Search Results (9,714)

This study presents an analytical model to reduce the impact of wave-induced forces on a vertical seawall by introducing a floating elastic plate (EP) located at a specific distance from two bottom-standing porous structures (BSPs). The hydrodynamic interaction with the EP is described using thin plate theory, while the fluid flow through the porous medium is described by the model developed by Sollit and Cross. The resulting boundary value problem is addressed through linear potential theory combined with the eigenfunction expansion method (EEM), and model validation is achieved through consistency checks with recognized results from the literature. A comprehensive parametric analysis is performed to evaluate the influence of key system parameters such as the porosity and frictional coefficient of the BSPs, their height and width, the flexural rigidity of the EP, and the spacing between the EP and BSPs on vital hydrodynamic coefficients, including the wave force on the seawall, free surface elevation, wave reflection coefficient, and energy dissipation coefficient. The results indicate that higher frictional coefficients and higher BSP heights significantly enhance wave energy dissipation and reduce reflection, in accordance with the principle of energy conservation. Oscillatory trends observed with respect to wavenumbers in the reflection and dissipation coefficients highlight resonant interactions between the structures. Moreover, compared with a single BSP, the double BSP arrangement is more effective in minimizing the wave force on the seawall and free surface elevation in the region between the EP and the wall, even when the total volume of porous material remains unchanged. The inter-structural gap is found to play a crucial role in optimizing resonance conditions and supporting the formation of a tranquility zone. Overall, the proposed configuration demonstrates significant potential for coastal protection, offering a practical and effective solution for reducing wave loads on marine infrastructure. Full article

This study presents the development of a noise-monitoring system for the storage ring at the Siam Photon Source, designed to detect and classify noise patterns in real time using beam position monitor (BPM) data. Noise patterns were categorized into four classes: broad peak, multipeak, normal peak, and no beam. Two BPMs located at the multipole wiggler section, BPM-MPW1 and BPM-MPW2, were selected for detailed monitoring based on consistent noise trends observed across the ring. The dataset was organized in two complementary formats: two-dimensional (2D) images used for training and validating the models and one-dimensional (1D) CSV files containing the corresponding raw numerical signal data. Pre-trained deep learning and 1D convolutional neural network (CNN) models were employed to classify these patterns, achieving an overall classification accuracy of up to 99.83%. The system integrates with the EPICS control framework and archiver log data, enabling continuous data acquisition and long-term analyses. Visualization and monitoring features were developed using CS-Studio/Phoebus, providing both operators and beamline scientists with intuitive tools to track beam quality and investigate noise-related anomalies. This approach highlights the potential of combining beam diagnostics with machine learning to enhance operational stability and optimize the synchrotron radiation performance for user experiments. Full article

We propose a novel telescope concept based on Earth’s gravitational lensing effect, optimized for the detection of distant dark matter sources, particularly axion-like particles (ALPs). When a unidirectional flux of dark matter passes through Earth at sufficiently high velocity, gravitational lensing can concentrate the flux at a distant focal region in space. Our method combines this lensing effect with stimulated backward reflection (SBR), arising from ALP decays that are induced by directing a coherent electromagnetic beam toward the focal point. The aim of this work is to numerically analyze the structure of the focal region and to develop a framework for estimating the sensitivity to ALP–photon coupling via this mechanism. Numerical calculations show that, assuming an average ALP velocity of 520 km/s—as suggested by the observed stellar stream S1—the focal region extends from $9\times {10}^9$ m to $1.4\times {10}^{10}$ m, with peak density near $9.6\times {10}^9$ m. For a conservative point-like ALP source located approximately 8 kpc from the solar system, based on the S1 stream, the estimated sensitivity in the eV mass range reaches $g/M=\mathcal{O}\left({10}^{-22}\right){\mathrm{GeV}}^{-1}$. This concept thus opens a path toward a general-purpose, space-based ALP observatory that could, in principle, detect more distant sources—well beyond $\mathcal{O}\left(10\right)\mathrm{kpc}$—provided that ALP–photon coupling is sufficiently strong, that is, $M\ll M_{\mathrm{Planck}}$. Full article

