Population Distribution Research Articles

Temporal trends in muscular fitness among French children and adolescents between 1999 and 2023

ABSTRACT The aim was to estimate national temporal trends in muscular fitness for French youth between 1999 and 2023. Data were obtained from five cross-sectional studies on 53,314 children and adolescents (age range: 6–16 years). Lower- and upper-body strength were assessed by standing broad jump (SBJ) and handgrip strength (HGS). BMI z-scores (BMIz) were calculated using WHO growth curves. We found a statistically significant negligible decline in SBJ performance (standardised effect size (ES) trend per decade [95%CI]: −0.08 [−0.10, −0.07] or −2.1 cm [95%CI: −2.4, −1.8]) and a statistically significant negligible improvement in HGS (ES trend per decade [95%CI]: 0.11 [0.08, 0.13]) or 0.6 kg [(95%CI: 0.4, 0.8]). We found evidence of significant increases in distributional variability and asymmetry, with poorer trends in the low performers (<25th percentile) and better trends in the high performers (>75th percentile) compared to the average performers. Our data suggest negligible trends in mean SBJ and HGS, coupled with increased distributional variability and asymmetry. Trends were not uniform across the population distribution with data suggesting an increase over time in the gap between low and high performers. These results reinforce the importance of interventions and programmes aiming at improving muscular fitness specifically in children and adolescents with low muscular strength.

Evolution of population distribution and its influencing factors in the poverty-stricken mountainous region of Southwest China from 2000 to 2020

Understanding the characteristics and determinants of population distribution is essential for formulating effective policies and strategies, especially in the poverty-stricken mountainous regions. This study investigates the characteristics, evolution (2000–2020), and influencing factors of population distribution in the Liangshan Yi ethnic region, a representative poverty-stricken mountainous region in Southwest China. The results reveal that: (1) Over the past two decades, the spatial pattern of population distribution has remained stable. However, the balance of population distribution has improved, as indicated by the decreasing size of the standard deviation ellipse, reflecting a more even population spread. (2) The population distribution demonstrates significant clustering in town centers, with strong positive correlations, as reflected in Moran’s I index values of 0.732, 0.708, 0.620, 0.556, and 0.554 for the years 2000, 2005, 2010, 2015, and 2020, respectively. (3) The vertical zonation pattern and the differentiation characteristics in slope and aspect play a significant role in population distribution. Over time, these factors have played an increasingly significant role in shaping the evolution of population distribution. The interaction between natural factors and vegetation is pivotal in the spatiotemporal patterns of population distribution. These factors have directly and indirectly contributed to the persistence of poverty in these mountainous areas by limiting accessibility, resource availability, and economic opportunities. The study’s results provide valuable insights for enhancing population distribution strategies in impoverished mountainous regions and informing policy-making.

Global stability and asymptotic profiles of a partially degenerate reaction diffusion Cholera model with asymptomatic individuals

Abstract Considering the prevalence of asymptomatic individuals during the spread of disease, this article develops a model of degenerate reaction diffusion Cholera with asymptomatic individuals. First, the well-posedness of model is studied, including the global existence of solutions and the existence of attractor. Second, the basic reproduction number ℛ 0 {{\mathcal{ {\mathcal R} }}}_{0} is defined to determine whether the disease is vanishing or persistent. In particular, we also analyze the asymptotic behavior of the endemic steady state when the diffusion rate of susceptible or asymptomatic individuals tends to 0 or infinity. Finally, by fitting the theoretical results with some numerical simulations, we find that the spatial distribution of disease and local epidemic risk are less affected by the mobility of susceptible populations, whereas the mobility of asymptomatic or symptomatic populations significantly affects the spatial and temporal distribution of infected populations. In addition, we found that the proportion of asymptomatic individuals to infected individuals is also a key factor in disease epidemics, and how to quickly diagnose asymptomatic individuals for disease control and prevention should be of a particular concern.

