Search Results (320)

This study develops an integrated bi-level operations–assignment model to optimise express service on the Gyeongin Line, a core corridor connecting Seoul and Incheon. The upper level jointly selects express stops and time-of-day headways under coverage constraints—a minimum share of key stations and a maximum inter-stop spacing—while the lower level assigns passengers under user equilibrium using a generalised time function that incorporates in-vehicle time, 0.5× headway wait, walking and transfers, and crowding-sensitive dwell times. Undergrounding and alignment straightening are incorporated into segment run-time functions, enabling the co-design of infrastructure and operations. Using automatic-fare-collection-calibrated origin–destination matrices, seat-occupancy records, and station-area population grids, we evaluate five rail scenarios and one intermodal extension. The results indicate substantial system-wide gains: peak average door-to-door times fall by approximately 44–46% in the AM (07:00–09:00) and 30–38% in the PM (17:30–19:30) for rail-only options, and by up to 55% with the intermodal extension. Kernel density estimation (KDE) and cumulative distribution function (CDF) analyses show a leftward shift and tail compression (median −8.7 min; 90th percentile (P90) −11.2 min; ≤45 min share: 0.0% → 47.2%; ≤60 min: 59.7% → 87.9%). The 45-min isochrone expands by ≈12% (an additional 0.21 million residents), while the 60-min reach newly covers Incheon Jung-gu and Songdo. Backcasting against observed express/local ratios yields deviations near the ±10% band (PM one comparator within and one slightly above), and the Kolmogorov–Smirnov (KS) statistic and Mann–Whitney (MW) test results confirm significant post-implementation shifts. The most cost-effective near-term package combines mixed stopping with modest alignment and capacity upgrades and time-differentiated headways; the intermodal express–transfer scheme offers a feasible long-term upper bound. The methodology is fully transparent through provision of pseudocode, explicit convergence criteria, and all hyperparameter settings. We also report SDG-aligned indicators—traction energy and CO₂-equivalent (CO₂-eq) per passenger-kilometre, and jobs reachable within 45- and 60-min isochrones—providing indicative yet robust evidence consistent with SDG 9, 11, and 13. Full article

Hydraulic fracturing is a key technique for creating complex fractures in unconventional reservoirs to enhance energy recovery. Asymmetric branched fractures, as fundamental units, are widely observed in complex fracture networks. Effective proppant distribution within such structures is critical but remains poorly understood. To investigate this, a rough-walled slot with two branches was developed, where asymmetry was introduced by inserting plates with different geometries on one side. The results show that the structural asymmetry between the left and right branches can significantly induce non-uniform transport and irregular sand bed morphology. Reducing the height and width of branch fractures increases fluid velocity, limiting proppant settling within the branch. As the flow area decreases, the fluid velocity increases, driving more proppant through the branch toward the distal fracture region. Injection pressure increases as the flow area of the branch fracture decreases. At a height ratio of 0.25, sand plugging and ineffective proppant placement probably occur within the natural fracture. When the branch is located at the upper section, proppants hardly settle to form a bed, leading to closure of the fracture. The study provides new insights into optimizing proppant placement in complex fractures. Full article

Particle Swarm Optimization (PSO) has been widely employed to optimize the deployment of Unmanned Aerial Vehicles (UAVs) in various scenarios, particularly because of its efficiency in handling both single and multi-objective optimization problems. In this paper, a framework for optimizing the deployment of edge-enabled UAVs using Pareto-PSO is proposed for data collection scenarios in which UAVs operate autonomously and execute onboard distributed multi-objective PSO to maximize the total non-overlapping coverage area while minimizing latency and energy consumption. Performance evaluation is conducted using key indicators, including convergence time, throughput, and total non-overlapping coverage area across bandwidth and swarm-size sweeps. Simulation results demonstrate that the Pareto-PSO consistently attains the highest throughput and the largest coverage envelope, while exhibiting moderate and scalable convergence times. These results highlight the advantage of treating the objectives as a vector-valued objective in Pareto-PSO for real-time, scalable, and energy-aware edge-UAV deployment in dynamic Internet of Flying Things environments. Full article

