High Population Density Research Articles

Factors affecting the number of influenza patients before and during COVID-19 pandemic, Thailand.

This study was aimed to explore the association between potential factors including public health and social measures and the number of influenza patients in Thailand between 2014-2021. Secondary data from relevant agencies were collected. Generalized Estimating Equation (GEE) and regression coefficient (β) were performed at a significance level of 0.05. We found factors associated with number of influenza patients during the time prior to COVID-19 pandemic were monthly income per household (Adjusted β = -0.02; 95% CI: -0.03, -0.01), population density (Adjusted β = 1.00; 95% CI: 0.82, 1.18), rainy season (Adjusted β = 137.15; 95% CI: 86.17, 188.13) and winter time (Adjusted β = 56.46; 95% CI: 3.21, 109.71). During the time of COVID-19 pandemic, population density (Adjusted β = 0.20; 95% CI: 0.15, 0.26), rainy season (Adjusted β = -164.23; 95% CI: -229.93, -98.52), winter time (Adjusted β = 61.06; 95% CI: 0.71, 121.41), public health control measures (prohibition of entering to into an area with high number of COVID-19 infections (Adjusted β = -169.34; 95% CI: -233.52, -105.16), and restriction of travelling also reduced the number of influenza patients (Adjusted β = -66.88; 95% CI: -125.15, -8.62) were associated with number of influenza patients. This study commends strategies in monitoring influenza patients to focus on the areas with low income, high population density, and in specific seasons. Public health and social measures which can be implemented are prohibition of entering to risk-areas (lock down), and restriction of travelling across provinces which their effectiveness in reducing influenza infections.

Enteroparasites and risk factors for infection in native and exotic domiciled birds in the North Pioneer region of Paraná State, Brazil

Although parasitic infections are common in free-ranging birds, they pose more significant threats in captivity. Free-ranging birds can live in large areas and have low exposure to parasitosis. On the other hand, birds kept in captivity, the high population density results in greater exposure, putting the animal's survival at risk. The aim of this study was to assess the occurrence of gastrointestinal endoparasites in domiciled birds (native and exotic) in the Mesoregion North Pioneer of Paraná. For this, 59 fecal samples were collected from 63 birds and analyzed by the centrifugation-flotation method in hypersaturated sucrose solution. Of the 63 birds, 38 (60%) were native, 22 (35%) exotic and 3 (5%) hybrids. Oocysts, eggs and larvae were found in 22.03% (13/59) of the samples analyzed. Higher occurrence of protozoa (20.34% - 12/59) than helminths (5.08% - 3/59) was observed, in which seven genera found: Isospora, Eimeria, Ancylostoma, Heterakis, Strongyloides, Cryptosporidium and one cestode. No endoparasites were found in the ten exotic birds and three native birds analyzed. It is concluded that the birds were infected by helminths and protozoa with a higher occurrence of coccidia, with the genus Isospora predominating. Probably due to the low sampling, there was no influence of keeping birds in individual cages compared to birds kept in collective cages, birds raised in rural or urban areas, nor of the adequacy and hygiene of drinkers and feeders, thermal comfort and hygiene of the birds' enclosures. Studies on parasites in wild birds are necessary to gain a more profound understanding of the intensity of anthropogenic influences on these animal species.

Distribution patterns and environmental risk assessments of microplastics in the lake waters and sediments from eight typical wetland parks in Changsha city, China

The quality of water in urban parks is closely related to people’s daily lives, but the pollution caused by microplastics in park water and sediments has not been comprehensively studied. Therefore, eight typical parks in the urban area of Changsha, China, were selected, and Raman spectroscopy was used to explore the spatial distributions and compositions of the microplastics in the water and sediments, analyze their influencing factors, and evaluate their environmental risks. The results showed that the abundances of surface water microplastics in all parks ranged from 150 to 525 n L−1, and the abundances of sediment microplastics ranged from 120 to 585 n kg−1. The microplastics in the surface water included polyethylene terephthalate (PET), chlorinated polyethylene (CPE), and fluororubber (FLU), while those in the sediments included polyvinyl chloride (PVC), wp-acrylate copolymer (ACR), and CPE. Regression analyses revealed significant positive correlations between human activities and the abundances of microplastics in the parks. Among them, the correlations of population, industrial discharge and domestic wastewater discharge with the abundance of microplastics in park water were the strongest. However, the correlations of car flow and tourists with the abundance of microplastics in park water were the weakest. Based on the potential ecological risk indices (PERI) classification assessment method, the levels of microplastics in the waters and sediments of the eight parks were all within the II-level risk zone (53–8,549), among which the risk indices for Meixi Lake and Yudai Lake were within the IV risk zone (1,365–8,549), which may have been caused by the high population density near the park. This study provides new insights into the characteristics of microplastics in urban park water and sediment.

