Space Distribution Research Articles

Examining Residents’ Perceptions and Usage Preferences of Urban Public Green Spaces Through the Lens of Environmental Justice

Improving the equity of urban public green space is crucial for residents’ well-being and is a key objective in green space planning. While most existing studies focus primarily on the spatial distribution characteristics of green space resources, fewer explore the mechanisms influencing residents’ subjective perceptions and preferences. This study, based on a survey of 1419 residents in Hunan Province, constructs a structural equation model (SEM) to investigate the impact of the unequal distribution of urban public green space on residents’ happiness, mediated by social–psychological factors such as environmental perception, sense of security, and neighborhood cohesion. Additionally, a random forest (RF) algorithm is employed to identify the main factors influencing residents’ green space usage preferences. The results demonstrate that equity in green space distribution significantly influences residents’ happiness through environmental perception (path coefficient γ = 0.744, p = 0.001), security (γ = 0.664, p = 0.001), and neighborhood cohesion (γ = 0.830, p = 0.001). Key factors influencing residents’ preferences for green space use include age, housing prices, and walkability, with walkability contributing 17.5%, green space equity contributing 11.0%, and age contributing 10.2% to the frequency of green space use. These findings are critical for developing fairer and more effective urban green space policies, contributing to the creation of a more sustainable, equitable, and satisfying urban environment.

Spatial Distribution and Quality Status of Open Green Spaces and Parks in Calabar Metropolitan Area, Cross River State, Nigeria

Urban green areas are often seen in highly developed countries as urban green lungs because of their ability to mediate between man and nature. However, it is not the case in developing countries, where the means of subsistence are considered pivotal and paramount to human existential status. The study examined spatial distribution of open green spaces and parks in the study area and determined differences in their quality. Data for the study were obtained from both primary and secondary sources. A total of 400 copies of the questionnaire were issued to the respondents. Low-level analysis was done using non-parametric statistics, while a hypothesis was tested using Chi-Square parametric/inferential statistics. The result shows that there are significant differences in urban green areas quality at (χ2 =588.680, p<0.05) and accessibility (χ2 = 942.200, p<0.05) in Calabar Metropolis. Further, a Global Positioning System (GPS) device was used to acquire the coordinates of the green spaces and parks in order to delineate them spatially. Geographic Information systems (GIS) infrastructure was used to visualize the spatial distribution of open green spaces and parks in the area. The result is presented in the map output. It was therefore recommended that the destruction of the flora components of the urban green spaces and parks associated with obtaining wood fuel for energy should be discouraged. Finally, the quality of the open green spaces and parks should be improved through the provision of signposts, walkways, tracks, hiking paths, and cycling routes.

Parameter estimation of high-altitude electromagnetic pulse based on physics and data co-supervised neural network

In this paper, we propose what we believe to be a novel physics and data co-supervised neural network (PaDCoSNN) for estimating the mathematical parameters of a double exponential function based on the physical parameters—rise time and pulse width—of high-altitude electromagnetic pulse (HEMP). Two key structural innovations improve the neural network’s estimation accuracy and generalization ability. First, the input (physical parameters) and output (mathematical parameters) layers are structured to reflect their numerical characteristics. Second, nonlinear equations that interpret the relationship between the physical and mathematical parameters are embedded into the loss function to supervise the neural network’s learning process. Additionally, a dual-scale probabilistic sampling strategy is proposed to address the issue that uniform sampling in the output space (traditional practice) will result in extremely uneven sample distribution in the input space, thereby generating more representative training samples. Comparative experiments, using 100 sparse training samples and 10000 test samples, demonstrate that PaDCoSNN reduces relative errors by an order of magnitude compared with conventional artificial neural networks (ANNs), with processing times remaining under 1.5 seconds. On out-of-scope test samples, PaDCoSNN demonstrates strong generalization, maintaining relative errors below 0.00001, compared to conventional ANNs, which reach up to 1.7. Moreover, PaDCoSNN has the potential to estimate parameters without sample-based training.

