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Due to the increasing population density in metropolitan areas, architects have focused on high-rise building designs that combine architectural considerations with functional requirements. The optimal design of the building shape in the case of wind interaction can be determined using the CFD evaluation method. This study uses the CFD analysis method to analyse the airflow around a new high-rise building. The first part of the paper presents a comprehensive overview of the state of the art regarding the building shapes used and the main simulation method. In the second part of the paper, the buildings model is created using dedicated CAD software. Two simulation cases are being prepared with two wind flow situations at 15 m/s velocity. In the third part of the paper, the results of CFD analysis of the buildings group model are presented. The conclusions of this evaluation are shown in the last part of the paper. [ABSTRACT FROM AUTHOR]

In this paper, the original RSEI model (including greenness index, humidity index, heat index and dryness index) and their contribution rate (%) are used to evaluate the change of ecological environment. To study how natural and anthropogenic changes in ecological environment affect ecosystem function and how these factors interact, CASA model was used to estimate the correlation between the net primary productivity of vegetation (NPP), population density and land use. This could reveal the influence factors of ecological environment change in the Wanjiang River Basin from 2000 to 2022. The results show that the combing RSEI and CASA models can effectively show the spatial-temporal variation and spatial distribution of NPP of vegetation in Wanjiang Basin. During this period, RSEI of the basin showed an overall upward trend, and the RSEI increased by about 0.1/ 10 a. The vegetation productivity in most areas was gradually improved, the ecological environment was restored, and the ecological environment quality was gradually improved. The average annual NPP simulated by CASA was 266.81 g C-m-2-a-1 The variation trend of NPP in vegetation showed a slight decrease, but the overall NPP level was basically unchanged. There is a significant correlation between NPP and population density, a negative correlation between NPP and population density areas such as city centers, and a positive correlation between NPP and population density in areas with frequent agricultural activities. From 2010 to 2020, there is a significant positive correlation between population density and land use. [ABSTRACT FROM AUTHOR]

Rapid urbanization has resulted in the substantial population growth in metropolitan areas. However, existing research on population change of the cities predominantly draws on grid statistical data at the administrative level, overlooking the intra-urban variegation of population change. Particularly, there is a lack of attention given to the spatio-temporal change of population across different urban forms and functions. This paper therefore fills in the lacuna by clarifying the spatio-temporal characteristics of population growth in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2000 to 2020 through the methods of local climate zone (LCZ) scheme and urban–rural gradients. The results showed that: (1) High population density was observed in the compact high-rise (LCZ 1) areas, with a noticeable decline along urban–rural gradients. (2) The city centers of GBA experienced the most significant population growth, while certain urban fringes and rural areas witnessed significant population shrinkage. (3) The rate of growth tended to slow down after 2010, but the uneven development of population-based urbanization was also noticeable, as urbanization and industrialization varied across different LCZ types and cities in GBA. This paper therefore contributes to a deeper understanding of population change and urbanization by clarifying their spatio-temporal contingences at landscape level. [ABSTRACT FROM AUTHOR]

This study attempts to compare the density of human expiratory droplet deposition on commonly exposed/used surfaces of an indoor residential setting by simulating the droplet exhalation using mist sprays filled with a colored medium. The simulation is not an exact replica of a human exhale but is designed to reveal the variations between surfaces. The droplets dispersed in expiratory air in an indoor environment can carry microorganisms, both bacteria and viruses, causing respiratory infections. The process involved a human actor performing predefined daily tasks and was followed around by a second actor, who mimicked breath exhalation using mist sprays. The activities included reading a magazine, watching TV, using a mobile phone, a laptop, making tea, receiving visitors, and talking to a friend. Paper surfaces were used to collect the spray pigment. The results were scanned and analyzed by a computer. The output was in the form of percentage and pixel count of colored pigment on each paper. The results showed that the most significant percentage of pigment was received on the surfaces that simulated activities performed closest to the face. The top recipient of pigment by far was the mobile phone, followed by the remote controller, laptop, keyboard, and mouse. The surfaces farthest from the face, such as the floor, received little to no detectable pigment. [ABSTRACT FROM AUTHOR]

Tracking the state of biodiversity over time is critical to successful conservation, but conventional monitoring schemes tend to be insufficient to adequately quantify how species' abundances and distributions are changing. One solution to this issue is to leverage data generated by citizen scientists, who collect vast quantities of data at temporal and spatial scales that cannot be matched by most traditional monitoring methods. However, the quality of citizen science data can vary greatly. In this paper, we develop three metrics (inventory completeness, range completeness, spatial bias) to assess the adequacy of spatial observation data. We explore the adequacy of citizen science data at the species level for Australia's terrestrial native birds and then model these metrics against a suite of seven species traits (threat status, taxonomic uniqueness, body mass, average count, range size, species density, and human population density) to identify predictors of data adequacy. We find that citizen science data adequacy for Australian birds is increasing across two of our metrics (inventory completeness and range completeness), but not spatial bias, which has worsened over time. Relationships between the three metrics and seven traits we modelled were variable, with only two traits having consistently significant relationships across the three metrics. Our results suggest that although citizen science data adequacy has generally increased over time, there are still gaps in the spatial adequacy of citizen science for monitoring many Australian birds. Despite these gaps, citizen science can play an important role in biodiversity monitoring by providing valuable baseline data that may be supplemented by information collected through other methods. We believe the metrics presented here constitute an easily applied approach to assessing the utility of citizen science datasets for biodiversity analyses, allowing researchers to identify and prioritise regions or species with lower data adequacy that will benefit most from targeted monitoring efforts. Citizen science data are increasingly being used to monitor biodiversity, but datasets produced by citizen scientists come with a number of well‐recognised challenges. In this paper, we develop several metrics to assess the adequacy of spatial observation data from citizen science projects and explore these metrics at the species level for Australia's terrestrial birds. We find that data adequacy for most Australian birds is increasing, but several gaps still remain in the spatial coverage of citizen science data across the Australian continent. [ABSTRACT FROM AUTHOR]

