Cold Spots Research Articles

How do productivity gradient and diffusion shape patterns in a plant–herbivore grazing system?

Natural systems show heterogeneous patchy distributions of vegetation over large landscapes. Reaction–diffusion systems can demonstrate such heterogeneity of species distributions. Here, we analyse a reaction–diffusion model of plant–herbivore interactions in two-dimensional space to illustrate non-homogeneous distributions of plants and herbivores. The non-spatial system shows bottom-up control, where herbivore density is low under low and high primary productivity but increased at intermediate productivity. In addition, the non-spatial system provides bistability between a dense vegetation state devoid of herbivores and a coexisting state of plants and herbivores. In the spatiotemporal model, we give analytical conditions of occurring diffusion-driven (Turing) instability, where a novel point in our model is the relative dispersal of herbivores, which represents the movement of herbivores from a higher to a lower vegetation state in addition to the self-diffusion of both species. It is shown that heterogeneity in the population distribution does not occur if the relative dispersal of herbivores is low, but it appears in the opposite case. Due to bistability in the underlying non-spatial system, the spatiotemporal model produces initial value-dependent patterns. The two initial values make different patterns despite having the same primary productivity and relative dispersal rate. As productivity increases with a given relative herbivore dispersal, pattern transition occurs from a blend of stripes and spots of low vegetation state to a predominantly low-density vegetation state with smaller patches of densely vegetated states with one initial value. On the contrary, a discernible change in vegetation patterns from cold spots in the dense vegetation to hot stripes in the primarily low-vegetated state is noticed under the other initial population value. Furthermore, the population distributions of plants and herbivores in the entire domain after a long period are heterogeneous for both initial values, provided the relative herbivore dispersal is substantial. We estimated mean population densities to observe species fitness in the whole domain under variable productivity. When productivity is high, the mean population density of plants may go up or down, depending on the herbivore’s relative dispersal rate. In contrast to the bottom-up control dynamics of the non-spatial system, the system exhibits a top-down control under high relative dispersal, where the herbivore regulates vegetation growth under high productivity. On the other hand, herbivores are extinct under high productivity if the relative dispersal is low.

ИНТЕРПРЕТАЦИЯ ГОРЯЧИХ ПЯТЕН УЛЬТРАФОЛЕТОВОГО МУТАГЕНЕЗА, ОБРАЗУЮЩИХСЯ НА ЗАПАЗДЫАЮЩЕЙ НИТИ ДВУХЦЕПОЧЕЧНОЙ ДНК ГЕНА supF

At present, the mechanism of formation of hot and cold spots of ultraviolet mutagenesis is not clear. I developed a polymerase-tautomeric model of the mechanism of formation of hot and cold spots of ultraviolet mutagenesis and showed that the probability of mutation formation depends on the processes of propagation of excitation energy along the DNA molecule. In my proposed polymerase-tautomeric model of ultraviolet mutagenesis, it was shown that mutations are formed opposite only those cis-syn cyclobutane pyrimidine dimers, one or both of which are in rare tautomeric forms. In the polymerase-tautomeric model of the mechanism of formation of hot and cold spots of ultraviolet mutagenesis, I have shown that the hot spots of ultraviolet mutagenesis are those cis-syn cyclobutane pyrimidine dimers to which the most excitation energy is transferred. In a number of works, I calculated the relative probabilities of mutations formed opposite the DNA bases that are part of the cis-syn cyclobutane pyrimidine dimers that appeared upon irradiation of double-stranded DNA of the supF gene. In this article, based on the results of previous calculations, I interpret experimental data in which hot spots of ultraviolet mutagenesis are DNA regions consisting of three or more pyrimidine DNA bases arranged in a row.

The Spatial Scale and Spread of Child Victimization.

