Search Results (4,405)

Labor shortages in seedling nurseries, particularly in manual inspection and replanting, hinder operational efficiency despite advancements in automation. This study aims to develop a cost-effective, GPU-free machine vision system to automate the detection of deficient seedlings in plug trays, specifically for small-scale nursery operations. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. Under controlled laboratory conditions, the DDRP-Machine achieved high detection accuracy (96.0–98.7%) and precision rates (82.14–83.78%). Benchmarking against deep-learning models such as YOLOv5x and Mask R-CNN showed comparable performance, while requiring only one-third to one-fifth of the cost and avoiding complex infrastructure. The Batch Detection (BD) mode significantly reduced processing time compared to Continuous Detection (CD), enhancing real-time applicability. The DDRP-Machine demonstrates strong potential to improve seedling inspection efficiency and reduce labor dependency in nursery operations. Its modular design and minimal hardware requirements make it a practical and scalable solution for resource-limited environments. This study offers a viable pathway for small-scale farms to adopt intelligent automation without the financial burden of high-end AI systems. Future enhancements, adaptive lighting and self-learning capabilities, will further improve field robustness and including broaden its applicability across diverse nursery conditions. Full article

Establishing a sustainable human presence on the Moon and Mars will require the use of locally available resources for construction. A binder material similar to concrete is a promising candidate, provided that its production and performance under reduced gravity can be reliably understood. Previous microgravity investigations demonstrated the feasibility of mixing cementitious materials in space but produced irregular or low-quality specimens that limited standardized mechanical testing. To address these limitations, the MASON (Material Science on Solidification of Concrete) team developed the first-generation MASON Concrete Mixer (MCM), which enabled the safe production of cylindrical specimens aboard the International Space Station (ISS). However, its fully manual operation introduced variability and required significant astronaut time. Building on this foundation, the development of an automated MCM prototype is presented in this study. It integrates motorized mixing and programmable process control into the established containment architecture. This system enables reproducible specimen production by eliminating operator-dependent variations while reducing crew workload. In comparison to manually mixed samples, the automated MCM demonstrated reduced variability in the tested concrete properties. The automated MCM represents a first step toward autonomous space instrumentation for high-quality materials research and provides a scalable path to uncrewed missions and future extraterrestrial construction technologies. Full article

This contribution investigates the potential and the catalytic role of landscape and its collective values in driving territorial regeneration processes. Specifically, it reflects on how the public dimension of landscape—conceived as a shared space of identity, memory, and future-oriented practices—can serve as a strategic lever for initiating local development pathways. Local communities, as custodians of the knowledge and practices that have historically shaped cultural landscapes, are increasingly recognized by territorial policies for their participatory and generative capacity. Building on these premises, the research explores the case of the disused Noto–Pachino railway line, located in southeastern Sicily (Italy), as a living laboratory for testing collaborative strategies aimed at enhancing landscape value and fostering territorial cohesion. The ongoing investigation has identified several civic and grassroots initiatives seeking to reactivate this dormant infrastructure, repositioning it as a strategic asset for sustainable territorial enjoyment, cultural heritage promotion, and the revitalization of marginalized areas. The main objective of the study is to define an “action lab”—a collaborative framework capable of aligning diverse visions, actors, and resources—through which landscape can be reimagined as both a driver of social innovation and a foundational tool for shaping inclusive and resilient development scenarios. Full article

The dehesa, as a socio-ecological system and cultural landscape, is a strategic resource for environmental education, territorial sustainability, and the intergenerational transmission of knowledge. This study analyzes the perception of primary school students in Extremadura regarding this environment, using a mixed methodology that combines statistical, semantic, and spatial analysis. The results show a generally positive assessment of the dehesa heritage, although accompanied by a disconnect between this symbolic assessment and direct experience of the territory, especially in urban contexts. It identifies significant differences between students from rural and urban environments in terms of their knowledge of trades, products, and dehesa spaces, as well as their preferred activities in the dehesa. While rural students show greater interest in operational activities and direct contact with the environment (such as feeding livestock and milking), urban students lean toward sensory or symbolic experiences (such as consuming products or occasional harvesting), reflecting different ways of connecting with the territory. Spatial analysis reveals that more than 80% of schools are located less than 5 km from well-preserved dehesa areas, which represents an opportunity to integrate these landscapes into formal education. However, inequalities in access from special education centers have been detected, posing challenges in terms of territorial and educational equity. This study concludes that the dehesa should be recognized as an open classroom, capable of fostering roots, ecological literacy, and cultural sustainability through contextualized and territory-sensitive pedagogical approaches. Full article