Automated age grading of female Culex pipiens by an optical sensor system coupled to a mosquito trap

BackgroundThe age distribution of a mosquito population is a major determinant of its vectorial capacity. To contribute to disease transmission, a competent mosquito vector, carrying a pathogen, must live longer than the extrinsic incubation period of that pathogen to enable transmission to a new host. As such, determining the age of female mosquitoes is of significant interest for vector-borne diseases surveillance and control programs.MethodsIn this contribution, an automated age-grading system was developed to classify the age of female Culex pipiens, which is the primary vector of West Nile virus and other pathogens of medical and veterinary importance in northern latitudes. The system comprises an optical wingbeat sensor coupled to the entrance of a mosquito trap and a machine learning model. Three age classes were used in the study: young (2–4 days), middle (7–9 days) and old (14–16 days). From a balanced dataset of flight data, four features were extracted: wingbeat fundamental frequency, spectrogram, power spectral density and Mel frequency cepstral coefficients. The features were used for training with the XGBoost algorithm to generate a model for age classification.ResultsThe best performing model was trained with the power spectral density feature on two age classes, ≤ 4 days old and ≥ 7 days old, and had an accuracy of 71.8%.ConclusionsAn automated mosquito age-grading system was applied for the first time to our knowledge for automated age classification in mosquitoes; and complements the mosquito genus and sex classification capability of the system reported in our previous work. The system may find use in mosquito-borne disease surveillance and control to help to discriminate young mosquitoes (≤ 4 days old) from older mosquitoes, which may act as vectors of arboviruses.Graphical

A mathematical model for population distribution II: Linear systems

The present paper constitutes a continuation of a previous relevant paper, entitled “A mathematical model for population distribution” by Elias (2023), in which the general theoretical model was described, and some initial applications were presented, namely some approximations of population distribution of a one-dimensional inertial system and a special case of one-dimensional dynamic system. Herein, by using the above model, the following issues will be addressed: a) the examination of multidimensional linear systems, both inertial and dynamic, facilitating the study of polycentric cities and systems of multiple cities (metropolitan areas) and b) the variation of the population distribution due to the geographical diversifications of the habitat of the system, as in a sloped terrain or of coastal cities. For each of the above cases, their behaviour is presented by producing and analysing the corresponding equations of motion and distribution and, whenever possible, an effort has been made to qualitatively compare the theoretical results to field data.

Diet and seasonal distribution of piranha populations in the São Miguel River, Rondônia, Brazil

This study analyzed the spatial and seasonal distribution of piranha species and their respective diets. Samples were collected monthly from August 2020 to July 2021 using various types of fishing gear in different sections of the river. Limnological data were also analyzed to assess correlations with the distribution of piranha species. A total of 326 fish were identified, encompassing nine species and three genera. The most abundant species were Serrasalmus rhombeus (N = 155), Pygocentrus nattereri (N = 89), and Serrasalmus spilopleura (N = 23), which were found in the headwaters, intermediate section and river mouth, respectively. The stomach contents of 56 piranhas were analyzed and revealed that 55.35% of the stomachs were full and 44.65% were empty. The results indicated that fish remains were the most relevant food items at all the collection points. The results demonstrated spatial effects among the fish communities in the headwaters, intermediate section and river mouth, along with variations in water levels, with differences between high- and low-water periods. The redundancy analysis indicated significant effects for temperature, but not for other water parameters. It can be concluded that the piranha populations of the São Miguel River are distributed according to the water levels and the different sections of the river, though they utilize the same type of food resource.