As a clean and renewable energy source with huge reserves, hot dry rock geothermal resources have received wide attention. The geothermal field plays a crucial role in studying the heat source mechanism of hot dry rock, defining target areas, and evaluating resources. In this study, the three-dimensional structural inversion of the Gonghe Basin is carried out using magnetotelluric sounding, and the Curie isothermal surface is obtained by analyzing regional aeromagnetic data. By coupling low-resistance and high-conductivity zones with temperature distribution and integrating the Curie isothermal surface with high-temperature anomalies of some melts, we constructed an initial temperature field model based on comprehensive geophysical data. The temperature field model of the Gonghe Basin is established by using the adaptive finite-element temperature conduction control equation and the constraints of the temperature data from geothermal wells. The temperature field model provides a basis for the future exploration of hot dry rock resources in the Gonghe area. Full article

The mudflat crab (H. tientsinensis) is a dominant species in coastal tidal flat areas, primarily inhabiting the high tide region of the intertidal zone, and possesses significant ecological and economic value. Vibrio species are one of the main bacterial pathogens responsible for diseases in marine organisms, and they are widely distributed in seawater and estuarine environments. However, the immune mechanisms employed by H. tientsinensis in response to Vibrio infections remain unclear. This study aims to investigate the physiological and immune mechanisms by analyzing the structural changes and differential gene expression in the gill and hepatopancreas following Vibrio parahaemolyticus infection. The results indicate that V. parahaemolyticus infection causes cellular damage, with structural alterations observed in the gills (epithelial cell edema in the gill filaments, and aneurysm formation) and the hepatopancreas (changes in lumen size, nuclear condensation, and modifications in connective tissue morphology). Transcriptome analysis revealed 9766 differentially expressed genes (DEGs) in the gills of the experimental group, with 4687 upregulated and 5079 downregulated genes. These DEGs are primarily involved in different ribosomal subunits. In the hepatopancreas, 1594 DEGs were identified, with 834 upregulated and 760 downregulated. These DEGs are predominantly associated with energy-coupled proton transmembrane transport, electron transport-coupled proton transport, and lipid transporter activity. H. tientsinensis gene annotation and KEGG enrichment analysis revealed that chemical carcinogens DNA adducts, amino acid metabolism, and some immune pathways play key roles in the ability of H. tientsinensis to defend against V. parahaemolyticus infection. The findings of this study contribute to a deeper understanding of the immune mechanisms of H. tientsinensis against V. parahaemolyticus infection and provide new insights for aquaculture management. Full article

Broadband absorption of electromagnetic energy plays an important role in energy harvesting and stealth. Here, we present and demonstrate an absorber with a wide bandwidth of 2.1 μm in mid-infrared. The trapezoidal metamaterial consists of alternating silicon carbide and dielectric films. We have numerically demonstrated that an ultrahigh absorption energy efficiency higher than 97.7% can be calculated from 10.6 μm to 12.7 μm. The proposed absorber has high absorption efficiency at a wide-angle range. The simulation results are consistent with the theoretical calculation based on effective medium theory. The theoretical model simplifies the multilayer structure into an effectively homogeneous metamaterial with hyperbolic dispersion. In addition, the distributions of magnetic field depict that different wavelengths can be trapped at structures with various widths. The mechanism of this phenomenon is attributed to the slowlight modes. Furthermore, a dual-sized absorber is designed to achieve high efficiency and broadband absorption, which is easy to manufacture. Our study has potential applications in the areas of energy harvesting materials, thermal emitters and photovoltaic devices in the mid-infrared. Full article