The study of the perceived affective qualities (PAQs) in soundscape assessments have increased in recent years, with methods varying from in-situ to laboratory. Through technological advances, virtual reality (VR) has facilitated evaluations of multiple locations in the same experiment. In this paper, VR reproductions of different urban sites were presented in an online and laboratory environment testing three locations in Greater Manchester ('Park', 'Plaza', and pedestrian 'Street') in two population densities (empty and busy) using ISO/TS 12913–2 (2018) soundscape PAQs. The studied areas had audio and video recordings prepared for 360 video and binaural audio VR reproductions. The aims were to observe population density effects within locations (Wilcoxon test) and variations between locations (Mann-Whitney U test) within methods. Population density and comparisons among locations demonstrated a significant effect on most PAQs. Results also suggested that big cities can present homogenous sounds, composing a 'blended' urban soundscape, independently of functionality. These findings can support urban design in a low-cost approach, where urban planners can test different scenarios and interventions. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) modeling has emerged as a valuable tool for investigating complex processes like microencapsulation. This paper aims to validate the ability of CFD simulations to predict particle size distribution in a polymer microencapsulation process. The CFD modeling approach employed a Eulerian multiphase framework, incorporating a discrete population balance model to track the evolution of the droplet population. A realizable k-ε turbulence model and a multiple reference frame strategy were utilized to capture the system's flow dynamics. The results reveal that while the CFD simulations align well with experimental data at higher agitation speeds (>10,000 rpm), discrepancies arise at lower speeds (<7500 rpm), indicating a challenge in accurately capturing turbulent viscous regimes. Despite these challenges, the CFD model demonstrates robust predictive capabilities for droplet formation and distribution in microencapsulation processes, validated by error margins within the acceptable limits. The validated model can be used as a reliable tool to guide experimental efforts and optimize process parameters, contributing to an enhanced understanding and control of microencapsulation processes. [ABSTRACT FROM AUTHOR]

This paper aims to investigate how social media use and gender affect beliefs in conspiracy theories on COVID-19 and how these beliefs correlate with the frequency and patterns of their use, as well as the distribution of population density in rural, town, and urban areas. I collected data from Valcon Project surveys, analyzing the usage of social media by citizens from six European countries (Italy, Germany, France, Spain, Poland, and Ireland) on issues like the origin of the COVID-19 pandemic spread. The findings, which take into consideration gender and population density, suggest that different social media platforms affected such beliefs in different ways (platform association), and this effect is also mitigated by the specific content of such conspiracy theories (content association). [ABSTRACT FROM AUTHOR]

Wetland ecosystem service function provides and maintains the Earth's life system, which supports human and social development. However, in recent years, with the intensification of human social activities, the wetland area in northeast China has been reduced, and wetland ecosystem service function has been damaged. This paper evaluates the ecosystem service function of wetlands in northeast China based on the InVEST model, taking 40 prefecture-level cities as the evaluation unit, calculating the carbon stock, soil retention, and habitat quality of the wetlands in the study area and analyzing the drivers of changes in ecosystem service function using the PLUS model. The following results were obtained: temporally, the wetland carbon stock decreased from 754 Tg in 2000 to 688 Tg in 2020; the wetland soil retention increased from 24,424 Tg in 2000 to 33,160 Tg in 2010, and then decreased to 28,765 Tg in 2020; and the quality of wetland habitats was roughly unchanged. The wetland habitats in the study area were categorized into 5 types, classified as I, II, III, IV, or V, and the spatial changes in the 40 prefecture-level cities in northeast China were analyzed. The driving factors affecting the change in the wetland ecosystem service function were further analyzed, mainly focusing on changes in the wetland area itself. The influence of other land-use types and the influence of related policies were analyzed in three aspects, among which the GDP and spatial density of the population are social factors, and the elevation and slope are natural factors that provide larger contributions to the change in wetland area. The reduction in forest and grassland areas and the increase in cultivated land and construction land areas have a negative effect on the ecosystem service function of wetlands, and the implementation of relevant wetland protection policies promotes the ecosystem service function of wetlands. According to the problems faced by wetlands in different regions, the government formulates strategies that are in line with local development, with a view to implementing wetland ecological development in the northeast region in the new context, which will help to realize intensive land use and stimulate the vitality of the region. [ABSTRACT FROM AUTHOR]

Copyright of Archives of Civil Engineering (Polish Academy of Sciences) is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper evaluates various modes of transport against the dual requirements of Net‐Zero carbon emissions and user convenience, in particular, speed of travel and cost of transportation. Results show that when operated across a whole country, battery‐powered ePlanes have the lowest energy use as measured by well‐to‐wing efficiency of other high‐speed transport systems such as the UKs HS2 and conventional diesel rail systems. This condition may not hold for extremely high passenger numbers per hour as seen in metropolitan areas with high density populations. Various proposed disruptive technologies lower cost of ownership when combined with changes in the transport paradigm that has rarely been explored in other papers. [ABSTRACT FROM AUTHOR]