Opioid and other drug use and drug-related mortality as indicators of Hepatitis C and Human Immunodeficiency Virus in Oklahoma

Objectives Outbreaks of injection drug use (IDU)-associated infections have become major public health concerns in the era of the opioid epidemic. This study aimed to (1) identify county-level characteristics associated with acute HCV infection and newly diagnosed IDU-associated HIV in Oklahoma and (2) develop a vulnerability index using these metrics. Methods This study employs a county-level ecological design to examine those diagnosed with acute or chronic HCV or newly diagnosed IDU-associated HIV. Poisson regression was used to estimate the association between indicators and the number of new infections in each county. Primary outcomes were acute HCV and newly diagnosed IDU-associated HIV. A sensitivity analysis included all HCV (acute and chronic) cases. Three models were run using variations of these outcomes. Stepwise backward Poisson regression predicted new infection rates and 95% confidence intervals for each county from the final multivariable model, which served as the metric for vulnerability scores. Results Predictors for HIV-IDU cases and acute HCV cases differed. The percentage of the county population aged 18–24 years with less than a high school education and population density were predictive of new HIV-IDU cases, whereas the percentage of the population that was male, white, Pacific Islander, two or more races, and people aged 18–24 years with less than a high school education were predictors of acute HCV infection. Counties with the highest predicted rates of HIV-IDU tended to be located in central Oklahoma and have higher population density than the counties with the highest predicted rates of acute HCV infection. Conclusions There is high variability in county-level factors predictive of new IDU-associated HIV infection and acute HCV infection, suggesting that different public health interventions need to be tailored to these two case populations.

Strategic threat health response in Australia capital cities: Predicting the optimum locations for field hospitals through geospatial analysis

AbstractObjectiveThe advent of the COVID‐19 pandemic has accentuated the critical importance of epidemic preparedness within national healthcare systems. This study presents a geospatial analysis aimed at optimising the placement of field hospitals in Australia to ensure adequate healthcare access during pandemics.MethodsThe latest census data from the Australian Bureau of Statistics were integrated with the spatial locations of current emergency departments within Australian capitals. Buffer zones with a 7.5 km radius were created around the public emergency departments (EDs). Buffer zones outside the 7.5 km radius that exhibited high population densities were categorised into high‐density (red), moderate‐density (yellow) and low‐density (green) zones to prioritise and tailor healthcare responses during a pandemic. The identification of high‐density population areas outside the ED radius enabled the stratification of potential sites for ED facilities.ResultsNinety‐one potential field hospital sites were identified across Australia's capital cities. The findings indicate that the addition of these sites would place over 95% of the population within a 7.5 km radius of an ED facility. This network of proposed sites is designed to serve a spectrum of population densities, ensuring equitable healthcare access for both densely populated urban centres and less populated areas.ConclusionsThis study underscores the potential of field hospitals to strengthen Australia's public health system against emergencies. By advocating for the creation of 91 field hospitals within a 7.5 km reach for over 95% of urban dwellers across major cities, it demonstrates a strategic approach to ensure comprehensive ED coverage. Drawing on international examples, including China's Fangcang hospitals, the USA's post‐acute care (PAC) facilities and the United Kingdom's National Health Service (NHS) Nightingale Hospitals, it highlights the need for healthcare agility and scalability, especially during pandemic outbreaks. The research presents a blueprint for field hospital deployment, marking a significant advancement in public health logistics and protection across Australia's varied demographic and geographical landscapes.