A perforated aquaculture vessel represents an environmentally sustainable approach to fish farming, leveraging seawater circulation to optimize water quality and enhance fish health and growth. The perforations on the side of the fish tank significantly influence its hydrodynamic characteristics. This study investigated the influence of pore parameters on the perforated fishing tank with various pore designs, such as the asymmetric distribution of the opening in depth, windward, and leeward directions. A numerical study was conducted using STAR-CCM+ to analyze the perforated tank under beam wave conditions. This study aimed to analyze the effects of pore location, opening ratio, and asymmetric distribution on the hydrodynamic performance and flow characteristics within aquaculture tanks. The results demonstrated that an asymmetric pore distribution on the windward and leeward sides of the vessel had a notable impact on the roll motion and the flow velocity in the vicinity of the pores. The findings also indicated that the effects of pore distribution were more significant than those of opening ratio, especially regarding asymmetry. The results revealed that higher flow velocities occurred under a smaller opening ratio. Modifying pore structure parameters on the windward and leeward sides can alter the local flow field. Full article

Understanding the reproductive ecology of birds and the factors influencing nest predation is essential for developing scientifically sound and effective bird conservation strategies. Certain pheasant species sensitive to environmental changes are vulnerable to threats and face survival pressures such as habitat destruction and human activities. However, research related to their reproductive ecology is lacking. Here for the first time we reported information on breeding biology of the Chinese francolin (Francolinus pintadeanus). This study was conducted during the breeding seasons of the Chinese francolin in 2021, 2023, 2024, and 2025, combining traditional survey and infrared camera technology to monitor its reproductive ecology and nest predators in the Datian and Bangxi Reserves and to identify its potential predators through artificial nest experiments. All nests were open-ground nests located at the roots of dwarf shrubs and grasses. Our findings revealed that the breeding season of the Chinese francolin was mainly in March–September, peaking in May; its clutch size was 4.09 ± 1.27 (N = 22), reproductive success was 27.27%, and 16 nests were failed; and all failed nests were predated, with abandoned nests accounting for 93.75% of the failed nests. In artificial nest experiments, the predation rates of Datian Reserve and Bangxi Reserve were 70.91% (N = 55) and 60.00% (N = 30), respectively, with no significant difference in predation rates between the fully covered and exposed groups (Datian: χ² = 0.258, p = 0.612; Bangxi: p = 0.710). Natural nest monitoring and artificial nest experiments on the Chinese francolin identified snakes and the small Indian civet (Viverricula indica) as the main predators in Datian Reserve, as well as the greater coucal (Centropus sinensis) and wild boar (Sus scrofa) as potential predators. In contrast, the main predators in Bangxi Reserve were snakes and rodents. These findings indicate differences in nest predator taxa between the two reserves. We recommend prioritizing the restoration of dwarf scrub vegetation and optimizing the habitat management strategy in these reserves to better protect the breeding habitats of pheasants while promoting long-term stability and continuation of their populations. Full article

The growing concern about climate change and increased carbon emissions has promoted the electric vehicle market. Lithium-Ion Batteries (LIBs) are now the prevailing technology in electromobility, and large amounts will soon reach their end-of-life (EoL). Most counties have not designed sustainable reverse logistics networks to collect, remanufacture and recycle EoL electric vehicle batteries (EVBs). This study is focused on estimating the future EoL LIBs generation through dynamic material flow analysis using a three parameter Weibull distribution function under two scenarios for battery lifetime and then designing a reverse logistics network for the region of Attica (Greece), based on a generalizable modeling framework, to handle the discarded batteries up to 2040. The methodology considers three different battery handling strategies such as recycling, remanufacturing, and disposal. According to the estimated LIB waste generation in Attica, the designed network would annually manage between 5300 and 9600 tons of EoL EVBs by 2040. The optimal location for the collection and recycling centers considers fixed costs, processing costs, transportation costs, carbon emission tax and the number of EoL EVBs. The economic feasibility of the network is also examined through projected revenues from the sale of remanufactured batteries and recovered materials. The resulting discounted payback period ranges from 6.7 to 8.6 years, indicating strong financial viability. This research underscores the importance of circular economy principles and the management of EoL LIBs, which is a prerequisite for the sustainable promotion of the electric vehicle industry. Full article

