Spatial Association Research Articles

Spatiotemporal interactions between ocelots and agoutis in Neotropical protected forests.

Understanding how predators and their prey coexist in space and time is a core interest in ecology. Vast amounts of photographic detection data are now available from a growing number of camera-trap studies worldwide. These data boost our ability to study an elusive yet important topic in ecology: species interactions in space and time. Here, we investigated the spatiotemporal configuration of the activity of a typically nocturnal and crepuscular predator and a diurnal prey in protected areas. We explored whether agoutis (Dasyprocta leporina) respond to predation risks by adjusting the timing of activity to the occurrence and timing of activity of its potential predator, the ocelot (Leopardus pardalis) and whether the ocelot's occurrence responds to that of the prey. Using a custom Bayesian occupancy model for two species, we analysed camera-trap data collected over three protected tropical forests from Brazil and Suriname (2 to 9 years). Our model distinguishes between occupancy (i.e. spatial distribution) and detection (i.e. activity in space and time). We detected a positive spatial association between predator and prey, suggesting that ocelots seek places where agoutis are present. Instead of segregating in space, agoutis appeared to respond to increased predation risk by reduced activity. The most pronounced reduction in agouti activity (i.e. probability of detection) was during twilight in sites where ocelots occurred. Our results illustrate how jointly modelling interactions in both space and time informs our understanding of predator-prey coexistence.

Exploring the spatial association characteristics of carbon emission efficiency in China’s construction industry: A network perspective

Exploring the spatial association characteristics of carbon emission efficiency in China’s construction industry: A network perspective

Structural Basis of Differential Gene Expression at eQTLs Loci from High-Resolution Ensemble Models of 3D Single-Cell Chromatin Conformations.

Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies (GWASs) have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in non-coding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of non-random interactions from all Hi-C interactions. Using these non-random interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci. Supplementary data are available at Bioinformatics online.

First Search for Pulsed CH Maser Emission Stimulated by a Pulsar

Abstract We present the first search for pulsed CH maser emission potentially stimulated by PSR J1644-4559, conducted using the ultra-wide-bandwidth low-frequency receiver on Murriyang, CSIRO's Parkes Radio Telescope. Observations targeted three CH Λ-doublet transitions at 3264, 3335, and 3349 MHz, with a variability timescale of 78 ms. We detected ten CH emission features at 3335 and 3349 MHz, and seven features at 3264 MHz, during both pulsar-ON and pulsar-OFF phases. The observed velocities align with the OH emission and absorption reported by a previous study, suggesting a close spatial association between CH and OH molecules. The derived column densities for CH clouds within the Parkes beam range from 0.05 to 9.8 × 1013 cm−2, indicating that these clouds are likely in diffuse and translucent states. Upper limits for CH column densities within the pulsar beam ranged from 0.3 to 9.8 × 1013 cm−2. Comparison of these column densities suggests that CH clouds may exhibit clumpiness and substructure. No significant stimulated emission feature was detected in the optical depth spectra. Additionally, as part of our search for pulsed stimulated emission, we investigated the potential CH absorption of the pulsar signal and found none, in agreement with astrophysical expectations. The upper limits for the potential maser amplification factors towards PSR J1644-4559 at 3264, 3335, and 3349 MHz are 1.014, 1.009, and 1.009, respectively. This study demonstrates the feasibility of detecting pulsed CH maser emission in the interstellar medium stimulated by pulsar photons.

Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand.

Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.

Knowledge-driven semantic converting method of multimodal models toward a geospatial perspective

ABSTRACT In the virtual geographic environment, conducting status analysis on urban structures and similar objects is crucial for enhancing their detailed management level. However, it is challenging to directly convert the same object across various software systems with different modalities (such as spatial analysis, BIM design, numerical simulation etc.). Therefore, the effective conversion of multi-modal models becomes pivotal. Due to the characteristics of inconsistent spatial description and complex association relationship among multimodal models, resulting in low knowledge reuse rate, poor accuracy of unit mapping, and low efficiency of state sharing in the process of model conversion. Aiming at these problems, this article delves into the knowledge-driven semantic conversion techniques for multi-modal models from a geospatial viewpoint. The mapping relationships between multimodal models in terms of spatial, geometric, and semantic information were first clarified. Subsequently, a structural matching template based on knowledge reuse was established, and a knowledge-guided algorithm for multimodal model transformation was designed. Finally, using a suspension bridge as a case study, a prototype system was developed and experimental analysis was conducted. The experimental results show that the method proposed in this article can accurately convert between BIM models, numerical analysis models, and GIS scene models, with spatial coordinate accuracy controlled within 1 mm and a conversion efficiency increase of more than 10 times. This can effectively enhance the integrated performance of models in applications such as digital geospatial twin scenarios.