Research background: Taylor rule is a widely adopted approach to follow monetary policy and investigate various mechanisms related to or triggered by monetary policy. To date, no in-depth examination of scale, determinants and spillovers of state-level monetary policy stress, stemming from the Federal Reserve Board's (Fed's) policy has been performed. Purpose of the article: This paper aims to investigate the nature of monetary policy stress on US States delivered by the single monetary policy by using a quarterly dataset spanning the years between 1989 and 2017. Methods: We apply a wide array of time series and panel regressions, such as unit root tests, co-integration tests, co-integrating FMOLS and DOLS regressions, and Spatial Panel SAR and SEM models. Findings & value added: When average stress imposed on states is calculated, it is observed that the level of stress is moderate, but the distribution across states is asymmetric. The cross-state determinants behind the average stress show that states with a higher percentage of working-age and highly educated population, as well as those with higher population density and more export-oriented are negatively stressed (i.e. they experience excessively low interest rates), whereas higher unemployment rate contributes to a positive stress (too high interest rates). To the best of our knowledge, the contribution of this paper lies in estimating monetary policy stress at the state level and unveiling some of the determinants of this stress. Moreover, the paper makes the first attempt to empirically test spatial spillovers of the stress, which are indeed found significant and negative. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of constructing a mathematical model of population density dynamics and the dynamics of forest areas damaged by spongy moth (Lymantria dispar L.) outbreaks in the United States, Europe, Russia, and Japan. The key variable of the model is either the pest population density or the area of forests damaged by spongy moths during a season. This variable can be considered proportional to the total current pest abundance in the study area. For the purposes of modeling, data from a number of different authors was used (see bibliography), as well as data from surveys conducted at the egg or caterpillar stage. The complexity of modeling the dynamics of L. dispar abundance is largely due to the fact that, when studying the dynamics of spongy moth population density, the values of external factors such as parasites, predators, and the amount of available food are often unknown. A simple model was proposed using only two types of data: population density and monthly weather characteristics. Our analysis demonstrated that, even in the absence of knowledge regarding the characteristics of ecosystem components interacting with the spongy moth population (parasites, predators, and the state of forage trees), it is possible to introduce models that characterize the regulatory processes in the population in terms of (i) the presence of negative and positive feedbacks in the system and (ii) the influence of external weather factors. The system under investigation was described as an autoregressive system, whereby the current state of the population is dependent on its state in previous years. The order of autoregression in the system was estimated using the order of the maximum significant partial autocorrelation function. It was found that the regulation of spongy moth population density was characterized by the presence of two feedback loops: positive feedback between the current population density and the population density in the previous season and negative feedback between the current population density and the population density two years ago. To evaluate the model, its stability margin was calculated and found to be directly proportional to the positive feedback coefficient and inversely proportional to the negative feedback coefficient. The model was demonstrated to explain up to 90% of the observed variance of real data. Although the model coefficients for different local populations (North America, Europe, and Asia) differ, the general form of the equation describing both direct data on population densities and indirect data on pest dynamics characterized by areas of stand damage is consistent. Consequently, the form of the ADL model is general, irrespective of the location of the local population. [ABSTRACT FROM AUTHOR]

Sporotrichosis is a mycosis with zoonotic potential caused by species of Sporothrix. Once thought rare in northeastern Brazil, the disease has recently been spreading, leading to an emergency health issue. In this paper, we describe an outbreak of feline sporotrichosis in the Seventh Health District of Maceió-AL. We collected samples from 23 domiciled and non-domiciled felines without regard for age, breed, sex, and neutering state. Skin samples were analyzed cytologically under a light microscope and seeded onto Sabouraud dextrose agar at 25 °C for from 15 to 30 days. Fifteen of the twenty-three cats with suspected skin lesions were positive for Sporothrix spp. on either cytological or microbiological evaluation. Most of the infected cats were male, young adults, non-neutered, with free access to external areas, and living in environments with poor sanitation, a high population density, and an accumulation of garbage and organic matter. Three owners were bitten or scratched by infected cats and subsequently developed suspicious cutaneous lesions suggestive of sporotrichosis. The epidemiological features of feline sporotrichosis in the outbreaks of Maceió seemed to share similarities with the data obtained from outbreaks in current hyperendemic areas. Identifying geographical sites of infection and providing compulsory notification of the disease is essential for avoiding an epidemic in Alagoas. [ABSTRACT FROM AUTHOR]

Recently, there has been an increasing effort to promote energy efficiency, using renewable energies and electric mobility to achieve a more sustainable future and even carbon neutrality by 2050. This paper aims to understand if combining these technologies leads to a win–win solution. For that, the system's characteristics that will be used for the simulation were defined as a residential community consumption scenario with and without electric vehicles charging overnight. The simulation was completed in software, and eight scenarios were tested: high population density/low population density with/without electric mobility and hourly tariff/simple tariff. After these scenarios had been tested, the conclusion was that the low population density and hourly tariff without and with electric mobility were the best two cases economically (in terms of levelized cost of energy, net present costs, and savings) and environmentally, and the worst was high population density with hourly tariff and electric mobility. Other scenarios were then tested, including changes in the load curve, namely a commercial load curve, and changes in the load curve of electric vehicle chargers, mainly daytime charging. The conclusion was that even though the initial hypothesis did not lead to a win–win solution, with changes in the hypothesis, the integration of electric mobility in energy communities might lead to that. [ABSTRACT FROM AUTHOR]

We examine a biological population model of fractional order (FBPM) in this paper using the Riccati-Bernoulli sub-ODE approach. Many scenarios in computational biology make use of this fundamental fractional model. Of particular note is that our study's FBPM uses fractional derivatives to track changes in the density populations. The study is concerned with the construction of new solitary wave solutions for the FBPM, a system of two nonlinear fractional ordinary differential equations. In this investigation, we use the conformable derivative as the fractional derivative. The Backlund transformation is the foundation of the solution process. We create a variety of families of soliton wave solutions and explain different physical behaviours that are inherent in the problems we explore. In particular, we apply the suggested methods to investigate rational, periodic, and hyperbolic solutions. The solutions found in various classes provide insightful information about the underlying physical mechanisms. To sum up, our current methods are superior instruments for analyzing different families of solutions in fractional-order issues. [ABSTRACT FROM AUTHOR]

