Study on stability evaluation of goaf based on AHP and EWM-taking the northern new district of Liaoyuan city as an example.

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Spatiotemporal Evolution of Winter Wheat Planting Area and Meteorology-Driven Effects on Yield under Climate Change in Henan Province of China.

This study examines the impact of climate change on winter wheat production in Henan Province. The analysis, under the utilization of GLASS LAI data, focuses on shifts in the planting areas of winter wheat. In addition, a comprehensive assessment of the spatiotemporal trends in meteorological factors during the winter wheat growth period has also been conducted. The findings reveal a fluctuating increase in accumulated temperature across Henan Province, ranging from 3145 °C to 3424 °C and exhibiting a gradual rise from north to south. In particular, precipitation patterns from 1980 to 2019 showed limited significant trends, while notable abrupt changes were observed in 1983, 2004, 2009, and 2016. Geographically, southwestern Henan Province experiences greater precipitation than the northeast. Moreover, a fluctuating downward trend in sunshine hours has been observed, gradually decreasing from north to south. The study further highlights an increase in winter wheat planting frequency in the northwestern region of Luoyang and the northeastern part of Zhumadian, contrasted by a decrease in Zhengzhou and Kaifeng. Accumulated temperature is positively correlated with the expansion of winter wheat planting areas (R2 = 0.685), while sunshine hours exert a suppressive effect (R2 = 0.637). Among meteorological factors, accumulated temperature emerges as the most crucial determinant, followed by precipitation, with sunshine hours having a relatively minor influence. Yield demonstrates a positive association with accumulated temperature (R2 = 0.765) and a negative correlation with sunshine hours (R2 = -0.614). This finding is consistent with the impact of meteorological factors on winter wheat production. The results of this study enhance the understanding of how the underlying mechanisms of climate change impact crop yields.

Hospital Factors Influencing the Mobility of Patients for Systemic Therapies in Breast and Bowel Cancer in the Metastatic Setting: A National Population-based Evaluation.

AIMS: This national study investigated hospital quality and patient factors associated with treatment location for systemic anticancer treatment (SACT) in patients with metastatic cancers. MATERIALS AND METHODS: Using linked administrative datasets from the English NHS, we identified all patients diagnosed with metastatic breast and bowel cancer between 1 January 2016 and 31 December 2018, who subsequently received SACT within 4 months from diagnosis. The extent to which patients bypassed their nearest hospital was investigated using a geographic information system (ArcGIS). Conditional logistic regression models were used to estimate the impact of travel time, hospital quality and patient characteristics on where patients underwent SACT. RESULTS: 541 of 2,364 women (22.9%) diagnosed with metastatic breast cancer, and 2,809 of 10,050 (28.0%) patients diagnosed with metastatic bowel cancer bypassed their nearest hospital providing SACT. There was a strong preference for receiving treatment at hospitals near where patients lived (p < 0.001). However, patients who were younger (p = 0.043 for breast cancer; p < 0.001 for bowel cancer) or from rural areas (p = 0.001 for breast cancer; p < 0.001 for bowel cancer) were more likely to travel to more distant hospitals. Patients diagnosed with rectal cancer were more likely to travel further for SACT than patients with colon cancer (p = 0.002). Patients were more likely to travel to comprehensive cancer centres (p = 0.019 for bowel cancer) and designated Experimental Cancer Medicine Centres (ECMCs) although the latter association was not significant. Patients were less likely to receive SACT in hospitals with the highest readmission rates (p = 0.046 for bowel cancer). CONCLUSION: Patients with metastatic cancer receiving primary SACT are prepared to travel to alternative more distant hospitals for treatment with a preference for larger comprehensive centres providing multimodal care or hospitals which offer early phase cancer clinical trials.

Integrating portable X-ray fluorescence site survey and ArcGIS models for rapid risk assessment and mitigation strategies at an abandoned arsenic mine site: a case study.

