County Area Research Articles

Analysis of the Influencing Factors of the High-Quality Utilization of Territorial Space Based on the Perspective of Spatial Equilibrium: A Case Study of Hunan Province, China

In order to promote the efficient and coordinated utilization of counties’ territorial space in Hunan Province, this paper identifies the state of high-quality utilization of territorial space based on the perspective of spatial equilibrium from 2010 to 2020, and uses the spatial econometric model to analyze its influencing factors and propose effective optimization strategies. The results show that: (1) From 2010 to 2020, the quality of agricultural space utilization continued to decline in some areas, and elsewhere to decreased first and then increased. The core area of Chang-Zhu-Tan and the central urban areas of some prefectures have always been high-value areas for the quality of urban space utilization; the agricultural space utilization quality in the Dongting Lake Plain area and the Chang-Zhu-Tan area were high. By 2020, the range of Chang-Zhu-Tan agricultural space categorized as of high-value utilization quality areas has been significantly reduced; the high-value ecological space utilization quality areas were located in areas with large ecological scales, such as counties in the Wuling Mountains, etc. (2) From 2010 to 2020, the near-imbalance and barely balanced development have always been the main types of balanced development, and the balanced development in the core area of Chang-Zhu-Tan and Dongting Lake plain is high. (3) From 2010 to 2020, the types of high-quality utilization of territorial space in Hunan Province were mainly urban-agricultural-ecological spaces with low-quality equilibrium, and high-quality utilization of county areas were rare. The number of high-quality utilization counties was gradually decreasing, and by 2020, there was only one in Wuling District, Changde City. Therefore, the other 121 counties’ territorial space utilization status needs to be improved. (4) The high-quality utilization of territorial space in Hunan province was influenced by both regional background factors and external factors, and the external factors were more significant. Among them, population density, consumption level and other factors played an important role. Relevant departments can take effective measures to promote the efficient and coordinated use of county territorial space by taking such measures as relaxing the conditions for the introduction of talents, increasing financial investment, and so on.

Responses of sustainable development indicators to human activities and climate change in ecologically fragile areas of impoverished counties in China

AbstractBased on Landsat MSS/TM/OLI (1975–2018), MODIS NDVI (2000–2015), and DMSP/OLS (1992–2013) multitemporal remote sensing data, as well as annual average precipitation and temperature data from meteorological stations (1980–2018) and SRTM DEM data, this study extracted information on climate change, human activity, and eco‐environmental factors in the Zijin Mountain (ZJM) area of Shanxi Province, and then analyzed the spatiotemporal changes in ecological structure, landscape structure, and climate response. The results revealed that in the ZJM area some sustainable development indicators associated with human activity, ecology, climate, and landscape geography have changed. Specifically, over the 44‐year period from 1975 to 2018, the urban and rural construction land area increased by 4.29 times; in the 22‐year period from 1992 to 2013, the regional light index has increased by 26.9 times; in the past 32 years, that is, from 1987 to 2018, the average vegetation index of the entire basin increased by about 54.7%, the vegetation cover exhibited a gradual positive trend, and the land use types in the ZJM area were mainly converted from bare land to grassland or forest. Compared with 1987, the area of bare land decreased 32.5% by 2018, whereas the forest and grassland areas increased by 85.7% and 40.7%, respectively. In addition, over the 44‐year period from 1975 to 2018, the road density increased by 8.57 times. The area affected by human activities, comprised roads, urban and rural construction land, and their buffer areas, accounted for 64.87% of the total study area. As a result, the fragmentation index of landscape patches has increased by 6.81 times since 1987. We conclude that in the ZJM area, the ecosystem type has transformed from an indigenous mountainous grassland to mountainous arid agriculture, and from an isolated habitat to a fragmented habitat.

Environmental justice analysis of wildfire-related PM2.5 exposure using low-cost sensors in California

The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM2.5 in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM2.5 concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM2.5 concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM2.5 during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.