Ecosystems are undergoing continuous degradation due to the dual perturbation of global climate change and human activities, posing unprecedented threats and challenges to the ecosystem services they provide. To gain a deeper understanding of the spatio-temporal evolution of ecosystem service value (ESV), it is essential to accurately capture the characteristics of its spatial and temporal changes and its influencing factors. However, traditional spatio-temporal statistical methods are limited to analyzing the heterogeneity of ESV in a single temporal or spatial dimension, which fails to meet the comprehensive analysis needs for spatio-temporal heterogeneity over an extended continuum. Therefore, this paper constructs a Bayesian spatio-temporal hierarchical model to analyze the ESV heterogeneity in both temporal and spatial dimensions in Northeast China from 2000 to 2020 to accurately identify the regions with unstable fluctuations in ESV and analyze the influencing factors behind them. It aims to comprehensively and systematically reveal the intrinsic laws of spatio-temporal evolution of ESV, and provide a scientific basis for relevant decision-making. The study found a continuous fluctuating downward trend of ESV in Northeast China from 2000 to 2020, with significant spatial and temporal heterogeneity. Notably, the distribution of hot and cold spots is regularly concentrated, especially in the transition zone from low hills to plains, which forms an "unstable zone" of spatial and temporal fluctuations of ESV. Natural factors such as NDVI and NPP exhibit a significant positive correlation with ESV, while social factors like population density and GDP show a strong negative correlation. Compared to traditional statistical methods, the Bayesian spatio-temporal hierarchical model, with its outstanding flexibility and accuracy, provides a new perspective and way of thinking for analyzing classical spatio-temporal problems. Firstly, the model examines time and space as a whole and fully accounts for the influence of spatio-temporal interactions on ESV. Secondly, the Bayesian spatio-temporal hierarchical model meets the needs of long-term continuous ESV outcome detection, which provides us with solid support for a deeper understanding of the evolution of ESV. [ABSTRACT FROM AUTHOR]

The catastrophic failure of two dams in Libya on 10 and 11 September 2023 resulted in the devastating flooding of the city of Derna, which is located downstream of the dams, causing more than 6000 fatalities and displacing thousands of residents. The failure was attributed to heavy rainfall from Storm Daniel, leading to the dams reaching full capacity and subsequently overflowing and failing. This paper presents an analysis of the dam break, including the modelling of flow discharge and the resulting flooding of Derna. For validation purposes, this study compares the modelled quantities with post-event satellite imagery from UNOSAT and Copernicus, local reports, and data collected from social media using AI detection. The findings provide valuable insights into the dynamics of the dam break and its initial parameters, as well as an assessment of the accuracy of the results. The analysis is performed using a rapid estimation technique developed by JRC to provide the international emergency community with a swift overview of the impact and damage assessment of potential or actual dam break events. The use of all available data shows a satisfactory comparison with the calculated quantities. The rapid modelling of dam break events and combined analysis of multiple data types are proven suitable for promptly assessing the expected dynamic of the event, as well as reconstructing the unknown initial conditions before the break. Incorporating sensitivity analyses provides an estimate of the uncertainties associated with the deduced values of the unknown parameters and their relative importance in the analysis. [ABSTRACT FROM AUTHOR]

This paper describes various selected properties and features of negative binomial (NB) random variables, with special reference to NB2 (i.e., p = 2), and some generalizations to NBp (i.e., p ≥ 2), specifications. It presents new results (e.g., the NBp moment-generating function) with regard to the relationship between a sample mean and its accompanying variance, as well as spatial statistical/econometric numerical and empirical examples, whose parameter estimators are maximum likelihood or method of moment ones. Finally, it highlights the Moran eigenvector spatial filtering methodology within the context of generalized linear modeling, demonstrating it in terms of spatial negative binomial regression. Its overall conclusion is a bolstering of important findings the literature already reports with a newly recognized empirical example of an NB3 phenomenon. [ABSTRACT FROM AUTHOR]

The authors present an analysis of the correlation between demographic and territorial indicators and greenhouse gas (GHG) emissions, emphasizing the spatial aspect using statistical methods. Particular attention is given to the application of correlation techniques, considering the spatial correlation between the involved variables, such as demographic, territorial, and environmental indicators. The demographic data include factors such as population, demographic distribution, and population density; territorial indicators include land use, particularly settlements, and road soil occupancy. The aims of this study are as follows: (1) to identify the direct relationships between these variables and emissions; (2) to evaluate the spatial dependence between geographical entities; and (3) to contribute to generating a deeper understanding of the phenomena under examination. Using spatial autocorrelation analysis, our study aims to provide a comprehensive framework of the territorial dynamics that influence the quantity of emissions. This approach can contribute to formulating more targeted environmental policies, considering the spatial nuances that characterize the relationships between demographics, territory, and GHGs. The outcome of this research is the identification of a direct formula to obtain greenhouse gas emissions from data about land use starting from the case study of Pavia Province in Italy. In the paper, the authors highlight different methodologies to compare land use and GHG emissions to select the most feasible correlation formula. The proposed procedure has been tested and can be used to promote awareness of the spatial dimension in the analysis of complex interactions between anthropogenic factors and environmental impacts. [ABSTRACT FROM AUTHOR]

While numerous studies have explored the correlation between the built environment and ride-hailing demand, few have assessed their nonlinear interplay. Utilizing ride-hailing order data and multi-source built environment data from Nanjing, China, this paper uses the machine learning method, eXtreme Gradient Boosting (XGBoost), combined with Shapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) to investigate the impact of built environment factors on ride-hailing travel demand, including their nonlinear and threshold effects. The findings reveal that dining facilities have the most significant impact, with a contribution rate of 30.75%, on predicting ride-hailing travel demand. Additionally, financial, corporate, and medical facilities also exert considerable influence. The built environment factors need to reach a certain threshold or within a certain range to maximize the impact of ride-hailing travel demand. Population density, land use mix, and distance to the subway station collectively influence ride-hailing demand. The results are helpful for TNCs to allocate network ride-hailing resources reasonably and effectively. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the characteristics and mechanisms of cultural diversity that affect foreign direct investment (FDI) using the panel data on provinces in China from 1999 to 2019 and find that, in general, cultural diversity inhibits FDI absorption. However, this kind of adverse effect has a nonlinear threshold characteristic. That is, when the population density reaches a certain level or urbanization is controlled within a certain range, the increase in cultural diversity can weaken the inhibitory effect on FDI. Additionally, by exploring the mechanisms of cultural diversity affecting FDI, we further find that cultural diversity inhibits FDI mainly through the channels of inhibiting population density and urbanization. The conclusions of this paper not only enrich the theoretical research on FDI location from the perspective of cultural diversity but also shed light on how to better attract FDI to China and other countries, such as resolving cultural conflicts and constructing an inclusive investment environment. [ABSTRACT FROM AUTHOR]