Electromagnetic (EM) metamaterials have a wide range of applications due to their unique properties, but their design is often based on specific topological structures, which come with certain limitations. Designing with stochastic topologies can provide more diverse EM properties. However, this requires experienced designers to search and optimise in a vast design space, which is time-consuming and requires substantial computational resources. In this paper, we employ a deep learning network agent model to replace time-consuming full-wave simulations and quickly establish the mapping relationship between the metamaterial structure and its electromagnetic response. The proposed framework integrates a Convolutional Block Attention Module-enhanced Variational Autoencoder (CBAM-VAE) with a Transformer-based predictor. Incorporating CBAM into the VAE architecture significantly enhances the model’s capacity to extract and reconstruct critical structural features of metamaterials. The Transformer predictor utilises an encoder-only configuration that leverages the sequential data characteristics, enabling accurate prediction of electromagnetic responses from latent variables while significantly enhancing computational efficiency. The dataset is randomly generated based on the filling rate of unit cells, requiring only a small fraction of samples compared to the full design space for training. We employ the trained model for the inverse design of metamaterials, enabling the rapid generation of two cells for 1-bit coding metamaterials. Compared to a similarly sized metallic plate, the designed coding metamaterial radar cross-section (RCS) reduces by over 10 dB from 6 to 18 GHz. Simulation and experimental measurement results validate the reliability of this design approach, providing a novel perspective for the design of EM metamaterials. Full article

Laboratories are complex and dynamic environments where diverse hazards—including toxic gas leakage, volatile solvent combustion, and unexpected fire ignition—pose serious threats to personnel safety and property. Traditional monitoring systems relying on single-type sensors or manual inspections often fail to provide timely warnings or comprehensive hazard perception, resulting in delayed response and potential escalation of incidents. To address these limitations, this study proposes a multi-node laboratory safety monitoring and early warning system integrating multi-source sensing, heterogeneous communication, and cloud–edge collaboration. The system employs a LoRa-based star-topology network to connect distributed sensing and actuation nodes, ensuring long-range, low-power communication. A Raspberry Pi-based module performs real-time facial recognition for intelligent access control, while an OpenMV module conducts lightweight flame detection using color-space blob analysis for early fire identification. These edge-intelligent components are optimized for embedded operation under resource constraints. The cloud–edge–app collaborative architecture supports real-time data visualization, remote control, and adaptive threshold configuration, forming a closed-loop safety management cycle from perception to decision and execution. Experimental results show that the facial recognition module achieves 95.2% accuracy at the optimal threshold, and the flame detection algorithm attains the best balance of precision, recall, and F1-score at an area threshold of around 60. The LoRa network maintains stable communication up to 0.8 km, and the system’s emergency actuation latency ranges from 0.3 s to 5.5 s, meeting real-time safety requirements. Overall, the proposed system significantly enhances early fire warning, multi-source environmental monitoring, and rapid hazard response, demonstrating strong applicability and scalability in modern laboratory safety management. Full article

Urban park green spaces (UPGSs) play a critical role in enhancing residents’ quality of life, particularly for older adults. However, inequities in accessibility and resource distribution remain persistent challenges in aging urban areas. To address this issue, this study takes Gulou District, Nanjing City, as an example and proposes a comprehensive framework to evaluate the overall quality of UPGSs. Furthermore, an enhanced Gaussian two-step floating catchment area (2SFCA) method is introduced that incorporates (1) a multidimensional park quality score derived from an objective evaluation system encompassing ecological conditions, service quality, age-friendly facilities, and basic infrastructure; and (2) a Gaussian distance decay function calibrated to reflect the walking and public transit mobility patterns of the older adults in the study area. The improved method calculates the accessibility values of UPGSs for older adults living in residential communities under the walking and public transportation scenarios. Finally, factors influencing the social equity of UPGSs are analyzed using Pearson correlation coefficients. The experimental results demonstrate that (1) high-accessibility service areas exhibit clustered distributions, with significant differences in accessibility levels across the transportation modes and clear spatial gradient disparities. Specifically, traditional residential neighborhoods often present accessibility blind spots under the walking scenario, accounting for 50.8%, which leads to insufficient accessibility to public green spaces. (2) Structural imbalance and inequities in public service provision have resulted in barriers to UPGS utilization for older adults in certain communities. On this basis, targeted improvement strategies based on accessibility characteristics under different transportation modes are proposed, including the establishment of multi-tiered networked UPGSs and the upgrading of slow-moving transportation infrastructure. The research findings can enhance service efficiency through evidence-based spatial resource reallocation, offering actionable insights for optimizing the spatial layout of UPGSs and advancing the equitable distribution of public services in urban core areas. Full article