Evaluation of the Ecological Environment Quality of the Kuye River Source Basin Using the Remote Sensing Ecological Index.

Landsat remote sensing images obtained from 2000, 2005, 2010, 2015, and 2020 were analyzed. The normalized vegetation index (NDVI), moisture index (WET), land surface temperature (LST), and normalized building-soil index (NDBSI) were extracted based on the four aspects of greenness, humidity, heat, and dryness. The Remote Sensing Ecological Index (RSEI) was calculated using principal component analysis to quantitatively analyze and dynamically monitor and evaluate the ecological environment changes in the Kuye River Basin over the past 20 years. From the perspective of spatial and temporal distribution, the ecological and environmental quality of Kuye River Basin had a downward trend from 2000 to 2020. The overall RSEI grade was medium or poor, and the average RSEI decreased. The proportion of excellent and good grade watershed areas decreased, whereas that of medium, low, and poor grade watershed areas increased over the study period. Spatially, RSEI decreased gradually from southeast to northwest. The degraded areas were mainly distributed in urban areas with frequent human activities. Conversely, the superior eco-environmental quality areas were mainly distributed in eastern sections of the watershed. Compared with 2000, the eco-environmental quality of the Yulin urban area and Shenmu County in the southern section of the watershed are worsening.

Evaluating the effects of heat vulnerability on heat-related emergency medical service incidents: Lessons from Austin, Texas

Extreme heat exposure and sensitivity have been a growing concern in urban regions as the effects of extreme heat pose a threat to public health, the water supply, and the infrastructure. Heat-related illnesses demand an immediate Emergency Medical Service (EMS) response since they might result in death or serious disability if not treated quickly. Despite increased concerns about urban heat waves and relevant health issues, a limited amount of research has investigated the effects of heat vulnerability on heat-related illnesses. This study explores the geographical distribution of heat vulnerability in the city of Austin and Travis County areas of Texas and identifies neighborhoods with a high degree of heat vulnerability and restricted EMS accessibility. We conducted negative binomial regressions to investigate the effects of heat vulnerability on heat-related EMS incidents. Heat-related EMS calls have increased in neighborhoods with more impervious surfaces, Hispanics, those receiving social benefits, people living alone, and the elderly. Higher urban capacity, including efficient road networks, water areas, and green spaces, is likely to reduce heat-related EMS incidents. This study provides data-driven evidence to help planners prioritize vulnerable locations and concentrate local efforts on addressing heat-related health concerns.

Small Ruminants Coccidiosis in High Altitude Region of Iran

Coccidiosis (Eimeria spp.) is a parasite disease in small ruminants that causes diarrhea and reduced economic benefits. The purpose of this epidemiological study was to use microscopical and molecular assays to detect coccidia prevalence and isolate species-specific Eimeria from sheep and goats kept in a common pan in the central Zagros region. This region is a mountainous and cold region which its southern counties are warmer than other districts. Throughout the course of several seasons, 1200 fecal samples were obtained from three age groups (less than six months, six to twelve months, and more than six months). Oocytes were counted using saturated saline floating and modified MacMaster techniques and the physical characteristics of sporulated Eimeria oocytes were used to identify them. Eimeria infection was shown to be more prevalent in sheep than in goats, with the highest prevalence in spring and the lowest in winter. Females and animals younger than 6 months were similarly found to be more susceptible to coccidiosis than males and older animals (P<0.05). In comparison to the southern area, the western and eastern counties had the highest rates of oocyst excretion in sheep and goats, respectively. In addition, a total of fourteen Eimeria species were isolated, including the highly pathogenic Eimeria granulosa for sheep and E. jolchijevi for goats. These findings explain how coccidia prevalence varies with age, season, and geographic direction, and use of PCR to rule out the possibility of co-infection between sheep and goats kept in the same stall.