(Un)just Distribution of Visible Green Spaces? A Socio-Economic Window View Analysis on Residential Buildings: The City of Cologne as Case Study

As urbanization processes, climate disasters such as heat waves, or pandemics such as COVID-19, increase, prioritizing visible green space is crucial to provide equitable access to green spaces for vulnerable groups with limited mobility. In the long term, this will enable sustainable and resilient urban development. In this study, we examined green window views in residential buildings to identify patterns of distributive equity for seniors and children, considering their socioeconomic status for the first time. We combined the methodology around the BGWVI and the methodological framework by Huang et al. (Urban Forestry & Urban Greening 95: 128,313:1–128,313:12, 2024) to measure the visibility potential of green spaces for approximately 160,000 residential buildings in order to geostatistically analyze the equity of the spatial distribution of visible urban green spaces. Using the Gini coefficient, the share index, and the location entropy, an evaluation of the access to visible green spaces according to socio-economic status and age group was carried out at the district level for the City of Cologne, Germany. The results show that children and the elderly have slightly higher percentages of visible green space than the social mean percentage. In addition, the influence of the mean net household income on visual green spaces is low. These findings underscore the importance of visibility as an access alternative in urban green space planning for an equitable and resilient urban environment.

Microscale investigation of bentonite distribution in pore spaces of sand after infiltration of stabilising solution

In the earth drilling method, which is an example of construction of structural foundations, the ground is excavated using a stabilising solution composed mainly of bentonite, and the trench walls are stabilized by an impermeable mud film formed on the trench walls. Microscopically, the mud film is supposed to be formed when bentonite in the stabilising solution occludes the pores, but this has never been experimentally verified. To elucidate the mechanism of mud film formation, a test apparatus of stabilising solution infiltration that can be applied to X-ray micro CT was developed, and the soil particle structure before and after infiltration of the stabilising solution is visualised. An image analysis algorithm was developed to investigate spatial and volumetric distribution of bentonite inside the sand. As results, the formation of a uniformly continuous mud film was successfully visualised in three dimensions. Furthermore, it was found that bentonite occluded many pores in the sand, and that the higher the infiltration pressure, the larger the volume of bentonite was spatially distributed. Under low infiltration pressure, small volumes of bentonite distribute over a wider area along the infiltration direction.

Experimental study on smoke temperature distribution and thermal-driven propagation in groove-like spaces under different fan arrangements

Experimental study on smoke temperature distribution and thermal-driven propagation in groove-like spaces under different fan arrangements

A Theoretical Model for Optimizing Signalized Intersection and Roundabout Distance Using Microsimulations

Traffic congestion in urban areas is a pressing challenge, with roundabouts and signalized intersections offering different operational benefits. This study explores the integration of these two intersection types, focusing on the optimal distance between them to ensure efficient traffic flow. Using traffic microsimulations in VISSIM, the research examines multiple scenarios involving isolated roundabouts and those adjacent to signalized intersections, considering variables such as peak-hour traffic volume, flow distribution, and intersection spacing. Results indicate that shorter distances (<50 m) between roundabouts and signalized intersections lead to increased traffic indicators due to congestion spillback. In contrast, distances exceeding 100 m mitigate these inefficiencies, approaching the performance of isolated roundabouts. Balanced traffic distribution between approaches (50:50) enhance system performance at lower volumes but exacerbate congestion at higher volumes. A novel aspect of this study is the development of a regression model that integrates microsimulation outputs to predict travel time based on peak-hour traffic volume, flow ratios, and intersection distance, demonstrating a 90.9% explanatory power. These findings emphasize the need for strategic planning in integrating roundabouts and signalized intersections to balance operational efficiency.

Using Approximate Bayesian Computation to Calibrate the Model Parameters Characterizing the Autoregulatory Behavior of Microvessels.

This study aims to leverage available experimental data on the myogenic and endothelial responses of the microvessels to calibrate the parameters and refine the functional form of the compliance feedback model. The experimental data used in this study trace the changes in the vessel calibre of individual arteriolar vessels in response to changes in the intraluminal pressure and/or the pressure gradient, which correspond to the myogenic and endothelial mechanisms, respectively. The compliance feedback model was previously developed to characterize the elastic and autoregulatory behavior of microvessels. We devise and employ a two-stage sequential Monte Carlo (MC) approximate Bayesian computation (ABC) scheme to obtain the posterior distribution of the model's parameters, such that the final parameter space distribution integrates information from any prior knowledge of the parameters, the model dynamics, and the available experimental data. Furthermore, the calibration scheme provides key insights into the underlying mechanistic features of the dynamical system; namely, the ABC scheme reveals that there is a marked difference in the time constants between the myogenic-induced dilation and constriction. Overall, upon parameter calibration, the computationally low-cost compliance feedback model achieves very good agreement with the experimental measurements, despite limited data availability, demonstrating that the model provides a simple, compact, yet robust and physiologically grounded characterization of the autoregulatory response, all of which are essential attributes to increase the translatability of hemodynamic models into the clinical environment for future clinical applications.

Unsupervised tooth segmentation from three dimensional scans of the dental arch using domain adaptation of synthetic data.

