Search Results (1,922)

Modern-day urban warehouses face exploding large inventory and tight spaces requiring fast, accurate, and safe stocktaking in a narrow aisle in a GPS-denied environment. This paper proposes a complete UAV-enabled framework performing real-time QR code scanning with inventory synchronization through a safety-aware trajectory generation for obtaining collision-free motion. A novel hybrid workflow integrating MATLAB/Simulink R2024b and Unreal Engine is used for dynamics and photorealistic rendering, alongside a real-time warehouse setup using drone cameras and 3D LiDAR coupled with a ground control station and live dashboard. The system in this paper was evaluated by testing with single and multi-UAV models across high-fidelity simulations and experiments. Results demonstrate simulated QR accuracy of approximately 95 to 96%, with experimental validation achieving between 86 and 90.5% due to real-world environmental factors. In experimental and simulation analysis, mean end-to-end latency remained under half a second, trajectory error range between 8 and 10 cm, and safety margins were consistently maintained throughout the test. It was further observed that multi-UAV coordination halved mission time compared to single-drone tests while keeping duplicate reads negligible, indicating a scalable and safe pipeline for industry application. Full article

The growing importance of integrating renewable energy sources (RESs) into mainline railway traction networks stems from the sector’s substantial electricity demand, which is traditionally met by carbon-intensive thermal generation. This paper addresses the potential of wind power to enhance energy efficiency and reduce emissions in rail transport. It details the development of digital models for simulating DC traction power systems (TPSs) coupled with RESs, specifically wind turbines. Given the complexity of TPSs, effective integration requires digital modeling that accounts for their unique properties. The proposed methodology, based on phase coordinate algorithms, offers a universal and comprehensive framework. It enables the identification of various operational modes (normal, emergency, and special) for diverse network components, including traction networks, transmission lines, and transformers. These models were used to simulate real-world train operations, generating data on electrical parameter dynamics and transformer thermal conditions. The results confirm that wind integration can improve energy efficiency, validating the methodology’s practical applicability for RES projects in DC traction networks, including advanced high-voltage systems. Full article

This study explores the coupling relationship between wetland ecotourism and resource–environmental carrying capacity in the Dongting Lake region. By constructing a comprehensive index system and utilizing a coupling coordination degree model, we analyzed the temporal and spatial evolution characteristics across 24 districts and counties from 2014 to 2022. The results indicate the following: (1) The quality of both ecotourism and environmental carrying capacity has steadily improved, though significant regional disparities remain. (2) The coupling coordination degree exhibits a “high in the center, low in the periphery” spatial pattern, showing a positive correlation between ecotourism levels and environmental capacity. (3) The region comprises three development types: balanced coordination, well-matched, and lagging. These findings provide a scientific basis for optimizing ecotourism pathways and achieving high-quality regional sustainable development. Full article

Accurately assessing dynamic water resource carrying capacity (WRCC) is essential and challenging, particularly in regions like the Gansu sections of the Yellow River Basin (GSYRB), a core water source protection zone in the arid northwest of China, due to its pressing challenge of balancing water resources for socioeconomic needs and ecological security. This study proposes a novel integrated computational assessment framework named SD-VIKOR to address the complexities arising from nonlinear interactions within the “water resources–socioeconomic–ecological environment” (W–S–E) system. The core of this framework is the tight coupling of a system dynamics (SD) simulation model with a VIKOR multi-criteria evaluation module, where indicator weights are objectively–subjectively determined via an Analytic Hierarchy Process (AHP)–entropy weight method. This integrated SD-VIKOR engine enables dynamic, scenario-based WRCC trajectory simulation. To move beyond simulation and enable mechanistic insight, the framework further incorporates a diagnostic suite: a Geodetector module quantifies dominant drivers and their interactions; an obstacle degree model pinpoints key limiting factors; and a coupling coordination degree model evaluates subsystem synergies. Together, they form a closed-loop “dynamic simulation → multi-criteria assessment → driving mechanism analysis and constraint diagnosis → subsystem coordination analysis” workflow. Applied to the GSYRB from 2012 to 2030 under five development scenarios, the framework demonstrated high efficacy. It successfully captured path-dependent WRCC evolution, revealing that the ecological-priority scenario (B2), which shifts system drivers from economic-scale expansion to resource-efficiency and environmental governance, yielded optimal WRCC and the highest system coordination. In contrast, business-as-usual and single-minded economic expansion scenarios underperformed. Six key obstacle factors were quantitatively identified, linking WRCC constraints to natural endowments, economic patterns, and domestic demand. The results reveal pronounced spatial–temporal heterogeneity in WRCC across the GSYRB, with socioeconomic development, water resource use efficiency, and ecological conditions acting as the primary joint drivers of WRCC evolution. Critically, several key indicators are identified as persistent constraints on regional water sustainability. In contrast to conventional static evaluations, the integrated framework captures the complex dynamics and multi-subsystem interactions governing WRCC, offering a more robust diagnostic of resource–environment systems. These insights provide a transferable analytical basis for designing sustainable water management strategies in arid river basins. Full article