Rising Incidence and Spatiotemporal Dynamics of Emerging and Reemerging Arboviruses in Brazil

Background: Brazil has witnessed the co-circulation of dengue virus (DENV), Zika virus (ZIKV), and chikungunya virus (CHIKV), with outbreaks exacerbated by environmental factors, social determinants, and poor sanitation. The recent re-emergence of Oropouche virus (OROV) has added complexity to vector control strategies, emphasizing the need for integrated approaches to curb arboviruses spread. We aimed to analyze temporal trends and spatial distributions with national scope of these emerging arboviruses. Methods: An ecological study using data from the Brazilian Notifiable Diseases Information System the period from 2023 to 2024 was undertaken. Temporal trends were evaluated using Joinpoint regression, while spatial analysis was conducted using Moran’s I, and local indicators of spatial association. Results: Dengue fever cases increased by 322%, while Oropouche fever (OF) increased by 300%. The states of Amazonas and Espírito Santo reported increases in OF cases. Moran’s I test revealed spatial clustering of DENV and CHIKV. Two municipalities in the state of Mato Grosso do Sul showed cocirculation of DENV, CHIKV, and ZIKV. Conclusions: This study identified a surge in arbovirus cases between 2023 and 2024, with peak incidences from January to March and October to December, linked to favorable climatic conditions. Clustering patterns and co-circulation of arboviruses highlight the need for tailored control and prevention strategies and targeted interventions to mitigate their impact.

Geographic distribution and demographic factors associated with use of a long-acting reversible contraceptive (LARC) in Ethiopia.

Increasing access to and utilization of long-acting reversible contraceptives (LARC) can prevent unintended pregnancies and reduce unmet need for family planning in Ethiopia However, LARC uptake lags behind less effective contraceptive methods. This study aimed to analyze the geographical distribution and demographic factors associated to LARC uptake. The 2019 Performance Monitoring For Action Ethiopia (PMA Ethiopia) survey data was used. Spatial autocorrelation was examined using Global Moran's I and Local Indicators of Spatial Association (LISA). Bivariate Moran's I and bivariate LISA (BiLISA), Spatial lag, and spatial error regression analyses were performed to assess the spatial correlation and association between LARC uptake and demographic factors. LARC uptake was 8% among the study population, with Afar and Somali regions having the lowest uptake. There was a statistically significant positive spatial autocorrelation for LARC uptake (Moran's I= 0.308, p<0.001). Additionally, an inverse correlation was observed between LARC uptake and the percentage of Muslims, rural population, no formal education, and low wealth quantile. The spatial lag model indicated that zones with higher Muslim populations and those with higher percentages of population with no formal education had lower LARC uptake. To expand access to LARC, the Ethiopian government, policymakers, and non-governmental organizations might implement programs targeting low-uptake areas (Afar and Somali regions). Muslim religious leaders could play an important role in promoting acceptance of LARC among their members. Tailored health education programs should be developed for Muslim populations and those with no formal education to enhance awareness and acceptance of LARC.

P1203 Spatial mapping and geographic variation of inflammatory bowel disease in Canada: A population-based study using Statistics Canada data