The automated segmentation of individual teeth from 3D models of the human dental arch is challenging due to variations in tooth alignment, arch form and overall maxillofacial anatomy. Domain adaptation is a specialised technique in deep learning which allows models to adapt to data from different domains, such as varying tooth and dental arch forms, without requiring human annotations. This study aimed to segment individual teeth from various dental arch morphologies in 3D intraoral scans using domain adaptation. Twenty scanned dental arches from various age groups and developmental stages were used to generate 20 simplified synthetic variants of the scans. These synthetic variants, along with 16 natural scanned dental arches, were used to train the deep learning models. Domain adaptation was employed using Gradient Reversal Layer and Siamese Network techniques. The PointNet and PointNet++ model backbones were trained to align the latent space distribution of real and synthetic domains. Validations were performed on four unseen natural scanned arches, with and without domain adaptation enabled, to evaluate whether a 3D deep neural network can be trained without any human-annotated 3D models. PointNet and PointNet++ models demonstrated a mean intersection-over-union between 0.34 and 0.36 mIoU without domain adaptation enabled and 0.80 and 0.95 mIoU, respectively with domain adaptation enabled when assessing natural scanned dental arches. Domain adaptation techniques can enable training a segmentation deep learning model using synthetically generated 3D jaw scans without requiring human operators annotating the training data.

ESDA: Zero-shot semantic segmentation based on an embedding semantic space distribution adjustment strategy

ESDA: Zero-shot semantic segmentation based on an embedding semantic space distribution adjustment strategy

A study on the spatial characteristics and spatial heterogeneity of influencing factors in the tourist market of coastal scenic area: taking Wanpingkou scenic area in Rizhao City as an example

ABSTRACT Fully understanding the spatial characteristics of the tourist market and deeply analyzing the influencing factors are important theoretical references for targeted attraction of tourists and tourism industry promotion. By analyzing the tourist market structure, distribution characteristics, and the spatial heterogeneity of the influencing factors in the Wanpingkou Scenic Area of Rizhao City during the peak summer season of 2023, the results showed that the tourist market of the scenic area was relatively scattered and the attraction range was relatively small. It showed a hierarchical distribution in space, and it was divided into three levels. Tourists from 47 core layer cities accounted for 85.8% of total tourists, most of which were distributed within the Shandong province, neighbouring provincial cities, or more distant developed cities. Additionally, the influencing factors and effects of the tourism market exhibited spatial heterogeneity at different levels, and the interaction effect between factors enhanced the explanatory power. Leisure time (X11) had the highest interactive effect variation ratio (IEVR) in the whole region and middle layer. The maximum interaction factor in the core layer and the edge layer was the distance from the coastline (X9). The research aims to provide a theoretical basis for differentiated positioning and collaborative development of scenic areas.

Patterns of mercury concentration in annual tree rings in Siberia (Russia) and the Republic of Vietnam

Relevance. The method of dendrogeochemistry makes it possible to determine the concentration of chemical elements in tree rings. As part of this work, a spatio-temporal reconstruction of mercury pollution of local and regional origin was carried out Aim. Determination of the characteristics of the Hg distribution in space and over a long time in order to identify the main factors affecting Hg accumulation by annual rings of pine, as well as the establishment and clarification of patterns in Hg accumulation in each study area. The object of the study is the core of Scots pine (Pinus syvestris L.) (Tomsk, Irkutsk regions, Republic of Buryatia) and dalat pine (Pinus dalatensis Ferré) (Socialist Republic of Vietnam). Methods. Ten cores were selected for the study in the years range from 1930 to 2022. The sampling was carried out using the Haglof age drill. The number and width of annual rings are determined with an accuracy of 0.001 mm on the LINTAB device at the Institute of Monitoring of Climatic and Ecological Systems SB RAS (Tomsk). Mercury analysis was conducted on the mercury analyzer RA-915+ by atomic absorption (pyrolysis method) on the basis of the Engineering School of Natural Resources of Tomsk Polytechnic University. Results and conclusions. The accumulation of Hg by the wood of Scots pine and Dalate pine in the studied territories is affected by natural and anthropogenic factors: natural emanations of Hg due to the degassing of the Earth's crust (Irkutsk Region and the Republic of Buryatia); local technogenesis (Tomsk Region), as well as military actions using chemical weapons (Republic of Vietnam). The study assessed the dynamics of Hg accumulation by wood over 93 years (1930–2021/2023). In the period from 1930 to the end of the 1960s there is an increased average content of the element in all the studied territories. The increased concentrations of Hg in this period on the territory of the Republic of Vietnam related to the transboundary transport of mercury from the continental part of East Asia, as well as chemical weapons used during the wars; on the territory of Russia – the growth of industrial production during the Great Patriotic War and the post-war reconstruction of the country, as well as seismicity and geological conditions.

