Search Results (3,452)

Abstract: Buildings, as key factors influencing population distribution, have various functional attributes. Existing research mainly focuses on the relationship between land functions and population distribution at the macro scale, while neglecting the finer-grained, micro-scale impact of building functionality on population distribution. To address this issue, this study integrates multi-source geospatial and spatio-temporal big data and employs the XGBoost algorithm to classify buildings into five functional categories: residential, commercial, industrial, public service, and landscape. The proposed model innovatively incorporates texture, geometric, and temporal features of building images, as well as socio-economic characteristics extracted using the distance decay algorithm. The results yield the following conclusions: (1) The proposed method achieves an overall classification accuracy of 0.77, which is 0.12 higher than that of the random forest-based approach. (2) The introduction of time features and the distance decay method further improved the model performance, increasing the accuracy by 0.04 and 0.03, respectively. (3) The correlation between the building functions and population distribution varies significantly across different scales. At the district and county levels, residential, commercial, and industrial buildings show a strong correlation with population distribution, whereas this correlation is relatively weak at the street scale. This study advances the understanding of building functions and their role in shaping population distribution, providing a robust framework for urban planning and population modeling. Full article

Urban blue-green space cooling island effect (BGCI) is effective in improving the thermal comfort of residents. However, there is little knowledge regarding the diurnal variation of BGCIs and the influencing factors. Therefore, we selected Beijing as the study area and used ECOSTRESS LST data and the inflection–maximum perspective method to explore the diurnal variation of BGCIs. Additionally, we investigated diurnal variations in the relative influence of the characteristics of the blue-green space itself, as well as the surrounding 2D and 3D landscape metrics using boosted regression tree model. The results indicated that BGCIs displayed distinct diurnal patterns. BGCIs progressively increased from sunrise to midday, decreased thereafter to sunset, reached its peak around midday, and diminished to a relatively low level and constant intensity at night. BGCIs of water bodies exhibited a significantly higher intensity compared to vegetation during the day, particularly around midday, with a difference in mean cooling intensity (CI) of 1.06 °C and mean cooling distance (CD) of 63.27 m, while the differences were minimal at night with a difference in mean CI of 0.02 °C and mean CD of 9.64 m. The features of vegetation had a more significant impact on BGCIs during the day, particularly around midday (CI: 32.30% around midday and 13.86% at night), while the 3D metrics influenced BGCIs more at night (CI: 26.40% around midday and 35.81% at night). The features of water bodies had a greater impact during the midday (52.87% around midday and 10.46% at night), with the landscape metrics of surrounding water bodies playing a more important role at night (15.56% around midday and 38.28% at night). The effect of tree height, shape index of vegetation, and surrounding building coverage ratio of water bodies on BGCIs exhibited opposite trends around midday and at night. Optimizing the landscape surrounding blue-green spaces is more cost-effective than the blue-green spaces themselves for nighttime thermal comfort, especially in 3D urban landscapes. These findings emphasize the imperative and essentiality of exploring diurnal variations in BGCIs, providing valuable information for mitigating UHI effects. Full article

A myriad of diverse factors affect the contemporary business environment and all business areas, causing organisations to innovate new business models, or to use innovations to navigate the complexity of contemporary HRM practice successfully. Despite the plenitude of notable studies, a particular theoretical gap exists regarding the innovation’s impact on particular HRM practices and on understanding how multiple-criteria decision-making (MCDM) methods can be effectively applied in the context of human resource management (HRM) to address important aspects of successful practices and prioritise the considered alternative solutions. Recognising the potential of the MCDM field highlighted the possibility of involving the MCDM methods in detecting the most influential and innovative HRM practices and defining the rank of companies that are most successful in applying them. The innovative MCDM approach proposed here utilises the CRITIC (CRiteria Importance Through Intercriteria Correlation) method and PIPRECIA-S (Simple PIvot Pairwise RElative Criteria Importance Assessment) method for prioritising innovative HRM practices, and the COBRA (COmprehensive Distance Based RAnking) method for assessing the companies under evaluation. The research, which involved 21 respondent experts from the HRM field and 12 companies from the Republic of Serbia, revealed that employee participation is the most significant innovative HRM practice that yields the best results in the contemporary business environment. Consequently, the first-ranked company most successfully met the requirements of the innovative HRM practices presented. Full article