Multi-Scenario Simulation of Land-Use Change and Delineation of Urban Growth Boundaries in County Area: A Case Study of Xinxing County, Guangdong Province

Delineating urban growth boundaries (UGBs) by combining the land-use/land-cover (LULC) change simulation method has become common in recent studies. However, few of the existing studies have integrated multi-source big data to analyze the driving factors of LULC dynamics in the simulation. Moreover, most of previous studies mainly focused on the UGBs delineation in macroscale areas rather than small-scale areas, such as the county area. In this study, taking Xinxing County of Guangdong Province as the study area, we coupled a system dynamics (SD) model and a patch-generating land-use simulation (PLUS) model to propose a framework for the LULC change simulation and UGBs delineation in the county area. Multi-source big data such as points of interest (POIs), night-time light (NTL) data and Tencent user density (TUD) were integrated to analyze the driving forces of LULC change. The validation results indicate that the coupled model received high accuracy both in the land-use demand projection and LULC distribution simulation. The combination of multi-source big data can effectively describe the influence of human socio-economic factors on the expansion of urban land and industrial land. The UGBs delineation results have similar spatial patterns with the LULC change simulation results, which indicates that the proposed UGBs delineation method can effectively transform the LULC simulation results into available UGBs for the county area. It has been proven that the proposed framework in this study is effective for the LULC change simulation and UGBs delineation in the county area, which can provide insight on territorial spatial planning in the county area.

County Ecosystem Health Assessment Based on the VORS Model: A Case Study of 183 Counties in Sichuan Province, China

The scientific assessment of the health level of county ecosystems is the basis for formulating county-based sustainable development strategies. In this paper, we take the county areas of Sichuan Province as the evaluation objects and combine the SDGs (the Sustainable Development Goals) to establish a county ecosystem health evaluation index system based on the VORS (Vigor–Organization–Resilience–Service) model. On this basis, we used the entropy weight method, the Moran index method, and the obstacle degree model to analyze the ecosystem health level, spatial distribution characteristics, and obstacles of 183 counties in Sichuan Province. The main results were as follows: (1) A total of 80.87% of the counties in Sichuan Province were at sub-healthy and healthy levels, concentrated in the southeastern part of Sichuan, and 19.13% of the counties were at an unhealthy level, mainly in the Aba, Ganzi, and Liangshan areas. (2) The health levels of county ecosystems in Sichuan Province had high spatial autocorrelation characteristics. The H–H (High–High) agglomeration area and the L–L (Low–Low) agglomeration area had significant agglomeration characteristics, which were distributed in the Cheng-Mian area and the northwestern Sichuan area, respectively. (3) The key indicators restricting the healthy development of urban ecosystems in Sichuan counties are economic vitality, economic resilience, and quality of life, all of which belong to the economic subsystems, with obstacles reaching 17.25%, 16.68%, and 13.52%, respectively. This study can provide theoretical and methodological support for research into ecosystem health evaluations at the county level, and provide a decision-making basis for promoting the health of county ecosystems and coordinating regional development in Sichuan Province.

Overweight and obesity status and its associated factors among primary and secondary school students in China rural middle and western regions