Australia's metalliferous abandoned mine sites (MAMSs), pose tangible threats to the environment and human health. To address these concerns, our study utilised state-of-the-art handheld XRF technology to conduct a real-time assessment of the Mole River arsenic mine site. The data revealed notably elevated levels of arsenic and manganese, with the southeast corner of the site identified as a contaminant hotspot. We used a tiered risk assessment approach to compare the detected contaminant concentrations to the Australian health investigation levels (tier 1). This led us to a broader examination of erosion vulnerabilities and the potential migration of contaminants (tier 2). Further, a hydrological assessment (tier 3) identified significant erosion in southern regions, indicating the potential for contaminants to be transported off-site through surface water runoff to Sam's Creek and Mole River. The proximity of a reservoir to these runoff pathways brought forth additional challenges, especially during heavy rainfall events. Subsequent laboratory analysis of water samples reinforced our findings, as they confirmed heightened arsenic concentrations in Mole River downstream, accentuating the potential risks to ecosystems and human health. By integrating the XRF contour map and erosion assessment with the RUSLE model, valuable insights are gained into critical hotspots with high contamination and erosion potential. By directing rehabilitation efforts towards critical hotspots, resources can be allocated more efficiently and cost-effectively.

Spatial distribution characteristics and source apportionment of heavy metal(loid)s in park dust in the Mianyang urban area, China.

Park dust is a carrier of heavy metal pollutants and could potentially harm the health of urban residents. The concentrations of 10 heavy metal(loid)s (HMs) in park dust from the Mianyang urban area were analysed via X-ray fluorescence spectrometry. Based on ArcGIS spatial analysis, Spearman correlation analysis, spatial autocorrelation analysis, and the positive matrix factorization (PMF) model, the spatial distribution and sources of HMs in park dust were studied. The average contents of Zn, Co, Cu, Cr, Pb, and Ba in park dust were 185.0, 33.7, 38.7, 178.7, 51.0, and 662.1 mg/kg, respectively, which are higher than the reference values. The 10 HMs exhibited obvious spatial distribution and local spatial agglomeration patterns. High concentrations of As and Pb were primarily concentrated in the eastern part of the Mianyang urban area. High concentrations of Zn, Cr, and Cu were largely distributed in parks near the Changjiang River and Fujiang River. A high concentration of Co was concentrated in the northern region. The high-value areas of Mn, Ba, V, and Ni occurred far from the city centre and were located in the southwestern region. We found that Pb and As primarily originated from mixed traffic and natural sources; Zn, Cr, and Cu mainly originated from industrial activities; Co largely originated from building sources; and Ba, Ni, Mn, and V were mostly derived from natural sources. Mixed, industrial, building, and natural sources accounted for 24.5%, 24.8%, 24.7%, and 26.0%, respectively, of the HM sources. Co, Cu, Cr, and Zn in the Mianyang urban area were obviously influenced by human activities and should receive close attention.

Spatial Clustering of Malnutrition and Anemia Among Reproductive Women and Its Associated Risk Factors in India: Evidence From National Family Health Survey-5.

BACKGROUND: Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. Malnutrition is defined as poor nutritional condition that encompasses both under nutrition and over nutrition. The prevalence of overweight or obesity and anemia has increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for underweight, overweight/obesity, and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021). METHODS: We conducted hot-spot analysis using Moran's Index (MI) with the help of spatial analysis software (i.e., GeoDa 1.18 and ArcGIS 10.8). It also demonstrates the autocorrelation. Multivariable logistic regression analysis has been performed to examine different determinants and risk associated with underweight, overweight/obesity, and anemia with various dependent variable by using Stata-14 software. RESULTS: Moran's Index for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P < .001) exists across the districts in India. As a result, a total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of under nutrition and anemia are both reduced by media exposure and eating habits. Moreover, low income and low education level raises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level. CONCLUSION: The study recommends targeting hot-spot districts for malnutrition and anemia, and policy level initiatives by addressing the responsible risk factors.

Plain language titleSpatial Clustering of Malnutrition and Anemia Among Women Across Districts in IndiaPlain language summaryMost of the low-income and middle-income countries are affected by the double burden of malnutrition. Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. However, the prevalence of undernutrition among women of reproductive age in India has decreased, while the prevalence of overweight or obesity and anemia has also increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for nutritional deficiency and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021). This information is expected to help with district-level policy formulation and advocacy, which can, in turn, can play an important role in reducing nutritional deficiency and anemia among women. The results of spatial analysis show the Moran's Index (MI) for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P < .001) (i.e., districts are similar to each other) exists across the districts in India. A total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of undernutrition and anemia are both reduced by media exposure and eating habits. Low income and low education level rises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level. Based on these findings, the present study recommends to implement a district level policy by targeting hot spot districts. The needful preventive measures as suggested in the study can also be implemented to control the incident and burden of women's malnutrition and anemic status in India.