Previous research shows that large, densely populated urban areas have higher rates of child victimization that have persisted over time. However, few investigations have inquired about the processes that produce and sustain hot and cold spots of child victimization. As a result, the mechanisms that produce the observed spatial clustering of child victimization, and hence "why" harms against children tend to cluster in space, remains unknown. Does the likelihood of being a victim of violence in one location depend on a similar event happening in a nearby location within a specified timeframe? Rather, are child victims of violence more likely to reside in suboptimal neighborhood conditions? This paper aims to present an analytical and theoretical framework for distinguishing between these locational (point) processes to determine whether the empirical spatial patterns undergirding child victimization are more reflective of the "spread" via contagion (i.e., dependency) or whether they are produced by neighborhood structural inequality resulting from spatial heterogeneity. To detect spatial dependence, we applied the inhomogeneous K-function to Los Angeles Medical Examiner data on child homicide victim locations while controlling for regional differences in victimization events (i.e., heterogeneity). Our analysis found strong evidence of spatial clustering in child victimization at small spatial scales but inhibition at larger scales. We further found limited support for the spatiotemporal clustering of child victimization indicative of a contagion effect. Overall, our results support the role of neighborhood structural vulnerability in the underlying mechanisms producing patterns of child victimization across Los Angeles County. We conclude by discussing the policy implications for understanding this spatial patterning in geographical context and for developing effective and targeted preventive interventions.

Spatiotemporal dynamic evolution and influencing factors of land use carbon emissions: evidence from Jiangsu Province, China

Land use/cover change has an important impact on global climate change and carbon cycle, and it has become another major source of carbon emission after energy consumption. Therefore, this study focuses on the main line of “land use carbon emissions-spatial and temporal patterns-influencing factors,” and selects 13 cities in Jiangsu Province as the research object. Based on the data of land use and energy consumption, combined with the method of land use carbon emissions and ArcGIS technology, this study conducted a quantitative analysis of the spatio-temporal distribution of carbon emissions in Jiangsu Province. The factors affecting the spatial distribution of carbon emissions from land use in Jiangsu Province were discussed by using Geographic detector. The results show that: 1) Carbon emissions in Jiangsu Province showed an overall growth trend, from 16215.44 ×104tC in 2010–23597.68 ×104tC in 2020, with an average annual growth rate of 4.55%, of which the construction land and watersheds had a greater impact on carbon sources and sinks, respectively. 2) During the period, there were significant differences in carbon emission levels among different cities in Jiangsu Province, and the land use carbon emission in Jiangsu Province showed a stable spatial pattern of “northwest—southeast.” The southern part of Jiangsu is always the hot area of carbon emission, while the cold spot area is mainly distributed in the northern and central parts of Jiangsu. 3) The interaction of factors such as economic development, industrial structure, energy intensity, land use and human activities is an important reason for the spatio-temporal differences of land use carbon emissions in Jiangsu Province. Among them, the level of urbanization, population size and economic aggregate have significant effects on carbon emissions.

Assessing the environmental factors affecting the sustainability of Aini Falaj system.

This study investigates the spatial distribution patterns and environmental factors influencing the Aini Falaj system in a specific study area. The research findings are presented through the lens of the following four categories: collinearity diagnostics, spatial autocorrelation analysis, kernel density (KD) findings, and multivariate geographically weighted regression (MGWR) analysis. The collinearity diagnostics were applied to examine the interrelationships among 18 independent environmental variables. The results indicate the absence of significant multicollinearity concerns, with most variables showing values below the critical threshold of five for variance inflation factors (VIFs). The selected variables indicate minimal intercorrelation, suggesting that researchers should be confident utilizing them in subsequent modelling or regression analyses. A spatial autocorrelation analysis using Moran's Index revealed positive spatial autocorrelation and significant clustering patterns in the distribution of live and non-functional Aini Falajs. High concentrations of live or dead Falajs tended to be surrounded by neighbouring areas with similar characteristics. These findings provide insights into the ecological preferences and habitat associations of Aini Falajs, thereby aiding conservation strategies and targeted studies. The kernel density (KD) analysis depicted distribution patterns of live and dry Aini Falajs through hotspots and cold spots. Specific regions exhibited high-density areas of live Falajs, indicating favourable environmental conditions or historical factors contributing to their concentrated distribution. Identifying these high-density zones can enhance our understanding of the spatial patterns and potential factors influencing the prevalence and sustainability of Aini Falajs. The multivariate geographically weighted regression (MGWR) models revealed strong associations between the live or dead status of Aini Falajs and environmental factors. The precipitation, topographic wetness index (TWI), aspect and slope exerted positive impacts on the live status, while evaporation, solar radiation, distance to drains and drain density exerted negative influences. Similar associations were observed for the dead status, emphasising the importance of controlling evaporation, shading mechanisms, proper drainage planning and sustainable land-use practices. This study provides valuable insights into the spatial distributions and factors influencing the live and dead status of Aini Falajs, thereby contributing to our understanding of their ecological dynamics and guiding conservation efforts and management strategies.