The rapid expansion of the Internet of Things (IoT) demands scalable, efficient, and user-friendly gateway solutions that seamlessly connect resource-constrained edge devices to cloud services. Low-cost, widely available microcontrollers, such as the ESP32 and its ecosystem peers, offer integrated Wi-Fi/Bluetooth connectivity, low power consumption, and a mature developer toolchain at a bill of materials cost of only a few dollars. For smart-home deployments where budgets, energy consumption, and maintainability are critical, these characteristics make MCU-class gateways a pragmatic alternative to single-board computers, enabling always-on local control with minimal overhead. This paper presents the design and implementation of an embedded IoT gateway powered by the ESP32 microcontroller. By using lightweight communication protocols such as Message Queuing Telemetry Transport (MQTT) and REST APIs, the proposed architecture supports local control, distributed intelligence, and secure on-site data storage, all while minimizing dependence on cloud infrastructure. A real-world deployment in an educational building demonstrates the gateway’s capability to monitor energy consumption, execute control commands, and provide an intuitive web-based dashboard with minimal resource overhead. Experimental results confirm that the solution offers strong performance, with RAM usage ranging between 3.6% and 6.8% of available memory (approximately 8.92 KB to 16.9 KB). The initial loading of the single-page application (SPA) results in a temporary RAM spike to 52.4%, which later stabilizes at 50.8%. These findings highlight the ESP32’s ability to serve as a functional IoT gateway with minimal resource demands. Areas for future optimization include improved device discovery mechanisms and enhanced resource management to prolong device longevity. Overall, the gateway represents a cost-effective and vendor-agnostic platform for building resilient and scalable IoT ecosystems. Full article

The urbanisation process of cities disrupts the natural energy balance and surface radiation, making cities relatively warm. While vegetation has been widely recognised as a key factor in mitigating urban heat, its effectiveness is shaped by interactions with urban morphology, surface cover types, and the background climate. This paper presents a bibliometric analysis of studies examining the role of vegetation in mitigating urban heat, with a particular focus on its interactions within the urban environment across four major Köppen–Geiger climate groups: tropical, arid, temperate, and cold. A total of 130 publications were reviewed, categorised, and analysed according to geographic distribution, study period, and methodological approaches. This review identifies underexplored areas, synthesises key findings, and summarises the most significant results. Vegetation and water bodies emerged as primary contributors to heat mitigation, along with building configuration, wind speed, and shading. Temperate climates were the most frequently studied. Remote sensing was the predominant methodological approach, followed by fixed in situ observations. Meso-scale studies, examining entire cities and their surroundings, dominated in terms of spatial scale. This review offers methodological recommendations for analysing urban vegetation within the context of urban climate research. As climate change intensifies, it is increasingly important to design and implement adaptation strategies that incorporate but are not limited to vegetation. Such strategies are essential to supporting sustainable and resilient urban development in diverse climatic contexts. Full article

Smart cities and urban planning have succeeded in gathering the attention of researchers worldwide, especially in the last decade, as a result of a series of technological, social and economic developments that have shaped the need for evolution from the traditional way in which the cities were viewed. Technology has been incorporated in many sectors associated with smart cities, such as communications, transportation, energy, and water, resulting in increasing people’s quality of life and satisfying the needs of a society in continuous change. Furthermore, with the rise in machine learning (ML) and artificial intelligence (AI), as well as Geographic Information Systems (GIS), the applications of big data analytics in the context of smart cities and urban planning have diversified, covering a wide range of applications starting with traffic management, environmental monitoring, public safety, and adjusting power distribution based on consumption patterns. In this context, the present paper brings to the fore the papers written in the 2015–2024 period and indexed in Clarivate Analytics’ Web of Science Core Collection and analyzes them from a bibliometric point of view. As a result, an annual growth rate of 10.72% has been observed, showing an increased interest from the scientific community in this area. Through the use of specific bibliometric analyses, key themes, trends, prominent authors and institutions, preferred journals, and collaboration networks among authors, data are extracted and discussed in depth. Thematic maps and topic discovery through Latent Dirichlet Allocation (LDA) and doubled by a BERTopic analysis, n-gram analysis, factorial analysis, and a review of the most cited papers complete the picture on the research carried on in the last decade in this area. The importance of big data analytics in the area of urban planning and smart cities is underlined, resulting in an increase in their ability to enhance urban living by providing personalized and efficient solutions to everyday life situations. Full article