Abstract Background Crohn’s Disease (CD) and Ulcerative Colitis (UC) pose significant challenges to patients and healthcare systems, with a rising incidence and prevalence globally1,2. To address the challenges of health resource allocation and understand the geographic distribution of these conditions in Canada, we conducted the spatial mapping of IBD across Canada using national population survey data available from Statistics Canada. Methods We utilized data from the 2009-2018 Canadian Community Health Survey (CCHS) to identify individuals with CD or UC. Prevalence rates, both crude and adjusted for age and sex, were calculated for each health region in Canada. Spatial dependencies between health regions were estimated using global Moran’s I and local indicators of spatial association (LISA) were used to identify clusters of health region (hot-spots) where the prevalence was significantly higher than in other areas. We further applied spatial simultaneous autoregressive lag models to explore the influence of region-level sociodemographic factors on identified spatial dependencies. Results A total of 492,560 individuals from 2010-2018 CCHS were included, representing 29,846,350 Canadians across 109 health regions. Survey data revealed that 0.38% of Canadians self-reported having CD and 0.47% reported having UC. The majority of respondents reported being urban-residing, middle-aged, and white. Across Canadian provinces, the age and sex-standardized prevalence of IBD ranged from 742 per 100,000 in Quebec to 1267 per 100,000 in Nova Scotia (Figure 1). Spatial analysis identified significant dependencies among health regions, but these spatial associations were explained by the differing distributions of sociodemographic characteristics in each health region (Table 1). Increased health region-level prevalence of CD and UC was associated with a larger proportion of individuals 30+ years, identifying as a female, immigrants, or as white (p&amp;lt;0.05 for each). Conclusion Data from this large, population-based Canadian national survey demonstrated significant geographic variation in the prevalence of CD and UC. However, after adjusting for patient demographic characteristics, the spatial dependency became non-significant. Key characteristics related to urbanization including the age distribution and proportion of immigrants in a health region were associated with increased prevalence rates. These results suggest that differences in CD and UC prevalence between geographic areas are primarily driven by individual demographics rather than differences in characteristics of local healthcare delivery systems and further support the notion that characteristics of urbanization increase the prevalence of IBD in an area1.

The role of spatial processing in verbal serial order working memory.

In a sequence, at least two aspects of information-the identity of items and their serial order-are maintained and supported by distinct working memory (WM) capacities. Verbal serial order WM is modulated by spatial processing, reflected in the Spatial Position Association of Response Codes (SPoARC) effect-the left-beginning, right-end positional association between space and serial position of verbal WM memoranda. We investigated the individual differences in this modulation with both behavioral and neurobiological approaches. We administered a battery of seven behavioral tasks with 160 healthy adults and collected resting-state fMRI data from a subset of 25 participants. With a multilevel mixed-effects modeling approach, we found that the SPoARC effect's magnitude predicts individual differences in verbal serial order WM capacity and is related to spatial item WM capacity. With a graph-theory-based analytic approach, this interaction between verbal serial order WM and spatial WM was corroborated in that the level of interaction between corresponding cortical regions (indexed by modularity) was predictive of the magnitude of the SPoARC effect. Additionally, the modularity of cortical regions associated with verbal serial order WM and spatial attention predicted the SPoARC effect's magnitude, indicating the involvement of spatial attention in this modulation. Together, our findings highlight multiple sources of the interplay between verbal serial order WM and spatial processing.

A left-to-right bias in number-space mapping across ages and cultures

Number and space are inherently related. Previous research has provided evidence that numbers are aligned to a so-called “mental number line”, which is malleable and affected by cultural factors mostly linked to literacy-related habits. However, preverbal humans and non-human animals also map numerosities into space, in a consistent left-to-right direction. These contrasting findings raise the question of whether Spatial Numerical Associations (SNA) are culturally or biologically determined. Here, we investigated Italian adults, Italian preschoolers, and Himba adults (an indigenous population with an oral cultural system) to examine whether cultural influences are necessary for SNA to emerge. We found that, when explicitly asked to order numerosities, only Italian adults showed a consistent left-to-right preference, while preschoolers and Himba adults did not have a consistent preference for one direction or the other. On the other hand, in a numerosity comparison task, all groups performed better when small numerosities were presented in the left hemispace. These results suggest that humans may display two forms of SNAs, one that emerges mostly in implicit tasks and is biologically determined, and one that emerges in explicit ordering tasks and is determined by cultural habits.

Patriarchy, Fertility and Excess Female Child Mortality in India

Research investigating association between patriarchy and demographic behavior is limited in India. The only study on this subject utilized 1981 Indian Census data to examine associations between patriarchy and fertility. We examined the association of patriarchy, measured using India Patriarchy Index (IPI), with total fertility rate (TFR) and excess female child mortality in India. Additionally, we examined independent associations of the 5 dimensions included in the IPI with the two outcomes. We used univariate and bivariate Local Indicators of Spatial Autocorrelation, multivariable ordinary least squares and spatial error- regressions to examine the associations. Spatial heterogeneity beyond the north–south divide was evident in the spatial association of IPI with TFR and excess female child mortality. Results show positive association of IPI with TFR and excess female child mortality. While son preference and socio-economic domination were positively associated with TFR, domination of men over women and son preference were positively associated with excess female child mortality. This study is the first of its kind to examine the association of a novel measure of patriarchy with TFR and excess female child mortality. As patriarchy is deep-rooted in Indian society, a great deal of effort is needed to shift these traditionally held social norms and practices.

