Search

African swine fever (ASF) is a severe infectious disease affecting domestic and wild suids. Spatiotemporal dynamics analysis of the ASF is crucial to understanding its transmission. The ASF broke out in Vietnam in February 2019. The research on the spatiotemporal evolution characteristics of ASF in Vietnam is lacking. Spatiotemporal statistical methods, including direction analysis, spatial autocorrelation analysis, and spatiotemporal scan statistics were used to reveal the dynamics of the spatial diffusion direction and spatiotemporal aggregation characteristics of ASF in Vietnam. According to the cessation of the epidemic, it was divided into three phases: February to August 2019 (phase 1), April to December 2020 (phase 2), and January 2021 to March 2022 (phase 3). The ASF showed a significant spread trend from north to south in phase 1. The occurrence rate of the ASF aggregated spatially in phase 1 and became random in phases 2 and 3. The high−high ASF clusters (the province was a high cluster and both it and its neighbors had a high ASF occurrence rate) were concentrated in the north in phases 1 and 2. Four spatiotemporal high-risk ASF clusters were identified with a mean radius of 121.88 km. In general, there were significant concentrated outbreak areas and directional spread in the early stage and small-scale, high-frequency, and randomly scattered outbreaks in the later stage. The findings could contribute to a deeper understanding of the spatiotemporal spread of the ASF in Vietnam.

Background: Research on the impact of the environment on COVID-19 lacks a full-comprehensive perspective, and neglecting the multiplicity of the human-environment system can lead to misleading conclusions. We attempted to reveal all environmental-to-human and human-to-human determinants that influence the transmission of COVID-19.Methods: We estimated the daily case incidence ratios (CIR) of COVID-19 for prefectures across mainland China, and used a mixed-effects mixed-distribution model to study the association between the CIR and 114 considered factors related to climate, atmospheric environmental quality, terrain, population, economic, human mobility as well as public health control measures (PHCMs). Results: CO, O3, PM10 and PM2.5 were positively linked with CIR, but the effect of NO2 was negative. The temperature had no significant association with CIR, and the daily minimum humidity was a significant negatively predictor. National emergency response level was negatively associated with CIR until with a lag of 15 days. Higher accumulated destination migration scale flow from the epicenter and lower distance to the epicenter (DisWH) were associated with a higher CIR, however, the interaction between DisWH and the time was positive. In China, the more economically developed and more densely populated cities have a higher probability of CIR occurrence, but they may not have a higher CIR intensity.Conclusion: The COVID-19 pandemic’s diffusion patterns are caused by a multiplicity of environmental, economic, social factors as well as public health control measures PHCMs. First, multiple pollutants carried simultaneously on particulate matter act in a synergistic way to affect COVID-19 transmission. Second, the temperature has a limited impact on the spread of the epidemic. Third, PHCMs must last for at least 15 days or longer before the effect has been apparent. Fourth, preventing the introduction of the epidemic between cities seemed to be more complex and difficult than controlling the growth of the epidemic within the city. China's relatively cautious response to the epidemic could provide lessons for countries that are still experiencing a health emergency and help to prevent future pandemics similar to COVID -19.

With the development of big data,Artificial intelligence applications are born,And has been better developed and improved.Artificial intelligence is no longer a concept on paper.It's developing as a world-changing and revolutionizing everything.Artificial intelligence is also gradually being widely used in various industries.The needs of artificial intelligence in each industry field are different,The development of artificial intelligence technology has also become a hotspot of research direction and application.For example, the communication industry is inseparable from our work life,This article will analyze the mutual integration of artificial intelligence technology and the communication industry,propose overlapping innovations between the two, In the field of information and communication, artificial intelligence helps the construction and operation of communication network, turns the conventional operation process to process automation, and realizes the cost reduction and efficiency increase of communication operation enterprises. AI can also optimize communication products and services, realize the convenient, accurate and intelligent development of communication services, and improve customer experience.

This article explores the obesity state and the changes in the level of lipophagy in adipose tissue after exercise to lose weight, so as to provide direction and basis for theoretical research on obesity prevention and control. We established a high-fat diet model of obese mice, and applied exercise intervention and intraperitoneal injection of chloroquine to inhibit autophagy. Long-term high-fat diet can cause obesity in mice, and the process of lipophagy is inhibited, which may be one of the reasons for fat accumulation. Eight weeks of aerobic exercise can effectively reduce the weight of obese mice and promote lipolysis; this process is mainly completed by lipase decomposition, in addition to require the participation of the lipophagy process.