Objective: To analyze the overweight and obesity status of students in the national pilot counties of the Nutrition Improvement Program for Rural Compulsory Education Students in 2019 and its associated factors. Methods: In 2019, a multi-stage cluster random sampling method was used to select about 40 students from each grade in primary and secondary schools in China's central and western regions where the Nutrition Improvement Program for Rural Compulsory Education Students was implemented. The height and weight of the children were measured using height or weight scales. The school questionnaire and county questionnaire were used to investigate the associated factors. A Chi-square test was used for comparison between groups. The logistic regression analysis was used to analyze the associated factors. Results: In 2019, the prevalence of overweight and obesity among rural primary and secondary school students aged 6-15 years in central and western China 2019 was 11.5%. It was higher for boys (13.1%) than that for girls (9.8%), higher in central (14.3%) than that in the west (9.9%) and higher for elementary school students (12.4%) than that for secondary school students (9.5%, all P<0.001). The logistic regression showed that boys (OR=1.388), primary school students (OR=1.271), students without other dietary subsidies(OR=1.037), schools in rural areas (OR=1.133), schools with enterprise-based feeding mode (OR=1.043), schools without the provision of lunch (OR=1.143), schools without the provision of dinner (OR=1.122), and schools without providing drinking water (OR=1.015) were positively associated with overweight and obesity among students (P<0.05). Schools with snack shops (OR=0.952) were negatively associated with overweight and obesity among students (P<0.001). Conclusion: A certain proportion of primary and secondary school students in rural areas of central and western China are overweight and obese. The prevalence is not only related to children's gender, school section and county area but also related to school meals, whether schools provide drinking water and other factors.

Irrigation-Induced Environmental Changes Sustain Malaria Transmission and Compromise Intervention Effectiveness.

Irrigated agriculture enhances food security, but it potentially promotes mosquito-borne disease transmission and affects vector intervention effectiveness. This study was conducted in the irrigated and nonirrigated areas of rural Homa Bay and Kisumu Counties, Kenya. We performed cross-sectional and longitudinal surveys to determine Plasmodium infection prevalence, clinical malaria incidence, molecular force of infection (molFOI), and multiplicity of infection. We examined the impact of irrigation on the effectiveness of the new interventions. We found that irrigation was associated with >2-fold higher Plasmodium infection prevalence and 3-fold higher clinical malaria incidence compared to the nonirrigated area. Residents in the irrigated area experienced persistent, low-density parasite infections and higher molFOI. Addition of indoor residual spraying was effective in reducing malaria burden, but the reduction was more pronounced in the nonirrigated area than in the irrigated area. Our findings collectively suggest that irrigation may sustain and enhance Plasmodium transmission and affects intervention effectiveness.

기초자치단체별 급성기 뇌졸중 사망률과 지역사회 위험요인 분석

We aim to elucidate the discrepancies in acute stroke mortality among primary local governments and identify the risk factors of the mortality at loco-regional level to establish tailored health policies in Korea.&#x0D; From January 1, 2017 to December 31, 2019, the mortality rates of patients who died from stroke within 30 days of hospitalization in 226 municipalities were analyzed using the claims data accumulated by Health Insurance Review and Assessment Service. Demographic factors (elderly population ratio, gender ratio, alcohol consumption rate, smoking rate, subjective health status awareness), socioeconomic factors (ratio of old houses, financial autonomy rate, rate of medical aid beneficiaries) and medical resource factors (number of hospitals/ doctors) were analyzed.&#x0D; Acute stroke mortality rate in Korea is 12.1 ± 2.2%. The region with the lowest mortality rate is Gyeonggi Province (local government mainly consisting of urban cities) and regions with the highest mortality rates are North Chungcheong Province and South Jeolla. The elderly population is associated with mortality using overall nationwide data. It was also risk factor for stroke mortality in the cities or counties in rural areas. The male-female ratio, alcohol consumption rate, financial autonomy rate, and number of hospitals in the region were also mortality risk factors based on the data of urban cities.&#x0D; Based on the results from counties, the proportion of elderly population and financial autonomy rate were found to be a significant risk factor for stroke mortality in small towns in rural areas. Regional differences of acute stroke mortality were also found.&#x0D; Aside from demographic factors (proportion of elderly population), socioeconomic factors (financial autonomy rate) were identified as risk factors for acute stroke mortality. Collectively, it is necessary to build health care policies that address the health inequality at the loco-regional level.