Widespread Occurrence of Former Anhydrite Phenocrysts in Laramide-Age Magmas Related to Porphyry–Skarn Cu Mineralization at Santa Rita and Hanover-Fierro, New Mexico, USA

Abstract Reports of magmatic anhydrite are relatively rare, with only ~30 occurrences documented worldwide so far. However, magmatic anhydrite saturation is difficult to recognize because anhydrite decomposes rapidly in near-surface environments. In most cases, only anhydrite inclusions shielded within other phenocryst phases were able to survive. Alternatively, since anhydrite phenocrysts preserved in fresh volcanic rocks are characteristically intergrown with apatite phenocrysts, the former presence of anhydrite phenocrysts can be recognized based on the occurrence of lath-shaped cavities that show a strong spatial association with apatite phenocrysts. These cavities can be either empty or filled with low-temperature, secondary minerals such as zeolites, carbonates, or microcrystalline silica. A systematic search for the occurrence of such cavities, combined with optical and Raman-spectroscopic identification of anhydrite inclusions preserved within apatite, hornblende and quartz phenocrysts, demonstrates that most of the Laramide-age magmas associated with the Santa Rita and Hanover-Fierro porphyry–skarn Cu (Zn, Mo, Au, Pb) deposits were saturated in magmatic anhydrite. The anhydrite typically coexisted with monosulfide solid solution (MSS), suggesting oxygen fugacities of ~2.0 ± 0.5 log units above the fayalite–magnetite–quartz buffer. The magmas range from andesitic to rhyodacitic in composition, and from shortly pre-mineralization (~61 Ma) to shortly post-mineralization (~57 Ma) in age. In three samples with particularly well-recognizable former anhydrite phenocrysts, their modal abundance could be quantified based on high-resolution scans of polished hand specimens. The observed modal anhydrite abundances of 0.63 to 1.8 vol % translate into minimum magma sulfur contents of 0.20 to 0.56 wt % S. The highest sulfur content of 0.56 wt % S is difficult to reconcile with available anhydrite solubility models, but it could be reproduced in an anhydrite solubility experiment performed at 950°C and 1.15 GPa on a natural latite containing 13.1 wt % dissolved H2O. The sample with the second-highest sulfur content of 0.26 wt % S requires ~10 wt % H2O in the silicate melt, and, consequently, a minimum pressure of ~0.5 GPa. Taken together, the results suggest that the magmas of the Central Mining District were extremely hydrous and thus originated from great depth. Indeed, their major element compositions and reconstructed H2O and S contents agree well with experimentally observed and numerically predicted compositions of residual silicate melts after 50 to 70 wt % crystallization of ordinary arc basalts at high pressure and high oxygen fugacities.

DRAF-Net: Dual-Branch Residual-Guided Multi-View Attention Fusion Network for Station-Level Numerical Weather Prediction Correction

Accurate station-level numerical weather predictions are critical for disaster prevention and mitigation, with error correction playing an essential role. However, existing correction models struggle to effectively handle the high-dimensional features and complex dependencies inherent in meteorological data. To address these challenges, this paper proposes the dual-branch residual-guided multi-view attention fusion network (DRAF-Net), a novel deep learning-based correction model. DRAF-Net introduces two key innovations: (1) a dual-branch residual structure that enhances the spatial sensitivity of deep high-dimensional features and improves output stability by connecting raw data and shallow features to deep features, respectively; and (2) a multi-view attention fusion mechanism that models spatiotemporal influences, temporal dynamics, and spatial associations, significantly improving the representation of complex dependencies. The effectiveness of DRAF-Net was validated on two real-world datasets comprising observations and predictions from Chinese meteorological stations. It achieved an average RMSE reduction of 83.44% and an average MAE reduction of 84.21% across all eight variables, significantly outperforming other methods. Moreover, extensive studies confirmed the critical contributions of each key component, while visualization results highlighted the model’s ability to eliminate anomalous values and improve prediction consistency. The code will be made publicly available to support future research and development.

A study of the impact of urban business credit environment on environmental pollution.

