Baoji City Research Articles

MAGNETIC RESPONSE OF ENVIRONMENT POLLUTION ABOUT DUST-LOADED VEGETATION LEAVES ON MAIN ROADS IN BAOJI CITY

In order to explore the magnetic response of environmental pollution about dust-loaded leaves on main road in Baoji city, different types of leaves on both sides of streets were collected for systematic environmental magnetic tests. The results showed that the concentration of magnetic minerals on street leaves were higher than that in the campus and the main magnetic minerals were multi-domain magnetite and maghemite. The diameter of magnetic mineral was concentrated in 0.1~5 μm, among which the herbaceous far from the traffic lines had a relatively fineer particle size of 0.1~1 μm. Environmental pollution recorded by vegetation leaves at the same height and at different times (May and November) was different. Pollution recorded by herbaceous at 0.05 m height and trees leaves at 4 m height was more serious in May than in November, while that of the leaves of shrubs at 0.25 m and 1 m was worse in November. The spatial distribution of urban main roads presented two pollution peak areas, the zone A including Jiangtan road and Baofu road, and the zone B where Dongfeng road was located in, which are related to heavy traffic and heavy industrial enterprises.

Local Scour of Bridge Pier Sited on a Multi-Layered Sedimentary Bed in Rivers

The riverbeds or sea beds are usually composed of multi-layers of sediments. The scour around bridge piers sited on such beds is vital to the bridge safety, but is still very difficult to be predicated as its complicated interaction between the flow and bed layers. A simple model is proposed in this study for calculating the local scour maximum depth around bridge piers sited on multi-layer of sedimentary bed, which is based on HEC-18 formula revised by Richardson and Davis (2001) and the formula of the repose angle of sediment particles proposed by Cheng (1993). This model considers the particle sorting when the scour proceeds. An application of the model into the local scour depth of Guopan bridge pier sited on the Weihe River bed in Baoji city of China preliminarily demonstrates its reliability to calculate the local scour maximum depth around bridge piers sited on multi-layer of sedimentary bed.

Heavy Metal Pollution Characteristics and Influencing Factors in Baoji Arban Soils

In order to analyze the sources and factors influencing heavy metal pollution in industrial cities, 62 surface layer (0-20 cm) soil samples were collected in Baoji City for analysis using inductively coupled plasma mass spectrometry (ICP-MS). Cd, As, Cu, Pb, Zn, Cr, Mn, and Ni were detected in the samples. Based on geostatistical methods and geo-detector models, the soil heavy metal pollution load index (PLI) was selected as the best indicator of factors affecting heavy metal pollution. The Unmix 6.0 receptor model was also used to analyze the heavy metal source. The results showed that:① The average concentrations of Cd, Pb, Cu, Zn, As, Cr, Mn, and Ni in the surface soils of Baoji City were 0.77 mg·kg-1, 16.75 mg·kg-1, 40.52 mg·kg-1, 261 mg·kg-1, 17.03 mg·kg-1, 49.18 mg·kg-1, 331 mg·kg-1, and 30.52 mg·kg-1, respectively. These values exceeded the national secondary standard for Cd and Zn, which were 8.2 and 3.8 times more abundant, respectively, than in the background soils of Shaanxi Province, indicating that urban soils are seriously polluted with Cd and Zn. The average concentrations of Cu, As, and Ni also exceeded the background levels; ② The total pollution load index (PLIzone) for heavy metals in the surface soils of Baoji City was 1.36, which indicated mild levels of pollution, as analyzed using a geo-detector. Soil texture and distance to the city's railway had the strongest explanatory power for the distribution of pollutants (PD, H=0.040 and 0.026, respectively, with a combined explanatory power of 0.099); ③ Cd, Cu, and As mainly derive from "artificial sources" associated with industrial and agricultural activities, and Zn and Ni derive from traffic emissions. Cr, Pb, and Mn mainly derive from "mixed sources". Overall, the main source of heavy metals in the surface soils of the study area was classified as "mixed source" and soils were classified as having a mild level of pollution. These results provide scientific support for the prevention and control of heavy metal pollution in the soils of Baoji City.