Determination of Population Dynamics of Cicadellidae (Hemiptera) Species and Their Relationship with Climatic Parameters in Organic Cotton Fields in Hatay Province, Türkiye

In this study, population dynamics of leafhopper (Hemiptera: Cicadellidae) species in organic cotton-growing areas of Hatay province were investigated along with their associations with climatic parameters. Weekly sampling using a sweep net (100 sweep net/parcel) identified nine species within the Cicadellidae family. Among these, Asymmetrasca decedens+Empoasca decipiens displayed high population densities throughout the entire vegetative phase of cotton, while Zyginidia sohrab, Psammotettix striatus, Orosius orientalis, Anaceratagallia laevis, and Anaceratagallia sinuata were present in both vegetative and reproductive phases of cotton, with Z. sohrab reaching significant population levels. Cicadulina bipunctella and Balclutha hebe were found only during the reproductive phase, yet they achieved considerably high populations. Correlation and regression analyses have shown a moderate to high level of positive correlation between the population development of five leafminer species and various temperature (°C) parameters (r=0.578-0.790, p

Small Intestinal Bacterial Overgrowth (SIBO) and Twelve Groups of Related Diseases—Current State of Knowledge

The human gut microbiota creates a complex microbial ecosystem, characterized by its high population density, wide diversity, and complex interactions. Any imbalance of the intestinal microbiome, whether qualitative or quantitative, may have serious consequences for human health, including small intestinal bacterial overgrowth (SIBO). SIBO is defined as an increase in the number of bacteria (103–105 CFU/mL), an alteration in the bacterial composition, or both in the small intestine. The PubMed, Science Direct, Web of Science, EMBASE, and Medline databases were searched for studies on SIBO and related diseases. These diseases were divided into 12 groups: (1) gastrointestinal disorders; (2) autoimmune disease; (3) cardiovascular system disease; (4) metabolic disease; (5) endocrine disorders; (6) nephrological disorders; (7) dermatological diseases; (8) neurological diseases (9); developmental disorders; (10) mental disorders; (11) genetic diseases; and (12) gastrointestinal cancer. The purpose of this comprehensive review is to present the current state of knowledge on the relationships between SIBO and these 12 disease groups, taking into account risk factors and the causal context. This review fills the evidence gap on SIBO and presents a biological–medical approach to the problem, clearly showing the groups and diseases having a proven relationship with SIBO, as well as indicating groups within which research should continue to be expanded.

Quantyfing the impact of the water security index on socio-economic development in EU27

The issue of environmental security in the context of sustainable development is a highly topical one, being intensively studied by specialists both in terms of its impact on biodiversity and on the protection of non-renewable resources, and in terms of its economic and social impact. The authors aim to quantify the impact of water security on economic and social development based on a new structural equation model and identify changes in the latent variable Water Security Index. (WSI), economic development (ED) and social development (SD) dynamics over the period 2000–2022 for the 27 EU Member States. The methodology is based on the use of structural equation systems and the use of the Independent-Samples Kruskal-Wallis Test to identify the influences of water security measures on economic and social indicators and to assess regional disparities of environmental policy development in relation to economic and social development. The research results will highlight the level of homogeneity of regional water security clusters in Europe and the influence of this approach on economic and social disparities. The results of the study highlight the significant correlation between population density, pollution levels and the costs associated with maintaining water quality. The study shows that high population density and high pollution levels disproportionately increase the financial burden of water quality management. In addition, the analysis highlights the social ramifications of neglecting the sustainability of water sources, particularly in regions experiencing low economic growth. In such scenarios, the negative social impact intensifies, highlighting the importance of sustainable practices. The results allow the formulation of the following public policies: Standardization of the national water quality management framework in line with the European framework; Establishment of organizations to monitor the safety of water sources and the health of the local population; Continuation of innovations in the field of water environment protection; Promotion of social responsibility towards the aquatic environment; Continuation of the process of improving water management governance. The results are useful for economic, environmental and social policy makers to optimise European sustainable development strategies.

A data-driven clustering approach for assessing spatiotemporal vulnerability to urban emergencies

Urban vulnerability to emergencies has become a relevant issue as cities get bigger and the negative impacts of climatic changes become more prominent. In recent years, smart city systems devoted to detecting, alerting, and mitigating emergency situations have gained momentum, with different complexities and expected outcomes. Although such systems have become more common, their proper configuration and adoption should rely on a more comprehensive perception of urban vulnerabilities to critical events. This article defines a data-driven approach to numerically evaluate the vulnerability of each region of a city, taking real-world data from open databases as a reference for a proposed clustering-based assessment algorithm. Additionally, the temporal dynamics within a city are modelled through the definition of time frames, each one comprising an associated risk assessment factor based on the expected flow of inhabitants over time. This clustering analysis categorises urban areas with similar vulnerability profiles by modelling the temporal dynamics of urban infrastructure, capturing their fluctuating nature and impact on vulnerability. By leveraging temporal urban perceptions, this approach may contribute to more effective emergency management in urban areas since regions with higher population density may be assumed as more vulnerable to emergencies, potentially supporting the optimisation of smart cities and general urban planning. Experimental results for the Portuguese cities of Porto and Lisbon demonstrate the practical applicability of the proposed approach by accurately identifying regions with higher temporal vulnerability to urban emergencies.

