The examination of the characteristic law of traditional village transformation over time represents a vital nexus in cultural heritage preservation and the transmission of vernacular culture. Historical event points were used to augment village development information, facilitating the restoration of the village\'s historical pattern. Geographical analysis methods, including Standard Deviation Ellipse Analysis (SDSEA), Nearest Neighbor Analysis (NNA), and Source-Destination Analysis (SDA), were employed to explore the characteristics of the village\'s geographical center of gravity, changes in concentration and dispersion, and functional transfer. The stepwise progression of the village\'s evolution was investigated, as well as the mechanism of residents\' behavior during the evolution process. The results reveal: 1) The spatial evolution of the settlement shows a trend of agglomeration. As time passes, the center of gravity of each functional space gradually converges, and the average distance between elements decreases, resulting in a shift from a dispersed to a clustered distribution. 2) The village space changes from simple to complex due to the conduct of the villagers. Residential behaviors promote the establishment of residential space and the development of public and commercial space. The usage, abandonment, and functional transitions that occur inside the space cause functional zones to nest with each other, resulting in a more intricate spatial structure. 3) Both the degree of change and the preservation of the village\'s functional space show an increasing trend, indicating that the protection of the built space and the expansion of the unbuilt space occur simultaneously. This represents a developmental trend that is consistent with the social surroundings and the villagers\' ambitions.

It is significant to systematically quantify the propagation thresholds of meteorological drought to different levels of agricultural drought in karst areas, and revealit\'s the propagation driving mechanisms. This can guide early warning and fine management of agricultural drought. In this study,we selected Guizhou Province as an example. The standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI) were used to characterize meteorological and agricultural drought. The run theory was used to identify, merge and eliminate drought events. The maximum correlation coefficient was used to capture the propagation time of meteorological-agricultural drought. The regression models were used to quantify the propagation intensity threshold from meteorological drought to different levels of agricultural drought. Finally, the propagation threshold driving mechanism was explored using geographical detectors. The results show that: (1) in terms of temporal variations during the past 21 years, regional meteorological drought had a shorter duration and a higher intensity than agricultural drought, Particularly, 2011 was a year of severe drought, and agricultural drought was significantly alleviated after 2014. (2) In terms of spatial variations, the \"long duration area\" of meteorological drought duration showed an \"S\" shaped distribution in the northeast, and the \"short duration area\" showed a point-like distribution. The overall duration of agricultural drought showed a spatial distribution of northeast to \"medium-high in the northeast and low in the southwest. (3) The drought propagation time showed an alternating distribution of \"valley-peak-valley-peak\" from southeast to northwest. In terms of propagation intensity thresholds, light drought showed an overall spatial distribution of high in the east and low in the west. Moderate, severe, and extreme droughts showed a spatial distribution of low in the center north of southern Guizhou) and high in the borders. (4) There was a strong spatial coupling relationship between karst development intensity, altitude and meteorological-agricultural drought propagation thresholds. The interaction of different factors exhibited a two-factor enhancement and nonlinear enhancement on the propagation threshold. This indicates that synergistic effects of different factors on the propagation threshold were larger than single-factor effects.

An aging population is one of the main features of China\'s current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province\'s southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced multi-scale geographical weighted regression to explore its influencing factors. The results show that Anshun City\'s older people population proportion (OPP) is generally high with more than 7% of the older people there, making it part of an aging society. The OPP appeared high in the east and low in the west in spatial distribution; the older people population density (OPD) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.

The topographical, geological, climatic and biodiversity complexity of Mesoamerica has made it a primary research focus. The Mesoamerican highlands is a region with particularly high species richness and within-species variation. The Cinnamon-bellied Flowerpiercer, Diglossa baritula (Wagler, 1832), is a species endemic to the Mesoamerican highlands, with three allopatric subspecies currently recognized. To characterize divergence within this species, we integrated genomics, morphology, coloration and ecological niche modeling approaches, obtained from sampling individuals across the entire geographic distribution of the species. Our results revealed a clear genomic divergence between the populations to the east versus the west of the Isthmus of Tehuantepec. In contrast to the genomic results, morphology and coloration analyses showed intermediate levels of differentiation, indicating that population groups within D. baritula have probably been under similar selective pressures. Our morphology results indicated that the only sexually dimorphic morphological variable is the wing chord, with males having a longer wing chord than females. Finally, ecological data indicated that there are differences in ecological niche within D. baritula. Our data suggest that D. baritula could contain two or more incipient species at the intermediate phase of the speciation continuum. These results highlight the importance of the geographical barrier of the Isthmus of Tehuantepec and Pleistocene climatic events in driving isolation and population divergence in D. baritula. The present investigation illustrates the speciation potential of the D. baritula complex and the capacity of Mesoamerican highlands to create cryptic biodiversity and endemism.