Coalbed-methane (CBM) extraction involves complex processes such as desorption, diffusion, and seepage, significantly increasing the difficulty of numerical simulation. To enable efficient CBM development, this study establishes an integrated simulation workflow for CBM, encompassing geological modeling, geomechanical modeling, hydraulic fracture simulation, and production dynamic simulation. Specifically, the unconventional fracture model (UFM), integrated within the Petrel commercial software, is applied for fracture simulation, with an unstructured grid constructing the CBM production model. Subsequently, based on the case study of well pad A in the Daning–Jixian block, the effects of well spacing and hydraulic fractures on gas production were analyzed. The results indicate that the significant stress difference between the coal seam and the top/bottom strata constrains fracture height, with simulated hydraulic fractures ranging from 169.79 to 215.84 m in length, 8.91 to 10.45 m in height, and 121.92 to 248.71 mD·m in conductivity. Due to the low matrix permeability, pressure drop and desorption primarily occur in the stimulated reservoir volume (SRV) region. The calibrated model predicts a 10-year cumulative gas production of 616 × 10⁴ m³ for the well group, with a recovery rate of 10.17%, indicating significant potential for enhancing recovery rates. Maximum cumulative gas production occurs when well spacing slightly exceeds fracture length. Beyond 200 mD·m, fracture conductivity has diminishing returns on production. Fracture length increases from 100 to 250 m show near-linear growth in production, but further increases yield smaller gains. These findings provide valuable insights for evaluating development performance and exploiting remaining gas resources for CBM. Full article

Background/Objectives: Pediatric mental health is a major public health concern worldwide and primary care providers struggle to meet the growing demand for mental healthcare. Child Psychiatry Access Programs have emerged to fill gaps in primary care provider (PCP) training, confidence, and workflow support. This study aimed to describe the iterative development of a Child Psychiatry Access Program and present initial findings on its reach and feasibility in supporting PCPs. Methods: The Practical, Robust Implementation and Sustainability Model (PRISM) implementation framework guided the development and evaluation of the program. Pre-implementation surveys and invested partner interviews informed the creation of a multidisciplinary program comprising three components: (1) consultation services and resource navigation, (2) education and training, and (3) provider care guides. The program was then implemented, and reach was assessed via consultation calls, attendance at education and training series, resource navigation encounters, and care guide usage. Feasibility was evaluated through pre- and post-series self-reported ratings across six learning objectives. Results: Pre-implementation evaluation indicated high provider interest across all educational modalities. The resulting program included consultation services, education and training, resource navigation, and provider care guides. Educational trainings led to significant improvements in self-reported knowledge and confidence across six learning objectives, including assessment, treatment planning, family engagement, and navigating local resources. Resource navigation primarily facilitated ongoing management within the primary care setting, with PCPs retaining care in the majority of cases. Engagement with the Colorado Care Guide demonstrated sustained reach, with over 4600 page views from 1300 active users, reflecting broad and ongoing utilization of program resources. Consultation call data mirrored these trends, highlighting both frequently addressed diagnoses and expanding program reach over time. Conclusions: Child psychiatry access programs help support access to youth mental health care in the primary care space and offer potential solutions to workforce limitations during an era of increasing mental health concerns in youth and teens. Findings from this implementation may inform adaptation of child psychiatry access programs in other regions seeking to expand mental health support for children and adolescents in primary care settings. Full article