An approach to assess the consequence of a hypothetical radionuclide release in Singapore - a densely populated urban setting

This study is to demonstrate an approach to investigate the consequence of a hypothetical radionuclide release scenario in Singapore, a typical urban setting with high population density. To this end, we made use of MACCS 4.1, a Gaussian-based atmospheric dispersion model to compute the peak dose and the population health effects. We developed the meteorological and site files from data provided by local government agencies. Our investigation showed that the chosen scenario poses very little to negligible risk to the health of local population as the peak dose received across the country is below the radiation safety level recommended by ICRP.

A machine learning approach to evaluate coastal risks related to extreme weather events in the Veneto region (Italy)

A significant and unprecedented increase of temperature has been recorded worldwide during the last decades, leading to the occurrence of numerous extreme events. Coastal areas, with their high population density, interconnected economic activities, fragile ecosystems, are particularly vulnerable to climate change impacts. These impacts can be intensified by the interactions of multiple hazards which operate at different spatio-temporal scales and affect exposure and vulnerability patterns. An integrated approach is here proposed to assess the relationship between risk factors and to evaluate the multiplicity of impacts that may affect the coastline. A new path to tackle these multi-risk events is offered by ML algorithms to effectively handle vast amounts of heterogenous data, and model complex non-linear relationships between multiple factors and feedback mechanisms. To assess impacts caused by extreme events (storm surges, extreme precipitation, wind events) in the Veneto coastal municipalities, a ML approach was developed to understand connections between atmospheric and marine hazards and impacts recorded by the Veneto region emergency archive during the 2009–2019 timeframe, identifying the most influencing factors triggering multiple risks. Additionally, the coastal municipalities were clustered considering the intrinsic relationships between impact occurrences, exposure and vulnerability features. Several algorithms were compared to estimate daily risk of impacts to occur providing hazards, exposure and vulnerability information. The MLP algorithm showed satisfactory performances (weighted-F1-score of 0.94) to estimate the relative importance of input features. The proposed algorithm was designed as support tool to increase the understanding of impacts’ occurrence in coastal areas, thus helping the adaptation planning process.

Mapping socio-environmental vulnerability to assess rural migration in Ghana

Rural communities in Ghana, dependent on agriculture and lacking resources and infrastructure, are highly vulnerable to climate and environmental change. Internal migration is often considered as a strategy to mitigate local livelihood constraints. Understanding the challenges of rural communities requires knowledge of local conditions. As only few studies have mapped vulnerable areas in the context of migration in Ghana at a spatially explicit and nationwide level, this study provides a geodata-based examination of how rural areas in Ghana are vulnerable to multiple, co-occurring socio-economic and environmental factors influencing migration. A multifactorial and expert-based weighted overlay analysis was applied, integrating diverse data sources including climate, remote sensing, and recent census data from Ghana. Bivariate maps visualize vulnerable areas where a high impact of the factors coincides with a high rural population density. High levels of factor impact are observed in the northern regions and coastal areas of Ghana. Relatively low impact is found in more central parts of the country. The results align with current net migration rates, confirming the applicability of our method for assessing rural internal migration. This method enhances the understanding of migration dynamics in Ghana and emphasizes the role of spatial data in migration studies.