Environmental pollution has become a global concern, so it is critical to find out the elements that influence it. Is the urban business credit environment influencing urban environmental conditions? The study takes the entropy method for calculating the environmental pollution index of 276 prefecture-level cities across China from 2010 to 2021, the CE1 index to describe the urban business credit environment, and a spatial Durbin model to empirically analyze the mechanism and transmission path of the urban business credit environment on environmental pollution. The findings demonstrate that: (1) there is an important positive spatial association between China's urban pollution index and urban business credit index, and that the level of spatial clustering of the two is increasing over time. (2) the urban business credit environment and environmental pollution have an inverted "U" shape relationship and a significant spatial spillover effect, which means that once a certain threshold is reached, improving the urban business credit environment reduces environmental pollution in local and neighboring areas. (3) The influence of the urban business credit environment on environmental deterioration varies by region. The extra heterogeneity test results for the different regions show that the relationship between business credit level and environmental pollution is consistent with the overall situation in the eastern and western regions, the opposite effect was observed in the central region. (4) Changes in the urban business credit environment have an indirect impact on environmental conditions due to the amount of regional financial development and technological innovation potential. To reduce pollution in the region, prefectural-level cities must strengthen the construction of urban business credit systems, strive to create a favorable business credit environment, strengthen the spatial spillover effect, and guide the resource elements of business credit planning to flow into the central and western parts of China reasonably. The study's findings have significant practical implications for modifying the government's development strategy and improving the urban environment.

Spatial Analysis of Vulnerability and Social Capital in Relation to COVID-19 Mortality in the 50 States of the U.S. in the First Year of the Pandemic

The lack of social determinants of health has significantly influenced COVID-19 mortality; however, the few studies that have investigated the relationship among social capital, vulnerability, and COVID-19 mortality have either shown mixed directions of association or were not conducted at a larger scale on the state level. Our study aimed to fill this research gap. We aimed to test the association of comprehensive vulnerability and social capital measures and COVID-19 mortality in 50 states in the U.S. during the first year of the pandemic. We hypothesized that states with low social capital would register the highest mortality rates and high vulnerability would be proportional to a high number of deaths due to COVID-19 in the U.S. Methods: Our ecological analytic study used aggregate secondary data from nine open access databases. The outcome was COVID-19 mortality (January 2020 to July 2021). The main exposures were social capital and social vulnerability. We also tested 28 covariates and selected socioeconomic variables at the state level. Statistical analysis consisted of a multivariate technique factor analysis and a bivariate Local Indicators of Spatial Association (LISA) analysis. Findings: Social capital (SCI) and social vulnerability (SVI) explained 57% of the COVID-19 mortality rate variation (R2 adjusted = 0.57). This analysis resulted in a statistically significant model (p ≤ 0.001), where SCI (β = 23.256, t = 2.649, p = 0.011) and SVI (β = 150.316, t = 4.235, p = 0.001) were predictors for COVID-19 mortality in the investigated period.

Grapevine and cover crop spectral response to evaluate vineyard spatio-temporal variability

The use of cover crops in vineyards is considered a management strategy that contributes to improving soil structure. Remote sensing techniques of cover crops provide information on spatial variability that can be useful in precision viticulture. This study aims to investigate soil-plant interactions using biometric data, spectral response and soil physico-chemical parameters measured across 2021-2022, with the scope of assessing spatio-temporal variations of cover crop and vineyard. These evaluations were conducted on an on-farm vineyard in a semi-arid Mediterranean environment. During the winter season (T1), the cover crop (Vicia Faba) growth was evaluated. Equally, during the summer season (T2), vineyard monitoring was carried out during the phenological stages of flowering (T2A) and grape ripening (T2B). Multispectral images acquired through unmanned aerial vehicle (UAV) were employed, and subsequently, the normalized difference vegetation index (NDVI) was calculated to obtain crops vigor maps. Through bivariate LISA cluster maps, cover crop vigor maps were compared with those of the vineyard, revealing the presence of significant positive spatial autocorrelation between the two crops. Indeed, in areas where the cover crop exhibited higher dry matter accumulation, grapevine high vigor growth was observed. The spatial association identified in surveys conducted in T1 and T2 was examined considering soil parameters. It emerged that in areas where both the cover crop and the vines exhibited high NDVI values, soil factors such as soil organic carbon (SOC) content and total nitrogen (TN) were higher. Conversely, in areas where both crops showed low NDVI values, they were associated with higher soil bulk density (BD). Moreover, in low vigor zones, higher soil penetration resistance (SPR) values were observed in both T1 and T2, contributing to limiting root elongation and thus reducing overall crop growth. Vegetative growth variability observed through vigor maps and soil physicochemical properties was evaluated through principal component analysis (PCA). Soil parameters considered within these components highlighted their influence on crop growth. This study emphasizes how soil factors directly influence the spatiotemporal variability of crops. Monitoring cover crops allows for early detection of spatial variability, supporting vine growers in choosing sustainable vineyard management techniques.