At present, single-domain MPLS VPN is widely used. In many services, MPLS VPN across multiple autonomous systems is required. Nowadays, three main cross-domain VPN technologies are used at home and abroad. This thesis mainly discusses the third VPN-OptionC used to reduce the burden of ASBR. In this paper a typical VPN-OptionC model is used to introduce the configuration methods and considerations in detail. Meanwhile, the configuration requirements and the ideas and methods for solving practical problems are analyzed. Finally, the corresponding configuration process and phase detection methods are proposed in order to reduce the number of failures.

Cropland redistribution to marginal land has been reported worldwide; however, the resulting impacts on environmental sustainability have not been investigated sufficiently. Here we investigated the environmental impacts of cropland redistribution in China. As a result of urbanization-induced loss of high-quality croplands in south China (∼8.5 t ha–1), croplands expanded to marginal lands in northeast (∼4.5 t ha–1) and northwest China (∼2.9 t ha–1) during 1990–2015 to pursue food security. However, the reclamation in these low-yield and ecologically vulnerable zones considerably undermined local environmental sustainability, for example increasing wind erosion (+3.47%), irrigation water consumption (+34.42%), fertilizer use (+20.02%) and decreasing natural habitats (−3.11%). Forecasts show that further reclamation in marginal lands per current policies would exacerbate environmental costs by 2050. The future cropland security risk will be remarkably intensified because of the conflict between food production and environmental sustainability. Our research suggests that globally emerging reclamation of marginal lands should be restricted and crop yield boost should be encouraged for both food security and environmental benefits., Widespread loss of high-quality cropland induced by urbanization and increasing shift of crop production to low-quality marginal land threaten food security and environmental sustainability.

As a highly contagious disease, COVID-19 caused a worldwide pandemic and it is still ongoing. However, the infection in China has been successfully controlled although its initial transmission was also nationwide and has caused a serious public health crisis. The analysis on the early-stage COVID-19 transmission in China is worth investigating for its guiding significance on prevention to other countries and regions. In this study, we conducted the experiments from the perspectives of COVID-19 occurrence and intensity. We eliminated unimportant factors from 113 variables and applied four machine learning-based classification and regression models to predict COVID-19 occurrence and intensity, respectively. The influence of each important factor was analysed when applicable. Our optimal model on COVID-19 occurrence prediction presented an accuracy of 91.91% and the best R2 of intensity prediction reached 0.778. Linear regression-based model was identified as unable to fit and predict the intensity, and thus only the variable influence on COVID-19 occurrence can be explained. We found that (1) CO VID-19 was more likely to occur in prosperous cities closer to the epicentre and located on higher altitudes, (2) and the occurrence was higher under extreme weather and high minimum relative humidity. (3) Most air pollutants increased the risk of COVID-19 occurrence except NO2 and O3, and there existed a lag effect of 6–7 days. (4) NPIs (non-pharmaceutical interventions) did not show apparent effect until two weeks after.

Background Schistosomiasis remains prevalent in Africa, Asia and South America with an estimated burden of 1.9 million disability-adjusted life years in 2016. Targeting snails as a key to success for schistosomiasis control has been widely approved, but the long-term quantitative effects of interventions on snail control that would inform and improve future control programmes are unclear. Over the last six decades, schistosomiasis in China had been brought largely under control, and snail control as supplementary methods or part of integrated multisectoral approaches in different historical periods has played an essential role. Methods Ecological environment factors, prevalence and control data on Oncomelania hupensis between 1985 and 2015 at 5-year intervals in Qianjiang city, China, were collected. A multilevel growth model approach was used to examine the long-term effects of ecological environmental changes and mollusciciding on snail-infested area (SIA) and living snail density (LSD) during the 30 years. Results The variation of SIA was 68.4% in spatial distribution, while the variation of LSD was 68.4% in temporal distribution. Continuous mollusciciding could result in significant LSD reduction, but may not lead to significant SIA reduction. The normalized difference vegetation index (NDVI), patch size coefficient of variation (PSCoV) and mean patch size (MPS) reduction, slightly due to eco-environmental changes decreased SIA, while mean perimeter-area ratio (MPAR) and dry farm-land proportion (DFLP) reduction might increase SIA. Only NDVI and MPAR reduction led to a lower LSD. Conclusions Mollusciciding was more effective in reducing snail density, but it is not easy to eliminate snails completely. Environmental modifications could completely change the snail breeding environment and reduce its infestation area. Due to difficulty of scaling-up the current environmental modifications in waterway network regions, more effective snail control methods are needed. The experience in China could thereby provide guidance for other schistosomiasis endemic areas with a high snail prevalence.