Load forecasting for Integrated Energy Systems (IESs) is critical to enabling multi-energy coordinated optimization and low-carbon scheduling. Facing multi-load types and multi-site high-dimensional heterogeneous data, there remains a global learning challenge stemming from insufficient representation of spatiotemporal coupling features. In response to the multi-source heterogeneous characteristics of IES loads, this paper designs a Spatiotemporal Topology Encoder that maps load data into a tensorized multi-energy spatiotemporal topological representation via fuzzy classification and multi-scale ranking. In parallel, we construct a MultiScale Hybrid Convolver to extract multi-scale, multi-level global spatiotemporal features of multi-energy load representations. We further develop a Temporal Segmentation Transformer and a Steady-State Exponentially Gated Memory Unit, and design a jointly optimized forecasting model that enforces global dynamic correlations and local, steady-state preservation. Altogether, we propose a multi-scale spatiotemporal fusion and steady-state memory-driven load forecasting method for integrated energy systems (MSTF-SMDN). Extensive experiments on a public real-world dataset from Arizona State University demonstrate the superiority of the proposed approach: compared to the strongest baseline, MSTF-SMDN reduces cooling load RMSE by 16.09%, heating load RMSE by 12.97%, and electric load RMSE by 6.14%, while achieving R² values of 0.99435, 0.98701, and 0.96722, respectively, confirming its feasibility, efficiency, and promising potential for multi-energy load forecasting in IES. Full article

As a representative digital additive construction material, three-dimensional printed concrete (3DPC) imposes a synergistic rheological requirement on fresh cementitious mixtures, namely “pumpability–extrudability–buildability,” throughout the forming process. Rheological parameters and their temporal evolution not only govern the stability of the material during pumping, nozzle extrusion, and layer-by-layer deposition, but also directly determine interlayer interfacial integrity, geometric fidelity, and the development of macroscopic mechanical performance. This paper provides a systematic review of the regulation strategies and evolutionary characteristics of 3DPC rheology, with particular emphasis on how raw material composition, printing parameters, and multiscale evolution mechanisms influence yield stress, plastic viscosity, and thixotropic behavior. The time-dependent evolution of rheological properties is elucidated across multiple length scales, encompassing microscopic particle interactions and hydration-induced bridging, mesoscopic aggregate force-chain networks and particle migration, and macroscopic shear stimulation coupled with temperature–humidity effects. On this basis, it is further highlighted that existing models and characterization frameworks remain insufficient to capture the time-dependent structural evolution under realistic printing conditions. Therefore, the establishment of unified characterization standards, together with in situ rheological measurements and multiscale simulations, is urgently required to enable the coordinated optimization of material design and printing processes and to facilitate engineering-scale implementation. Full article