The 3D modeling of transmission towers currently depends on manual operations, resulting in high labor and time costs. To this end, an automatic 3D modeling technique based on 2D drawings is proposed. Using this method, the 2D drawings of transmission towers were analyzed first, then a 3D model of a tower was reconstructed using a counter-to-detail strategy. The analysis of the 2D drawings aimed to segment the geometric shapes and subsequently extract the vectors. All obtained vectors were classified into outer contour vectors and internal structure vectors. For each tower section, the 3D outer contour framework was constructed first using the wireframe model algorithm, followed by the assembly of internal details onto the 3D contour framework to fully reconstruct the 3D model. Experiments demonstrated that constructed 3D models exhibited high accuracy, with an average chamfer distance to the real scanned dense LiDAR point clouds of less than 0.05 m, which was less than 1% relative to the whole size of the created models. Furthermore, the automation of this technique implies its potential for various applications. Full article

The integration of robotics in the garment industry remains relatively limited, primarily due to the challenges in the highly deformable nature of garments. The objective of this study is thus to explore a vision-based garment recognition and environment reconstruction model to facilitate the application of robots in garment processing. Object SLAM (Simultaneous Localization and Mapping) was employed as the core methodology for real-time mapping and tracking. To enable garment detection and reconstruction, two datasets were created: a 2D garment image dataset for instance segmentation model training and a synthetic 3D mesh garment dataset to enhance the DeepSDF (Signed Distance Function) model for generative garment reconstruction. In addition to garment detection, the SLAM system was extended to identify and reconstruct environmental planes, using the CAPE (Cylinder and Plane Extraction) model. The implementation was tested using an Intel Realsense^® camera, demonstrating the feasibility of simultaneous garment and plane detection and reconstruction. This study shows improved performance in garment recognition with the 2D instance segmentation models and an enhanced understanding of garment shapes and structures with the DeepSDF model. The integration of CAPE plane detection with SLAM allows for more robust environment reconstruction that is capable of handling multiple objects. The implementation and evaluation of the system highlight its potential for enhancing automation and efficiency in the garment processing industry. Full article

We propose a multi-sensor fusion localization framework for autonomous heavy-duty trucks suitable for mining scenarios, which enables high-precision, real-time trajectory generation, and map construction. The motion estimated through pre-integration of the inertial measurement unit (IMU) can eliminate distortions in the point cloud and provide an initial guess for LiDAR odometry optimization. The point cloud information obtained from LiDAR can assist in recovering depth information from image features extracted by the monocular camera. To ensure real-time performance, we introduce an iKD-tree to organize the point cloud data. To address issues arising from bumpy road segments and long-distance driving in practical mining scenarios, we can incorporate a large number of relative and absolute measurements from different sources, such as GPS information and AprilTag-assisted localization data, including loop closure, as factors in the system. The proposed method has been extensively evaluated on public datasets and self-collected datasets from mining sites. Full article

In order to reduce CO₂ emissions from industrial processes, countries have commenced the vigorous development of CCUS (carbon capture, utilization and storage) technology. The high geographical overlap between China’s extensive coal mining regions and CO₂-emitting industrial parks provides an opportunity for the more efficient reduction in CO₂ emissions through the development of Enhanced Coal Bed Methane (ECBM) Recovery for use with CCUS technology. Furthermore, the high geographical overlap and proximity of these regions allows for a shift in the transportation mode from pipelines to tanker trucks, which are more cost-effective and logistically advantageous. The issue of transportation must also be considered in order to more accurately assess the constructed cost function and CCUS source–sink matching model for the implementation of ECBM. The constructed model, when considered in conjunction with the actual situation in Shanxi Province, enables the matching of emission sources and sequestration sinks in the province to be realized through the use of ArcGIS 10.8 software, and the actual transport routes are derived as a result. After analyzing the matching results, it is found that the transportation cost accounts for a relatively small proportion of the total cost. In fact, the CH₄ price has a larger impact on the total cost, and a high replacement ratio is not conducive to profitability. When the proportion of CO₂ replacing CH₄ increases from 1 to 3, the price of CH₄ needs to increase from $214.41/t to $643.23/t for sales to be profitable. In addition, electric vehicle transportation costs are lower compared to those of fuel and LNG vehicles, especially for high-mileage and frequent-use scenarios. In order to reduce the total cost, it is recommended to set aside the limitation of transportation distance when matching sources and sinks. Full article