// Ruixia Yuan 1, 2 , Hairong Wu 3 , Heng Zeng 2 , Ping Liu 2 , Quangang Xu 2 , Lu Gao 2 , Yin Li 2 , Rendong Li 4 , Duan Huang 4 , Chuanhua Yu 1 and Xiangdong Sun 2 1 Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei Province, China 2 China Animal Health and Epidemiology Center, Qingdao 266032, Shandong Province, China 3 College of Journalism and Communication, Guangxi University, Nanning 530004, Guangxi Province, China 4 Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, Hubei Province, China Correspondence to: Chuanhua Yu, email: yuchua@whu.edu.cn Xiangdong Sun, email: sunxiangdong@cahec.cn Keywords: cystic echinococcosis, prevalence, risk factors, herding families, China’s western provinces Received: June 03, 2017 Accepted: August 04, 2017 Published: September 23, 2017 ABSTRACT Echinococcosis is a severe zoonosis that endangers the health of herdsmen in China’s western provinces. This study aimed to examine the prevalence of this disease and identify potential factors associated with human echinococcosis among herding families. A cross-sectional study was conducted in five provinces in western China from May 1, 2016 to November 30, 2016, and 1500 herding families participated in the study. A total of 1211 completed questionnaires were analyzed. The prevalence of Cystic echinococcosis (CE) among surveyed herding families was 1.55%. The results of multivariate analysis revealed that the sheep immunization (OR=0.35, 95%CI 0.21-0.58), being concerned about family members echinococcosis (OR=0.49, 95%CI 0.28-0.84) were protective factors, while allowing dogs to roam free (OR=3.17, 95%CI 1.89-5.31), feeding dogs with viscera (OR=3.04, 95%CI 1.83, 5.03), slaughter at home (OR=3.53, 95%CI 2.04-6.12), drinking non-boiled water (OR=2.15, 95%CI 1.28-3.63), eating raw vegetables (OR=1.87, 95%CI 1.13-3.10), not washing hands before meals (OR=3.08, 95%CI 1.68-5.65), and often seeing stray dogs (OR=2.60 95%CI 1.38-4.91) and wild animals (OR=1.92, 95%CI 1.17-3.14) near habitations were more associated with increased risk of infection. Immunizing sheep, appropriately managing domestic and stray dogs, and improving living environments and behavioral factors may help to reduce the risk of human echinococcosis in western China.

Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.

The spatiotemporal dynamics of Schistosoma japonicum, combined with temporal heterogeneity among regions of different epidemic areal-types from a microscale viewpoint might capture the local change dynamics and thus aid in optimizing the combinations of precise schistosomiasis control measures. The prevalence data on schistosomiasis infection from 2007 to 2012 in the 30 most endemic counties of Hubei Province, Central China, were appended to the village-level administrative division polygon layer. Anselin local Moran&rsquo, s I, a retrospective space&ndash, time scan statistic and a multilevel-growth model analysis framework, was used to investigate the spatiotemporal pattern of schistosomiasis resident infection rate (RIR) at the village level and how natural geographical environment influence the schistosomiasis RIR over time. Two spatiotemporal high-risk clusters and continuous high-rate clusters were identified mainly in the embankment region across flooding areas of lakes connected with the Yangze and Hanjiang Rivers. Moreover, 12 other clusters and outlier evolution modes were detected to be scattered across the continuous high-rate clusters. Villages located in embankment region had the highest initial values and most rapidly reduced RIRs over time, followed by villages located in marshland-and-lake regions and finally by villages located in hilly region. Moreover, initial RIR values and rates of change did significantly vary (p &lt, 0.001 and p &lt, 0.001, respectively) irrespective of their epidemic areal-type. These local spatiotemporal heterogeneities could contribute to the formulation of distinct control strategies based on local transmission dynamics and be applied in other endemic areas of schistosomiasis.