Seabirds reveal mercury distribution across the North Atlantic

Mercury (Hg) is a heterogeneously distributed toxicant affecting wildlife and human health. Yet, the spatial distribution of Hg remains poorly documented, especially in food webs, even though this knowledge is essential to assess large-scale risk of toxicity for the biota and human populations. Here, we used seabirds to assess, at an unprecedented population and geographic magnitude and high resolution, the spatial distribution of Hg in North Atlantic marine food webs. To this end, we combined tracking data of 837 seabirds from seven different species and 27 breeding colonies located across the North Atlantic and Atlantic Arctic together with Hg analyses in feathers representing individual seabird contamination based on their winter distribution. Our results highlight an east-west gradient in Hg concentrations with hot spots around southern Greenland and the east coast of Canada and a cold spot in the Barents and Kara Seas. We hypothesize that those gradients are influenced by eastern (Norwegian Atlantic Current and West Spitsbergen Current) and western (East Greenland Current) oceanic currents and melting of the Greenland Ice Sheet. By tracking spatial Hg contamination in marine ecosystems and through the identification of areas at risk of Hg toxicity, this study provides essential knowledge for international decisions about where the regulation of pollutants should be prioritized.

Identification of Important Wetlands and Optimization of Landscape Patterns Based on Human Pressure Index: The Case of the Linghekou Wetland in China

The Linghekou wetland is a rich repository of ecological resources and serves as an important habitat for numerous rare and protected animals. However, due to a confluence of natural and anthropogenic factors, the ecological environment of the Linghekou wetland is facing a multitude of threats, including the reduction in wetland area, the degradation of wetland resources, and the instability of ecological structure. This paper employs an anthropogenic focus, utilizing the human pressure index (HPI), spatial autocorrelation, and cold and hot spot methods to identify crucial wetlands. These identified wetlands are then utilized as ecological source sites to optimize the landscape pattern of the Linghekou wetland, employing the minimum cumulative resistance (MCR) model. The final results indicated the identification of 6 ecological sources, 8 ecological corridors, and 42 ecological nodes. These were primarily concentrated in the southern region of the study area and were distributed in a reasonable manner. The method of identifying ecological sources when optimizing the landscape pattern with the MCR model was enriched by this approach. Additionally, the paper offers recommendations for the optimization of the landscape pattern of the Linghekou wetland and establishes a foundation for the protection and restoration of other similar wetlands.

Spatiotemporal Evolution and Factors Influencing Regional Ecological Land in a Multidimensional Perspective: A Case Study of the Beijing–Tianjin–Hebei Region

A systematic analysis of the spatiotemporal evolution patterns and factors influencing ecological land (EL) can support the optimization of EL protection policies and ensure the stability of regional ecosystems. Based on remote sensing data, using the gravity center shift model, the landscape pattern index, and the equivalent factor method, the characteristics of EL evolution in the Beijing–Tianjin–Hebei (BTH) region from 1980 to 2020 were analyzed. A fixed-effects model was used to quantitatively explore the factors influencing EL evolution and heterogeneity analysis. The results are as follows: (1) The EL area exhibited a trend of initial decrease followed by a subsequent increase during the study period. The most significant area transfer occurred between cropland and EL, but, after the 21st century, the proportion of area transfer between construction land and EL noticeably increased. (2) The compactness and fragmentation of EL showed a certain spatiotemporal stability, but the spatial distribution of compactness and fragmentation hot and cold spots exhibited significant differences. The fragmentation hot spots mainly displayed a strip distribution, while those of compactness showed a clustered distribution. (3) Although the ecosystem service value in the BTH region demonstrated dynamic “M”-shaped changes, the distribution of hot and cold spots still exhibited spatial stability. Regulating services consistently occupied a higher proportion of the sub-service functions, while cultural services still needed further enhancement. (4) Factors influencing the evolution of areas and values demonstrated similarities. The landscape was significantly influenced by construction land, showing a non-linear “U”-shaped relationship with fragmentation. Different economic development gradients and altitudes exhibited differentiated characteristics in terms of their influencing factors. This study provides scientific support for dynamically and precisely adjusting governmental EL management policies, contributing to the sustainable development of regional socio-economics.