To reduce the carbon emissions of existing residential buildings while pursuing maximum cost benefits, a multi-optimization design method for the existing residential building rooftops, retrofitted by attaching the solar photovoltaic panels and thermal collectors, was proposed in the study. At first, the life cycle carbon emission and cost benefit of the retrofitted buildings were assigned as the optimization objectives, and the models of carbon emission and cost benefit were developed. Furthermore, a typical existing residential community located in the cold zone of China was selected to perform the multi-optimization based on the Grasshopper platform. Meanwhile, the laying area, laying angle, and allocation ratio of the solar photovoltaic panels and thermal collectors were selected as the design parameters. And then the best retrofitting solution suitable for the existing residential buildings was proposed. The results show that the weightings of the carbon emission of retrofitting life cycle are 42.68%, and that for the cost benefit is 57.32%. Significantly, there is a 31% reduction in carbon emissions compared to the building before retrofitting, and a 24.7% reduction in cost benefit. Full article

In the context of the rapid development of e-commerce, the selection of optimal land plots for the construction of warehouse complexes that meet environmental, technical, and political requirements has become increasingly relevant. This task requires a comprehensive approach that accounts for a wide range of factors, including transportation accessibility, environmental conditions, geographic features, legal constraints, and more. Such an approach enhances the efficiency and sustainability of decision-making processes. This article presents a solution to the aforementioned problem that employs the use of land suitability maps generated by aggregating multiple evaluation criteria. These criteria represent the degree to which each land plot satisfies the requirements of various stakeholders and are expressed as suitability functions based on attribute values. Attributes describe different characteristics of the land plots and are represented as layers on a digital terrain map. The criteria and their corresponding attributes are classified as either quantitative or binary. Binary criteria are aggregated using the minimum operator, which filters out plots that violate any constraints by assigning them a suitability score of zero. Quantitative criteria are aggregated using the second-order Choquet integral, a method that accounts for interdependencies among criteria while maintaining computational simplicity. The criteria were developed based on statistical and environmental data obtained from an analysis of the Samara region in Russia. The resulting suitability maps are visualized as gradient maps, where land plots are categorized according to their degree of suitability—from completely unsuitable to highly suitable. This visual representation facilitates intuitive interpretation and comparison of different location options. These maps serve as an effective tool for planners and stakeholders, providing comprehensive and objective insights into the potential of land plots while incorporating all relevant factors. The proposed approach supports spatial analysis and land use planning by integrating mathematical modeling with modern information technologies to address pressing challenges in sustainable development. Full article

This paper is a result of the search for design assumptions for a sensor to detect oil dispersed in the sea waters (oil-in-water emulsions). Our approach is based on analyzing changes in the underwater solar radiance (L) field caused by the presence of oil droplets in the water column. This method would enable the sensor to respond to the presence of oil contaminants dispersed in the surrounding environment, even if they are not located directly at the measurement point. This study draws on both literature sources and the results of current numerical modeling of the spread of solar light in the water column to account for both downward and upward radiance (Es). The core principle of the analysis involves simulating the paths of a large number of virtual solar photons in a seawater model defined by spatially distributed Inherent Optical Properties (IOPs). The IOPs data were taken from the literature and pertain to the waters of the southern Baltic Sea. The optical properties of the oil used in the model correspond to crude oil extracted from the Baltic shelf. The obtained results were compared with previously published spectral analyses of an analogous polluted sea model, considering vertical downward radiance, vertical upward radiance, and downward and upward irradiance. It was found that the optimal wavelength ratio of 555/412, identified for these quantities, is also applicable to scalar irradiance. The findings indicate that the most effective way to determine this index is by measuring it using a sensor with its window oriented in the direction of upward-traveling light. Full article

