversely, under long-period waves (T = 1.6 s), the attenuation mechanism shifted to density-independent, depth-induced breaking. This establishes a critical hydrodynamic trade-off: higher wave attenuation (lower Kt) inherently generates a higher coastal wave setup due to momentum transfer. Crucially, while both structures reduced transmission, the internal porosity of the multi-branched replica facilitated sub-surface return flow, effectively capping the maximum normalized wave setup at 0.09. This represents an 18% reduction in setup-induced coastal hazards compared to the monolithic baseline. To facilitate practical engineering design, new empirical equations (R2≈0.80) for predicting Kt were derived, integrating the frontal area index (λf). Ultimately, these findings demonstrate that multi-branched biomimetic structures provide an optimal NbS design, balancing effective wave energy attenuation with the mitigation of secondary setup hazards for vulnerable coastal regions. Full article

Three-dimensional (3D) bioprinting has emerged as a versatile biofabrication strategy that enables the precise, spatiotemporally controlled co-deposition of living cells, biomaterials, and bioactive agents, including growth factors, cytokines, and extracellular matrix (ECM) components, into geometrically defined 3D constructs. By translating digital design models derived from computed tomography (CT), magnetic resonance imaging (MRI), or computational modeling directly into physical tissue architectures, 3D bioprinting facilitates the assembly of hierarchically organized constructs that closely recapitulate the structural, mechanical, and functional characteristics of native tissues. The principal 3D bioprinting strategies are broadly classified into scaffold-based and scaffold-free approaches. Engineered bioinks, whether formulated as cell-laden natural, synthetic, or composite polymer hydrogels, tissue-derived decellularized ECM (dECM) components, or pure cellular spheroids and organoids, constitute the cornerstone of these biofabrication platforms. Scaffold-based 3D bioprinting comprises extrusion-based, droplet-based (inkjet and drop-on-demand), light-based vat photopolymerization (stereolithography and digital light processing), and laser-assisted bioprinting based on laser-induced forward transfer (LIFT). Each of these modalities imposes distinct constraints on bioink rheology, crosslinking mechanisms, spatial resolution, throughput, and post-printing cell viability; consequently, a specific 3D bioprinting strategy is selected according to the specific requirements of the target tissue application. Scaffold-free 3D bioprinting and bioassembly techniques, including the Kenzan method, aspiration-assisted bioprinting, magnetic bioprinting, and other field-directed tissue assembly approaches, enable the fabrication of spheroid- and organoid-based constructs without the necessity for exogenous biomaterial scaffolds. Because native tissues exhibit diversity in cellular composition, ECM architecture, mechanical properties, and physiological function, no individual bioprinting platform or bioink formulation serves as a universal 3D bioprinting solution. The engineering of biomimetic tissue constructs, therefore, requires the selection of application-tailored fabrication approaches. Under this biofabrication paradigm, 3D bioprinting has been applied across a wide range of tissue engineering targets, including skin, bone, cartilage, osteochondral interfaces, cardiac and vascular tissue, neural structures, ocular, dental, and adipose tissue. This review discusses recent advances in scaffold-based and scaffold-free 3D bioprinting applications for tissue engineering and regenerative medicine across diverse tissue systems. Full article

Nature-based Solutions (NbS) are increasingly recognised as effective approaches for enhancing coastal resilience while simultaneously supporting biodiversity, ecosystem services, and, where appropriate, climate-change mitigation. Their importance is particularly evident in the Mediterranean Basin, a climate-change hotspot exposed to sea-level rise, coastal erosion, land subsidence, sediment deficits, and intense anthropogenic pressures. This review provides a structured evidence synthesis of NbS for Mediterranean coastal adaptation, integrating ecological, hydrodynamic, geomorphological, biodiversity, governance, and implementation perspectives. We examine the principal NbS typologies, including vegetated habitats, biogenic reefs, sediment-based interventions, and hybrid approaches, with particular attention to vulnerable microtidal systems such as coastal lagoons and subsiding shorelines, including the Venice Lagoon and the Emilia-Romagna coast. Drawing on peer-reviewed literature together with evidence from European LIFE projects and restoration initiatives, the review highlights how process-based interventions can restore ecosystem functioning, strengthen coastal resilience, and provide multiple ecosystem services. At the same time, the analysis emphasises that NbS are inherently context-dependent, with their effectiveness influenced by local geomorphology, sediment availability, hydrodynamic conditions, governance capacity, and long-term management. Although important scientific uncertainties remain, wider implementation is increasingly constrained by economic, institutional, and governance barriers. The review concludes that NbS should not be regarded as stand-alone alternatives to conventional engineering, but as key components of integrated and adaptive hybrid coastal management strategies capable of supporting resilient Mediterranean coastal systems under future climate change. Full article