Second trimester cervical length screening, in a low-risk European population

Purpose The aim of this work is to assess cervical length (CL) distribution in a low-risk population in order to evaluate the applicability of a possible universal CL screening in the second trimester, aimed at preventing preterm birth (PTB). Methods In a multicentric, prospective cohort study, singleton pregnant women attending second trimester anatomy scan between 18 + 0 to 22 + 6 weeks of gestation were eligible. Teenage pregnancy and women with previous PTB were excluded. The recruitment occurred from February 2020 to December 2022. TVU CL was measured by expert sonographers, in 12 National Health Service (NHS) care clinics of Modena and Parma districts (Emilia-Romagna Region, Italy). Internal quality check of images was performed. Personal and obstetric history, as well as gestational age were collected. Primary outcomes were to define CL curves and the incidence of CL ≤25 mm in low-risk pregnant women Secondary outcomes were the incidences of PTB <37, <34, and <32 weeks. Results Among 3226 screened women, mean and median CL were 40.8 and 40 mm, respectively. The 10th centile was equal to 33 mm while 25 mm represented the 2nd centile of the distribution. The incidence of CL ≤25 mm (short cervix) was 1.25%. Among those women, 7.5% were shorter than 150 cm, opposed to 2.1% in the normal CL group (p = .02); in addition there were more nullipara, women ≥ 40 and smokers (p = .03). Women with short cervix were at higher risk of PTB (23.6 vs 4.3%; RR: 4.6, 95%CI 2.49–8.48). At multivariate analysis, both CL ≤ 25 mm (RR: 5.51, 95%CI: 2.45–12.3) and stature ≤150 cm (RR: 2.54, 95%CI: 1.11–5.79) resulted independent predictors for PTB, once adjusted for other risk factors (fibroids, cervical surgery, obesity, low education, older age, smoking habit). Conclusion Although our study confirmed that women with short cervix are more likely to deliver preterm, the low incidence of such risk factor means that most of the preterm births occurred among women with normal cervical length. Thus, in a low-risk Italian population, ineffectiveness of universal screening is forecast.

Analysis of Regions of Homozygosity: Revisited Through New Bioinformatic Approaches

Background: Runs of homozygosity (ROHs), continuous homozygous regions across the genome, are often linked to consanguinity, with their size and frequency reflecting shared parental ancestry. Homozygosity mapping (HM) leverages ROHs to identify genes associated with autosomal recessive diseases. Whole-exome sequencing (WES) improves HM by detecting ROHs and disease-causing variants. Methods: To streamline personalized multigene panel creation, using WES and ROHs, we developed a methodology integrating ROHMMCLI and HomozygosityMapper algorithms, and, optionally, Human Phenotype Ontology (HPO) terms, implemented in a Django Web application. Resorting to a dataset of 12,167 WES, we performed the first ROH profiling of the Portuguese population. Clustering models were applied to predict consanguinity from ROH features. Results: These resources were applied for the genetic characterization of two siblings with epilepsy, myoclonus and dystonia, pinpointing the CSTB gene as disease-causing. Using the 2021 Census population distribution, we created a representative sample (3941 WES) and measured genome-wide autozygosity (FROH). Portalegre, Viseu, Bragança, Madeira, and Vila Real districts presented the highest FROH scores. Multidimensional scaling showed that ROH count and sum were key predictors of consanguinity, achieving a test F1-score of 0.96 with additional features. Conclusions: This study contributes with new bioinformatics tools for ROH analysis in a clinical setting, providing unprecedented population-level ROH data for Portugal.

Multi-source tri-environmental conceptual framework for fire impact analysis

The summer of 2023 highlighted the growing threat of wildfires in isolated areas, with Maui Island in Hawaii experiencing one of its largest wildfires. Our study employs a multi-source approach, integrating high-resolution optical data, thermal infrared data, and demographic information to assess the environmental, built, and social impacts of this event. Our innovative tri-environmental framework reveals significant vegetation degradation, land cover change, and disproportionate effects on various demographic groups. The fire caused extensive damage, with residential properties incurring 77.6% of the total losses, equating to approximately $563.2 million. Social impacts were profound, particularly among females, children, and the elderly, with employment and commuting disruptions affecting both low- and high-income groups. The study highlights the effectiveness of combining dasymetric mapping with real-time satellite data to refine population distribution estimates in affected areas. Our findings are applicable beyond wildfires, offering valuable insights into disaster response and mitigation strategies across various natural hazards like floods and earthquakes.