Schistosomiasis is a snail-borne parasitic disease endemic to the tropics and subtropics, whose distribution depends on snail prevalence as determined by climatic and environmental factors. Here, dynamic spatial and temporal patterns of Oncomelania hupensis distributions were quantified using general statistics, global Moran&rsquo, s I, and standard deviation ellipses, with Maxent modeling used to predict the distribution of habitat areas suitable for this snail in Gong&rsquo, an County, a severely affected region of Jianghan Plain, China, based on annual average temperature, humidity of the climate, soil type, normalized difference vegetation index, land use, ditch density, land surface temperature, and digital elevation model variables, each variable&rsquo, s contribution was tested using the jackknife method. Several key results emerged. First, coverage area of O. hupensis had changed little from 2007 to 2012, with some cities, counties, and districts alternately increasing and decreasing, with ditch and bottomland being the main habitat types. Second, although it showed a weak spatial autocorrelation, changing negligibly, there was a significant east&ndash, west gradient in the O. hupensis habitat area. Third, 21.9% of Gong&rsquo, an County&rsquo, s area was at high risk of snail presence, and ditch density, temperature, elevation, and wetting index contributed most to their occurrence. Our findings and methods provide valuable and timely insight for the control, monitoring, and management of schistosomiasis in China.

Paddy rice is one of the main grain crops in the world. Accurate estimations of the gross primary production (GPP) of paddy rice are essential for assessing rice grain production and monitoring the carbon cycle in paddy fields with the aim of providing ideal conditions for crops throughout the growing season. Several studies have demonstrated the advantages of combining the eddy covariance technique with remotely sensed data to model GPP at CO2 eddy flux tower sites. As paddy rice continuously changes during its growth and development, and important growth events frequently occur, it is critical to observe the growing conditions at various stages of the process. To better understand the variations in GPP at different growth stages, two key parameters that drive the vegetation photosynthesis model (VPM) are analyzed and estimated at various phenological phases. Specifically, general piecewise logistic functions are used to extract phenological transitions from data at four paddy rice flux tower sites. The maximum light-use efficiency (LUE) and optimum temperature are estimated from these phenological transitions, and these indicators are used to drive the VPM to simulate GPP over multiple years at the four sites. The simulation results show that GPP based on our phenological transition-based VPM (GPPPVPM) agrees reasonably well with the variations of GPP estimated from CO2 flux data (GPPEC) (R2 > 0.9). In addition, a comparison indicates that GPPPVPM tracks the seasonal dynamics of GPPEC better than GPP estimated from the original VPM. Furthermore, GPP based on the improved maximum LUE is lower than GPPEC at most flux sites and GPP based on the improved optimum temperature is higher than GPPEC. These comparisons imply that the maximum LUE and optimum temperature estimated in the phenological transitions of paddy rice are beneficial to enhance the accuracy of GPP estimation. The improved estimation of GPP provides phenological insights into the temporal dynamics of vegetation photosynthesis in paddy fields.

More attentions have been paid on humping characteristic in single pass high energy density welding of medium or thick plate in recent years. In this paper, the hump phenomenon of the weld root is observed by laser-leading laser-arc hybrid welding of 12 mm-thick steel plate. Combining with the surface molten pool flow behavior, force mechanism of force analyzed, the hump formation process can be divided into pool pooling stage, pool sagging growth stage, and the solidification stage. It is proved that the balance between gravity and surface tension of the molten pool is the main reason for the formation of hump. Furthermore, the arc-leading laser-arc hybrid welding process was realized to obtain single-pass welding joint without hump defects. In view of comparing and discussing the droplet transition feature, electrical parameters, and exerted force under the optimal process of arc-leading and laser-leading, we had a better understanding of reasons why the arc-leading inhibits the formation of hump, and proved that the arc-leading electrical parameters are more stable.

The study aimed to reveal the risk factors and predict the prevalence of human cystic echinococcosis (CE) in Western China. To do this, we analyzed county-wide data relating to the prevalence of human CE in seven provinces of Western China, along with associated human, natural geographical environmental data. We then used spatial analysis and multiple regression analysis to investigate the correlation between the prevalence of human CE and associated environmental factors and to create a risk map of the disease in the seven provinces. Our analysis showed that grassland area ratio and Tibetan population ratio were independent variables positively correlated with the prevalence of human CE and that gross domestic product (GDP) and land surface temperature (LST, Spring) were negative independent variables. We also created a predictive risk map of human CE that revealed that the high-risk areas were mainly located in the south of Qinghai, the Northwest of Sichuan and most of the Tibet Autonomous Region. Knowledge of the spatial distribution and risk factors associated with human CE could help to prevent and control echinococcosis in China.