Additive manufacturing (AM) has brought new possibilities to the moulding industry, particularly regarding the use of high-performance materials as maraging steels. This work explores 18Ni300 maraging steel reinforced with 4.5 vol.% TiC nanoparticles, fabricated by Selective Laser Melting (SLM), addressing the effect of post-fabrication aging treatment on both thermal and mechanical properties. Design of Experiments (DoE) was used to generate twenty-five experimental groups, in which laser power, scanning speed, and hatch distance were varied across five levels, with the aim of generating conclusions on optimal fabrication conditions. A comprehensive analysis was performed, starting with the nanocomposite feedstock and then involving the microstructural, mechanical, and thermal characterisation of SLM-fabricated nanocomposites. Nanocomposite relative density varied between 92.84% and 99.73%, and the presence of martensite, austenite, and TiC was confirmed in the as-built and heat-treated conditions. Results demonstrated a hardness of 411 HV for the as-built 18Ni300-TiC nanocomposite, higher than that of the non-reinforced steel, and this was further increased by performing aging treatment, achieving a hardness of 673 HV. Thermal conductivity results showed an improvement from ~12 W/m·K to ~19 W/m·K for nano-TiC-reinforced 18Ni300 when comparing values before and after heat treatment, respectively. Results showed that the addition of TiC nanoparticles to 18Ni300 maraging steel led to a combined thermal and mechanical performance suited for applications in which heat extraction is required, as in injection moulding. Full article

This paper presents a streamlined approach to describing potential habitats for red deer (Cervus elaphus) in situations where in situ data collected through observations and monitoring are absent or insufficient. The main objectives of this study were as follows: (a) to minimize the negative effects of limited in situ data; (b) to identify landscape features with a functional relationship between habitat quality and landscape structure; and (c) to use imprecise in situ data for statistical analyses to specify these relationships. The test area was located in the eastern part of Mecklenburg-Western Pomeriania (Germany). For this area, remotely sensed forest maps were used to determine landscape metrics as independent variables. Dichotomous habitat suitability was determined based on hunting distances over a five-year period. Ecological and biological habitat requirements of red deer were derived from suitable landscape measures, which served as model inputs. Correlation analysis identified the most relevant independent landscape metrics. Logistic regression then tested various metric combinations at both class and landscape levels to assess habitat suitability. Within the model variants, the contagion index, edge density, and percentage of forested area showed the largest relative impact on habitat suitability. The approach can also be applied to other mammals, provided there are appropriate structural preferences and empirical data on habitat suitability. Full article

Due to the dynamic development of energy generation in photovoltaic installations, a reliable assessment of their impact on the level of energy losses in distribution networks is needed. For energy companies managing network resources, this issue has a very tangible practical aspect. Therefore, ongoing analyses of the level of electricity losses based on actual measurement data of prosumers are needed. In the paper, the influence of energy introduced by prosumer photovoltaic installations on energy losses in a low-voltage radial line is investigated. The issue is examined from three perspectives: 1. Focused on energy supplied into the low-voltage grid from photovoltaic installations; 2. the installations’ locations; and 3. the product of energy and distance from the power source. Comparative assessments are made of the examined aspects for 87 possible locations of prosumer installations in the tested low-voltage network. An analysis of energy losses is carried out both for the entire analysed network and separately for the line and the transformer. The changes in energy losses are influenced by both the power and the location of the photovoltaic installations. Based on the research findings, functions defining relative changes in energy losses in the low-voltage network are determined. Full article