Towards Deterministic-Delay Data Delivery Using Multi-Criteria Routing over Satellite Networks

The satellite Internet can cover up to 70% of the surface of our planet Earth to provide network services for nearly 3 billion people. As such, it is promising to become the building block of future 6G networks. The satellite Internet is capable of providing uniform communication capacity to every part of the Earth’s surface, due to its uniform and symmetrical constellation structure, while the uneven distribution of ground populations leads to globally uneven traffic delivery requests, incurring a mismatch between the capacity and traffic transmission demands. As such, traditional single-criteria (e.g., shortest delay) routing algorithms can lead to severe network congestion and cannot provision delay-deterministic data delivery. To overcome this bottleneck, we propose a multi-criteria routing and scheduling scheme to redirect time-tolerant data, thus preventing congestion for time-sensitive data, based on the spatiotemporal distribution of data traffic. First, we construct a traffic spatiotemporal distribution model, to indicate the network load status. Next, we model the satellite network multi-criteria routing problem as an integer linear programming one, which is NP-hard and challenging to solve within polynomial time. A novel link weight design based on both the link delay and load is introduced, transforming the mathematical programming problem into a routing optimization problem. The proposed correlation scheduling algorithm fully utilizes idle network link resources, significantly improving network resource utilization and eliminating resource competition between non-time-sensitive and time-sensitive services. Simulation results show that compared with traditional algorithms, the proposed method can increase the throughput of time-sensitive data by up to 20.8% and reduce the packet loss rate of time-sensitive services by up to 76.8%.

Reconstructing the population history of theNicobarese.

The Nicobarese are the major tribal groups in the Nicobar district, situated south of the Andaman group of Islands. Linguistic phylogeny suggests that the linguistic ancestors of the Nicobarese settled the Nicobar archipelago in the early Holocene. So far, genetic research on them is low-resolution and restricted to the haploid DNA markers. Therefore, in the present analysis, we have used the high-resolution biparental (1554 published and 5 newly genotyped Nicobarese individuals) and uniparental genetic markers and looked at the genetic association of Nicobarese with the South and Southeast Asian populations. We report a common ancestral component shared among the Austroasiatic of South and Southeast Asia. Our analyses have suggested that the Nicobarese peoples retain this ancestral Austroasiatic predominant component in their genomes in the highest proportion. On the Southeast Asian mainland, the Htin Mal, who speak an Austroasiatic language of the Khmuic branch, represent a population that has preserved their ethnic distinctness from other groups over time and consequently shown the highest drift with the Nicobarese. The analysis based on haplotypes indicated a significant level of genomic segment sharing across linguistic groups, indicating an ancient broader distribution of Austroasiatic populations in Southeast Asia. Based on the temporal analyses of haploid DNA, it is suggested that the forebears of the Nicobarese people may have arrived on the Nicobar Islands in the last 5000 YBP. Therefore, among the modern populations, the Nicobarese peoples and the Htin Mal language community represent good genetic proxies for ancient Austroasiatics.

Changes in guanaco distribution from Late Holocene to present times in Northwest Patagonia: connecting archaeological, ethnohistoric and current data

Context The guanaco (Lama guanicoe) is one of the four species of South American camels, and is the largest native mammal inhabiting arid and semi-arid environments in South America. Although the guanaco was abundant and widely distributed in the past, currently its density and distribution range are substantially reduced, inhabiting mainly Southern Patagonia in small isolated groups. The decline in guanaco populations is most likely related to the Anthropocene defaunation process that is affecting large mammals in developing countries worldwide, but the extent and causes of these changes are not well understood. Aims To explore both the changes in the distribution of guanaco populations in Northwest Patagonia and the environmental and anthropic factors that shaped the distribution patterns, by employing a long-term perspective spanning from the end of the Late Holocene to present times (i.e. the last 2500 years). Methods We combine archaeological information, ethnohistorical records and current observations and apply Species Distribution Models using bioclimatic and anthropic factors as explanatory variables. Key results Guanaco spatial distribution in Northwest Patagonia changed significantly throughout time. This change consisted in the displacement of the species towards the east of the region and its disappearance from northwest Neuquén and southwest Mendoza in the last 30 years. In particular, the high-density urban settlements and roads, and secondly, competition with ovicaprine livestock (goats and sheep) for forage are the main factors explaining the change in guanaco distribution. Conclusions Guanaco and human populations co-existed in the same areas during the Late Holocene and historic times (16th to 19th centuries), but during the 20th century the modern anthropic impact generated a spatial dissociation between both species, pushing guanaco populations to drier and more unproductive areas that were previously peripheral in its distribution. Implications As with many other large mammal species in developing countries, Northwest Patagonia guanaco populations are undergoing significant changes in their range due to modern anthropic activities. Considering that these events are directly related to population declines and extirpations, together with the striking low density recorded for Northwest Patagonia guanaco populations, urgent management actions are needed to mitigate current human impacts.