This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff&rsquo, s spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial cluster in 2007 covered the north-central part of Jianghan Plain, whereas those observed from 2008 to 2012 were toward the south, with extended coverage in generally the same areas across various periods, and some variation nevertheless in precise locations. Furthermore, the 2007 period was more likely to be clustered than any other period. We found that temperature, land use, and soil type were the most critical factors associated with infection rates in humans. In addition, land use and soil type had the greatest impact on the prevalence of schistosomiasis in 2009, whereas this effect was minimal in 2007. The effect of temperature on schistosomiasis prevalence reached its maximum in 2010, whereas in 2008, this effect was minimal. Differences observed in the effects of those two factors on the spatial distribution of human schistosomiasis were inconsistent, showing statistical significance in some years and a lack thereof in others. Moreover, when two factors operated simultaneously, a trend of enhanced interaction was consistently observed. High-risk areas with strong interactions of affected factors should be targeted for disease control interventions.

The spatial pattern of dengue fever cases is the result of complex interactions between the virus, the host and the vector, which may be affected by environmental conditions. The largest outbreak of dengue fever in Guangzhou city, China occurred in 2014 with case numbers 2.7 times the number of cumulative cases since 1978 and a significantly non-random spatial distribution. Selecting Guangzhou City as the study area, we used scan statistics to analyze the spatial heterogeneity of dengue fever and a generalized additive model to evaluate and examine the effects of socio-economic and environmental factors on spatial heterogeneity at a fine scale. The study found that the spatial distribution of dengue fever is highly heterogeneous and various factors differ in relative importance. The junction of the central districts of Guangzhou is a high-risk area with the urban village and urban-rural fringe zone formed by urbanization as important regional factors. The low gross domestic product per capita, the high population density, the high road density were perceived as risk factors. The Asian subtropical coastal area together with the socioeconomic and environmental factors were found to be the key drivers at the fine scale explaining the high spatial heterogeneity of dengue fever in Guangzhou City.

Mapping the magnitude and spatial distribution of forest aboveground biomass (AGB, in Mg·ha−1) is crucial to improve our understanding of the terrestrial carbon cycle. Landsat/TM (Thematic Mapper) and ICESat/GLAS (Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System) data were integrated to estimate the AGB in the Changbai Mountain area. Firstly, four forest types were delineated according to TM data classification. Secondly, different models for prediction of the AGB at the GLAS footprint level were developed from GLAS waveform metrics and the AGB was derived from field observations using multiple stepwise regression. Lastly, GLAS-derived AGB, in combination with vegetation indices, leaf area index (LAI), canopy closure, and digital elevation model (DEM), were used to drive a data fusion model based on the random forest approach for extrapolating the GLAS footprint AGB to a continuous AGB map. The classification result showed that the Changbai Mountain region was characterized as forest-rich in altitudinal vegetation zones. The contribution of remote sensing variables in modeling the AGB was evaluated. Vegetation index metrics account for large amount of contribution in AGB ranges

Schistosomiasis japonica is an infectious disease caused by Schistosoma japonicum, and it remains endemic in China. Flooding is the main hazard factor, as it causes the spread of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum, thereby triggering schistosomiasis outbreaks. Based on multi-source real-time remote sensing data, we used remote sensing (RS) technology, especially synthetic aperture radar (SAR), and geographic information system (GIS) techniques to carry out warning research on potential snail habitats within the snail dispersal range following flooding. Our research result demonstrated: (1) SAR data from Sentinel-1A before and during a flood were used to identify submerged areas rapidly and effectively; (2) the likelihood of snail survival was positively correlated with the clay proportion, core area standard deviation, and ditch length but negatively correlated with the wetness index, NDVI (normalized difference vegetation index), elevation, woodland area, and construction land area; (3) the snail habitats were most abundant near rivers and ditches in paddy fields; (4) the rivers and paddy irrigation ditches in the submerged areas must be the focused of mitigation efforts following future floods.