Integrated assessment and mapping of provisioning services for sustainable management of natural resources, the case of Lake Hawassa Basin, Ethiopia.

Lake Hawassa Basin (LHB)-the study area is known for its rich and diverse aquatic and terrestrial natural resource base. However, the prevailing environmental and social problems, such as land degradation, deforestation, pollution, resource exploitation, etc. impacted the existing provisioning services (PS), and the effect becomes remarkable unless sound management is in place. The study aimed at the assessment and mapping of PS to suggest development options for decision-makers. The study employed various methods including primary and secondary data collection, including existing Land Use Land Cover (LULC), desk review, stakeholder consultations, site visits, expert judgment matrix, and ArcGIS v10.1. The study results include 6 PS identified and prioritized from the existing 14 PS, mapping of the spatial pattern of the selected 6 PS at the basin scale, and alternative development options recommended for the decision-making process conducted by decision-makers and development partners to ensure efficient management of ecosystem services in LHB. The importance of this study, as well as the simplicity and user-friendly nature of the methods and approach adopted, enables interested parties to replicate while conducting similar studies in different places within the country or globally. The intervention of adopting this study approach helps also to avoid or minimize the aforesaid biophysical and socioeconomic environmental problems and ensure development activities planned or implemented in the respective study area are environmentally friendly, and socially acceptable, through sustainable management of natural resources. In this regard, decision-makers and development partners shall provide adequate consideration for this study approach and the result of demonstrating basin scale spatial variability of PS. This plays a vital role in the sustainable management of natural resources as well as provisioning services existing in the study area to benefit the community members, ensure human well-being, and secure the livelihood of the people residing within or around the Lake Hawassa Basin.

Potential impact of climatic factors on the distribution of Graphium sarpedon in China.

Graphium sarpedon is a significant foliar pest of Laurel plants in China. In this study, the MaxEnt model was used to investigate the distribution of G. sarpedon and predict its potential distribution areas in China in the future (2050s and 2090s) based on three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), and key environmental variables affecting its distribution were identified. The results showed that under the current climatic conditions, the suitable distribution areas of G. sarpedon were 92.17°-134.96° E and 18.04°-33.61° N, including Yangtze Plain (Middle and Lower), Pearl River Delta, Yangtze River Delta, and Lingnan areas. Under the future climate conditions, the total suitable distribution area of G. sarpedon decreased, but the area of medium suitable area increased. The study identified 11 key environmental variables affecting the distribution of G. sarpedon, the most critical of which was Precipitation of Warmest Quarter (bio18) and precipitation in April, May, June, and September (prec4, prec5, prec6, and prec9). This study is beneficial for monitoring and preventing the possible changes of G. sarpedon and provides theoretical references for its prevention and control.

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India.

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

A Comparison of Hospice Care Utilization Between Rural and Urban Children in Appalachia: A Geographic Information Systems Analysis.

Long driving times from hospice providers to patients lead to poor quality of care, which may exacerbate in rural and highly isolated areas of Appalachia. This study aimed to investigate geographic patterns of pediatric hospice care across Appalachia. Using person-level Medicaid claims of 1,788 pediatric hospice enrollees who resided in the Appalachian Region between 2011 and 2013. A database of boundaries of Appalachian counties, postal addresses of hospices, and population-weighted county centroids of residences of hospice enrollees driving times from the nearest hospices were calculated. A choropleth map was created to visualize rural/urban differences in receiving hospice care. The average driving time from hospice to child residence was 28 minutes (SD = 26). The longest driving time was in Eastern Kentucky-126 minutes (SD = 32), and the shortest was in South Carolina-11 min (SD = 9.1). The most significant differences in driving times between rural and urban counties were found in Virginia 28 (SD = 7.5) and 5 minutes (SD = 0), respectively, Tennessee-43 (SD = 28) and 8 minutes (SD = 7), respectively; and West Virginia-49 (SD = 30) and 12 minutes (SD = 4), respectively. Many pediatric hospice patients reside in isolated counties with long driving times from the nearest hospices. State-level policies should be developed to reduce driving times from hospice providers.