The licensed cannabis industry represents one of the top five most economically valued agricultural commodities in California, yet farming largely remains on remote, environmentally sensitive, \"marginal\" lands. Using mixed methods, this paper examines the determinants of this marginalization, their embedded elaboration, and their relation to historical policy regimes. We used Generalized Additive Models (GAMs) to determine the most important predictors of licensed cannabis industry development since the inception of a statewide licensing program in 2018 and to compare the distribution of licensed cannabis to other forms of rural agriculture, including vineyards and pasture, to understand landscape factors and environmental sensitivity of land uses. We found that a county\'s median income and the extent of traditional (non-cannabis) agriculture, as measured by the proportion of on-farm (non-cannabis) employment, were both negatively associated with its amount of licensed cannabis agriculture. Ethnographic data suggests that cannabis is often excluded from traditional agricultural areas, through formal local-level bans, restrictive zoning, high \"prime\" farmland values, and cultural exclusions from other powerful resource users. The resulting relegation to \"marginal\" lands foments conflicts with amenity land users and environmentalists, even as it partly supports \"legacy\" cultivators whose farms were established under prior policy regimes. Results suggest that cannabis is more likely to be grown under conditions that introduce regulatory hurdles, including farming on steeper slopes, with natural streams onsite, and without access to large groundwater aquifers for irrigation. Our findings suggest that failure to allow licensed cannabis farming in traditional agriculture regions has led to a self-fulfilling prophecy wherein cannabis cultivation is largely relegated to environmentally sensitive areas where cultivation activity has an elevated tendency for environmental impacts.

Identifying risk areas for envenomation by animals is relevant for public health, such as strategic distribution of antivenoms. Coral snakes are highly diverse in the Amazon, inhabit natural and human-modified environments, and the outcome of the cases tends to be serious and potentially lethal due to their neurotoxic venom. By integrating species\' geographical records and environmental variables, we used species distribution modeling to predict the distribution of coral snake species in the Brazilian Amazonia. We analyzed the relationship between the predicted distribution of coral snake species, along with envenomation data in the region, to propose actions to reduce the number of cases and to provide tools for a better policy of public health. We conclude that the entire Amazon shows high environmental suitability for coral snakes, and such suitability explains little about the incidence of cases. This is probably due to the low human density in the Amazon and to coral snake traits such as secretive habits and non-agressive behavior. Differently from other venomous snakes, the scenario regarding coral snakebites precludes the detection of prominent geographical areas of concern and demands a broad and equitable availability of health centers throughout Amazonia and along other areas of occurrence of the genus Micrurus.

BACKGROUND: Pediatric out-of-hospital cardiac arrest (POHCA) is associated with significant mortality and poor neurological outcomes. We aimed to describe the association between sociodemographic factors and POHCA risk in Ontario, Canada.
RESULTS: We conducted a province-wide case-control study at ICES, where patient records are linked across administrative databases. The case group included children (aged 1 day to 17 years) who experienced an out-of-hospital cardiac arrest between 2004 and 2020. Controls were matched up to 1:4 on age, sex, index date, and key comorbidities. We used conditional logistic regression to measure the association between sociodemographic indicators and POHCA risk. The case and control groups included 1826 and 7254 children, respectively. Children living in areas with the highest levels of material deprivation (adjusted odds ratio [aOR], 2.35 [95% CI, 1.94-2.85]) and dependency (aOR, 1.22 [95% CI, 1.01-1.48]) had a higher odds of POHCA, relative to children living in regions with the lowest levels of material deprivation and dependency, respectively. Children living in neighborhoods with the lowest levels of ethnic diversity had a higher odds of POHCA (aOR, 1.62 [95% CI, 1.30-2.01]), relative to children living in neighborhoods with the highest levels of ethnic diversity. The odds of POHCA were lower in immigrants (aOR, 0.67 [95% CI, 0.47-0.95]), relative to the general population. Northern urban residence was associated with a higher odds of POHCA (aOR, 1.45 [95% CI, 1.13-1.87]), relative to southern urban residence.
CONCLUSIONS: Children living in neighborhoods with high levels of marginalization may have an elevated risk of experiencing POHCA. These findings highlight the importance of addressing disparities through targeted prevention and intervention efforts.