A total of 134 laboratory-confirmed human cases of the novel avian-origin influenza A(H7N9) were reported in China between February to July 2013. To illustrate the spatiotemporal patterns of H7N9 outbreaks in humans and investigate the risk factors associated with their distribution, we mapped the distribution of affected human cases and carried out directional distribution analysis and a direction test. We also collected data on anthropogenic, vegetation, climatic, and topographic factors, and used multiple logistic regression to examine the contribution of each factor. Two different spatiotemporal patterns were found: clustered and regular directional distributions in four distinct temporal phases in the Yangtze River Delta, and sporadic but spread in three direction across the provinces adjacent to the Yangtze River Delta. Mean monthly precipitation, mean monthly temperature, normalized difference vegetation index, and poultry consumption were significantly associated with the occurrence of human H7N9 infection. The model generated a map showing the high-risk areas for human H7N9 infection for mainland China. These findings provide an empirical basis for identifying priority areas for implementing preventive intervention to reduce the number of future human infections.

China is the largest developing country worldwide, with rapid economic growth and the highest population. Light pollution is an environmental factor that significantly influences the quality and health of wildlife, as well as the people of any country. The objective of this study is to model the light pollution spatial pattern, and monitor changes in trends of spatial distribution from 1992 to 2012 in China using nighttime light imagery from the Defense Meteorological Satellite Program Operational Linescan System. Based on the intercalibration of nighttime light imageries of the study area from 1992 to 2012, this study obtained the change trends map. This result shows an increase in light pollution of the study area; light pollution in the spatial scale increased from 2.08% in the period from 1992–1996 to 2000–2004, to 5.64% in the period from 2000–2004 to 2008–2012. However, light pollution change trends presented varying styles in different regions and times. In the 1990s, the increasing trend in light pollution regions mostly occurred in larger urban cities, which are mainly located in eastern and coastal areas, whereas the decreasing trend areas were chiefly industrial and mining cities rich in mineral resources, in addition to the central parts of large cities. Similarly, the increasing trend regions dominated urban cities of the study area, and the expanded direction changed from larger cities to small and middle-sized cities and towns in the 2000s. The percentages of regions where light pollution transformed to severe and slight were 5.64% and 0.39%, respectively. The results can inform and help identify how local economic and environmental decisions influence our global nighttime environment, and assist government agencies in creating environmental protection measures.

This study aims to identify the landscape ecological determinants related to Oncomelania hupensis distribution, map the potential high risk of O. hupensis habitats at the microscale, and assess the effects of two environmental control strategies. Sampling was performed on 242 snail sites and 726 non-snail sites throughout Qianjiang City, Hubei Province, China. An integrated approach of landscape pattern analysis coupled with multiple logistic regression modeling was applied to investigate the effects of environmental factors on snail habitats. The risk probability of snail habitats positively correlated with patch fractal dimension (FD), paddy farm land proportion, and wetness index but inversely correlated with categorized normalized difference vegetation index (NDVI) and elevation. These findings indicate that FD can identify irregular features (e.g., irrigation ditches) in plain regions and that a moderate NDVI increases the microscale risk probability. Basing on the observed determinants, we predicted a map showing high-risk areas of snail habitats and simulated the effects of conduit hardening and paddy farming land rotation to dry farming land. The two approaches were confirmed effective for snail control. These findings provide an empirical basis for health professionals in local schistosomiasis control stations to identify priority areas and promising environmental control strategies for snail control and prevention.

Land-use/land-cover changes (LUCCs) have links to both human and nature inter- actions. China's Land-Use/cover Datasets (CLUDs) were updated regularly at 5-year inter- vals from the late 1980s to 2010, with standard procedures based on Landsat TM\ETM+ im- ages. A land-use dynamic regionalization method was proposed to analyze major land-use conversions. The spatiotemporal characteristics, differences, and causes of land-use changes at a national scale were then examined. The main findings are summarized as fol- lows. Land-use changes (LUCs) across China indicated a significant variation in spatial and temporal characteristics in the last 20 years (1990-2010). The area of cropland change de- creased in the south and increased in the north, but the total area remained almost un- changed. The reclaimed cropland was shifted from the northeast to the northwest. The built-up lands expanded rapidly, were mainly distributed in the east, and gradually spread out to central and western China. Woodland decreased first, and then increased, but desert area was the opposite. Grassland continued decreasing. Different spatial patterns of LUC in China were found between the late 20th century and the early 21st century. The original 13 LUC zones were replaced by 15 units with changes of boundaries in some zones. The main spatial characteristics of these changes included (1) an accelerated expansion of built-up land in the