Occurrence, source apportionment and ecological risk of bisphenol analogues in river sediments in areas with different land use patterns

Bisphenol analogues (BPs) have gained increasing attention in recent years due to their ubiquitousness and potential endocrine disrupting properties in environments. However, little information is available on their spatiotemporal distribution, source apportionment and ecological risk in river sediments, especially the case in river basins with a high population density and those typical regions with agricultural-urban gradient, where land use patterns and intensity of human activity are varying. In this study, field investigations of BPs in the sediment of the entire Qinhuai River Basin, a typical agricultural-suburban agricultural-urban gradient area, were conducted before and after the flood period. Thirty-two sites were sampled for six types of BPs, resulted in no significant difference in the concentration of ΣBPs between the two periods, with ΣBPs ranging from 3.92–151 ng/g and 2.16–59.0 ng/g, respectively. Bisphenol A (BPA) was the main contributor. Whereas a multivariate analysis of variance (MANOVA) suggested that the composition structure of BPs had been influenced by water periods. The land use patterns had an impact on the distribution of ΣBPs in river sediments, which was more significant in after the flood period, with ΣBPs in urban rivers was 1.85 times, 3.44 times, and 3.08 times higher than the suburban rivers, agricultural rivers, and reservoirs, respectively. Yet land use types did not significantly alter the composition structure of BPs. The correlation analysis between BPs and the physicochemical properties of sediments showed a significant positive correlation between BPA and total organic carbon (TOC). The positive matrix factorization model (PMF) suggested that BPs in sediments of the basin might be influenced by industrial coatings, textiles, electronics and biopharmaceuticals, as well as urban wastewater or solid waste generated from daily life. The ecological risk assessment posed by BPA, based on the risk quotient, indicated that the ecological risk of BPA in sediments was low for three indicator benthic organisms: crustaceans, worms, and mollusks. However, the risk of BPA in river sediments varied among different land use patterns, with the risk ranking as follows: reservoirs < agricultural rivers < suburban rivers < urban rivers.

Sexual violence against children and adolescents in Paraná State: geospatial analysis and main socioeconomic indicators

ObjectiveChild sexual violence is a multidimensional problem of many contemporary societies, affecting people of all sexes, social stratum and age groups. Offenses involving children and adolescents are more serious, given their total or partial dependence on parents and caregivers. Information on child sexual violence in Brazil is found in raw form and without detail. The objective was to compare the information with social and economic data in the state of Paraná. MethodsThe authors conducted a retrospective study of secondary data from the Notifiable Diseases Information System (SINAN) on cases of sexual violence involving victims aged 0 to 19 years. Results are presented according to notification characteristics. The authors applied exploratory spatial data analysis to assess spatial autocorrelations and investigated relationships by the ordinary least squares regression model. ResultsBetween 2017 and 2021, there were 13,403 reports of child sexual violence in Paraná State, Brazil. Most victims (82.8%) were female and aged between 10 and 14 years. The majority of sexual violence cases (67.8%) occurred in the home environment. The highest rates on a population basis were observed in the North Central and Greater Curitiba regions, mainly in cities with higher population density and with higher rates of other types of violence. ConclusionThe results provide data that can promote a broader understanding of the distribution of sexual violence and the state and associated variations. It is expected to improve the provision of care for victims of child sexual violence and assist in strategic planning to prevent future offenses.

Associations of street-view greenspace with Parkinson’s disease hospitalizations in an open cohort of elderly US Medicare beneficiaries

IntroductionProtective associations of greenspace with Parkinson’s disease (PD) have been observed in some studies. Visual exposure to greenspace seems to be important for some of the proposed pathways underlying these associations. However, most studies use overhead-view measures (e.g., satellite imagery, land-classification data) that do not capture street-view greenspace and cannot distinguish between specific greenspace types. We aimed to evaluate associations of street-view greenspace measures with hospitalizations with a PD diagnosis code (PD-involved hospitalization). MethodsWe created an open cohort of about 45.6 million Medicare fee-for-service beneficiaries aged 65 + years living in core based statistical areas (i.e. non-rural areas) in the contiguous US (2007–2016). We obtained 350 million Google Street View images across the US and applied deep learning algorithms to identify percentages of specific greenspace features in each image, including trees, grass, and other green features (i.e., plants, flowers, fields). We assessed yearly average street-view greenspace features for each ZIP code. A Cox-equivalent re-parameterized Poisson model adjusted for potential confounders (i.e. age, race/ethnicity, socioeconomic status) was used to evaluate associations with first PD-involved hospitalization. ResultsThere were 506,899 first PD-involved hospitalizations over 254,917,192 person-years of follow-up. We found a hazard ratio (95% confidence interval) of 0.96 (0.95, 0.96) per interquartile range (IQR) increase for trees and a HR of 0.97 (0.96, 0.97) per IQR increase for other green features. In contrast, we found a HR of 1.06 (1.04, 1.07) per IQR increase for grass. Associations of trees were generally stronger for low-income (i.e. Medicaid eligible) individuals, Black individuals, and in areas with a lower median household income and a higher population density. ConclusionIncreasing exposure to trees and other green features may reduce PD-involved hospitalizations, while increasing exposure to grass may increase hospitalizations. The protective associations may be stronger for marginalized individuals and individuals living in densely populated areas.