Is an Environment with High Biodiversity the Most Attractive for Human Recreation? A Case Study in Baoji, China

Evidence has been accumulating of the psychological and physiological benefits and well-being gained by individuals from recreational activities in urban green spaces due to their ability to sustain biodiversity, but maximizing both biodiversity and recreational values of green spaces has become increasingly difficult in practice. In order to better maximize the biodiversity and recreational value of urban green space, this study was conducted through the utilization of an onsite questionnaire to understand people’s perceptions of and preferences for biodiversity and recreational values of urban green spaces in Baoji City, China. The results showed that respondents were able to correctly perceive biodiversity and preferred to engage in recreational activities in the high biodiversity environment. However, the respondents’ perceptions of the eight perceived sensory dimensions (PSDs) in the different habitats were divergent, and an environment which is high in biodiversity does not necessarily have higher PSDs. Moreover, ‘living environment’ and ‘frequency to the park’ had significant impacts on perception of and preference for urban biodiversity. In addition, ‘education level’, ‘living environment’, ‘age’, and other indicators were more likely to influence the perception of the eight PSDs. Therefore, the presented findings can be applied by urban landscape planners to assess the qualities of urban green spaces in order to maintain urban biodiversity and meet the satisfaction of human recreation in the future.

GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model (IOE), the support vector machine model (SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70% (125) of the landslides which was optimized by 10-fold cross-validation being used for training purpose and the remaining 30% (54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index (NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic (ROC) curves and three statistical indexes involving positive predictive rate (PPR), negative predictive rate (NPR) and accuracy (ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model. Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.

Effects of vertical accuracy of digital elevation model (DEM) data on automatic lineaments extraction from shaded DEM

Remote sensing data, such as satellite images, and remote sensing derived digital elevation models (DEMs) are credited by simplifying many geological processes that require costly and laborious field work, such as lineament extraction. Furthermore, the recent increase in the availability of DEMs from many free open sources as well as their advantages over satellite imagery have promoted their wide application as remote sensing methods for lineament extraction. The quality of a DEM affects the results of its application, and this quality is controlled by its vertical accuracy and spatial resolution. The objectives of this study were to assess and verify the effects of the vertical accuracies of DEMs on lineament extraction. The area around Baoji city, Shaanxi province, China, was selected as a case study and the lineaments were automatically extracted using the LINE algorithm of PCI Geomatica from three DEMs with different vertical accuracies: tri stereo ZY3 imagery derived DEM, SRTM1V3, and ASTGDEMV2. All of these DEMs have 1″ spatial resolution (approx. 30 m). The results showed that the vertical accuracy of the applied DEM affects the number, length, and density of the extracted lineaments, where these quantities increase with increasing vertical accuracy of the DEM.

Analysis of Heavy Metal Pollution and Ecological Risk Assessment on Vegetation Leaves in Baoji City

Using seven types of vegetation and seven heavy metals (Cr, Cu, Ni, Mn, Pb, Cd, and As), the present study explored the ability of accumulation and degree of contamination in the leaves of vegetation in Binhe Road. The results demonstrated a negative trend between vegetation height and heavy metal content of vegetation leaves, i.e., as plant height increased, heavy metal contamination decreased. Leaves varied in the accumulation of heavy metals depending on the heavy metal and vegetation type. Cr, Mn, and Pb content were the most abundant in vegetation leaves. The highest values for Cr, Cu, Ni, and Mn were observed in the vegetative leaves of Hybrida vicary privet and were 217.33, 58.61, 36.79, 1676.14 mg·kg-1, respectively. The highest Pb content was 1295.64 mg·kg-1 in Ligustrun lucidum, the highest Cd content was 110.19 mg·kg-1 in Cedrus deodara, and the highest As content was 139.42 mg·kg-1in Prunus cerasifera. The degree of pollution in vegetation leaves was evaluated using the comprehensive index method Single-factor pollution index method and the Nemero Composite Index Method. The Single-factor pollution index of vegetation leaves with Prunus cerasifera, Platanus acerifolia, Cercis chinensis were between 0.02-1.23, and the Nemero Composite Index values were 1.01, 0.82, 0.4, respectively, with light pollution. The Single-factor pollution index of vegetation leaves by Cedrus deodara, Platycladus orientalis, Hybrida vicary privet and Ligustrun lucidum were much higher than 1, and the Nemero Composite Index was 16.53, 140.64, 98.80, and 37.52, respectively, with high levels of pollution. The potential ecological risk of heavy metals in vegetation leaves was determined using the Hakanson potential ecological risk assessment method. The order of the average potential ecological risk degree of the seven examined heavy metals was as follows:Cd > Ni > Cr > As > Pb > Cu > Mn, and the RI value range was 19.04-4020.29, with high levels of pollution.