The realization of 12mm thick laser-arc hybrid welding technology is the prerequisite for efficient production of new high-speed train bogies. In this work, for the laser-leading hybrid welding, the problem of hump defects in the root of the weld is easy to occur. The arc-leading mode is chosen to obtain the welded joint of high-strength bainitic steel with no hump, no unfilled and no porosity defects. Then the microstructure distribution of the welds of the high-strength bainitic steel is analyzed, which the weld metal is mainly composed of acicular ferrite and lath bainite and the heat affected zone mainly concludes coarse-grained bainite and granular bainite. Then, under the optimal process, the hardness distribution, arc action area size and weld impact performance of the laser-leading and arc-leading welds were compared. It was found that the arc-leading weld hardness distribution was more uniform and stable, and the hardness peaks both appear in the HAZ (coarse lath bainite), and the valleys both appear in partial phase-change zones (Bulk ferrite). Meanwhile, the arc-leading weld impact performance is 21.49% higher than that of laser-leading.

An investigation has been conducted to figure out the effect of plate thickness on the fatigue crack growth rate (FCGR) of a low carbon bainitic steel. Based on the standard ASTM E647, standard compact tension specimens with three different plate thicknesses were used in fatigue crack growth test and the crack closure was taken into consideration when calculating crack lengths. When analyzing the data obtained in fatigue tests, two different mathematic models were used to fit the relationship curve between crack length a and cycle number N. Results show that the low carbon bainitic steel with a bigger plate thickness has a lower crack growth rate in a short crack growing period. More information for crack growth behavior was obtained via the scanning electron microscope technique.

The prosperity of farmers is closely tied to governmental policies. The Jianghan Plain is an important region for commodity grains, cotton and edible oil for China. The trajectories of land use and land cover change (LUCC) of the study area from 1995 to 2010 were studied based on the LUCC database of the Chinese Academy of Sciences. The LUCC was characterised by a continuous decrease of arable land and continuous increase of waters and construction land. The LUCC was obviously concurrent with the implementation of related national policies. The transition to construction land was ever well controlled by 'Notice regarding the further strengthening of land management and arable land protection' promulgated in 1997. However, it flourished again with the 'Rise of Central China Strategy' taking effect since 2006. The transition of construction land to others reflects an uncommon trend, which must be strengthened with the strict implementation of the overall plan, which imposes a limited acreage quota of construction land to each district. The policies were quite contradictory to the transition of waters. LUCC related to waters is most active, which was driven by both natural forces and national policies. Just after the devastating flood of 1998, the state council of China put forward the Green Policy to govern the major rivers. As to the study area, it is mainly to 'push over dykes to let flood through and return farmland to lakes'. In 2004, the Grain Direct Subsidy Policy was implemented, which, along with the surge in the price of rice, resulted in a strengthening trend of conversion of ponds to paddy fields.

To understand the influence of meteorological factors on Oncomelania density in natural condition and provide scientific evidence for the control of the spread of schistosomiasis and Oncomelania.Based on the Oncomelania survey data in spring and ground meteorological observation data of Qianjiang from 1990 to 2014, the first-order autoregressive analysis method was used for trend fitting and disassemble, and the correlation between the change rate of Oncomelania density and various meteorological factors in different periods were analyzed.The greatest influence of meteorological factors on Oncomelania density was temperature, followed by precipitation. The average minimum temperature in January and from December to February had predominant influence on Oncomelania density and frame occurrence rate of living Oncomelania (FORLO) respectively. The rise (fall) of average minimum temperature in January by 1 °C would lead to the increase (decrease) of Oncomelania density by 5.080%-6.710%; The rise (fall) of average minimum temperature from December to February by 1 °C would lead to the increase (decrease) of FORLO by 15.521%-15.928%. The period with the biggest influence of precipitation on Oncomelania density was from November to April, as the rainfall declined20%, drought might occur, which would cause the reduction of Oncomelania density. Sunshine from September to November had some correlations with the change of Oncomelania density and FORLO. Statistical regression models for the change of Oncomelania density, FORLO and meteorological factors based on correlation analysis were established respectively.Weed removal in Oncomelania areas before December is beneficial to reduce the surface temperature and soil moisture content, which would result in Oncomelania density reduction in some extent. It' s notable that the winter temperature is in rise in Hubei province along with global climate change, causing the Oncomelania density to increase, to which more attention should be paid.