The spillover effect of economic institutions on the environment: A global evidence from spatial econometric analysis.

This study examines the impact of economic institutions on ecological footprint and their spatial spillover effects globally, covering the period from 2000 to 2021. We focus on economic institutions because institutions that espouse economic freedom are essential for safeguarding environmental quality. We hypothesize that the spatial influence of these institutions varies both globally and regionally. The Moran's I test reveals significant spatial associations among countries, while the Wald and likelihood tests identify the spatial Durbin model as the most appropriate approach. Furthermore, the Hausman test indicates that a fixed effects model best captures the coefficients. Globally, economic institutions demonstrate a direct reduction effect of 16.4% and a spillover reduction effect of 4.4% on ecological footprint. However, these effects show considerable regional variation. In North America, East Asia and the Pacific, the Middle East, North Africa, Europe, and Central Asia, economic institutions effectively reduce ecological footprint, while their impact is negligible in other regions. These regional differences underscore the importance of addressing institutional deficiencies, encouraging policymakers in regions with limited effects to learn from best practices to enhance institutional effectiveness. These insights collectively advance the literature on economic institutions and environmental economics, emphasizing regional policy adaptation and the transboundary effects of institutional quality. The findings further reveal that economic institutions moderate GDP per capita to curb ecological footprint significantly. These conclusions hold even after addressing endogeneity using the generalized spatial two-stage least squares method. The study recommends that policies promoting economic freedom are essential to mitigate global environmental degradation.

Transcriptional signatures of gray matter volume changes in mild traumatic brain injury

BackgroundNeuroimaging studies have shown that patients with mild traumatic brain injury (mTBI) often exhibit changes in gray matter volume (GMV) in the brain. However, the results regarding these changes are inconsistent, and the underlying molecular mechanisms remain unclear. This study aimed to investigate GMV changes in mTBI patients and uncover the molecular mechanisms driving these alterations. MethodsWe conducted a neuroimaging meta-analysis on nine studies, involving 396 mTBI patients and 338 healthy controls, to identify consistent patterns of GMV changes. Additionally, we utilized the Allen Human Brain Atlas database to explore transcriptome-neuroimaging spatial correlations, identifying genes whose expression profiles are linked to GMV changes in mTBI patients. Enrichment analyses were also performed to determine the biological significance of the altered GMV-related genes. ResultsWe observed consistent GMV increases in the bilateral middle cingulate/paracingulate gyri, right striatum, and right dorsolateral superior frontal gyrus, along with GMV decreases in the right insula and left lingual gyrus. Moreover, we found spatial associations between mTBI-related GMV changes and the expression of 977 genes, which were primarily enriched in specific biological processes, body tissues, and developmental time windows of the cerebral cortex. ConclusionOur findings improve the understanding of GMV abnormalities in mTBI patients and provide insights into the molecular mechanisms underlying these changes.

Managing urban heat islands in Rajarhat-Newtown, India, with the help of greenery and waterscapes

This study aims to fill the research gap by assessing the efficacy of urban blue-green infrastructure in reducing the impacts of Urban Heat Island (UHI) over the newly developed satellite township of Kolkata in the Rajarhat Area. In that process, land-use transformation mapping for the last 40 years (1987-2020) is executed and correlated with LST dynamics. Afterwards, the UHI is mapped, and the Local Indicators of Spatial Autocorrelation (LISA) is measured to determine the spatial association of urban hot and coldspots. Results show that between 1987 to 2020, nearly 914% (11.35 km2) of the built-up Area was increased. Accordingly, the mean LST of the entire Area increased by 6°C. Increased temperature has led to the development of UHI patches over bare and impervious areas until new urban green spaces and water features started functioning as coldspots, cooler by 4°C - 6°C than their adjacent hotspots. The efficacy of urban water bodies in mitigating UHI is observed significant compared to vegetation; water bodies dipped the LST by 1.5°C - 2°C more than vegetated areas. UHI management techniques are rarely evaluated in developing countries; urban managers should incorporate these findings into their future planning to mitigate urban thermal discomfort.