Achalinu ningshanensis (Yang, Huang, Jiang, Burbrink, and Huang, 2022) was first described in Ningshan County, Shaanxi Province, China in 2022, based on seven female specimens. In this study, based on phylogenetic analyses using mitochondrial 12S ribosomal RNA (12S), 16S ribosomal RNA (16S), cytochrome c oxidase subunit 1 (CO1), cytochrome b (cyt b) gene fragments, and morphological examinations of specimens, we revise the taxonomic status of A. ningshanensis, and provide additional data on this species. The molecular phylogeny indicated that A. ningshanensis is nested in a highly supported monophyletic group, forming a sister taxon to A. spinalis, and is divided into two well-supported lineages, A and B, with an uncorrected p-distance between lineages from 3.6 to 4.3% for CO1. Therefore, we proposed that Lineage B from western Sichuan and southwestern Shaanxi is a new subspecies, Achalinus ningshanensis occidentalis ssp. nov., and Lineage A from southern Shaanxi and northeastern Sichuan is allocated as Achalinus ningshanensis ningshanensis. Morphologically, the new subspecies can be distinguished from its congeners, especially from Achalinus ningshanensis ningshanensis, by the following characteristics: (1) the tail is relatively short, with a TAL/TL ratio of 0.202–0.226 in males, and 0.155–0.178 in females; (2) there are two pairs of chin-shields; (3) there are 21–22 maxillary teeth; (4) the length of the suture between internasals is significantly shorter than that between prefrontals, with an LSBI/LSBP ratio of 0.502–0.773; (5) there are six supralabials, with the fourth and fifth in contact with the eye; (6) there are five to six infralabials, and the first to third or fourth touches the first pair of chin-shields; (7) there is one hexagonal loreal, with an LorH/LorL ratio of 0.612–1.040; (8) the two anterior temporals are in contact with the eye; (9) there are 155–160 ventrals in males, and 165–174 in females; (10) there are 60–65 subcaudals in males, and 49–53 in females, which are not paired; and (11) the dorsum is iridescent and uniformly charcoal black, lacks a longitudinal vertebral line, and has a dark brown or dark gray ventral area. Full article

Sports performance initiation is of significant interest in sports sciences, particularly in beach volleyball (BV), where players usually combine indoor and BV disciplines in the formative stages. This research aimed to apply an electronic performance tracking system to quantify the physical-conditional performance of young male BV players during competition, considering age group (U15 or U19), sport specialisation (indoor or beach) and the set outcome (winner or loser). Thirty-two young male players, categorised by age and sport specialisation, were analysed during 40 matches using electronic performance tracking systems (Wimu PRO^TM). Data collected were the set duration, total and relative distances covered, and number and maximum values in acceleration and deceleration actions. U19 players and BV specialists, compared to their younger and indoor counterparts, covered more distance (719.25 m/set vs. 597.85 m/set; 719.25 m/set vs. 613.15 m/set) and exhibited higher intensity in terms of maximum values in acceleration (4.09 m/s² vs. 3.45 m/s²; 3.99 m/s² vs. 3.65 m/s²) and deceleration (−5.05 m/s² vs. −4.41 m/s²). More accelerations (557.50 n/set vs. 584.50 n/set) and decelerations (561.50 n/set vs. 589.00 n/set) were found in indoor players. Additionally, no significant differences were found in variables regarding the set outcome. These findings suggest that both age and specialisation play crucial roles in determining a great physical-conditional performance in young players, displaying a higher volume and intensity in external load metrics, whereas indoor players seem to need more accelerations and decelerations in a BV adaptation context. These insights highlight the age development and sport specialisation in young volleyball and BV athletes. Full article