Spatial prioritization of urban green open space development using weighted overlay analysis

Background: Urban areas are ecosystems where plants, animals, humans, and infrastructure interact. Green open spaces (RTH) like parks are vital in cities for facilitating this interaction. However, rapid urbanization and limited land often lead to the conversion of green spaces into built-up areas, which increases urban temperatures, disrupts ecosystems, and lowers the quality of life for city dwellers. The allocation of RTH development is often not aligned with the community's actual needs. This study aims to determine the priority locations for RTH development in Mataram City using the Weighted Overlay method in the ArcGIS application. Method: This study employs a qualitative approach using spatial analysis through the Weighted Overlay method in ArcGIS. Three key variables are considered: the comfort index (THI), vegetation density (NDVI), and population density. The data from these variables are combined to assess and prioritize areas in Mataram City for RTH development. Findings: The analysis shows that the sub-districts of Mataram and Cakranegara have the highest priority for RTH development, based on the combined analysis of comfort index, vegetation density, and population density. These areas require more green space to improve environmental quality and meet the community’s needs. Conclusion: The study highlights the importance of prioritizing RTH development in Mataram and Cakranegara sub-districts. It suggests that urban planning policies in Mataram City should focus on these areas to enhance urban living conditions and mitigate environmental degradation caused by limited green spaces. Novelty/Originality of this article: This research is unique in applying the Weighted Overlay method in ArcGIS to evaluate and prioritize RTH locations based on multiple urban variables. It provides valuable insights for urban planners, offering a data-driven approach to address the challenges of green space distribution in urban environments.

Design of an Aperiodic Optical Phased Array Based on the Multi-Strategy Enhanced Particle Swarm Optimization Algorithm

We have proposed a multi-strategy enhanced particle swarm optimization (PSO) algorithm to optimize the antenna spacing distribution of an optical phased array (OPA). The global search capability is improved by incorporating circle chaotic mapping initialization and an updated strategy based on adaptive inertia weights and dynamic learning factors. We used the peak side-lobe level (PSLL) at different steering angles as the fitness function, which effectively suppresses the rapid degradation of PSLL during scanning. Based on this approach, 32- and 64-channel aperiodic OPAs were designed with a scanning range of ±60°, with improvements of the PSLL of 1.94 and 2.05 dB at 60°, respectively. In addition, the analytical and numerical simulation results are in good agreement. We also analyzed the influence of spacing deviations on PSLL and found that the obtained OPAs exhibit sufficient robustness.

Particle swarm optimization algorithm-based strategy for three-dimensional warehouse cargo space distribution

In recent years, the logistics and warehousing industry has expanded rapidly, and storage efficiency has become a key factor. Optimization of warehouse space layout has become a strategic focus to enhance competitiveness. The mathematical model established using particle swarm optimization (PSO) algorithm comprehensively considers the access efficiency, shelf stability and cargo type correlation. The experimental results show that the optimized cargo layout is more reasonable, the similar goods are more concentrated, and the access efficiency is significantly improved, thus effectively enhancing the operational efficiency and enterprise competitiveness of the three-dimensional warehouse.

Predictable inventory management within dairy supply chain operations

PurposeWith the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC managementDesign/methodology/approachPreferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.FindingsAs a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.Practical implicationsMany sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.Originality/valueThis paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

Large diversity in the O-chain biosynthetic cluster within populations of Pelagibacterales.