Background. In crowded crowd images, traditional detection models often have the problems of inaccurate multiscale target count and low recall rate. Methods. In order to solve the above two problems, this paper proposes an MLP-CNN model, which combined with FPN feature pyramid can fuse the feature map of low-resolution and high-resolution semantic information with less computation and can effectively solve the problem of inaccurate head count of multiscale people. MLP-CNN "mid-term" fusion model can effectively fuse the features of RGB head image and RGB-Mask image. With the help of head RGB-Mask annotation and adaptive Gaussian kernel regression, the enhanced density map can be generated, which can effectively solve the problem of low recall of head detection. Results. MLP-CNN model was applied in ShanghaiTech and UCF_ CC_ 50 and UCF-QNRF. The test results show that the error of the method proposed in this paper has been significantly improved, and the recall rate can reach 79.91%. Conclusion. MLP-CNN model not only improves the accuracy of population counting in density map regression, but also improves the detection rate of multiscale population head targets. [ABSTRACT FROM AUTHOR]

Visual impact is defined as the modification of a visual resource of the landscape, generating an effect on the perception of potential observers. This effect is evaluated using the value of the landscape that has not been altered or destroyed (visual quality of the landscape), as is the case with building projects that generate visible changes in residential areas. Numerous authors have developed methodologies to evaluate visual intrusion; however, deficiencies exist, such as the predominance of subjectivity in procedures and the lack of evaluations for buildings. Therefore, this paper proposes a methodology to evaluate and quantify the visual impact of a new building in a high population density environment. This research is divided into a description of the basic methodology, the proposal of the methodology to capture and process photographs and information, and the application of a case study of a high-rise building in a sector of Valparaíso, Chile. The main contribution of this work is the delivery of a methodological proposal that allows the evaluation and quantification of the visual quality before and after the new structure to complement structural and urban design. [ABSTRACT FROM AUTHOR]

This paper proposes a scalable learning framework to solve a system of coupled forward–backward partial differential equations (PDEs) arising from mean field games (MFGs). The MFG system incorporates a forward PDE to model the propagation of population dynamics and a backward PDE for a representative agent's optimal control. Existing work mainly focus on solving the mean field game equilibrium (MFE) of the MFG system when given fixed boundary conditions, including the initial population state and terminal cost. To obtain MFE efficiently, particularly when the initial population density and terminal cost vary, we utilize a physics-informed neural operator (PINO) to tackle the forward–backward PDEs. A learning algorithm is devised and its performance is evaluated on one application domain, which is the autonomous driving velocity control. Numerical experiments show that our method can obtain the MFE accurately when given different initial distributions of vehicles. The PINO exhibits both memory efficiency and generalization capabilities compared to physics-informed neural networks (PINNs). [ABSTRACT FROM AUTHOR]

Purpose: With the proliferation of e-commerce companies, express delivery companies must increasingly maintain the efficient expansion of their networks in accordance with growing demands and lower margins in a highly uncertain environment. This paper provides a framework for leveraging demand data to determine sustainable network expansion to fulfill the increasing needs of startups in the express delivery industry. Design/methodology/approach: While the literature points out several hub assignment methods, the authors propose an alternative spherical-clustering algorithm for densely urbanized population environments to strengthen the accuracy and robustness of current models. The authors complement this approach with straightforward mathematical optimization and simulation models to generate and test designs that effectively align environmentally sustainable solutions. Findings: To examine the effects of different degrees of demand variability, the authors analyzed this approach's performance by solving a real-world case study from an express delivery company's primary market. The authors structured a four-stage implementation framework to facilitate practitioners applying the proposed model. Originality/value: Previous investigations explored driving distances on a spherical surface for facility location. The work considers densely urbanized population and traffic data to simultaneously capture demand patterns and other road dynamics. The inclusion of different population densities and sustainability data in current models is lacking; this paper bridges this gap by posing a novel framework that increases the accuracy of spherical-clustering methods. [ABSTRACT FROM AUTHOR]

The sustainable development goals (SDGs) reflect the pursuit of achieving spatial justice. Both SDG 1.4 and SDG 11.1 reflect a concern for urban services. Life service resources, which are the new concept proposed by the Chinese government, also call for sustainable development path. However, few studies have focused on the realization of spatial justice in life service resources. This paper proposes a two-level, four-step analysis framework composed of quantity, structure, pattern, and coupling coordination to perceive the spatial justice of life service resources. Based on remote sensing technology and geographic information science, this paper acquires and analyses multi-source data including population density, building outlines, point of interests, subway lines, etc. Furthermore, the case study in downtown Beijing found the following: (1) The total life service resources are extensive and varying in type; (2) regional differences are evident and low-level equilibrium and high-level priority development coexist; (3) life service resources are concentrated in contiguous and multi-centre clusters with a greater north–south than east–west difference; (4) the overall level of life service resources is low, specifically for "high in the centre and low in the periphery" and "high in the east and low in the west". Future management should consider narrowing the development gap and formulating industry development plans to improve spatial justice. Finally, the comparison between Beijing and London and more cities in the future needs to consider the urban development stage, population density, and other aspects. [ABSTRACT FROM AUTHOR]