Efficacy and safety of sympathetic mapping and ablation of renal nerves for the treatment of hypertension (SMART): 6-month follow-up of a randomised, controlled trial

Previous trials of renal denervation (RDN) have been designed to investigate reduction of blood pressure (BP) as the primary efficacy endpoint using non-selective RDN without intraoperatively verified RDN success. It is an unmet clinical need to map renal nerves, selectively denervate renal sympathetic nerves, provide readouts for the interventionalists and avoid futile RDN. We aimed to examine the safety and efficacy of renal nerve mapping/selective renal denervation (msRDN) in patients with uncontrolled hypertension (HTN) and determine whether antihypertensive drug burden is reduced while office systolic BP (OSBP) is controlled to target level (＜140mmHg). We conducted a randomized, prospective, multicenter, single-blinded, sham-controlled trial. The study combined two efficacy endpoints at 6 months as primary outcomes: The control rate of patients with OSBP ＜140mmHg (non-inferior outcome) and change in the composite index of antihypertensive drugs (Drug Index) in the treatment versus Sham group (superior outcome). This design avoids confounding from excess drug-taking in the Sham group. Antihypertensive drug burden was assessed by a composite index constructed as: Class N (number of classes of antihypertensive drugs)×(sum of doses). 15 hospitals in China participated in the study and 220 patients were enrolled in a 1:1 ratio (msRDN vs Sham). The key inclusion criteria included: age (18-65 years old), history of essential HTN (at least 6 months), heart rate (≥70 bpm), OSBP (≥150mmHg and ≤180mmHg), ambulatory BP monitoring (ABPM, 24-h SBP ≥130mmHg or daytime SBP ≥135mmHg or nighttime SBP ≥120mmHg), renal artery stenosis (＜50%) and renal function (eGFR ＞45mL/min/1.73m2). The catheter with both stimulation and ablation functions was inserted in the distal renal main artery. The RDN site (hot spot) was selected if SBP increased (≥5mmHg) by intra-renal artery (RA) electrical stimulation; an adequate RDN was confirmed by repeated electronic stimulation if no increase in BP otherwise, a 2nd ablation was performed at the same site. At sites where there was decreased SBP (≥5mmHg, cold spot) or no BP response (neutral spot) to stimulation, no ablation was performed. The mapping, ablation and confirmation procedure was repeated until the entire renal main artery had been tested then either treated or avoided. AftermsRDN, patients had to follow a predefined, vigorous drug titration regimen in order to achieve target OSBP (＜140mmHg). Drug adherence was monitored by liquid chromatography-tandem mass spectrometry analysis using urine. This study is registered with ClinicalTrials.gov (NCT02761811) and 5-year follow-up is ongoing. Between July 8, 2016 and February 23, 2022, 611 patients were consented, 220 patients were enrolled in the study who received standardized antihypertensive drug treatments (at least two drugs) for at least 28 days, presented OSBP ≥150mmHg and ≤180mmHg and metall inclusion and exclusion criteria. In left RA and right RA, mapped sites were 8.2 (3.0) and 8.0 (2.7), hot/ablated sites were 3.7 (1.4) and 4.0 (1.6), cold spots were 2.4 (2.6) and 2.0 (2.2), neutral spots were 2.0 (2.1) and 2.0 (2.1), respectively. Hot, cold and neutral spots was 48.0%, 27.5% and 24.4% of total mapped sites, respectively. At 6M, the Control Rate of OSBP was comparable between msRDN and Sham group (95.4% vs 92.8%, p=0.429), achieved non-inferiority margin-10% (2.69%; 95% CI-4.11%, 9.83%, p ＜ 0.001 for non-inferiority); the change in Drug Index was significantly lower in msRDN group compared to Sham group (4.37 (6.65) vs 7.61 (10.31), p=0.010) and superior to Sham group (-3.25; 95% CI-5.56,-0.94, p=0.003), indicating msRDN patients need significantly fewer drugs to control OSBP ＜140mmHg. 24-hour ambulatory SBP decreased from 146.8 (13.9) mmHg by 10.8 (14.1) mmHg, and from 149.8 (12.8) mmHg by 10.0 (14.0) mmHg in msRDN and Sham groups, respectively (p<0.001 from Baseline; p>0.05 between groups). Safety profiles were comparable between msRDN and Sham groups, demonstrating the safety and efficacy of renal mapping/selective RDN to treat uncontrolled HTN. The msRDN therapy achieved the goals of reducing the drug burden of HTN patients and controlling OSBP <140mmHg, with only approximately four targeted ablations per renal main artery, much lower than in previous trials. SyMap Medical (Suzhou), LTD, Suzhou, China.