Quantifying Subnational Economic Complexity: Evidence from Romania

Over the last two decades, Romania has undergone strong economic growth, catching up to advanced economies and producing one of the best economic performances in the world. Along with these positive changes, industrial product diversification has increased through expanded foreign economic relations, with all of these supporting the complexity of economic activities. Even though there is a world ranking of countries showing the highest level of economic complexity, there is no information about regional contributions to the overall score in Romania. This paper fills this gap by measuring the economic complexity of Romania’s subnational areas (counties) in the last ten years. To calculate the Economic Complexity Index (ECI) at a regional level, 615 economic activities (four-digit classes according to the NACE classification) were taken into consideration, grouped into 68 cluster categories. The results show that significant changes in economic complexity have mainly occurred in less developed areas, the upper- and middle-ranked counties’ positions being relatively stable. Furthermore, we examined the impact of complexity on growth and convergence, finding that the ECI index is a good predictor both for future economic growth as well as for the evolution of income inequalities.

Patient Access to Care: In-Network and Out-of-Network Utilization of Services

Background: Access to health care is impacted by several key factors such as urbanization, insurance coverage, availability of health care facilities, specialists, and equipment. For an in-depth understanding of Portage County area residents' health care utilization location choices, a study was conducted to identify the main factors and assess health care outmigration. Methods: A total of 125 292 patients were identified using 2019 administrative health data from University Hospitals Portage Medical Center in Portage County, Ohio. A descriptive analysis, t test, and chi-square tests were used to examine 3 primary outcomes: (1) patients’ demographics (age, gender, insurance, etc.), (2) time and distance patients are willing to travel for care, and (3) health services demand that is causing outmigration. Results: An analysis of 119 034 patients showed 66% of patients stayed in network and 34% went out of network. In-network participants had an average travel time of 30 minutes [95% CI, 29.5 to 29.8] and an average distance of 19.4 miles [95% CI, 15.9 to 16.1]. Conversely, out-of-network participants averaged 43 minutes [95% CI, 43.1 to 43.5] and 30.8 miles [95% CI, 30.4 to 30.8]. Outmigration was mainly influenced by the need for radiology services (66.3%), specifically mammograms (12.7%), computerized tomography (CT) (39.2%), and lab (18.2%). Conclusion: Outmigration can negatively impact a county's health care infrastructure and growth and contribute to a loss of revenue to the local hospitals. In this case, out-of-network services are more commonly used for radiology and lab work than for chronic conditions. It is recommended that both physicians and patients become knowledgeable about the impact of seeking out-of-network care

Study on the threshold value of disaster-causing factors of engineering slope cutting in red-layer areas

Slope cutting is becoming more common in engineering construction to obtain a large floor area. Slope cutting disrupts a slope’s inherent stability, causing instability and sliding. To solve the problem of geological disasters caused by artificial slope cutting, Cangxi County is used as an example to analyze the cutting slope and the height of different slope structures in the county, to study the disaster mode and disaster factors caused by slope cutting, and to analyze the influence of slope cutting height and slope cutting gradient on the disaster process. This study demonstrates that the stability of cutting on different types of slopes is weakened to different degrees, with mixed rocky-soil slopes having the strongest resistance to weakening, thick-soil slopes the second strongest, and thin-soil slopes the weakest. Slope cutting is the main factor of disaster, and rainwater infiltration promotes landslide formation. Numerical simulation is employed to determine the proximities of the slope cutting height and slope cutting gradient, and 75% of the critical value is taken as the proposed threshold value of slope cutting. The recommended cut slope threshold value corresponds to the real stable cut slope gradient on site, and the research findings can be used to guide engineering cut slope decisions in Cangxi County and other red-layer areas.