To address the calibration challenge caused by the nonlinear variation in intrinsic parameters during continuous camera zooming in UAV electro-optical pods, this paper proposes an online calibration method based on IMU-visual fusion. Traditional offline calibration cannot adapt to dynamic scenarios, while existing self-calibration methods suffer from slow convergence and insufficient robustness. The proposed method aims to achieve real-time and accurate estimation of camera intrinsic parameters during zooming. Specifically, we first construct a unified state estimation framework that encodes the internal and external parameters of the camera and the 3D positions of scene feature points into a high-dimensional state vector, then establish a camera motion model based on IMU data, construct a visual observation model by combining the pinhole camera and second-order radial distortion model to establish a nonlinear mapping from 3D feature points to 2D pixel coordinates, and adopt an improved ORB algorithm for feature extraction and LK optical flow method to achieve high-precision cross-frame feature matching to enhance the stability of visual observation. Most importantly, we design a tight-coupling fusion strategy based on the Extended Kalman Filter (EKF) prediction-update iteration mechanism, which fuses IMU high-frequency motion constraints and visual geometric constraints in real time to suppress parameter drift induced by focal length changes. Finally, we recursively solve the state vector to complete the online dynamic estimation of intrinsic parameters. Monte Carlo simulation experiments and real UAV flight experiments confirm that the method has both high estimation accuracy and strong environmental adaptability, can meet the high-precision calibration needs of UAVs in dynamic scenarios, and provides reliable technical support for accurate target positioning. Full article

The deep integration of green finance and the digital economy serves as a critical lever for achieving the “dual carbon” goals and the “Digital China” strategy. This study constructs a “Technology–Capital–Environment” (TCE) analytical framework and integrates a coupling coordination degree model with a dynamic Qualitative Comparative Analysis (QCA) approach. Based on panel data of the Pearl River Delta urban agglomeration from 2014 to 2023, we investigate the synergistic development level, multiple pathways, and dynamic evolution between the two systems. Key findings include: (1) The coupling coordination degree of the two systems has steadily increased, yet significant spatial heterogeneity persists. The average annual growth rate of potential catch-up cities (3.37%) surpasses that of core leading cities (1.77%). (2) Four equifinal driving pathways are identified, which can be summarized into three patterns: technology-dominated institutional synergy, human capital–policy dual-core guidance, and technology–infrastructure synergistic driven. (3) Dynamic analysis reveals that pathways embedded with digital human capital and new infrastructure exhibit stronger resilience to shocks, whereas pathways reliant on institutional synergy demonstrate higher vulnerability. (4) Guangzhou and Shenzhen have already exhibited “ecosystem-level” synergistic characteristics, rendering existing configurational models limited in explanatory power. This study provides a theoretical foundation for promoting regionally differentiated deep integration of green finance and the digital economy and for building a resilience-oriented synergistic development system. Full article

This paper investigates the fractal dynamical behavior of a discrete Caputo fractional-order hepatitis C virus model. First, we analyze the stability of the system by using spectral radius and design the fractional-order controller based on coordinate transformation. Then, a nonlinear coupling controller is constructed to achieve synchronization between two fractional-order models with different parameters and different fractional orders, and the synchronization is supported by rigorous mathematical proof. Numerical simulations are used to verify the effectiveness of control and synchronization. Full article

Given less than five years remaining until the target year for the first phase of China’s dual carbon goals, this paper studies carbon allowance allocation with an in-depth study of Jiangsu Province due to its significant role in driving the Yangtze River Delta’s pioneering achievement of the dual carbon goals. This study considered 2017 (the intermediate target year) as the base year and incorporated socio-economic data such as population, GDP, and the urbanization rate. Then, methods including the entropy weight method, gravity model and social network analysis were applied to classify Jiangsu’s 95 counties. From a regional coordination perspective, carbon governance clusters were constructed with the Shapley value, based on which spatial heterogeneity patterns were analyzed, and a carbon quota allocation was proposed. The findings reveal that: (1) The dominant factors influencing cross-scale carbon reduction capacity at the county level are natural carbon sink capacity (indicator weight: 0.180) and urbanization rate (indicator weight: 0.145). (2) The correlation between carbon reduction factors among different districts and counties exhibits an uneven spatial pattern. And the spatial configuration exhibits a multi-tiered, network-like distribution. (3) Through conducting spatial analysis and spatial grouping, Jiangsu could be divided into 14 county-level carbon governance alliances, with the number of member counties ranging from 4 to 10 within each alliance. (4) The allocation of carbon quotas in Jiangsu exhibits a distinct descending gradient from the southern to the northern regions, which is coupled with the regional economic geography. This is exemplified by the highest quota in Jiangyin (496.46 Mt) in the south and the lowest in Lianyun (34.90 Mt) in the north. It is concluded that two carbon emission reduction pathways should be established as a priority: (a) Tongshan-Gulou (Xuzhou)-Yunlong-Quanshan-Jiawang and (b) Tianning-Jiangyin-Zhangjiagang-Changshu-Taicang-Kunshan. Full article