Pattern and driver of Rosa roxburghii Tratt suitability and its effect on ecological services in karst desertification control areas

The eco-industry is an effective path to achieve ecological and economic sustainable development. However, the role played by Rosa roxburghii Tratt (R. roxburghii) industry in karst desertification control still needs to be determined. In this study, we predict the suitability probability and driving variables of R. roxburghii's distribution through a Maximum Entropy model, combining climate, population, vegetation, and soil data, and conducted a sample plot survey in a high-suitability area to explore the role of the R. roxburghii industry in ecological services by using adjacent non-R. roxburghii patches as comparisons. The results showed that South China Karst, with its simultaneous rain and heat climate characteristics, was the most suitable area for the industrialization of R. roxburghii in the world. In South China Karst, the area of no, low, medium, and high suitability zones for R. roxburghii was 4.2 × 105, 6.12 × 105, 4.64 × 105, and 4.42 × 105 km2, respectively, and population distribution was the dominant variable controlling its distribution. The net primary productivity, soil conservation, water conservation, mean species abundance, and aboveground biomass of the R. roxburghii monoculture plot in the high-suitability area were significantly lower than those of adjacent non-R. roxburghii lands and forest patches. Furthermore, the monoculture had higher trade-offs between provision, regulation, and support service. This study found that the monoculture of R. roxburghii industry, dominated by human activities, failed to improve ecological services and exacerbated the trade-offs between services. Therefore, future karst desertification control still needs to follow the agroforestry development path.

Movement Ecology of a Coastal Foundation Seagrass Species: Insights From Genetic Data and Oceanographic Modelling

ABSTRACTAimSeed dispersal plays a key role in shaping the distribution and genetic complexity of seagrass populations and affects their resilience capacity under disturbance. The endemic seagrass Posidonia oceanica is a key component of Mediterranean coastal ecosystems, but knowledge about movement ecology in this species is limited, especially regarding seed movement pathways and dispersal potential.LocationWestern coast of Sicily (central Mediterranean).MethodsBeach‐cast fruits of the Mediterranean seagrass P. oceanica were collected from nine localities along the Western coast of Sicily, along with adult shoots from eight putative donor meadows. We determined pair‐wise genetic differentiation between established meadows and seed cohorts. Genetic assignment tests were used to infer the most likely meadow of origin of individual seeds and were complemented with forward and backward Lagrangian simulations of dispersal.ResultsA significant genetic differentiation was found between seed pools and the most‐likely meadow of origin. The genetic assignment confirmed that seeds from the same cohort originated from multiple meadows and emphasised the presence of long‐distance‐dispersal (LDD) events (up to hundreds of km). Genetic connectivity appeared to be greater than that predicted by oceanographic simulations, which may reflect the longer temporal scales on which gene flow is shaped, in contrast to contemporary dispersal patterns. Lagrangian simulations highlighted that fruits were physically capable of dispersing beyond the study area and that the north Tunisian coast could be a key source of propagules for the populations studied.Main ConclusionsOur study represents a significant step forward in the understanding of P. oceanica movement ecology and could guide meadows' conservation and restoration actions. Our findings are significant in a broader context outside of the research area and could be the basis of similar studies in other regions, especially considering the increasing number of fruiting events recorded across the Mediterranean likely associated with ocean warming.