GIS-based landslide susceptibility zoning using a coupled model: a case study in Badong County, China.

Landslide susceptibility zoning is necessary for landslide risk management. This study aims to conduct the landslide susceptibility evaluation based on a model coupled with information value (IV) and logistic regression (LR) for Badong County in Hubei Province, China. Through the screening of landslide predisposing factors based on correlation analysis, a spatial database including 11 landslide factors and 588 historical landslides was constructed in ArcGIS. The IV, LR and their coupled model were then developed. To validate the accuracy of the three models, the receiver operating characteristic curves (ROC) and the landslide density curves were correspondingly created. The results showed that the areas under the receiver operating characteristic curve (AUCs) of the three models were 0.758, 0.786 and 0.818, respectively. Moreover, the landslide density increased exponentially with the landslide susceptibility, but the coupled model exhibited a higher growth rate among the three models, indicating good performance of the proposed model in landslide susceptibility evaluation. The landslide susceptibility map generated by the coupled model demonstrated that the high and very high landslide susceptibility area mainly concentrated along rivers and roads. Furthermore, by counting the landslide numbers and analyzing the landslide susceptibility within each town in Badong County, it was discovered that Yanduhe, Xinling, Dongrangkou and Guandukou were the main landslide-prone areas. This research will contribute to landslide prevention and mitigation and serve as a reference for other areas.

Human health risk assessment of Triclosan in water: spatial analysis of a drinking water system.

Triclosan (TCS) has been increased in the water during the COVID-19 pandemic because it cannot remove by conventional water treatment. In addition, it can accumulate in the human body over time through long-term exposure. Therefore, the occurrence of TCS in the water treatment plant (WTP) and tap water, and its human health risk assessment through tap water ingestion, dermal absorption, and inhalation routes in Isfahan, Iran, were investigated. Moreover, spatial regression methods were used for the prediction of water quality parameters, TCS concentration, and total hazard quotient (HQ). The average TCS concentration in the influent and effluent of WTP and tap water was 1.6, 1.4, and 0.4 µg/L, respectively. Conventional WTP has low efficiency in the removal of TCS (12.6%) from water. The average values of total HQ for males were 7.79×10-5, 4.97×10-4, and 4.97×10-5 and for females were 3.31×10-5, 2.11×10-4, and 2.11×10-5 based on RfDEPA, RfDMDH, and RfDRodricks, respectively that were in the low-risk levels (HQ<1). Furthermore, TCS concentration in tap water and the ingestion rate of drinking water had the highest effect on the risk of TCS exposure from tap water. The non-carcinogenic health risk of TCS in water was low. The results of this study may be useful for promoting WTP processes to remove emerging pollutants.

Effect of land use land cover changes on hydrological response of Punpun River basin.

The present study assessed the hydrological response of land use land cover (LULC) change on the Punpun River basin. High-resolution gridded rainfall and temperature data from the years 1995 to 2020 have been used in the Soil and Water Assessment Tool (SWAT) in the Geographic Information System (GIS) to analyze the hydrological response of the Punpun River basin and water balance components. Hydrological Response Units (HRUs) have been created for the basin. Each HRU is based on a distinct combination of soil, slope, and land use. Five SWAT models have been prepared based on the LULC of every 5-year interval to simulate the basin's hydrological response. The period selected for calibration is 1995-2015 and for validation is 2016-2020 for the modeling of daily streamflow data. The observed and simulated streamflow was checked for performance indices of coefficient of determination (R2), Nash-Sutcliffe Efficiency (NSE), and percent bias (PBIAS) on daily time steps. The results were found to be good with R2 = 0.72, NSE = 0.68, and PBIAS = 23.2 for calibration and R2 = 0.93, NSE = 0.77, and PBIAS = 19.8 for validation. The study reveals that 7.01% of evapotranspiration (ET) was increased from 1995 to 2020 with increase in agricultural area of 21.86%. It was also found that built-up area, surface runoff, and water yield have been increased by 9.14, 14.43, and 17.40%, respectively. Further, the groundwater contribution of the basin was decreased.