Parking by the bay: The supply and implications of parking infrastructure in the San Francisco Bay Area

The San Francisco Bay Area is one of the most progressive transportation regions in the deployment of high-capacity transit and the use of policies to encourage active transportation. Yet, there remains a dearth of knowledge on the abundance and location of parking infrastructure. The extent and location of parking supply, including on-street and off-street spaces, are estimated for the nine-county Bay Area by creating a federated database that joins land use, transportation, parcel, building, and parking code layers to estimate the number and characteristics of parking spaces at the census block scale. This bottom-up parking space inventory results in an estimated 15 million parking spaces in the region: 8.6 million on-street and 6.4 million off-street. Residential parking dominates the share of supply at 70%, followed by commercial at 9.4%. Space density is greatest in downtown San Francisco, Oakland, and San Jose—largely attributed to high-rise structures. On-street parking is dominant in the North Bay, commanding 78% of total parking in Napa, 75% in Solano, 68% in Sonoma, and 67% in Marin County. Parking area constitutes 7.9% of the total incorporated area. Notably, when compared to other southwest cities (Phoenix Metropolitan Area and Los Angeles County), the Bay Area parking supply appears better utilized considering spaces per person, per car, and per job. The density and quantity of parking spaces in the Bay Area are critical insights toward developing targeted policies that encourage active mobility and support affordable housing.

A case–control study regarding factors associated with digital dermatitis in Norwegian dairy herds

BackgroundDigital dermatitis (DD) is a contagious bovine foot disease causing painful lesions, lameness, and reduced animal welfare. Previous studies indicate a complex aetiology of the disease. The aim of this study was to compare DD negative and DD positive herds to identify factors associated with DD in Norwegian dairy herds by analysing data obtained in a questionnaire and data recorded in the Norwegian Dairy Herd Recording System (NDHRS). The questionnaire was e-mailed to the owners of all 380 herds recorded with DD in 2019 and to 1530 randomly selected herds with no recordings of DD. Altogether 559 dairy herds were included in the final study population, of which 113 was classified as DD positive (≥ one cow recorded with DD in NDHRS) and 446 as DD negative. When stratified by housing system, the ratio between DD positive and negative herds was 108/281 in free stalls and 5/165 in tie stalls. Multilevel logistic regression was used to model the association between potential risk factors and variables related to the detection and diagnosis of DD, and the outcome in the free-stall population. Geographical area (county) was included in the model as a random effect.ResultsIn the final study population 108/113 (96%) of the DD positive herds were housed in free stalls versus 5/113 (4%) in tie stalls. The free-stall herds’ DD status was associated with purchase of cattle during the last 5 years (baseline: 0 animals, OR = 2.30 for category 12–27 animals, OR = 4.34 for 28–52 animals, and OR = 5.39 for ≥ 53 animals). The DD status was also associated with claw trimming frequency (Baseline: 1 < 2/year, OR = 0.41 for category < 1/year, and OR = 4.09 for ≥ 3/year), whether the claw trimming was done by a certified professional trimmer or not (baseline: ≤ 90% of the cows, OR = 3.98 for category ≥ 90% of the cows), cleaning of feet in the chute before trimming (baseline: no cleaning, OR = 1.98 for category cleaning), and alley flooring (baseline: slatted floor, OR = 2.36 for category solid floor).ConclusionsDigital dermatitis was far more frequent in Norwegian dairy herds housed in free stalls versus those housed in tie stalls. In the free-stall herds purchase of cattle, increasing trimming frequency, use of certified professional trimmer, cleaning of the feet in the chute, and solid flooring in the alleys were associated with increased odds of recorded DD.

Bank Competition, Financing Constraints and Enterprise Innovation

Abstract In recent years, the innovation behavior of enterprises has attracted more and more attention. Our study proves that encouraging bank competition can promote enterprise innovation. The study found that there is a negative correlation between the bank concentration index in county areas and the innovation output of local enterprises in China. At the same time, we find that bank competition can more effectively improve the financing constraints of private enterprises and small enterprises, thus promoting enterprise innovation. JEL classification numbers: G21,O31,O32. Keywords: Bank Competition; Financing Constraints; Enterprise Innovation; Credit Discrimination.