The multi-branch horizontal well for coalbed methane (CBM) is a core technical means to achieve efficient CBM extraction, and its productivity is jointly restricted by geological and engineering factors. To accurately grasp the main controlling factors of the productivity of multi-branch horizontal wells and provide a scientific basis for the optimized design of CBM development, this study takes Well W1 in the Wenjiaba Coal Mine of the Zhina Coalfield in Guizhou, China, as an engineering example and comprehensively uses three-dimensional geological modeling and reservoir numerical simulation methods to systematically explore the key influencing factors of the productivity of multi-branch horizontal wells for CBM. This study shows that coal seam thickness, permeability, gas content, and branch borehole size are positively correlated with the productivity of multi-branch horizontal wells. With the simulation time set to 1500 days, when the coal seam thickness increases from 1.5 m to 4 m, the cumulative gas production increases by 166%; when the permeability increases from 0.2 mD to 0.8 mD, the cumulative gas production increases by 123%; when the coal seam gas content increases from 8 m³/t to 18 m³/t, the cumulative gas production increases by 543%; and when the wellbore size increases from 114.3 mm to 177.8 mm, the cumulative gas production increases by 8%. However, the impact of branch angle and spacing on productivity exhibits complex nonlinear trends: when the branch angle is in the range of 15–30°, the cumulative gas production shows an upward trend during the simulation period, while in the range of 30–75°, the cumulative gas production decreases during the simulation period; the cumulative gas production with branch spacing of 100 m and 150 m is significantly higher than that with spacing of 50 m and 200 m. Quantitative analysis through sensitivity coefficients reveals that the coal seam gas content is the most important geological influencing factor, with a sensitivity coefficient of 2.5952; a branch angle of 30° and a branch spacing of 100 m are the optimal engineering conditions for improving productivity, with sensitivity coefficients of 0.2875 and 0.273, respectively. The research results clarify the action mechanism of geological and engineering factors on the productivity of multi-branch horizontal wells for CBM, providing a theoretical basis for the optimized deployment of well locations, wellbore structure, and drilling trajectory design of multi-branch horizontal wells for CBM in areas with similar geological conditions. Full article

Environmental innovation represents a pivotal pathway toward achieving energy efficiency improvements, carbon footprint reduction, and ecological sustainability enhancement. The research investigates Chinese manufacturing enterprises listed on domestic stock exchanges throughout 2011–2023. The analytical framework utilizes count-based regression methodologies to explore how R&D investment intensity influences eco-innovation capabilities. Results demonstrate curvilinear associations linking R&D expenditure levels with both substantive and strategic environmental innovation achievements across industrial firms. This outcome successfully passed the turning-point test. Environmental oversight and financial incentives produce divergent moderating influences on innovation trajectories. Regulatory frameworks generate restrictive impacts through narrowing optimal investment ranges and dampening peak innovation outputs, whereas fiscal support mechanisms foster expansive effects via broadening resource availability and amplifying achievement levels. Cross-sectional examination uncovers substantial variations among ownership categories and geographical locations. State-owned enterprises demonstrate significantly lower optimal R&D intensity thresholds. Private firms require substantially elevated thresholds for optimal performance. Inland territories manifest unbalanced innovation dynamics. Coastal areas exhibit symmetric innovation patterns. The research enriches empirical knowledge in eco-innovation studies while offering context-specific strategic insights. The findings establish theoretical foundations and practical guidance for policy architects designing integrated environmental management systems that enhance innovation capabilities. Full article

The moving particle semi-implicit (MPS) method is employed to investigate the dynamic response of a wave energy converter (WEC) buoy subjected to dam-break flows. The buoy is connected to a hydraulic power take-off (PTO) system equipped with an accumulator, enabling it to capture wave energy. First, the MPS method is validated by comparison with experimental results, demonstrating its accuracy in simulating violent interactions between dam-break flows and the buoy. Subsequently, numerical simulations are conducted to analyze the influence of different PTO forces and buoy positions on the heave motion, fluid forces and captured power of the buoy. The results indicate that PTO force exerts a significant influence on heave motion, captured power and vertical fluid force while having a relatively minor effect on the horizontal fluid force. In addition, the maximum power that the buoy can capture increases as its distance from the wall decreases. Notably, the maximum average captured power of the buoy located near a wall can be five times higher than that of a buoy far away from the wall, indicating that a vertical wall can significantly increase the efficiency of nearshore WEC devices. These findings could provide valuable insights for the design, optimization and operation of nearshore WEC devices. Full article