Mangrove restoration is increasingly recognized as an effective nature-based solution for biodiversity conservation, climate-change mitigation, and coastal resilience. However, long-term evaluations of restoration outcomes remain scarce, particularly in arid coastal environments. This study assesses three decades of ecosystem recovery following the afforestation of Avicennia marina at Sajid Bay, Farasan Archipelago, Saudi Arabia. A total of 1050 seedlings were transplanted in 1994 into an unvegetated intertidal area and monitored using multi-temporal satellite imagery and Normalized Difference Vegetation Index (NDVI) analysis from 1994 to 2024. Results revealed a progressive expansion of mangrove cover to 15.48 ha over the 30-year period, corresponding to an average annual increase of approximately 0.516 ha yr⁻¹. Spatial patterns of expansion were strongly influenced by local geomorphological and hydrodynamic conditions. Central areas characterized by low wave energy and stable sediments exhibited the highest rates of colonization and vegetation development, whereas peripheral areas exposed to greater hydrodynamic stress expanded more slowly. The establishment of reproductive stands enabled natural regeneration, transforming the original plantation into a self-sustaining mangrove ecosystem. The findings demonstrate that relatively small-scale afforestation efforts can trigger long-term ecosystem recovery when implemented under suitable environmental conditions. The transition from planted seedlings to a naturally regenerating mangrove forest highlights the importance of site selection, hydrodynamic suitability, and ecological processes in determining restoration success. This study provides rare empirical evidence of long-term mangrove recovery in an arid coastal system and offers a practical conservation framework for restoring degraded coastal habitats throughout the Red Sea region and other environmentally comparable coastlines. Full article

Brinjal (Solanum melongena L.) is an important vegetable crop worldwide, but its cultivation faces challenges from pests, diseases, and variable environmental conditions that negatively affect quality and yield. Accurate fruit detection in natural field conditions is essential for yield estimation and perception module of automated harvesting, but existing deep learning techniques often require substantial computational support, restricting their deployment on edge devices. This study addresses this gap by evaluating the Faster Objects, More Objects (FOMO) model—a lightweight architecture for resource-constrained platforms—for brinjal detection under diverse field conditions. A dataset of 1500 images was captured under varying illumination and growth stages, annotated using a bounding box-based approach, and used to train FOMO models with 25, 50, and 100 epochs via transfer learning. Post-training quantization to INT8 format was applied to assess improvements in computational efficiency. The Float32 model achieved a precision of 0.827, recall of 0.915, and F1-score of 0.869 at 100 epochs. The INT8-quantized model maintained comparable accuracy (precision 0.829, recall 0.908, F1-score 0.866) while reducing model size by 63.33% (from 0.30 MB to 0.11 MB), inference time by 62.02% (from 65.3 ms to 24.8 ms), and RAM usage by 73.02% (from 887.2 KB to 239.4 KB). These results demonstrate that FOMO combined with INT8 quantization provides an efficient, accurate solution for real-time brinjal detection on edge platforms, supporting the advancement of precision agriculture through intelligent crop monitoring and serving as a perception module for future robotic harvesting systems. Full article