This paper presents a design research study that develops a comprehensive conceptual framework for an integrated digital twin system for architectural heritage. The framework aims to explore mechanisms for real-time monitoring and the coupled regulation of structural health, microclimatic conditions, and energy performance. In the context of the ongoing global warming emergency, this framework supports climate adaptation strategies for heritage sites. It enables a fully coordinated operational process encompassing real-time sensing, predictive analysis, coupled control, and decision support. In the structural dimension, the framework is designed to utilise sensors to monitor and warn against cracks, settlement, and deformation, whilst integrating models to analyse stress conditions. In the microclimate dimension, the study envisages predicting and adjusting HVAC and lighting systems based on environmental parameters and footfall monitoring data via algorithms, with the aim of balancing occupant comfort with humidity control and mould prevention. Regarding energy, the framework optimises equipment operation through smart metering and algorithms and we propose a modelling tool for the quantitative assessment of energy-saving retrofit effects. Furthermore, the framework incorporates the establishment of an open-access dataset covering structural, microclimate, and energy use data, providing data standards and a foundation for subsequent empirical research. Full article

Widespread acceptance of collaborative robots in human-involved scenarios requires accessible and intuitive interfaces for lay workers and non-expert users. Existing interfaces often rely on users to plan and issue low-level commands, necessitating extensive knowledge of robot control. This study proposes a multimodal agentic AI framework integrating natural user interfaces (NUIs) to foster effortless human-like partnerships in human–robot collaboration (HRC), which enhance intuitiveness and operational efficiency. First, it allows users to instruct robots using plain language verbally, coupled with gaze, revealing objects precisely. Second, it offloads users’ workload for robot motion planning by understanding context and reasoning task decomposition. Third, coordinating with AI agents built on large language models (LLMs), the system interprets users’ requests effectively and provides feedback to establish transparent communication. This proof-of-concept study included experiments to demonstrate a practical implementation of the agentic AI framework on a mobile manipulation robot in the collaborative task of human–robot wood assembly. Seven participants were recruited to interact with this AI-integrated agentic robotic system. Task performance and user experience metrics were measured in terms of completion time, intervention rate, NASA TLX survey for workload, and valuable insights of practical applications were summarized through a qualitative analysis. This study highlights the potential of NUIs and agentic AI-embodied robots to overcome existing HRC barriers and contributes to improving HRC intuitiveness and efficiency. Full article

In the context of the “dual carbon” goals, this study examines the spatiotemporal patterns and evolution of urban low-carbon coordinated development (LCCD). Based on the integrated Economy–Energy–Environment–Society (3E1S) framework, this study constructs a multidimensional evaluation index system for urban LCCD and applies a composite system coordination degree model to quantitatively assess and analyze the spatiotemporal evolution of LCCD across 271 prefecture-level and above cities in China from 2005 to 2020. The results indicate that (1) from a temporal perspective, the level of urban LCCD in China exhibits an overall upward trend during the study period, with relatively rapid growth from 2005 to 2015, a subsequent slowdown after 2015, and a stage-wise decline observed in 2020, reflecting a transition from rapid improvement to gradual adjustment; (2) from a spatial perspective, urban LCCD demonstrates a certain degree of spatial autocorrelation and an overall spatial structure characterized by a southwest–northeast-oriented axis, with spatial agglomeration features gradually strengthening over time; (3) from a system structure perspective, the coordinated evolution of the 3E1S subsystems shows clear differentiation, with the energy and economic subsystems following an inverted U-shaped trajectory, the environmental subsystem exhibiting a fluctuating upward trend, and the social subsystem maintaining continuous improvement, highlighting the inherent imbalance in the multidimensional process of subsystem coordination. From a multisystem coordination perspective, this study systematically identifies the spatiotemporal evolutionary characteristics and subsystem coupling relationships of urban low-carbon coordinated development, providing empirical evidence for a deeper understanding of multidimensional low-carbon coordination processes in cities. Full article