Regulation of photoassimilate transportation and nitrogen uptake to decrease greenhouse gas emissions in ratooning rice with higher economic return by optimized nitrogen supplies

Mechanized harvesting of the main crop rice, with low stubble height in rice ratooning is scaling up, especially in Southeast China with a higher population density and less cultivated land. Currently, the common nitrogen fertilization for ratoon rice is concentrated within 20 days before and after the harvest of the main crop. However, this fertilization pattern may not be suitable for low stubble regenerative rice due to its extended growth period, leading to diminished nitrogen utilization efficiency and heightened greenhouse gas emissions, particularly nitrous oxide (N2O) emissions. It is imperative to explore a nitrogen fertilizer management model for clean production of low stubble ratoon rice (RR). In this study, we examined the effects of nitrogen fertilizer application rates and methods (single or split application) on yield and greenhouse gas emissions during the regrowth season. We employed a multi-criteria assessment approach combined with field measurements, energy analysis, environmental assessment, and economic evaluation on ratoon rice under various nitrogen fertilizer treatments. The results showed that the ratoon rice produced the highest total energy output under 67.5N+22.5N (Fertilize with 67.5kg nitrogen ha-1 and 22.5kg nitrogen ha-1 3 days after main season rice harvesting and during the heading stage of ratoon rice) treatment compared to the 90N+0N (conventional fertilization, apply 90kg nitrogen ha-1 fertilizer 3 days after harvesting at once) treatment. It was also found that reducing nitrogen application during the tillering stage reduced CH4 emissions, fertilization during the heading stage of the ratoon rice did not increase CH4 emissions, Since fertilization during the heading stage of ratoon rice did not lead to an increase in the partitioning of photoassimilates (photosynthetic product assimilates) to the rhizosphere soil, significant differences in sugar and acetic acid levels were not observed in the rhizosphere soil. As a result, no change was found in the expression of the methanogenic mcrA gene in the microbial community. The study also demonstrated that the 67.5N+22.5N treatment was able to promote the absorption of nitrogen nutrients, reduction in N2O emissions by 16.61%, subsequently increasing resource use efficiency, final yield and net ecosystem economic benefit by 5.96%, 7.19% and 5.57%, respectively, thereby decreasing carbon and nitrogen footprints by 6.64% and 3.50% compared with the 90N+0N treatment in the ratoon rice. These results suggest that a reasonable ratoon rice cultivation scheme is a promising farming system that can simultaneously improve resource use efficiency and economic profits, reduce greenhouse gas emissions and environmental footprint, while still maintaining the high productivity in ratoon rice.

Lion lords and sharing hyaenas: Carnivore guild dynamics around elephant carcasses.

Megaherbivore carcasses represent sporadic but energetically rewarding resources for carnivores, offering a unique opportunity to study coexistence dynamics between facultative scavengers. South African fenced protected areas, such as Madikwe Game Reserve (Madikwe hereafter), host viable populations of large carnivores and high densities of elephants, Loxodonta africana. However, high carnivore densities can lead to potentially fatal interspecific encounters and increased competition, particularly around high-quality trophic resources. This study explores the temporal partitioning and co-detection strategies of carnivores at six elephant carcasses in Madikwe, aiming to understand how the increased carrion biomass available at elephant carcasses influences coexistence dynamics. Camera traps were deployed to monitor carcasses during two periods (2019 and 2020), revealing occurrences of six carnivore species. Carnivores, particularly black-backed jackals, Lupulella mesomelas, (hereafter jackal), lions, Panthera leo, and spotted hyaenas, Crocuta crocuta, comprised 56.7% of carcass observations, highlighting their pivotal roles in scavenging dynamics. Pairwise co-detection analysis demonstrated consistent association and shared peak activity periods between jackals and spotted hyaenas, indicating potential resource sharing. However, the minimal co-detection rates between lions and other carnivores highlight their resource domination. There was some evidence of temporal partitioning between carnivores, with most species exhibiting earlier peaks in nocturnal activity to avoid temporal overlap with lions. This study emphasises the importance of elephant carcasses in the diet of multiple species and coexistence techniques utilised to exploit this ephemeral resource. As fenced protected areas become crucial for conserving intact carnivore guilds globally, further research into carnivore behavioural adaptations at carcasses is recommended to shed light on their coexistence strategies.