The diameter of the sunflower flower head and the thickness of its margins are important crop phenotypic parameters. Traditional, single-dimensional two-dimensional imaging methods often struggle to balance precision with computational efficiency. This paper addresses the limitations of the YOLOv11n-seg model in the instance segmentation of floral disk fine structures by proposing the MBLA-YOLO instance segmentation model, achieving both lightweight efficiency and high accuracy. Building upon this foundation, a non-contact measurement method is proposed that combines an improved model with three-dimensional point cloud analysis to precisely extract key structural parameters of the flower head. First, image annotation is employed to eliminate interference from petals and sepals, whilst instance segmentation models are used to delineate the target region; The segmentation results for the disc surface (front) and edges (sides) are then mapped onto the three-dimensional point cloud space. Target regions are extracted, and following processing, separate models are constructed for the disc surface and edges. Finally, with regard to the differences between the surface and edge structures, targeted methods are employed for their respective calculations. Whilst maintaining lightweight characteristics, the proposed MBLA-YOLO model achieves simultaneous improvements in accuracy and efficiency compared to the baseline YOLOv11n-seg. The introduced CKMB backbone module enhances feature modelling capabilities for complex structural details, whilst the LADH detection head improves small object recognition and boundary segmentation accuracy. Specifically, the CKMB module integrates MBConv and channel attention to strengthen multi-scale feature extraction and representation, while the LADH module adopts a tri-branch design for classification, regression, and IoU prediction, structurally improving detection precision and boundary recognition. This research not only demonstrates superior accuracy and robustness but also significantly reduces computational overhead, thereby achieving an excellent balance between model efficiency and measurement precision. This method avoids the need for three-dimensional reconstruction of the entire plant and multi-view point cloud registration, thereby reducing data redundancy and computational resource expenditure. Full article

Rodents are the most diverse group of mammals, yet the natural history of many species remains poorly understood due to their elusive behavior. In this study, we examined the population structure, home range, space use, and food selection of two sympatric sigmodontine rodents, Euryoryzomys russatus and Sooretamys angouya, in the Morro Grande Forest Reserve, Brazil. E. russatus was more abundant than S. angouya, with its capture rates influenced by temperature. In contrast, the population variation of S. angouya showed no clear relationship with the assessed biotic (fruits and arthropods) or abiotic factors (temperature and precipitation), suggesting different primary regulatory factors for its population or a more generalist ecological strategy. The two species exhibited vertical stratification in space use: S. angouya displayed scansorial and arboreal locomotion, while E. russatus remained strictly terrestrial. Home range size, space use, and mobility were primarily influenced by resource availability, reproductive cycles, and individual body size. Our findings provide insights into the life strategies of these species, specifically regarding their vertical stratification in space use and their distinct responses to environmental resource fluctuations, enhancing our understanding of how sympatric rodents navigate shared spatial and temporal environments. Full article

Minor Southern Italian population centers present a fragmented and uneven urban landscape, resulting from abandonment and depopulation phenomena that have led, especially in historic city centers, to urban voids scattered with rubble, buildings in a state of ruin, and others with evident structural collapses. Within a broader urban regeneration strategy for these centers, aligned with current national and European policies, the recovery of these vacant spaces can play a decisive role in enhancing urban quality and the desired touristic appeal, with social, economic, and environmental implications. These areas may also become valuable resources for innovating the urban core in a green transition process, contributing to carbon neutrality goals while improving residents’ quality of life. This paper addresses the importance of pocket parks as systems of resilience against climate change and hydrogeological risks, as well as rainwater drainage systems in densely built urban areas with strong historical character. The study includes a case study application focusing on a location in the Sicilian hinterland, notable for its historical and architectural value. The urban center under examination, Naro in the province of Agrigento, has experienced significant depopulation over the past fifty years, and the designation of its provincial capital as the Italian Capital of Culture 2025 could provide the opportunity for revival through small-scale, low-cost, and sustainable actions. Full article