People's health is a necessary condition for the country's prosperity. Under the background of the COVID-19 pandemic and frequent natural disasters, exploring the spatial and temporal distribution, regional differences and convergence of China's provincial public health level is of great significance to promoting the coordinated development of China's regional public health and achieving the strategic goal of a "healthy China". Based on China's provincial panel data from 2009 to 2020, this paper constructs an evaluation index system for China's public health level from five dimensions: the popularization of a healthy life, optimization of health services, improvement of health insurance, construction of a healthy environment, and development of a health industry. In this paper, the entropy method, Dagum Gini coefficient, Kernel density function and spatial econometric model are used to analyze the spatiotemporal distribution, regional differences, dynamic evolution and convergence of China's public health level since the new medical reform. The study found that, first, China's public health level is generally low, structural contradictions are prominent and the construction of a healthy environment has become a shortcoming hindering the improvement of China's public health level since the new medical reform. The public health level of the four major regions showed a spatial distribution pattern of "high in the eastern, low in the northeastern, central and western" areas. Second, the overall Gini coefficient of China's public health level showed a "V-shaped" trend of first decreasing and then rising, but the overall decrease was greater than the increase, among which the regional difference was the main source of regional differences in China's public health level, but its contribution rate showed a downward trend. Third, except for the basic maintenance of a healthy environment, the Kernel density curves of China's public health level and its sub-dimensions have shifted to the right to a certain extent, and there is no polarization phenomenon. Finally, the level of public health in China has a significant spatial correlation. Except for the northeast region, the growth rate of low-level public health provinces in China and the other three major regions is higher than that of high-level public health provinces, showing a certain convergence trend. In addition, the impact of economic development, financial pressure, and urbanization on the convergence of public health levels in the four major regions is significantly heterogeneous. [ABSTRACT FROM AUTHOR]

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The regions near the Tropic of Cancer are a latitudinal geographical zone with typical climatic, topographic, and human landscape features. It is necessary to explore the region's net primary productivity (NPP) dynamics as it combines complex topography, various vegetation types, and intense human activities. The study sets the transect near the Tropic of Cancer (TCT) and uses the Carnegie–Ames–Stanford (CASA) model to estimate the NPP from 2000 to 2020. After using the RESTREND method, the paper calculates and compares the relative contributions of climate variability and anthropogenic activities to NPP changes. Finally, the geographical detector (Geodetector) model is applied to evaluate how anthropogenic and natural factors affect spatial distribution patterns and NPP changes. The results indicated that the average annual NPP is 820.39 gC·m−2·yr−1 during the 21 years. In addition, when the NPP varies, it increases over the entire study area, with a slope of 4.81 gC·m−2·yr−1, particularly in the western region. Across the entire research area, 63.39% and 77.44% of the total pixels positively contribute to climate variability and human activities in NPP, with a contribution of 0.90 and 3.91 gC·m−2·yr−1, respectively. Within the western, central, and eastern regions, anthropogenic activities have a stronger impact on NPP than climate variability, particularly pronounced in the eastern region. Furthermore, vegetation cover is the dominant factor in the spatial patterns and NPP trends across the TCT and the three regions. In contrast, climate factors are shown to be less influential in NPP distribution than in the western region. The results also demonstrated that the effect of population density and the GDP on NPP gradually rises. Two-factor interaction is much larger than any individual factor, with the dominant interaction factor being vegetation cover with climatic factors. Lastly, the findings revealed that anthropogenic activities positively promote NPP accumulation across the TCT, thus highlighting the importance of human activity-led ecological restoration and ecological protection measures that contribute to regional carbon sequestration and carbon balance. [ABSTRACT FROM AUTHOR]

A survey on household solid waste generation and physical composition was conducted in Hanoi City, the capital of Vietnam. The study sampled 110 households in specific areas with different population density and household scale. Household solid waste was classified into 13 main categories and 25 sub-categories. The results showed that average generation rate of waste in Hanoi City is 0.63 kg per person per day with a slightly higher rate in rural areas than urban ones. The largest proportion was food and garden waste at 78.9% followed by plastic and paper. Plastic waste was segregated into plastic and nylon, and nylon was double that of plastics in household solid waste. Compared to previous studies, this study found a higher portion of organic matter in the waste characterization that could be attributed to the changes in lifestyle patterns associated with COVID-19. This situation provides challenges and opportunities for introducing biomass technology to recover energy. [ABSTRACT FROM AUTHOR]

Water yield (WY) is an significant characteristic that reflects ecosystem services. In order to realize high-quality development, it is vital to explore the spatial and temporal (ST) distribution of WY and its driving factors in the Yiluo River Basin (YLRB) to uphold ecological stability and advance long-term sustainable growth. This paper quantifies WY in the YLRB from 2010 to 2020 using the WY model in the InVEST toolkit. Exploring ST characteristics and driving factors at both the raster and sub-watershed levels, results indicate that the overall WY (average water depth) of the YLRB in 2010, 2015, and 2020 was 26.93 × 108 m3 (136.50 mm), 22.86 × 108 m3 (113.38 mm), and 26.81 × 108 m3 (137.61 mm), respectively. The spatial pattern of watershed WY remains consistent across various periods, illustrating spatial variation in the depth of low WY in the central and western regions and high WY depth in the eastern region. At the sub-watershed level, the Luo River (LR) Basin has the highest contribution (69%) to the WY of the entire basin and served as the principal WY region of the YLRB. Conversely, the Yiluo River section, formed after the confluence of the Yi River (YR) and the LR, has the lowest WY contribution (7%) in the entire watershed. Distinct variations exist in the WY capacity among various land use (LU) types. Construction land (CSL) and unused land (UL) exhibited the highest WY capacity (315.16 mm and 241.47 mm), whereas water area (WA) had the lowest (0.01 mm). WY was significantly positively correlated with slope, precipitation, actual evapotranspiration, percentage of cultivated land, and NDVI. It showed a significant negative correlation with altitude, WA, and population density. This study helps promote the research and development of watershed ecosystem services. It also provides scientific support resolving conflicts between watershed protection and economic development and promoting harmony in the YLRB. [ABSTRACT FROM AUTHOR]