Accurate surface wind speed data are vital for atmospheric science, climatology, and energy applications. European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5), as one of the most widely used global reanalysis datasets, has insufficient assessment of its applicability across diverse landform types. Using the gridded observational dataset over China (CN05.1) and the Global Basic Landform Units dataset, this study evaluated the surface wind speed data from ERA5 over various altitudinal zones and undulating terrains in China via root-mean-square differences (RMSD) and mean absolute percentage error (MAPE) against CN05.1 observations. Results reveal significant regional variations, with ERA5 effectively capturing the spatial distribution of mean wind speeds but systematically underestimating magnitudes, particularly in plateau and mountainous regions. ERA5 reanalysis fails to reproduce the observed altitudinal increase in surface wind speed. Elevation-dependent biases are prominent, with RMSD and MAPE increasing from low-altitude to high-altitude areas. Terrain complexity exacerbates errors, showing maximum deviations in high-relief mountains and minimum deviations in hilly regions. These biases evolve seasonally, peaking in spring and reaching minima in winter. In summary, discrepancies between observations and ERA5 vary with altitude, topographic relief, and season. The most significant deviations occur for spring surface winds in high-altitude, high-relief mountains, with mean RMSD reaching 3.3 m/s and MAPE 553%. The findings highlight the limitations of ERA5 reanalysis data in scientific and operational contexts over complex terrains. Full article

Hydrodynamic cavitation is one of the most promising technologies for sustainable process intensification in the food, nutraceutical, and environmental sectors, due to its ability to generate highly localized and intense implosions. Venturi-type devices, known for their simplicity and efficiency, are widely used for non-thermal extraction, microbial inactivation, and cellular disruption. However, the effectiveness of cavitation critically depends on internal geometry—particularly the perimeter-to-area ratio (P/A), which influences both pressure gradient distribution and the density of nucleation sites. In this context, an innovative configuration based on the Reuleaux triangle is proposed, allowing for a significant increase in the P/A ratio compared to conventional circular-section devices. This theoretical study extends the Navier–Stokes and Rayleigh–Plesset models to describe bubble dynamics and assess the influence of geometric and rotational variants (VRAt) on the localization and intensity of cavitation collapse. The results suggest that optimized internal geometries can reduce treatment times, increase selectivity, and improve the overall energy efficiency of cavitation processes, offering strong potential for advanced and sustainable industrial applications. This work is entirely theoretical and is intended to support the future design and experimental validation of next-generation cavitating devices. Full article

Laser energy is widely used as a selective photothermal heating agent in cancer treatment, standing out for not relying on ionizing radiation. However, in vivo tests have highlighted the need to develop irradiation techniques that allow precise control over the illuminated area, adapting it to the tumor size to further minimize damage to surrounding healthy tissue. To address this challenge, a proof of concept based on a laser irradiation system has been designed, enabling control over energy, exposure time, and irradiated area, using galvanometric mirrors. The control software, implemented in Python, employs a set of cameras (visible and infrared) to detect and monitor real-time thermal distributions in the region of interest, transmitting this information to a microcontroller responsible for adjusting the laser power and controlling the scanning process. Image alignment procedures, tunning of the controller’s gain parameters and the impact of the different engineering parameters are illustrated on a dedicated setup. As proof of concept, this approach has demonstrated the ability to irradiate a phantom of black modeling clay within an area of up to 5 cm × 5 cm, from 15 cm away, as well as to monitor and regulate the temperature over time (5 min). Full article

In recent years, distributed energy power supply systems have been widely used in remote areas and extreme environments. However, the intermittent and uncertain output power may cause power grid fluctuations, leading to higher harmonics in electromechanical equipment, especially motors. For permanent magnet synchronous motor (PMSM) systems, an electromagnetic (EM) vibration can cause problems such as energy loss and mechanical wear. Therefore, it is necessary to design control algorithms that can effectively suppress EM vibration. To this end, a vibration suppression algorithm for fractional-slot permanent magnet synchronous motors based on a d-axis current injection is proposed in this paper. Firstly, this paper analyzes the radial electromagnetic force of the fractional-slot PMSM to identify the main source of EM vibration in fractional-slot PMSMs. Based on this, the intrinsic relationship between the EM vibration of fractional-slot PMSMs and the d-axis and q-axis currents is explored, and a method for calculating the d-axis current to suppress the vibration is proposed. Experimental verification shows that the proposed algorithm can effectively suppress EM vibration. Full article