Evaluation of water use impacts caused by real estate development with gentrification traits in the metropolitan area of San Luis Potosí

Water resource management is a technical, social, and political issue worldwide. Water, being a public good, is characterized as follows: “Unlike private goods, public goods are indivisible and cannot be satisfactorily met by the market or other private initiatives. The provision of public goods requires cooperation or coercion, either through collective action or effective government.” In this sense, water is a human right, as stated by the UN in its sixth sustainable development goal, which aims to “ensure availability and sustainable management of water and sanitation for all.” Gradually, housing in the city of San Luis Potosí has shifted from being affordable for the entire population to becoming increasingly unattainable. Due to the growing demand for housing driven by common population growth and urban development, in recent years, vertical construction-both residential and commercial-has been implemented as a potential solution to this phenomenon, now accounting for 10% of constructions in this area in the capital city, according to the Registro Único de la Vivienda as of 2023. However, such constructions have brought new challenges to urbanization in San Luis Potosí city. As noted by Lozano Niño Y., areas, where high-socioeconomic-status apartment buildings with gentrification features proliferate, were not planned to support high population densities. Eventually, one of the possible consequences of high densification in these areas will be the inadequacy of basic services such as water. While vertical housing offers an alternative to maximize land use within the urban sprawl and could address housing demands, there is also a need to improve public services and urban infrastructure in the surrounding areas where these constructions are planned to prevent social inequality in terms of public service distribution. This study aims to analyze the relationship between case studies—buildings with gentrification features-and their impact on the use and distribution of potable water among the inhabitants of the urban sprawl of San Luis Potosí, by using geospatial methods and technologies.

Population density effects on gamete traits and fertilisation dynamics under varying sperm environments in mussels.

Gamete traits can vary widely among species, populations and individuals, influencing fertilisation dynamics and overall reproductive fitness. Sexual selection can play an important role in determining the evolution of gamete traits with local environmental conditions determining the strength and direction of sexual selection. Here, we test for signatures of post-mating selection on gamete traits in relation to population density, and possible interactive effects of population density and sperm concentration on sperm motility and fertilisation rates among natural populations of mussels. Our study shows that males from high-density populations produce smaller sperm compared with males from low-density populations, but we detected no effect of population density on egg size. Our results also reveal that females from low-density populations tended to exhibit lower fertilisation rates across a range of sperm concentrations, although this became less important as sperm concentration increased. Variances in fertilisation success were higher for females than males and the effect of gamete compatibility between males and females increases as sperm concentrations increase. These results suggest that local population density can influence gamete traits and fertilisation dynamics but also highlight the importance of phenotypic plasticity in governing sperm-egg interactions in a highly dynamic selective environment.

A macroscopic safety indicator for road segment: application of entropy theory

Road traffic safety is confronted with unique challenges worldwide due to the varied road network, high population density, and the rapid increase in vehicle numbers. This necessitates an effective evaluation of traffic safety at the road segment level to improve traffic safety management. Existing safety indicators, such as crash frequency (which lacks real-time availability) and Surrogate Safety Measures (focused on micro-level interactions), fall short in quantifying the overall safety status of road segments. To overcome these limitations, we introduce the concept of entropy, typically used to measure disorder in complex systems, into road traffic safety assessment. Our research presents a novel macroscopic safety indicator named ‘velocity entropy,’ along with its calculation method, which involves discretization and the Parzen window technique. The efficacy of velocity entropy is validated using the UTE dataset, a high-fidelity trajectory dataset from China, showing a more significant correlation with traffic conflicts than other macroscopic traffic properties. Notably, velocity entropy can track the temporal and spatial evolution of traffic safety, providing insights into the dynamic development of traffic risks. Overall, velocity entropy offers an innovative, practical, and theoretically meaningful tool for assessing and predicting road safety.