This study introduces Multi-dimensional Disparity Index (MDI) to measure multi-form of disparity in different level of governments referencing Nepal. The measurement scale of MDI was developed by adopting Santos and Alkire\'s (2011) approaches. A wide range of thematic experts was consulted, employing the Semi-Delphi approach to determine its dimensions and indicators. The MDI in this study includes six dimensions and 34 indicators composited with dimension-wise indices like Economy Disparity Index [ECODI], Educational Disparity Index [EDUDI], Health Disparity Index [HDI], Geography and Climatic Vulnerability Index [GCVI], Living Standard Disparity Index [LSDI], and Demography Disparity Index [DDI]. Overall, the study revealed the extent of multi-dimensional disparity across three tiers of government in Nepal. More specifically, Nepal scored 0.388 MDI value. Karnali and Bagmati provinces are accounted as the highest and least deprived. This study contributes essential knowledge, particularly in exploring the dimensions and their indicators and develops an approach to measure multi-dimensional disparities. Most existing approaches for assessing disparities are mono-dimensional and measure the disparities in a single aspect. In this context, MDI provides a broader approach to consider multiple dimensions and measures multiple aspects in a country like Nepal, where disparity manifests at multiple levels.

The digital economy (DE) not only drives economic innovation and development but also has significant environmental effects by promoting lower carbon emissions. To investigate the spatial effects of DE on urban carbon emissions, this study comprehensively measures the level of DE development based on the panel data from 11 typical cities in Zhejiang Province from 2011 to 2020, by comparing analysis using different regression models. The following conclusions are obtained: (1) The total carbon emissions (TC) of Zhejiang cities in general show a fluctuating change trend of first increasing and then slowly decreasing, while carbon emission intensity and carbon emission per capita in general show a fluctuating change trend of decreasing. Cities with high TC are primarily concentrated in the Hangzhou Bay city cluster, accounted for 62 ~ 65% of the province\'s carbon emissions. The development of the DE in Zhejiang cities shows steady growth, but there are large differences among cities, with Hangzhou and Ningbo standing out as particularly prominent. (2) There is a significant inverted U-shaped relationship between the DE and the level of carbon emissions in Zhejiang Province. The influence coefficient of the DE on the primary term of TC is 0.613, and the influence coefficient of the quadratic term of TC is - 1.008. (3) In terms of the spatial spillover effect of the DE on carbon emissions, the study finds that compared to the direct effect, the spatial spillover effect is not significant. However, the allocation of transport resources shows a positive spatial spillover effect (increasing carbon emissions, coefficient value is 0.138), while technological progress shows a somewhat negative spatial spillover effect (decreasing carbon emissions, coefficient value is - 0.035). (4) The study also finds that the smart city pilot policy significantly reduces urban carbon emissions. Moreover, the effect of the DE on carbon emissions is confirmed through the significance test of the quadratic term when replacing the geographical and economic distance weight matrices. This indicates that the empirical findings are robust to these tests. Finally, several countermeasures to reduce carbon emissions are proposed from the perspective of DE development.

With the rapid advancement of urbanization, the green space well-being (GSWB) of developing countries faces drastic changes and is increasingly threatened. Green and residential spaces are the core elements of GSWB; however, we know very little about the interaction and combination of the two in terms of their effect on GSWB. This study identified the spatiotemporal features of GSWB and critically examined how patterns of residential-green combinations affect GSWB. Based on land-use data for Jinan from 2006 to 2018, and using the spatial measurement tool GeoDa, we found that both green and residential space have increased significantly in central Jinan. At the macro level, the spatial correlation between the two decreased significantly; meanwhile, at the micro level, there are obvious differences in time and geography. This led to differences in the distribution of GSWB between regions with high value and those with low value. We revealed that the development, preservation, and demolition of residential and green spaces influence changes in GSWB. The positive effects on GSWB come from (1) mountain park development policy in built-up areas, (2) theme park development policy in new urban areas, and (3) urban renewal and demolition policy. The negative effects on GSWB come from (1) issues remaining from prior extensive urban development, (2) the replacement of central areas driven by urban branding, and (3) the lack of supervision of nearby facilities for new housing development. To better understand changes in GSWB, it is necessary to consider its internal residential-green spatial collaboration and propose targeted response strategies. This can help to better safeguard the quality of human settlements in the process of urbanization in developing countries.