The thick-shelled river mussel, Unio crassus Philipson, 1788, is considered to be one of the species with the highest conservation priority in Serbia. The study represents the first comprehensive research of the distribution of U. crassus in Serbian waters. The research covered a variety of waterbody types throughout Serbia, and distribution data were considered over three time periods from 1953 to 2019. The paper summarizes all the available literature data, field research and information obtained during the review of the collection of malacological material of the Natural History Museum in Belgrade. The results show a positive population trend, which is reflected in an extension of the distribution area and an increase in population density. After reviewing the museum collection, 13 synonyms for U. crassus were identified. The study also revealed a better insight into the habitat requirements and the limiting factors of the species. Substrate characteristics, waterbody types, altitude, and nitrate content of the water seem to be of great importance for the occurrence of the species. The results presented here can improve further measures for the conservation of U. crassus, not only in Serbia, but also in the Western Balkans. [ABSTRACT FROM AUTHOR]

Very unhealthy air quality is consistently connected with numerous diseases. Appropriate extreme analysis and accurate predictions are in rising demand for exploring potential linked causes and for providing suggestions for the environmental agency in public policy strategy. This paper aims to model the spatial and temporal pattern of both moderate and extremely poor PM 10 concentrations (of daily mean) collected from 342 representative monitors distributed throughout mainland Spain from 2017 to 2021. We first propose and compare a series of Bayesian hierarchical generalized extreme models of annual maxima PM 10 concentrations, including both the fixed effect of altitude, temperature, precipitation, vapour pressure and population density, as well as the spatio-temporal random effect with the Stochastic Partial Differential Equation (SPDE) approach and a lag-one dynamic auto-regressive component (AR(1)). Under WAIC, DIC and other criteria, the best model is selected with good predictive ability based on the first four-year data (2017–2020) for training and the last-year data (2021) for testing. We bring the structure of the best model to establish the joint Bayesian model of annual mean and annual maxima PM 10 concentrations and provide evidence that certain predictors (precipitation, vapour pressure and population density) influence comparably while the other predictors (altitude and temperature) impact reversely in the different scaled PM 10 concentrations. The findings are applied to identify the hot-spot regions with poor air quality using excursion functions specified at the grid level. It suggests that the community of Madrid and some sites in northwestern and southern Spain are likely to be exposed to severe air pollution, simultaneously exceeding the warning risk threshold. [ABSTRACT FROM AUTHOR]

Pastoralist adaptation strategies have to address multiple, overlapping, and often inter-related processes of socio-ecological change. The present study addresses the need for inter-regional comparative studies that account for different geographic, climate, and socio-economic contexts in order to understand how pastoralists adapt to changes in livelihood conditions. The paper uses data from a unique survey study of pastoralist households in four neighbouring counties in dryland Kenya. Taking our point of departure from an empirically based classification of the livelihood strategies available to pastoralists in the Horn of Africa, the survey offers novel insights into adaptation and fodder management strategies of pastoralist individuals and households. The results show that the use of migration as a strategy is more dependent on the ability to migrate than climate conditions. This is the case in localities where a substantial part of the land is subdivided, the population density is high, and where opportunities for migration are subsequently restricted. Diversification of livelihoods as a strategy is largely defined by opportunity. Intensification through active fodder management is mainly common in areas where there has been a proliferation of managed enclosures. Climate change will test the adaptive capacity of pastoralists in the studied region, and diversification and intensification strategies of both herd composition and livelihoods can be seen as strategies for increased climate resilience. [ABSTRACT FROM AUTHOR]

Anthropogenic forcing caused the biodiversity loss and stability decline of communities. There is still controversy over whether the decline in biodiversity will lead to a decrease in community stability. The stability of biological communities is related to both biodiversity and structure, and this paper aims to reveal the human impacts on diatom communities' biodiversity and structure. We studied the richness, β‐diversity and network distance of diatom communities in Qinghai‐Xizang, Yunnan‐Sichuan and Lower Yangtze River Basin, China through empirical dataset and simulation method. The results showed that the diatoms richness in the Qinghai‐Xizang and the Yunnan‐Sichuan region was lower and the network distance was higher than that of the Lower Yangtze River Basin. β‐diversity in the Lower Yangtze River Basin was the lowest and the diatom network distance responds negatively to human population densities in China. The simulation showed that the network distance kept constant during random species loss, and declined while specialist species were lost or replaced by generalist species. The results suggested diatom communities' homogeneity and stability decline were associated with human activities. Human impacts may cause biodiversity loss targeted to specialist species or no biodiversity loss while generalist species replace those specialist species. This study showed that how diversity changes determined ecological stability depends on the type of species changes. [ABSTRACT FROM AUTHOR]

This paper analyses age-specific migration exchange between municipal formations (MFs) in Russia based on the net migration and population density data covering the period 2012–2018. Unlike many other developed countries, Russia's population concentrates in only 2–5% of the country's territory—in large cities and their suburbs. We utilise population density as an alternative measure for distinguishing between urban and rural populations (which is a formal distinction in most cases) in the urban–rural continuum. The results indicate that internal migration pattern in Russia corresponds to the urbanisation stage of the urban development model and is observed across all age groups. Net migration across all age groups is higher in more densely populated MFs. Migration to more densely populated territories peaks in the 15–19 age group and seems to have no viable alternative directions. Besides the analysis of internal migration role in the urban development patterns in Russia, the paper also contributes to a better understanding of the relationship between age-specific migration and urban development in the Russian context. [ABSTRACT FROM AUTHOR]

By employing data from Shanghai and Shenzhen A-share markets for the period of 2019–2020, this paper examines the relationship between the degree of the COVID-19 pandemic’s impact on firms’ cash-holdings levels in China. We find that firms that are severely affected by the COVID-19 pandemic have higher current cash holdings levels, suggesting that the more positive (negative) the management tone in responding to the COVID-19 pandemic impact, the lower (higher) the firm’s current cash holdings. However, future corporate cash holdings decrease considerably irrespective of the corporate sentiment towards COVID-19. The positive sentiment of each firm’s management team towards the supply chain and the government policies results in a relative reduction of current cash holdings, whereas the severe impact on operating performance, especially the impact of the outbreak on the supply chain, demand, production and operations, and government policies, reduces the firm’ s future cash holdings. In addition, the impact of the pandemic has increased the current cash holdings of state-owned enterprises and reduced the future cash holdings of non-state-owned enterprises. Meanwhile, companies located in a city with a higher density of population or companies that experience relatively higher competition in the industry tend to undergo a severer impact on their current and future cash holdings due to the COVID-19 pandemic. Overall, this study sheds the light on stimulating the vitality of enterprise investment and promoting the domestic economic cycle. [ABSTRACT FROM AUTHOR]