Urban green space (UGS) is a fundamental element of urban systems for enhancing the quality of urban life. UGS plays a pivotal role in promoting urban ecological sustainability if important criteria are integrated into urban planning programs. This paper explores the impacts of the ecological criteria on urban sustainability through UGS planning and examines these criteria within the context of the Adelaide Metropolitan Area as a case study. To address the study’s goals, a content analysis was conducted to identify the most critical criteria affecting urban ecological sustainability through UGS planning. Subsequently, based on the identified criteria, a household survey was conducted to evaluate the status of the case study concerning the ecological sustainability factors. In this stage, 100 responses were collected through a questionnaire survey. Then, based on the household survey results, a solution was provided to the challenging criteria by a local experts’ interview. For promoting urban ecological sustainability, ten criteria were identified as the most important and effective criteria based on the previous studies. Household survey data was analysed using one-sample T-test, multiple linear regression, and geographically weighted regression (GWR) model. The results indicated that the criteria of reviving ecological networks, water resources, and the protection of UGS with the score below standard average (which is 3), require practical guidelines and policies to enhance the sustainability of Adelaide Metropolitan Area. The regression analysis demonstrated that ecological landscape and design had the strongest positive effect on sustainability (adjusted R² = 0.685), while the geographically weighted regression highlighted biodiversity and vegetation as particularly influential in Plympton (local R² = 0.866) and Unley (local R² = 0.488). Expert interviews recommended strategies such as wastewater recycling, long-term conservation planning, and restoring ecological connectivity. This study provides a practical framework to guide urban planners and policymakers in enhancing ecological sustainability through UGS planning. Full article

In complex 3D maneuvering tasks (e.g., post-disaster rescue, urban operations, and infrastructure inspection), the trajectories that quadrotors need to track are often complex—containing both gentle flight phases and highly maneuverable trajectory segments. Under such trajectory tracking tasks with the composite characteristics of “gentle-high maneuvering”, quadrotors face challenges of limited onboard computing resources and short endurance, requiring a balance between trajectory tracking accuracy, computational efficiency, and energy consumption. To address this problem, this paper proposes a lightweight trajectory tracking control method based on hierarchical decision-making and dual-threshold adaptive switching. Inspired by the biological “prediction–reflection” mechanism, this method designs a dual-threshold collaborative early warning switching architecture of “prediction layer–confirmation layer”: The prediction layer dynamically assesses potential risks based on trajectory curvature and jerk, while the confirmation layer confirms in real time the stability risks through an attitude-angular velocity composite index. Only when both exceed the thresholds, it switches from low-energy-consuming Euler angle control to high-precision geometric control. Simulation experiments show that in four typical trajectories (straight-line rapid turn, high-speed S-shaped, anti-interference composite, and narrow space figure-eight), compared with pure geometric control, this method reduces position error by 19.5%, decreases energy consumption by 45.9%, and shortens CPU time by 28%. This study not only optimizes device performance by improving trajectory tracking accuracy while reducing onboard computational load, but also reduces energy consumption to extend UAV endurance, and simultaneously enhances anti-disturbance capability, thereby improving its operational capability to respond to emergencies in complex environments. Overall, this study provides a feasible solution for the efficient and safe flight of resource-constrained onboard platforms in multi-scenario complex environments in the future and has broad application and expansion potential. Full article

Rural community development in China has made progress under the rapid implementation of the rural revitalization strategy; however, it has also revealed challenges such as an overemphasis on spatial construction, severe homogenization, and low sustainability. Existing research on rural community development lacks sufficient localized experience, and there is a limited understanding of how the development process is generated, maintained, and evolved. This study examines Xiongfan Village in Dawu County, Hubei Province, using an innovative methodological integration of Actor-Network Theory (ANT) and Social Network Analysis (SNA). This mixed-methods approach qualitatively traces the formation of networks involving both human and non-human actors, while quantitatively mapping the collaborative structure among human actors. Qualitative analysis of actor networks identifies both human actors (such as government departments, enterprises, social organizations, and villagers) and non-human actors (such as natural and cultural landscapes) as key participants. Through processes like recruitment, mobilization, and dispute resolution, various actors have formed interest alliances centered around the core issue of “revitalizing and sustainably developing rural community resources.” Quantitative social network analysis reveals a “core-periphery” structure, with government departments and social organizations occupying central roles, while business institutions and community villagers are positioned at the periphery. This distribution contrasts with the overarching goal of community development, which seeks to enhance villagers′ intrinsic motivation. The study suggests that rural community development in this area can be improved by diversifying co-construction forms, restructuring core groups, and empowering peripheral actors. These measures will facilitate a shift from single-space development to enhanced community capacity-building, ultimately promoting sustainable rural development. Full article