Preparation of vanillin nanoparticle/polyvinyl alcohol/chitosan film and its application in preservation of large yellow croaker.

The novel polyvinyl alcohol/chitosan films incorporated with vanillin/zein/κ-carrageenan nanoparticles (VZCNPs) were developed. The polyvinyl alcohol/chitosan/vanillin nanoparticles (PVA/CS/NPs) films had exhibited enhanced tensile strength, hydrophobicity, antioxidant activities and antimicrobial efficacy, all of which varied with the different concentrations of VZCNPs. Notably, the PVA/CS/NPs-10 film exhibited exceptional performance, with a reduced water content of 15.68 ± 0.46 %, an increased water contact angle of 65.75°, and improved ABTS scavenging rate of 77.39 ± 0.54 %, demonstrating outstanding antioxidant activity and antimicrobial properties. The PVA/CS/NPs films were further applied to the packaging of large yellow croaker (Pseudosciaena crocea) to evaluate their preservation capability at 4 °C. The results indicated that the PVA/CS/NPs films effectively inhibited microbial growth and lipid oxidation, thereby delaying the spoilage of large yellow croaker. High-throughput sequencing study showed that the films effectively inhibited spoilage bacteria, including Comamonas, Pseudomonas, and, Burkholderia and affected the distribution of bacterial populations during storage. This study provides new insights into prolonging the shelf life of fresh-frozen large yellow croaker and developing advanced preservation methods for the future development of the aquatic product.

Exploring landscape ecological risk with human activity intensity and correlation in the Kuye River Basin

IntroductionThe Kuye River Basin, a typical erosion area of the Loess Plateau region with the second largest tributary of the Yellow River Basin, faces significant environmental challenges and intense human activities. Balancing environmental sustainability and economic development in this region is urgent.MethodsTherefore, this study takes this basin as the object and evaluates the landscape ecological risk and human activity intensity from 2000 to 2022 based on land use/land cover, population distribution and nighttime lighting data. And a geographically weighted regression model was used to reveal the correlation between the two.Results and discussionResults showed that the average landscape ecological risk index in 2000, 2015, and 2022 were 9.01×10-4, 5.61×10-4, and 7.40×10-4, respectively. This shows that the overall landscape ecological risk index is low in the first 15 years and then gradually increases over time. Cultivated land, grassland and construction land are the main landscapes, the expansion of 7.95 times construction land is a key factor in the intensification of human activities, mainly concentrated in the northwest, followed by a gradual expansion towards the south-east, and likewise the landscape ecological risks follow the same trend. Medium to high intensity human activities exacerbate landscape ecological risks, with a significant positive correlation, while low intensity human activities cause little damage to landscape ecology. To achieve sustainability, it is necessary to effectively control construction land and improve land use structure. Then, in the planning work, priority will be given to the northwest region with high human activity intensity and high landscape ecological risks, and the governance direction will gradually shift to the southeast region. These findings provide empirical evidence to support decision-making and underscore the need for comprehensive strategies to mitigate landscape ecological risks and promote sustainable development in the Kuye River Basin.

S5: New insights from deep spectroscopic observations of the tidal tails of the globular clusters NGC 1261 and NGC 1904