Holocene Slip Rate Along the Beng Co Fault and Dextral Strike‐Slip Extrusion of Central Eastern Tibet

AbstractThe dearth of quantitative studies of Holocene fault slip‐rates makes kinematic modeling of crustal deformation across SE Tibet debatable. The ∼230 km long, WNW‐striking, dextral Beng Co fault (BCF) is the most prominent strike‐slip fault of southern Tibet. Using new UAV topographic data and OSL/14C dating of geomorphic markers, we measure horizontal offsets and ages of fluvial terraces/fans and lacustrine shorelines at eight sites west and east of the Beng Lake pull‐apart. Along the eastern BCF's northern branch, our measurements at two different locations are consistent with offsets of ∼4.7 ± 1.1 and ∼8.7 ± 0.7 m during the past ∼3.1–3.6 and 3.6–5.2 ka, respectively. Along the southern branch, ∼25 ± 5 m of slip have accrued since ∼9 ka. The total Holocene slip‐rate across both faults (4.2–5.4 or 4.8 ± 0.5 mm/yr), consistent with GPS/InSAR values, implies that the BCF contributes significantly to the eastward extrusion of eastern‐central Tibet. This rate is slightly larger than the lower bound of the extension rate (∼6 ± 1.8 mm/yr) recently determined across the middle Gulu rift normal fault, which splays off southwards from the southeastern tip of the BCF's southern branch. Empirical relationships suggest that the reported ∼90 km length of theMw7.7, 1951 Beng Co earthquake surface rupture is too short, which implies that the eastern BCF is immature, or requires additional, partly deep slip, along other branches of the eastern BCF. That there is no field evidence of rupturing along the western BCF in the last ∼1,000 yr indicates that the Bange County area, west of Beng Co, may be at risk of anMw ≈ 7.4? event.

Spatial and Temporal Distribution Pattern of Oncomelania hupensis Caused by Multiple Environmental Factors Using Ecological Niche Models

Objective: This study aimed to predict the spatial and temporal distribution pattern of Oncomelania hupensis (O. hupensis) on a fine scale based on ecological niche models, so as to provide insights into O. hupensis surveillance.Methods: Geographic distribution and environmental variables of O. hupensis in Suzhou City were collected from 2016 to 2020. Five machine learning algorithms were used, including eXtreme gradient boosting (XGB), support vector machine (SVM), random forest (RF), generalized boosted (GBM), and C5.0 algorithms, to predict the distribution of O. hupensis and investigate the relative contribution of each environmental variable. The accuracy of the five ecological niche models was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) with ten-fold cross-validation.Results: Five models predicted that the potential distribution of O. hupensis was in southwestern areas of Wuzhong, Wujiang, Taichang, and Xiangcheng counties. The AUC of RF, XGB, GBM, SVM, and C5.0 algorithms were 0.8233, 0.8051, 0.7938, 0.7897, and 0.7282, respectively. Comparing the predictive results and the truth of O. hupensis distribution in 2021, XGB and GBM models were shown to be more effective. The six greatest contributors to predicting potential O. hupensis distribution included silt content (13.13%), clay content (10.21%), population density (8.16%), annual accumulated temperatures of ≥0°C (8.12%), night-time lights (7.67%), and average annual precipitation (7.23%).Conclusions: Environmental factors play a key role in the spatial and temporal distribution pattern of O. hupensis. The XGB and GBM machine learning algorithms are effective and highly accurate for fine-scale prediction of potential O. hupensis distribution, which provides insights into the surveillance of O. hupensis.

THE RESEARCH TREND OF EMOTION REGULATION PSYCHOLOGICAL GAME TECHNOLOGY IN SPECIAL EDUCATION IN CHINA FROM THE PERSPECTIVE OF SOCIAL NETWORK ANALYSIS

THE RESEARCH TREND OF EMOTION REGULATION PSYCHOLOGICAL GAME TECHNOLOGY IN SPECIAL EDUCATION IN CHINA FROM THE PERSPECTIVE OF SOCIAL NETWORK ANALYSIS