Genomic diversity in prokaryotic species is largely due to the existence of extensive pangenomes, allowing different gene complements to be drawn depending on the strain. Here, we have studied the diversity of the O-chain polysaccharide biosynthesis cluster (OBC) in marine bacteria of the Pelagibacterales order as a proxy to measure such genetic diversity in a single population. The study of single-amplified genomes (SAGs) from the whole order found a pattern similar to that of other well-studied microbes, such as the Enterobacteriales or Alteromonas, where distinct OBCs represent strains containing different gene pools. We found that most of the OBC sharing happened among individuals of the same clonal frame (>99% average nucleotide identity). Moreover, given the parsimonious way this cluster changes, the diversity of the OBCs can be extrapolated to the size of the population's pangenome. This assumes that different OBCs correspond to lineages containing unique flexible gene pools, as seen in the aforementioned microbes. Through long-read metagenomics, we could detect 380 different OBCs at a single Mediterranean sampling site. Within a single population (single species and sample) of the endemic Ia.3/VII (gMED) genomospecies, we identified 158 OBCs, of which 130 were unique. These findings suggest that the gene pool within a single population might be substantial (several thousands). While this figure is large, it aligns with the complexity of the dissolved organic matter that these organisms can potentially degrade.IMPORTANCEDifferent strains of the same bacterial species contain very different gene pools. This has been long known by epidemiologists. However, it is unknown what gene pool is present in a single set of environmental conditions, i.e., the same time and place in free-living bacteria. Here, we have leveraged information from SAGs to analyze the diversity of the gene cluster coding for the O-chain polysaccharide, a typical component of the flexible gene pool classically used as a tool to differentiate strains in clinical microbiology. It evolves at a similar rate to the rest of the genome and does not seem to be affected by an arms race with phages. One single species of Pelagibacteriales (gMED) revealed an astounding diversity in one sample studied by long-read metagenomics. Our results point to a large gene pool (local pangenome) present in a single population, which is critical to interpreting the biological meaning of the pangenome, i.e., it provides intrapopulation diversity rather than characterizing strains with different distribution in time and/or space.

Latitudinal gradient patterns and driving factors of the fruit types of woody plants based on multiple forest dynamic monitoring plots

Abstract Fruit type influences seed dispersal mode and its effectiveness, reflecting plant adaptability to their environments. However, the large-scale patterns of fruit type distribution in forest communities and differences in the drivers of various fruit types remain unclear. We present a large-scale biogeographic model of woody plant fruit types along a latitudinal gradient through the data analysis of 30 forest dynamic plots. Results showed the following. (1) Fleshy and dry fruits exhibited distinct distribution patterns in large-scale space. The distribution of fleshy fruits was greater in tropical and subtropical zones, while dry fruits were more common in temperate zones. (2) Climatic factors primarily drove the geographical distribution of the fruit types of woody plants. Climatic and spatial factors exerted greater effects on the species richness of dry fruits compared with that of fleshy fruits. Our results demonstrated the difference in the latitudinal gradient patterns of fleshy and dry fruits and identified the major abiotic environmental factors that drove their distribution in large-scale spaces, demonstrating the biogeography of the fruit types of woody plants.

Tight Focusing Holographic Network Enables 3D Real Time and Accurate Light Field Modulation

AbstractPhase‐only computer‐generated holography (CGH) is an effective technique to manipulate 3D light field distribution in the tight focusing volume for numerous applications in micro/nano‐manufacturing, optical tweezers, and optical communication. Unfortunately, hologram computation is slow and generally takes several seconds or longer for a single instance, which hinders broad applications in real time light modulation. Here, fast hologram computation is reported with the calculation time for a single instance down to 3.7 ms. A depth‐adaptive 3D tight‐focusing holographic network framework driven by a vectorial diffraction model is developed. The network adequately considers the tight‐focusing property and the spherical aberration effect in high NA objectives and employs a layer‐based learning strategy to reinforce the global constraints on reconstructed 3D focusing fields. This network enables the generation of high‐quality holographic phases in real time and facilitates large‐scale computations of focused fields with arbitrary spatial, intensity, and axial spacing distributions with high speed and high accuracy (up to 0.93). The proposed network is deployed in ultrafast laser direct writing and microscale fluorescence display applications, which indicates that the current 3D tight‐focusing field modulation technique will play a vital role in broad optical and photonic engineering.

Environmental and health effects of the Barcelona superblocks

BackgroundThe superblocks model of Barcelona (Spain) seeks to reorganize the city based on reversing the distribution of public space between vehicles and people by prioritizing citizens, thus improving their environmental conditions and quality of life. The objective of this paper was to describe the effects on environmental, health and quality of life of the first three superblocks implemented, discuss the lessons learned, and provide recommendations for the future.MethodsThe evaluation included different approaches depending on the superblock analyzed: A pre-post-intervention health survey, environmental measures of air quality, the Microscale Audit of Urban Landscapes for Pedestrians (MAPS), an observational study on target areas of physical activity (SOPARC), ethnographic guerrilla studies, and focus groups.ResultsResidents and workers in all three of the evaluated superblocks reported a perceived improvement in well-being, tranquillity and quality of sleep, some reduction in noise and pollution and an increase in social interaction. The built environment of the superblocks clearly influenced walkability, and the lower car traffic volume improved air quality measures. In one of the superblocks, the same intervention calmed traffic in one of the areas but not in another.ConclusionsAlthough on a small scale, this evaluation of the environmental, and health effects of the superblocks provides support for expanding the model to other areas of the city.