The aim of this study was to determine the frequency–temperature dependence of the AC conductivity and relaxation times in humid electrical pressboard used in the insulation of power transformers, impregnated with the innovative NYTRO^® BIO 300X bio-oil produced from plant raw materials. Tests were carried out for a composite of cellulose–bio-oil–water nanodroplets with a moisture content of 0.6% by weight to 5% by weight in the frequency range from 10⁻⁴ Hz to 5·10³ Hz. The measurement temperatures ranged from 20 °C to 70 °C. The current conductivity in percolation channels in cellulose–bio insulating oil–water nanodroplets nanocomposites was analyzed. In such nanocomposites, DC conduction takes place via electron tunneling between the potential wells formed by the water nanodroplets. It was found that the value of the percolation channel resistance is lowest in the case of a regular arrangement of the nanodroplets. As disorder increases, characterized by an increase in the standard deviation value, the percolation channel resistance increases. It was found that the experimental values of the activation energy of the conductivity and the relaxation time of the composite of cellulose–bio-oil–water nanodroplets are the same within the limits of uncertainty and do not depend on the moisture content. The value of the generalized activation energy is ΔE ≈ (1.026 ± 0.0160) eV and is constant over the frequency and temperature ranges investigated. This study shows that in the lowest frequency region, the conductivity value does not depend on frequency. As the frequency increases further, the relaxation time decreases; so, the effect of moisture on the conductivity value decreases. The dependence of the DC conductivity on the moisture content was determined. For low moisture contents, the DC conductivity is practically constant. With a further increase in water content, there is a sharp increase in DC conductivity. Such curves are characteristic of the dependence of the DC conductivity of composites and nanocomposites on the content of the conducting phase. A percolation threshold value of x_c ≈ (1.4 ± 0.3)% by weight was determined from the intersection of flat and steeply sloping sections. The frequency dependence of the values of the relative relaxation times was determined for composites with moisture contents from 0.6% by weight to 5% by weight for a measurement temperature of 60 °C. The highest relative values of the relaxation time τ_ref occur for direct current and for the lowest frequencies close to 10⁻⁴ Hz. As the frequency increases further, the relaxation time decreases. The derivatives d(logτ_ref)/d(logf) were calculated, from the analysis of which it was determined that there are three stages of relaxation time decrease in the nanocomposites studied. The first occurs in the frequency region from 10⁻⁴ Hz to about 3·10⁻¹ Hz, and the second from about 3·10⁻¹ Hz to about 1.5·10¹ Hz. The beginning of the third stage is at a frequency of about 1.5·10¹ Hz. The end of this stage is above the upper range of the Frequency Domain Spectroscopy (FDS) meter, which is 5·10³ Hz. It has been established that the nanodroplets are in the cellulose and not in the bio-oil. The occurrence of three stages on the frequency dependence of the relaxation time can be explained when the fibrous structure of the cellulose is taken into account. Nanodroplets, found in micelles, microfibrils and in the fibers of which cellulose is composed, can have varying distances between nanodroplets, determined by the dimensions of these cellulose components. Full article

High-flying insects that exploit tropospheric winds can disperse over far greater distances in a single generation than species restricted to below-canopy flight. However, the ecological consequences of such long-range dispersal remain poorly understood. For example, high-altitude dispersal may facilitate more rapid range shifts in these species and reduce their sensitivity to habitat fragmentation, in contrast to low-flying insects that rely more on terrestrial patch networks. Previous studies have primarily used surface-level variables with limited spatial coverage to explore dispersal timing and movement. In this study, we introduce a novel application of niche modelling to insect aeroecology by examining the relationship between a comprehensive set of atmospheric conditions and high-flying insect activity in the troposphere, as detected by weather surveillance radars (WSRs). We reveal correlations between large-scale dispersal events and atmospheric conditions, identifying key variables that influence dispersal behaviour. By incorporating high-altitude atmospheric conditions into niche models, we achieve significantly higher predictive accuracy compared with models based solely on surface-level conditions. Key predictive factors include the proportion of arable land, altitude, temperature, and relative humidity. Full article

The visual morphology of trees significantly impacts urban green micro-landscape aesthetics. Proximity to tall buildings affects tree form due to competition for space and light. The study investigates the impact of tall buildings on six visually morphological traits of eight common ornamental species in urban micro-landscapes in Beijing, with the distance and direction between trees and buildings as variables. It found that as trees grow closer to buildings, most angiosperms show increased crown asymmetry degree and crown loss, and reduced crown round degree and crown stretch degree (i.e., Sophora japonica L. and Acer truncatum Bunge saw a 52.26% and 47.62% increase in crown asymmetry degree, and a 20.35% and 21.59% decrease in crown round degree, respectively). However, the pattern of crown morphological changes in gymnosperms is poor (the closer the distance, the lower the height-to-diameter ratio of Pinus tabuliformis Carr., while the height-to-diameter ratio of Juniperus chinensis Roxb. significantly increases). In terms of orientation, gymnosperms on the west side of buildings have a greater crown asymmetry degree. It suggests that planting positions relative to buildings affect tree morphology. Recommendations include planting J. chinensis closer to buildings but keeping angiosperms like Fraxinus velutina Torr., S. japonica, and A. truncatum more than 3 m away to ensure healthy crown development. Full article