As a key spatial platform for implementing China’s Northeast Revitalization Strategy, coordinated development of production–living–ecological (PLE) functions in the Changchun Metropolitan Area is crucial for high-quality regional development. This study uses 24 counties (districts) in the metropolitan area as analytical units and develops a quantitative indicator system to evaluate PLE functions. We integrate the entropy-weighted TOPSIS method, social network analysis (SNA), and geographically and temporally weighted regression (GTWR) to examine the spatiotemporal dynamics, spatial correlation networks, and driving mechanisms of the three functions from 2013 to 2023. Temporally, the production function follows a growth–decline–recovery trajectory, the living function increases overall despite fluctuations, and the ecological function strengthens continuously. Overall, the three functions increasingly exhibit coupling and synergy. Spatially, the production function concentrates in core areas and diffuses along major axes. The living function is led by the core and followed by county-level catch-up. The ecological function is higher in the east, relatively stable in the west, and connected by corridors, together forming a multi-center, axis-based synergistic pattern. In the spatial correlation networks, densities of the production and ecological networks remain largely stable, whereas the living network becomes markedly denser. The three networks display distinct topologies and continue to evolve structurally. For driving mechanisms, the GTWR model provides the best fit. Geographic proximity positively contributes to the formation of all three functional networks, while the eight explanatory factors show pronounced spatiotemporal heterogeneity. These findings provide an evidence base for optimizing functional coordination and implementing differentiated spatial governance in metropolitan areas. Full article

Land use/cover change (LUCC) strongly regulates ecosystem carbon storage and provides a critical entry point for carbon-oriented territorial spatial governance. However, balancing carbon sequestration, food security, urban expansion, and ecological protection remains challenging in Southwest China’s Ecological Security Barrier Zone (ESBZ). In this study, we coupled the Patch-generating Land Use Simulation (PLUS) model with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) carbon module to reconstruct LUCC and carbon-storage dynamics during 1999–2024 and to project land-use patterns and carbon storage in 2049 under four scenarios: Natural Development (NDS), Urban Development (UDS), Cultivated land Protection (CPS), and Ecological Protection (EPS). Unlike most existing PLUS–InVEST studies focused on cities, watersheds, or single provinces, this study targets a national ecological security barrier and integrates land-use evolution, carbon-storage responses, scenario trade-offs, and zoning-oriented governance into one analytical framework. It therefore provides spatially explicit evidence not only for carbon-oriented land management but also for interprovincial ecological compensation and coordinated ecological security governance in ecologically fragile regions. The 2024 land system was dominated by forest land (56.40%), cultivated land (25.47%), and grassland (16.09%). From 1999 to 2024, forest land expanded by 1.966 × 10⁴ km², whereas cultivated land and grassland decreased by 9.738 × 10³ km² and 1.874 × 10⁴ km², respectively; 92.65% of construction-land expansion originated from cultivated land conversion. Correspondingly, total carbon storage followed a “fluctuation–decline–recovery” trajectory, decreasing from 3.833 × 10¹⁰ t in 1999 to 3.820 × 10¹⁰ t in 2014, before rebounding to 3.831 × 10¹⁰ t in 2024. Pronounced provincial heterogeneity was observed: Sichuan and Yunnan jointly contributed about 76% of regional carbon storage, while Chongqing and Guizhou remained relatively low. By 2049, EPS produced the highest carbon storage (3.854 × 10¹⁰ t), whereas CPS, UDS, and NDS all led to lower values than in 2024. These contrasts indicate that the four scenarios do not represent a simple ranking of “better” or “worse”, but rather different trade-offs among carbon sinks, cultivated land protection, urban development, and regional equity. Overall, the results support province-differentiated, zoning-based land governance and highlight the need to coordinate ecological protection, cultivated-land conservation, urban growth control, and interprovincial ecological compensation to enhance carbon sequestration and safeguard ecological security in the ESBZ. Full article