Visual art and graphic design tasks, such as generating a harmonious color palette or arranging the elements of a page, can be naturally formulated as mathematical optimization problems whose objective functions are non-convex, multimodal, and non-differentiable. Metaheuristic algorithms are well-suited to such problems. The secretary bird optimization algorithm (SBOA) is a recently proposed bio-inspired metaheuristic that mimics the hunting and predator-escaping behaviors of secretary birds, and it has shown competitive performance. However, SBOA still suffers from insufficient population diversity, premature convergence, and an unbalanced transition between exploration and exploitation, which limits its accuracy on complex design problems. To overcome these limitations, this paper proposes a multi-strategy secretary bird optimization algorithm (MSSBOA) that integrates three improvement strategies. First, a good point set initialization is employed to generate a low-discrepancy initial population that covers the search space more uniformly and enriches population diversity. Second, a lens opposition-based learning strategy is applied to the inferior individuals to help the population escape local optima while preserving the elite. Third, an adaptive Cauchy–Gaussian mutation is imposed on the best individual to balance global exploration and local exploitation throughout the search. The performance of MSSBOA is comprehensively examined on the CEC2017 benchmark suite in 10, 30, 50, and 100 dimensions and compared with the basic SBOA and nine state-of-the-art algorithms; the results are analyzed by the Friedman test, the Nemenyi post hoc test and the Wilcoxon rank-sum test. MSSBOA is then applied to two representative visual-design optimization problems: aesthetic color-harmony palette generation and graphic-layout aesthetics optimization. In all cases, MSSBOA outperforms the basic SBOA and the competing algorithms in terms of convergence speed, stability, and solution quality, confirming its effectiveness for computational-aesthetics applications in art design. Full article

Urban Heat Island (UHI) effects are increasingly acknowledged as a critical urban climate challenge with far-reaching consequences for human health and overall well-being. However, the conceptual structure, temporal evolution, and intellectual landscape of studies examining the relationships between UHI and human well-being remain fragmented, thereby constraining the development of integrated knowledge frameworks needed to guide future research, urban adaptation strategies, and evidence-based policy interventions. To this end, a total of 4857 studies were retrieved from the Scopus and Web of Science databases and screened following the PRISMA guidelines. These studies were then analyzed using Bibliometrix and VOSviewer. The results reveal a rapid and exponential growth in scientific output, particularly after 2010, with the output reaching its highest level in recent years. These outputs were shaped mostly in China and the United States with a well-established international collaboration network, while the Global South remain significantly underrepresented in scientific productions. We also found that studies are primarily structured around four dominant research clusters: urban heat island, thermal comfort, land surface temperature, and climate change. Furthermore, early studies predominantly focused on urban surface properties and built-environment characteristics, while recent research has increasingly shifted toward human health impacts, thermal stress, heat vulnerability, and well-being. Emerging research directions further highlight growing interest in nature-based solutions for mitigating UHI effects, alongside the application of advanced technologies such as machine learning and remote sensing for high-resolution urban climate assessment. Overall, our findings indicate a transition toward a more integrated urban climate–health–well-being research framework, while simultaneously revealing persistent geographical and conceptual gaps, particularly across the Global South. We therefore advocate for increased empirical research, stronger international collaboration, and context-specific urban adaptation strategies to better safeguard human well-being under intensifying urban heat conditions. Full article

This study investigates emergency scheduling optimization for natural gas networks under unexpected abnormal conditions, such as unplanned valve closures or equipment failures, which may trigger pressure alarms. Unlike normal planned operations, emergency scheduling requires rapid response and accounts for the dynamic lag of gas flow. A mixed-integer programming model is formulated to ensure system safety, satisfy pressure constraints, and minimize compressor energy consumption. To solve the high-dimensional nonlinear problem, a variable neighborhood search algorithm is proposed, which constructs initial feasible solutions via a greedy proximity-based approach and iteratively improves them using four “delete-compensate” neighborhood operators with the Metropolis acceptance criterion. Validation on a real natural gas network containing 645 stations, 69 pipelines, and 26 compressor stations, together with repeated computational experiments under two representative abnormal scenarios, demonstrates the effectiveness and applicability of the proposed method. Full article

Monitoring the surface thermal state of thermal protection structures (TPS) is essential for the safe operation and health assessment of hypersonic vehicles. However, direct sensor deployment on heated surfaces suffers from poor survivability, while many model-based approaches require prescribed thermophysical properties and boundary conditions. This study proposes an AutoRegressive with eXogenous input (ARX)-based surface temperature reconstruction method using deep-embedded sensors. By identifying a local equivalent dynamic mapping among internal temperature responses, the method reconstructs the near-surface temperature through virtual-point recursive extrapolation without requiring explicit thermophysical-property or boundary-condition information. Numerical simulations show high accuracy under adiabatic, natural-convection, and forced-convection rear-surface boundaries, with the global RRMSE remaining within 1.09%. Further analyses demonstrate tolerance to moderate temperature- and space-dependent variations in equivalent thermophysical properties; simulations using realistic LI-900 thermal conductivity variations confirm its applicability under different effective conductivity conditions. Single-sided heating experiments with two sensor-embedding layouts validate the method, yielding RRMSE values of 1.74% for the 5-point model and 4.27% for the 9-point model in the main validation case. The applicable conditions are further clarified through analyses of internal temperature-difference SNR, recursive error accumulation, and sensor-layout constraints. The proposed method provides a low-cost and long-life solution for online TPS surface temperature monitoring. Full article