Updated geographic distributions for Texas reptiles

As is the case for many taxa in the Anthropocene, reptile conservation is challenged by an assortment of human-mediated factors. Distributional data for reptile species can be highly useful for informing conservation action. For example, species occurrence data can be used to model suitable habitat as well as quantify contraction, expansion, or shift in the distribution of a species. Texas, USA has a rich reptile fauna including one crocodilian, 32 testudine, 55 lacertilian, and 82 serpent species. However, literature pertaining to the distribution of these species has not been synthesized for over a decade. The goals of our study were to visually summarize all published distributional data for reptile species in the state with updated distribution maps; to tabulate all novel and historic distribution data that is absent from the last statewide synthesis; and to characterize any taxonomic, geographic, or temporal trends of distribution record reporting that have occurred in the state over the last decade. We discovered a total of 659 records that supplement the maps provided in the last statewide synthesis, 40% of which were found in published materials that predate that synthesis. Regarding distributional records published over the last decade, there was no apparent temporal trend – record reporting across years appeared to be stochastic. The number of records published for reptile families generally followed patterns of species richness, although several families had fewer or more records than would be expected. These results might be due to several factors including species biology, variable rates of potential range spread or contraction, and variable research attention (historically and contemporarily). Spatially, we found hot spots of record reporting in the southern, western, and northern portions of the state. We suspect these represent either a contemporary geographic bias of research attention, historically poor range characterization for reptile species occupying these regions, or a combination of both. We also found cold spots of record reporting in the northwestern portion of the Panhandle. These are likely due to natural patterns of reptile diversity as well as geographically biased research attention. Future work to be conducted on reptile distributions in Texas should include a thorough synthesis and revisiting of the voucher specimen data associated with these records.

Abstract PO3-10-03: Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality

Abstract Title: Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality Background: Poverty is known to lead to the worst breast cancer (BC) outcomes, at the individual and county level. However, we believe that the relationship between poverty and breast cancer mortality is more complex and can be influenced by the economic status and available resources of the surrounding neighborhoods. Our goal is to understand to what extent poverty in the surrounding neighborhood may contribute to breast cancer mortality on a national scale and the county areas at the highest risk. Methods: This study examines the association between neighborhood effects of poverty on overall and BC mortality among women diagnosed between 2005 and 2019 from NCI SEER. We also obtained county-level five-year poverty estimates from the American Community Survey. Counties with poverty estimates above or below the national mean were high-poverty (H) or low-poverty (L) counties, respectively. We then used local indicators of spatial autocorrelation (LISA) analysis with Local Moran’s I of the poverty estimates and their H- and L-county categorization to define four neighborhood poverty environments for US counties. Specifically, H-counties among other H-counties were classified as poverty hotspots (HH) counties, L-counties among other L-counties were classified as poverty cold spots (LL), H-counties among LL-counties were HL-counties, and L-counties among HH-counties were LH-counties. Non-Hispanic White (NHW), Non-Hispanic Black, and Hispanic women at least 20 years of age diagnosed with local, regional, or distal stage BC between 2005-2009 and 2010-2014 that survived more than one year after diagnosis were aggregated by county of residence at diagnosis to determine their neighborhood poverty environment at BC diagnosis. Women included in the study had a Local Moran's I p-value less than or equal to 0.3 for their county of residence. A Poisson regression model that adjusts for age at diagnosis, race/ethnicity (NHW vs. not-NHW), BC stage, year of diagnosis (2005-2009 vs. 2010-2014), both local and systemic treatment except for hormone therapy, and Estrogen Receptor (ER) status (negative vs. positive) was used to assess the effects of county-level poverty cluster types on BC mortality. Results: Our analysis includes 24,070 women diagnosed with BC, of which 6,919 women died, and 2,262 of these deaths were specific to BC. In total, 4,528 women were in HH counties from CA, GA, KY, LA, NM, UT, and HI; 14,112 women were in LL counties; 4,338 women were in HL counties; 1,092 women were in LH counties. Women in HH, LH, and HL counties had a 1.28 (95%CI:1.15,1.42), 1.23 [95%CI:1.01-1.48], and 1.05 [CI: 0.93,1.17] relative risk of cause-specific BC death respectively when compared to deaths in LL counties after adjustment for year of diagnosis, age at diagnosis, race/ethnicity, stage at diagnosis, treatment, and estrogen receptor status. When stratified by ER status or BC stage at diagnosis, the relative risk of BC mortality for women in HH counties diagnosed with ER-positive, local or regional stage had a 1.35 (95% CI: 1.19,1.52), 1.32 (95%CI: 1.13,1.54), and a 1.21 (95%CI:1.02,1.43) when compared to women in LL counties, respectively. Our analysis also showed that total death trends were similar to the trends observed in cause-specific deaths. In addition, we observed similar total and cause-specific BC death trends when using a p-value of 0.05 for the LISA analysis. Conclusion: We use LISA spatial clustering to demonstrate the impact national poverty neighborhood environments have on BC mortality, thus identifying counties of worst BC outcomes through neighborhood poverty environments. Our findings suggest that prioritization of resource allocations to HH counties would significantly improve BC outcomes. Citation Format: Ifeoma Nwigwe, Michael Desjardins, Kala Visvanathan. Nationwide Impact of Neighborhood Poverty Hotspots on Breast Cancer Mortality [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-10-03.