Caragana korshinskii Kom. (CKB), widely cultivated in Inner Mongolia, China, has potential for silage feed development due to its favorable nutritional characteristics, including a crude protein content of 14.2% and a neutral detergent fiber content below 55%. However, its vascular bundle fiber structure limits the efficiency of lactic acid conversion and negatively impacts silage quality, which can be improved through mechanical crushing. Currently, conventional crushing equipment generally suffers from uneven particle size distribution, high energy consumption, and low processing efficiency. In this study, a layered aggregate model was constructed using the discrete element method (DEM), and the Hertz–Mindlin with Bonding contact model was employed to characterize the heterogeneous mechanical properties between the epidermis and the core. Model accuracy was enhanced through reverse engineering and a multi-particle-size filling strategy. Key parameters were optimized via a Box–Behnken experimental design, with a core normal stiffness of 7.37 × 10¹¹ N·m⁻¹, a core shear stiffness of 9.46 × 10¹⁰ N·m⁻¹, a core shear stress of 2.52 × 10⁸ Pa, and a skin normal stiffness of 4.01 × 10⁹ N·m⁻¹. The simulated values for bending, tensile, and compressive failure forces had relative errors of less than 10% compared to experimental results. The results showed that rectangular hammers, due to their larger contact area and more uniform stress distribution, reduced the number of residual bonded contacts by 28.9% and 26.5% compared to stepped and blade-type hammers, respectively. Optimized rotational speed improved dynamic crushing efficiency by 41.3%. The material exhibited spatial heterogeneity, with the mass proportion in the tooth plate impact area reaching 43.91%, which was 23.01% higher than that in the primary hammer crushing area. The relative error between the simulation and bench test results for the crushing rate was 6.18%, and the spatial distribution consistency reached 93.6%, verifying the reliability of the DEM parameter calibration method. This study provides a theoretical basis for the structural optimization of crushing equipment, suppression of circulation layer effects, and the realization of low-energy, high-efficiency processing. Full article

Gonghe Basin is an important frontier of resource and energy development and environmental protection on the Qinghai–Tibetan Plateau and upper sections of the Yellow River. As a characteristic ecotone, this area exhibits complex and diverse ecosystem types while demonstrating marked ecological vulnerability. The response of ecosystem services (ESs) to human activities (HAs) is directly related to the sustainable construction of an ecological civilization highland and the decision-making and implementation of high-quality development. However, this response relationship is unclear in the Gonghe Basin. Based on remote sensing data, land use, meteorological, soil, and digital elevation model data, the current research determined the human activity intensity (HAI) in the Gonghe Basin by reclassifying HAs and modifying the intensity coefficient. Employing the InVEST model and bivariate spatial autocorrelation methods, the spatiotemporal evolution characteristics of HAI and ESs and responses of ESs to HAs in Gonghe Basin from 2000 to 2020 were quantitatively analyzed. The results demonstrate that: From 2000 to 2020, the HAI in the Gonghe Basin mainly reflected low-intensity HA, although the spatial range of HAI continued to expand. Single plantation and town construction activities exhibited high-intensity areas that spread along the northwest-southeast axis; composite activities such as tourism services and energy development showed medium-intensity areas of local growth, while the environmental supervision activity maintained a low-intensity wide-area distribution pattern. Over the past two decades, the four key ESs of water yield, soil conservation, carbon sequestration, and habitat quality exhibited distinct yet interconnected characteristics. From 2000 to 2020, HAs were significantly negatively correlated with ESs in Gonghe Basin. The spatial aggregation of HAs and ESs was mainly low-high and high-low, while the aggregation of HAs and individual services differed. These findings offer valuable insights for balancing and coordinating socio-economic development with resource exploitation in Gonghe Basin. Full article