Application of TOPSIS method for flood susceptibility mapping using Excel and GIS.

This study elaborately manifests a simplified Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multicriteria decision-making (MCDM) approach that goals to determine the disparity among the distances between the positive and negative ideal solutions. MCDM methods evaluate options based on a variety of criteria by using mathematical and analytical methodologies. This promotes a more transparent and objective decision-making process by removing human biases and subjective judgements. By considering the comparative proximity to the optimal situation, TOPSIS considers the distances between the ideal and the negative-ideal alternatives. This study has concentrated on the normalization process, the appropriate determination of the ideal and the anti-ideal solution, and the metric utilized to compute the euclidean distances from the ideal best and the ideal worst.•This study expresses the simplified TOPSIS methodology as stated by Hwang and Yoon (1981). The categorization and weight assignments of the criteria have been executed from the expert's opinion and based on existing literatures.•Integration of the TOPSIS technique with GIS has been properly performed for the production of a flood susceptibility map of a highly vulnerable region and visual interpretation of the TOPSIS algorithm.•This kind of investigation saved time by sufficiently skilled specialized personnel in this field.

Spatial pattern and influencing factors of tourism based on POI data in Chengdu, China.

Based on the analysis of the spatial distribution characteristics and influencing factors of 2879 attractions POI in Chengdu, this paper studies the spatial distribution types, spatial concentration, and equilibrium of attractions by using standard deviation ellipse, geographic concentration index, and kernel density estimation. Buffer analysis, near analysis, correlation analysis, and grey relation analysis are used to study the influencing factors of tourism in Chengdu. The results show that: (1) The overall attractions POI in Chengdu is in an east-west direction, and except for other types of attractions POI, the remaining types are also in an east-west direction. (2) The spatial agglomeration areas of different types of attractions POI in Chengdu were quite different. Among them, parks and city squares were mainly concentrated in the central urban areas, namely Jinjiang, Qingyang, Jinniu, Wuhou, and Chenghua, forming a prominent gathering area. (3) There were differences in the influence degree of each factor on the spatial distribution of attractions POI. Topography and drainage, transportation, tourist source market, and other factors significantly correlated with the distribution of attractions, which were the main factors affecting the spatial distribution of attractions. Industrial development and economic population were also important factors affecting the distribution of attractions. Tourism is an important thrust for urban development. The study of the spatial distribution of tourism and its influencing factors has clear guiding significance for later tourism development, which can help optimize the integration of tourism resources, promote the cooperation of regional tourism development and provide a basis for decision-making for tourism development.

Dust temporal and spatial deposition affected by climate and soil mineralogical and chemical properties in a semi-arid area.

The important process of aerosol dusting is of economic, environmental and heath significance. The objective was to investigate the climatic parameters including rainfall (R), wind speed (WS), temperature (T), and relative humidity (RH), as well as soil mineralogical and chemical properties affecting dust deposition rate (DDR), in a unique and rarely studied area, the Kuhdasht watershed (456 km2) of Lorestan province, Iran. Data were collected seasonally using glass-traps inserted in ten research stations to indicate DDR seasonal and spatial variations using ARC-GIS. The spatial distribution of organic matter (OM), clay and CaCO3, and the mineralogical properties (using diffractograms obtained by XRD) of the dust and soil samples were determined. The city had the highest DDR decreasing toward the mountains. Spring (3.28-4.18 ton/km2) and autumn (1.82-2.52 ton/km2) resulted in the highest and the least DDR, respectively. The diffractograms indicated the sources of dust were local or from out of the borders. The clay minerals (kaolinite and illite) and the evaporating minerlas (gypsum, calcite, dolomite, and halite), detected in the soil and dust samples indicated their contribution to the process of DDR. According to the regression models and the correlation coefficients, DDR was highly and significantly correlated with R (R2= 0.691), WS (0.685) and RH (0.463) indicating such parameters can importantly affect DDR in the semi-arid areas.

Spatial Pattern Characteristics and Factors for the Present Status of Rural Settlements in the Lijiang River Basin Based on ArcGIS.