Visual grounding for remote sensing (RSVG) is the task of localizing the referred object in remote sensing (RS) images by parsing free-form language descriptions. However, RSVG faces the challenge of low detection accuracy due to unbalanced multi-scale grounding capabilities, where large objects have more prominent grounding accuracy than small objects. Based on Faster R-CNN, we propose Faster R-CNN in Visual Grounding for Remote Sensing (FR-RSVG), a two-stage method for grounding RS objects. Building on this foundation, to enhance the ability to ground multi-scale objects, we propose Faster R-CNN with Adaptive Vision-Language Fusion (FR-AVLF), which introduces a layered Adaptive Vision-Language Fusion (AVLF) module. Specifically, this method can adaptively fuse deep or shallow visual features according to the input text (e.g., location-related or object characteristic descriptions), thereby optimizing semantic feature representation and improving grounding accuracy for objects of different scales. Given that RSVG is essentially an expanded form of RS object detection, and considering the knowledge the model acquired in prior RS object detection tasks, we propose Faster R-CNN with Adaptive Vision-Language Fusion Pretrained (FR-AVLF_PRE). To further enhance model performance, we propose Faster R-CNN with Cascaded Hierarchical Attention Grounding and Multi-Level Adaptive Vision-Language Fusion Pretrained (FR-CHAGAVLF_PRE), which introduces a cascaded hierarchical attention grounding mechanism, employs a more advanced language encoder, and improves upon AVLF by proposing Multi-Level AVLF, significantly improving localization accuracy in complex scenarios. Extensive experiments on the DIOR-RSVG dataset demonstrate that our model surpasses most existing advanced models. To validate the generalization capability of our model, we conducted zero-shot inference experiments on shared categories between DIOR-RSVG and both Complex Description DIOR-RSVG (DIOR-RSVG-C) and OPT-RSVG datasets, achieving performance superior to most existing models. Full article

To increase the safety and efficiency of underground mining processes, it is important to advance automation. An important part of that is to achieve autonomous material loading using load–haul–dump (LHD) machines. To be able to autonomously load material from a muck pile, it is crucial to first detect and characterize it in terms of spatial configuration and geometry. Currently, the technologies available on the market that do not require an operator at the stope are only applicable in specific mine layouts or use 2D camera images of the surroundings that can be observed from a control room for teleoperation. However, due to missing depth information, estimating distances is difficult. This work presents a novel approach to muck pile detection developed as part of the EU-funded Next Generation Carbon Neutral Pilots for Smart Intelligent Mining Systems (NEXGEN SIMS) project. It uses a stereo camera mounted on an LHD to gather three-dimensional data of the surroundings. By applying a topological algorithm, a muck pile can be located and its overall shape determined. This system can detect and segment muck piles while driving towards them at full speed. The detected position and shape of the muck pile can then be used to determine an optimal attack point for the machine. This sensor solution was then integrated into a complete system for autonomous loading with an LHD. In two different underground mines, it was tested and demonstrated that the machines were able to reliably load material without human intervention. Full article

This study investigates the spatiotemporal optimization of small-scale emergency infrastructure in high-density urban environments, using nucleic acid testing sites in Macao as a case study. The objective is to enhance emergency responsiveness during future public health crises by aligning infrastructure deployment with dynamic patterns of population influx. A behaviorally informed spatial decision-making framework is developed through the integration of kernel density estimation, point-of-interest (POI) distribution, and origin–destination (OD) path simulation based on an Ant Colony Optimization (ACO) algorithm. The results reveal pronounced temporal fluctuations in testing demand—most notably with crowd peaks occurring around 12:00 and 18:00—and highlight spatial mismatches between existing facility locations and key residential or functional clusters. The proposed approach illustrates the feasibility of coupling infrastructure layout with real-time mobility behavior and offers transferable insights for emergency planning in compact urban settings. Full article