Spatiotemporal dynamics of prey-predator model incorporating Holling-type II functional response with fear and its carryover effects.

The recent focus in the fields of biology and ecology has centered on the significant attention given to the mathematical modeling and analyzing the spatiotemporal population distribution among species engaged in interactions. This paper explores the dynamics of the temporal and spatiotemporal delayed Bazykin-type prey-predator model, incorporating fear and its carryover effect. In our model, we incorporated a functional response of the Holling-type II. In the temporal model, a detailed dynamic analysis was carried out, investigating the positivity and boundedness of solutions, establishing the uniqueness and existence of positive interior equilibria, and examining both local and global stability. Additionally, we explored the presence of saddle-node, transcritical, and Hopf bifurcations varying attack rate parameter. The delayed system shows highly periodic behavior. Additionally, for the spatiotemporal model, we provide a complete analysis of local and global stability, and we derive the conditions for the existence of Turing instability for both self-diffusion and cross-diffusion, respectively. The two-dimensional diffusive model is further discussed, highlighting various Turing patterns, including holes, stripes, and hot and cold spots, along with their biological significance. Numerical simulations are executed to validate the analytical findings in both temporal and spatiotemporal models.

Cold Spot SCANNER: Colab Notebook for predicting cold spots in protein–protein interfaces

BackgroundProtein–protein interactions (PPIs) are conveyed through binding interfaces or surface patches on proteins that become buried upon binding. Structural and biophysical analysis of many protein–protein interfaces revealed certain unique features of these surfaces that determine the energetics of interactions and play a critical role in protein evolution. One of the significant aspects of binding interfaces is the presence of binding hot spots, where mutations are highly deleterious for binding. Conversely, binding cold spots are positions occupied by suboptimal amino acids and several mutations in such positions could lead to affinity enhancement. While there are many software programs for identification of hot spot positions, there is currently a lack of software for cold spot detection.ResultsIn this paper, we present Cold Spot SCANNER, a Colab Notebook, which scans a PPI binding interface and identifies cold spots resulting from cavities, unfavorable charge-charge, and unfavorable charge-hydrophobic interactions. The software offers a Py3DMOL-based interface that allows users to visualize cold spots in the context of the protein structure and generates a zip file containing the results for easy download.ConclusionsCold spot identification is of great importance to protein engineering studies and provides a useful insight into protein evolution. Cold Spot SCANNER is open to all users without login requirements and can be accessible at: https://colab.research.google.com/github/sagagugit/Cold-Spot-Scanner/blob/main/Cold_Spot_Scanner.ipynb.