As globular clusters (GCs) orbit the Milky Way, their stars are tidally stripped and form tidal tails that follow the orbit of the cluster around the Galaxy. The morphology of these tails is complex and shows correlations with the phase of orbit and the orbital angular velocity, especially for GCs on eccentric orbits. Here we focus on two GCs, NGC 1261 and NGC 1904, that were potentially accreted alongside Gaia-Enceladus and that have shown signatures of having, in addition to tidal tails, structures formed by distributions of extra-tidal stars that are misaligned with the general direction of the clusters' respective orbits. To provide an explanation for the formation of these structures, we made use of spectroscopic measurements from the Southern Stellar Stream Spectroscopic Survey ($S^5$) as well as proper motion measurements from $Gaia$'s third data release (DR3), and applied a Bayesian mixture modelling approach to isolate high-probability member stars. We recovered extra-tidal features surrounding each cluster matching findings from previous work. We then conducted N-body simulations and compared the expected spatial distribution and variation in the dynamical parameters along the orbit with those of our potential member sample. Furthermore, we used Dark Energy Camera (DECam) photometry to inspect the distribution of the member stars in the colour-magnitude diagram (CMD). We find that potential members agree reasonably with the N-body simulations, and that the majority follow a simple stellar population distribution in the CMD, which is characteristic of GCs. We link the extra-tidal features with their orbital properties and find that the presence of the tails agrees well with the theory of stellar stream formation through tidal disruption. In the case of NGC 1904, we clearly detect the tidal debris escaping the inner and outer Lagrange points, which are expected to be prominent when at or close to the apocentre of its orbit. Our analysis allows for further exploration of other GCs in the Milky Way that exhibit similar extra-tidal features.

A Machine Learning Method for Stackelberg Mean Field Games

We propose a single-level numerical approach to solve Stackelberg mean field game (MFG) problems. In the Stackelberg MFG, an infinite population of agents plays a noncooperative game and chooses their controls to optimize their individual objectives while interacting with the principal and other agents through the population distribution. The principal can influence the mean field Nash equilibrium at the population level through policies, and she optimizes her own objective, which depends on the population distribution. This leads to a bilevel problem between the principal and mean field of agents that cannot be solved using traditional methods for MFGs. We propose a reformulation of this problem as a single-level mean field optimal control problem through a penalization approach. We prove convergence of the reformulated problem to the original problem. We propose a machine learning method based on (feed-forward and recurrent) neural networks and illustrate it on several examples from the literature. We also give a modified example to show the scalability of the proposed method and show its efficiency by comparing its performance with an alternative bilevel approach.

Development and validation of a face database for the recognition of facial expressions of basic emotions in the Brazilian population

BackgroundThe recognition of facial expressions of emotions is an essential skill for social functioning, as it enables recognizing the possible intentions of others.Main body.Cultural context is an important aspect to consider in this skill, as it tends to modulate the recognition of facial expressions.ObjectiveTo develop and validate a set of facial expressions of basic emotions of Brazilian individuals considering the population distribution of the country according to age group, sex, and race.MethodsA procedure with three phases was created to generate basic emotions and photograph facial expressions. A total of 459 Brazilians were then asked to identify the emotions of these facial expressions. Content validity was investigated based on the analysis of specialists and the recognition of emotions by Brazilian individuals.ResultsThe final database consists of 56 high-quality color images. A good level of agreement was found for the expressions perceived by the assessors (81.6%).ConclusionThe percentage of correct recognition of each emotion and the characteristics of the models are presented so that future studies can choose the most adequate images to meet their specific needs.

A rapid analysis method for regional population distribution safety based on societal risk assessment

The population distribution within areas potentially impacted by major accidents is crucial for societal risk analysis. Population data are essential for land use planning activities related to major accident hazards. However, repeated quantitative risk assessments (QRA) and diverse planning scenarios complicate planning decisions in Major Hazard Installation (MHI) areas. This study introduces an analysis method for the safety of population distribution in potential impact zones of major accidents. By combining accident simulation and population distribution characteristics analysis, we established standardized indicators that succinctly indicate safety thresholds for societal risks, addressing the challenge of rapidly assessing off-site population safety. A rapid formula meeting practical needs is provided for urban managers and planners, enabling them to easily evaluate how population density and distribution affect societal risks in MHI areas. Finally, we applied this method to the flammable and explosive hazardous material enterprises in Shijiazhuang, China, demonstrating its functionality and practicality. The application results suggest its potential as a useful decision-support method for guiding urban planning and emergency management. This work offers new insights and valuable demonstrations for enhancing vulnerability and land use risk assessments in MHI regions.