In China, rural settlements have undergone significant changes in response to dramatic socioeconomic shifts. However, there has not been any report on rural settlements in the Lijiang River Basin. In this study, ArcGIS 10.2 (including hot spot analysis and kernel density estimation) and Fragstats 4.2 (such as the landscape pattern index) software were used to analyze the spatial pattern and causes of rural settlements in the Lijiang River Basin. The Lijiang River Basin is mainly dominated by micro- and small-sized rural settlements with small areas. Moreover, the results of a hot spot analysis showed that micro- and small-sized rural settlements were mainly located in the upper reaches, and medium- and large-sized rural settlements were mainly located in the middle and lower reaches. The kernel density estimation results showed that the distribution characteristics of the rural settlements in the upper, middle, and lower reaches were significantly different. The spatial forms of rural settlements were affected by physiographic factors such as elevation and slope, karst landforms, and river trunk channels as well as the national policy system, tourism economic development, town distribution, historical heritage, and minority culture. This study is the first to systematically elaborate on the rural settlement pattern and its internal logic from the perspective of the Lijiang River Basin, providing a basis for the optimization and construction of the rural settlement pattern.

Optimal Network of General Hospitals in Slovenia.

This article explores how the minimum number of general hospital locations can be determined with optimal population coverage. Due to the increasing financial problems of hospitals and the poor organization of general hospital healthcare, Slovenia is currently working to reform the healthcare system. Defining the optimal network of hospital providers is one of the key elements in reforming the healthcare system. To define the optimal network of general hospitals, the allocation-location model was used, and the maximize attendance model was used as the central method. The chief purpose of maximize attendance model is to optimize the demand attendance with respect to distance and time spent getting to the point of demand. In the analysis of optimal locations and the number of Slovenian general hospitals, we used data on the locations of settlements with their number of inhabitants and data on the Slovenian road network, based on which we defined average travel speeds on the categorized road network. The hypothetical locations of general hospitals and the number of optimally located general hospitals that provide access to the nearest provider were determined in three different time intervals. We found that the same accessibility to hospital services as provided by the existing network of general hospitals can be achieved with only ten optimally located general hospitals within a 30-min time interval. This means that two general hospitals could be rationalized or reorganized, which would bring significant savings in the field of hospital activity, which creates a large loss in the health system in Slovenia.

Landscape Epidemiology of Potato Blackleg.

Potato blackleg is a common bacterial disease that causes serious losses in potato (Solanum tuberosum) production worldwide. Despite this, relatively little is known of the landscape epidemiology of this disease. This study provides the first national-scale analysis of spatial and spatiotemporal patterns of blackleg incidence rates and associated risk factors for disease at the landscape scale. This was achieved through a combination of ArcGIS and interpretable machine learning applied to a longitudinal dataset of naturally infected seed potato crops from across Scotland. We found striking differences in long-term disease outcomes across the country and identified that features (variables) related to the health status and management of mother crops (seed stocks), matching features in daughter crops, and the characteristics of surrounding potato crop distributions were the most important predictors of disease, followed by field, bioclimatic, and soil features. Our approach provides a comprehensive overview of potato blackleg at a national scale, new epidemiological insights, and an accurate model that could serve as the basis of a decision support tool for improved blackleg management.

Research on regional water environmental carrying capacity based on GIS and TOPSIS comprehensive evaluation model.

Water environmental carrying capacity (WECC) is an important indicator for assessing the coordination between the water environment and the social-economic-resources and environment subsystems. In this study, to determine the WECC of Changsha-Zhuzhou-Xiangtan urban agglomeration in Xiang River Basin, a three-level index system was established using an analytic hierarchy process. Because the previous evaluation system lacked continuous indicators, the results could not reflect the differences of WECC within the administrative units, thus, this study selected 4 continuous indicators, and finally an evaluation index system including 15 indicators was established. Based on the TOPSIS model and logistic regression model, the current situation and change trend of WECC in the study area were obtained in ArcGIS. The results showed that the comprehensive WECC in this region was inferior in 2020, particularly in urban concentrated areas, and it was extremely uneven in spatial distribution. The WECC decreased significantly from 2011 to 2014 and gradually improved from 2014 to 2020. According to the prediction results, the WECC will increase in the future, with an average value of 0.54 in 2025 and 0.60 in 2035. This study will have important guiding implications for the protection and improvement of the water environment in the study area and related areas.