Analyzing the geographic influence of financial inclusion on illicit drug use in Nigeria

Nigeria grapples with a formidable public health concern, as approximately 14 million individuals partake in illicit drug use (IDU). This predicament significantly impacts psychiatric disorders, suicides, disability, and mortality rates. Despite previous investigations into predictors and remedies, the role of financial inclusion (FI) remains inadequately explored. Leveraging existing literature on FI and population health, this study asserts that bolstering FI could be instrumental in mitigating IDU prevalence in Nigeria. We employ spatial analysis to scrutinize the influence of FI and other social factors on IDU, revealing a 14.4 % national prevalence with spatial variations ranging from 7 % in Jigawa state to 33 % in Lagos state. Significant IDU hotspots were identified in the southwest states, while cold spots were observed in the Federal Capital Territory and Nassarawa. Multivariate spatial analysis indicates that FI, income, unemployment, and the proportion of the young population are pivotal predictors of IDU nationwide, explaining approximately 67 % of the spatial variance. Given these findings, the study advocates heightened levels of FI and underscores the need for intensified government initiatives to prevent and address illicit drug use.

Impacts of spatial and temporal patterns and economic development on carbon emissions in Chinese cities

With the economic and social development and the improvement of peoples living standards, the urban carbon emission increases. Studying the influence of industrial structure and spatial patterns on carbon emission under the economic development of different cities can help to find the main factors affecting carbon emission, formulate policies to solve the problem according to local conditions, and provide an important scientific basis for the transformation of economic growth mode and the construction of low-carbon cities. This paper draws conclusions by analyzing the trend curves of urban carbon emissions and economic factors over the years. Different regions of the citys economic development potential differences are obvious, and the potential for greater spatial concentration of cities; citys economic development potential in the spatial and temporal distribution of key cities and major urban agglomerations as the basis for the point - line - surface in order to promote. economically developed cities, the total carbon emissions, carbon emissions growth rate of a declining trend; economically underdeveloped areas, the total carbon emissions, carbon emissions growth rate of a year-on-year trend; the degree of carbon emissions and the degree of prosperity of the secondary industry is closely linked. Chinas urban carbon emissions have a significant positive spatial correlation between 2006 and 2016, the cold spot area of urban carbon emissions is relatively stable, mainly distributed in the eastern and southern economic zones, while the hot spot area is mainly distributed in the northwest, northeast and the middle reaches of the Yellow River economic zone.

Study on Transportation Green Efficiency and Spatial Correlation in the Yangtze River Economic Belt

The Yangtze River Economic Belt (YREB), a crucial transportation corridor spanning China’s east and west and linking coastal and inland regions, is not only pivotal in the nation’s strategic development but also drives regional economic and social progress through its transportation industry. Despite rapid growth, the industry faces challenges such as low efficiency, resource supply–demand imbalances, and environmental issues. To advance green and sustainable progress, this study establishes a regional transportation green efficiency evaluation system. Using principal component analysis (PCA) to refine input data, the undesirable super-SBM model quantitatively assesses green transportation efficiency (GTE) in YREB provinces and cities, revealing regional disparities. The study also explores spatial correlations and distribution characteristics of GTE. Results indicate that ① YREB’s GTE shows a U-shaped trend, with significant differences between upper, middle, and lower reaches, being stronger in the east and weaker in the west (lower &gt; middle &gt; upper reaches); ② GTE exhibits spatial correlation in YREB regions, with clear clustering; and ③ cold and hot spots of GTE in the middle reaches are relatively stable, with upstream areas generally cold or sub-cold, and hot spots mainly downstream.

Correlation between urbanization and vegetation cover in China and analysis of its influencing factors

ABSTRACT There are spatial differences in the correlation between urbanization (NL) and vegetation cover (NDVI), and the driving mechanism is not clear. This study aims to explore the spatial correlation between NL and NDVI in China and identify the influencing factors. The results showed that there was a north-south difference in the correlation, and this correlation was strongest in winter. Meteorological factors were the main influencing factors, Bivariate enhancement is observed for TEM-DEM at the national scale in winter, TEM-relative humidity (RH) in cold spot areas, and TEM-RH in hot spot areas in summer.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence.