Historic landscape forests within cultural heritage sites represent a distinct category of urban green space that provides critical ecosystem services under strict conservation constraints. This study applied i-Tree Eco v6.0 to quantify the ecosystem services of the historic landscape forest of Jinju Fortress (Jinjuseong; Historic Site No. 118), South Korea, with focus on species-level contributions. A total of 822 trees representing 30 species were inventoried across 1.272 ha of tree cover. Zelkova serrata was the dominant species (importance value = 57.8) and contributed disproportionately to all ecosystem service categories, accounting for 40.7% of air pollutant removal, 61.3% of carbon storage, 58.2% of carbon sequestration and oxygen production, and 55.4% of avoided runoff. The forest removed 123.1 kg yr⁻¹ of air pollutant Korean Won (KRW 8.834 million yr⁻¹), stored 200.7 t (KRW 138 million), sequestered 8.834 t/yr (KRW 6.09 million/yr), produced 23.56 t/yr⁻¹ of oxygen, avoided 10,413.7 L yr⁻¹ of runoff and had a structural replacement value of KRW 1.63 billion. Beyond providing a species-level baseline for evidence-based management, this study introduces the concept of Heritage Ecosystem Service Efficiency (HESE) and the Species Ecosystem Service Dominance Index (SESDI), offering transferable frameworks for evaluating and managing ecosystem service performance in conservation-constrained heritage forests. Full article

Climate change adaptation in cities increasingly requires not only technical and spatial solutions, but also a better understanding of residents’ beliefs and expectations towards green infrastructure. This study aimed to identify the relationship between climate change knowledge and preferences for urban green infrastructure among Warsaw residents. The research was based on a CAWI survey conducted at the end of 2024 among 780 adult residents of Warsaw. Respondent segmentation was performed using hierarchical cluster analysis and k-means clustering, while differences between groups were assessed using the Kruskal–Wallis and chi-square tests. Four resident segments were identified: Climate Aware, Natural-Factor Oriented, Sceptics, and Uncertain. These groups were found to differ significantly in their climate change knowledge and beliefs, socio-demographic characteristics, motivations for using green areas, and preferences for specific green infrastructure elements. Climate-aware residents attached particular importance to multifunctional green and blue infrastructure, including large parks, trees, water elements, and proximity to natural areas. More sceptical residents tended to perceive green areas mainly through their recreational and sport-related functions. The findings indicate that climate-adaptive green infrastructure should be planned in a socially differentiated way, combining environmental, recreational, and tourism-related functions to strengthen both urban resilience and the attractiveness of Warsaw. Full article

Living shorelines are widely promoted as nature-based solutions to coastal erosion and wetland protection, yet hardened shoreline structures continue to dominate even in jurisdictions with explicit policy mandates prioritizing living shorelines. In this research, we examine why non-optimal shoreline modification outcomes persist in Virginia (USA) despite a regulatory framework designed to promote ecological alternatives. We use primary data from interviews with wetlands board members, marine contractors, and nonprofit organizations and findings from a secondary survey of shoreline property owners to analyze shoreline management as a multi-sector collaborative decision-making process. Findings show that shoreline outcomes are shaped less by individual regulatory decisions than by recurrent interaction mechanisms across sectors that operate upstream of permit review. Contractors play a critical agenda-setting role by shaping the alternatives presented to property owners, while social norms, anticipatory adaptation to regulatory expectations, and informal decision heuristics constrain option sets before projects reach wetlands boards. Formal co-management institutions are therefore asked to arbitrate projects that are already highly constrained, limiting their ability to advance policy goals. Improving policy fidelity requires attention to decision sequencing, intermediary incentives, and structural feedback dynamics, rather than simply refining permitting guidance. Targeting upstream decision points and interaction mechanisms offers greater potential to align shoreline management outcomes with living shoreline policy objectives. Full article