Study shows that COVID-19 cases, deaths and recoveries vary in macro level. Geographical phenomena may act as potential controlling factor. The present paper investigates spatial pattern of COVID-19 cases and deaths in West Bengal (WB), India and assumes Kolkata is the source region of this disease in WB. Thematic maps on COVID related issues are prepared with the help of QGIS 3.10 software. As on 15th January 2021, WB has 564032 number of COVID-19 cases which is 0.618% to the total population of the state. However, the COVID-19 case for India is 0.843% and for world is 1.341% to its total population. Lorenz Curve shows skewed distribution of the COVID-19 cases in WB. 17 (90%) districts hold 84.11% of the total population and carry 56.30% of the total COVID-19 cases. However, the remaining two districts—Kolkata and North 24 Parganas—hold remaining 43.70% COVID-19 cases. Correlation coefficient with COVID-19 cases and Population Density, Urban Population and Concrete Roof of their house are significant at 1% level of significance. [ABSTRACT FROM AUTHOR]

Overlapping coefficients (OVL) are commonly used to estimate the similarity between populations in terms of their density functions. In this paper, we consider Pianka's overlap coefficient for two exponential populations. The methods for statistical inference of Pianka's coefficient are presented. The bias and mean square error (MSE) of the maximum likelihood estimator (MLE) and the Bayes estimator of Pianka's overlap coefficient are investigated by simulation. Confidence intervals for Pianka's overlap measure are constructed. [ABSTRACT FROM AUTHOR]

In this paper, we describe a 13-year (2009–2022) dataset of legacy POP concentrations (DDTtot and sumPCB14 from 2016 isomers and congeners concentrations are also reported) in the planktonic crustaceans of Lake Maggiore (≥450 µm size fraction). The data were collected in the framework of a monitoring program finalized to assess the presence of pollutants in the lake biota, including zooplankton organisms directly preyed by fish. The data report both concentration of DDTtot and sumPCB14 in the zooplankton and the standing stock density and biomass of the population in each season. The dataset allows for detecting changes in the concentration over the long term and within a year, thus providing evidence for the seasonal and the plurennial variations in the presence of these pollutants in the lake. They also provide a basis for further studies aimed at modeling paths and the fate of persistent organic pollutants, for which the amount of toxicants stocked in the zooplankton compartment linked to fish is a crucial estimate. Dataset:  https://doi.org/10.5281/zenodo.8109373 Dataset License: CC-BY 4.0 [ABSTRACT FROM AUTHOR]

Background: Accurately predicting the future development trend of population aging is conducive to accelerating the development of the elderly care industry. This study constructed a combined optimization grey prediction model to predict the structure and density of elderly population. Methods: In this paper, a GT-FGM model is proposed, which combines Theta residual optimization with fractional-order accumulation operator. Fractional-order accumulation can effectively weaken the randomness of the original data sequence. Meanwhile, Theta residual optimization can adjust parameter by minimizing the mean absolute error. And the population statistics of Shanghai city from 2006 to 2020 were selected for prediction analysis. By comparing with the other traditional grey prediction methods, three representative error indexes (MAE, MAPE, RMSE) were conducting for error analysis. Results: Compared with the FGM model, GM (1,1) model, Verhulst model, Logistic model, SES and other classical prediction methods, the GT-FGM model shows significant forecasting advantages, and its multi-step rolling prediction accuracy is superior to other prediction methods. The results show that the elderly population density in nine districts in Shanghai will exceed 0.5 by 2030, among which Huangpu District has the highest elderly population density, reaching 0.6825. There has been a steady increase in the elderly population over the age of 60. Conclusions: The GT-FGM model can improve the prediction accuracy effectively. The elderly population in Shanghai shows a steady growth trend on the whole, and the differences between districts are obvious. The government should build a modern pension industry system according to the aging degree of the population in each region, and promote the balanced development of each region. [ABSTRACT FROM AUTHOR]

Farm tractors have become a key part of daily routine agriculture, converting complex and time-consuming tasks into tasks that are easier to perform and less dependent on human labor, contributing directly to increasing the economic value generated by this activity sector, either by increasing the productivity or by making certain agricultural crops viable, which otherwise would not be sustainable. However, despite all the advantages, accidents with this type of equipment are common, often with critical and sometimes fatal consequences. The evolution of safety requirements of these machines has occurred at a good level; however, a significant part of the agricultural tractors in use are older models that do not have such solutions. Even in the new models, which contain such solutions, these are not always correctly used, and it is even common that they are turned off or simply not used at all. It is therefore natural that accidents continue to occur, a situation that is aggravated by other factors. Lack of situational awareness of the operators, which can result from advanced age, inadequate training, reduced sensitivity/respect for safety rules, or working on irregular terrain like mountainous areas, contribute to high-risk contexts that end in the loss of human life. The consequences of such accidents are clearly aggravated by the time it takes to assist the victims—either because accidents are simply not identified/reported immediately, or by the time it takes to locate and provide help to the victims. This is a scenario that is more common in mountainous regions and regions with low population density. The current paper, using NB-IoT, a set of sensors, and a web application, presents a conceptual toolset conceived to prevent accidents and minimize consequences (human and material) that can be applied to old and new farm tractors. The development was carried out taking the characterization of the farmers and the land in the region in which the authors' research institution is located into account, which has the highest rate of fatal accidents with agricultural tractors in the country; it is a region of mountainous with a very low population density. [ABSTRACT FROM AUTHOR]