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

The Newton-Stefan-Boltzmann-Planck Code. The Solar Microwave Background Formation on the Blackbody Sphere at the Distance R = 140 AU

In this model the Solar System presented to observers on the planet Earth the elegant gift: the Solar Microwave Background (SMB) formed on the Blackbody Sphere at the distance R = 140 AU. The thermalization of the Hydrogen wall at this distance was described using the Stefan-Boltzmann law where the temperature of the blackbody at the distance R = 1 AU is T = 393.6 K. Newton’s cooling law described the cooling of this blackbody surface temperature with the cooling constant κ = 1.139 × 10−4 s−1 calculated from data of the small planet Pluto (average distance R = 39.5 AU and the temperature T = 44 K). The SMB monopole temperature T = 2.7255 K was fitted for the distance R = 140 AU with the temperature of the surrounding TENV = 2.5887 K. The first important difference with the model of the cosmic microwave background (CMB) is the magnitude and direction of Newton’s dipole v = (200 + 141) kms−1 towards the galactic coordinates (l, b) = (84°, −48°) while the magnitude and the direction of the Doppler’s dipole of CMB is v = 368 kms−1 towards (l, b) = (264°, 48°). This new model enables to estimate the rotation velocity of the Sun in the Milky Way Galaxy, the motion of the Milky Way Galaxy through the Universe, and the Harress-Sagnac color excess: v = 200 + 141 + 27 = 368 kms−1. The total motion of the Milky Way Galaxy through the Universe can be estimated with the knowledge of the Cold Spot direction in the SMB and the motion towards the Galactic South Pole. In this model, the Milky Way Galaxy can avoid collision with the Andromeda Galaxy. The observed quadrupole, octopole, and hemisphere structure of the SMB can be explained as the local motion of the Sun and the Solar axis inclination towards the ecliptic–the Axis of evil should be renamed as the Solar axis bringing to us a good opportunity to discover differences between the SMB and the CMB. The first peak in the power spectrum of the SMB at the distance R = 140 AU is observed from the COBE, WMAP, and PLANCK satellites rotating around the Sun at the distance R = (2×1) AU under the angle θ = 0.818°. The power spectrum observed from the planets Mercury and Jupiter will have different positions of the first and higher peaks. The original Solar signature should be visible as the moving shadows of the Sunspots on the Blackbody Sphere. There were proposed several experiments on how to distinguish between the SMB and the CMB.

Geo-visualizing the hotspots of smog-induced health effects in district Gujranwala, Pakistan: a community perspective.

This study aims to examine the health effects of smog on different age groups in Gujranwala and its associated health effects. To achieve this, primary data was gathered through a questionnaire survey focused on health issues faced by elderly individuals during the smog season. The results of the survey revealed that older adults in Gujranwala are particularly vulnerable to a range of health problems during this period, including coughing, throat infections, irritated eyes, runny noses, shortness of breath, chest pain while breathing, wheezing, asthma, heart problems, and respiratory issues. In order to analyze the spatial distribution of these health concerns, spatial and geo-statistical methods were employed utilizing ArcGIS 10.5. By integrating field data and secondary sources, hotspot and cold spot zones were identified. Employing the statistical model within ArcMap 10.5, hotspot analysis was performed to determine areas with elevated air quality index (AQI) values and associated health problems. The application of the inverse distance weighted approach, incorporating the Z value, facilitated a visual representation of areas with heightened and reduced AQI and health-related issues. The study's outcomes underscore the prevalence of health challenges among older adults during the winter months in Gujranwala, particularly linked to smog-induced throat infections, irritated eyes, and runny noses. The research identified zones with escalated AQI values, encompassing regions such as Gujranwala, Chandaqella, Alam Chowk, Khali Shahpur, Sialkot Bypass, and Pindi Bypass. It was established that industrial pollutants and vehicular emissions are the primary contributors to smog in the area. Given the detrimental consequences of pollution on individuals of all age groups, it is imperative to take action to mitigate its impact. This can be achieved through addressing pollution sources, implementing effective emission control measures, and fostering public awareness. By adopting proactive measures, the adverse health effects of pollution can be minimized, thereby fostering a healthier and safer environment for the entire population. This study offers valuable insights for policymakers and environmentalists to implement targeted interventions and improve air quality, ultimately safeguarding the health of local populations.