The integration of urban and rural medical insurance to reduce the rural medical burden in China: a case study of a county in Baoji City

BackgroundIn 2003, the Chinese government launched the New Rural Cooperative medical System(NRCMS) for its rural population. In 2007, the Urban Resident Basic Medical Insurance Scheme(URBMS) was inaugurated, which aimed to cover all urban residents who are out of the labor market. However, the accessibility and fairness of the healthcare service have hindered the progress of universal healthcare. At the beginning of 2010, the Integration of Urban and Rural Medical Insurance Scheme(IURMIS) was implemented to bridge the gap in medical care between urban and rural areas. The main objective of this study is to determine the extent to which the IURMIS has been successful.MethodsThe statistical software packages SPSS 19.0 and STATA 12.0 were used for all analyses, and P < 0.05 was set as the required level of significance. Data were collected from outpatients from 2009 (July to December, n = 20,459) through 2011 (n = 65,258 in 2010, n = 59,036 in 2011) and from inpatients in 2011 (n = 3662). Due to the enormous amount of data and the short time span, most of our analysis was descriptive. However, regression discontinuity (RD) and the chi-squared (χ2) test were used to compare the ratios of medical expenses before and after the IURMIS.ResultsIn the RD analysis, there was a downward trend in the mean medical expense (Coef. = − 0.66, P < 0.001), and rural outpatients flowed to township hospitals and village clinics after the implementation of the IURMIS (Coef. = − 0.45, P < 0.001). However, compensation expenses showed an upward trend (Coef. = 11.59, P < 0.001). In the analysis of inpatient expenses, the average expenses (CNY 2067) and hospitalization days (10.0) for all the hospitals were less than those in the Chinese Fourth National Health Services Survey (CNY 3412 and 10.3, respectively).ConclusionsRural residents’ healthcare options and quality were improved and medical expenses were significantly reduced after implementation of the scheme. These results provide an evidence-based reference for improving the integration of the urban and rural medical security systems throughout China.

The Reducing Effect of Green Spaces with Different Vegetation Structure on Atmospheric Particulate Matter Concentration in BaoJi City, China

With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e., horizontal structure, vertical structure and vegetation type. Eleven types of green space with different structures were selected for investigating the relationships between atmospheric particulate matter (PM) concentration and green spaces with different vegetation structure, based on the “matrix effect” of environmental factors, i.e., location, time, wind velocity, temperature, humidity and area to the concentration of PM2.5 and PM10 in the green spaces. The results showed that: (1) Location, time, wind velocity, temperature and humidity had highly significant effects on the concentration of PM2.5 and PM10. In sunny and breeze weather conditions, PM2.5 and PM10 concentration increased with the wind velocity and humidity, and decreased with the temperature. The range of PM10 concentration was greater than the range of PM2.5 concentration. (2) Less than 2 hectares of the green space had no significant influence on the concentration of PM2.5 and PM10. (3) The concentration of PM2.5 and PM10 showed no significant difference between all the green spaces and the control group. There was no significant difference in the reduction of PM2.5 concentration between different structural green spaces, but there was a significant difference in the reduction of PM10 concentration. The above results will provide a theoretical basis and practical methods for the optimisation of urban green space structures for improving urban air quality effectively in the future.

Spatial-temporal distribution of vegetation net primary productivity and its driving factors from 2000 to 2015 in Shaanxi, China.

Using MOD17A3 NPP time series data, surface cover type data, weather data, MOD16 evapotranspiration products and terrain data, the temporal and spatial variability of vegetation net primary productivity (NPP) in Shaanxi Province from 2000 to 2015 was analyzed, and its response to each influencing factor were discussed. The results showed that the NPP of Shaanxi had a significant upward trend in the past 16 years with a slope of 5.02 g C·m-2·a-1. The annual average of NPP was 344 g C·m-2·a-1 with a range from 247 to 390 g C·m-2·a-1. The NPP at 61.2% area of Shaanxi Province showed a significant increasing trend, which were mainly distributed at northern part of Shaanxi, Weibei area and western part of Qinba Mountain. There was a decrease trend of NPP for the area around Xi'an and Baoji City, accounting for only 2.5% of the whole province. During the study period, the variation of annual mean temperature and annual precipitation in Shaanxi showed no significance. The temperature showed a increase trend and the precipitation showed a decrease trend, implying a drier and warmer climate trend in Shaanxi Province. The areas with significant correlation between NPP and precipitation and temperature accounted for 9.4% and 1.5% of the total area of the province. The frequent intervention of human activities reduced the impact of climate on the changes of NPP, so human activity had gradually become the dominant factor. NPP in northern Shaanxi and Guanzhong areas was significantly correlated with evapotranspiration. The increases of NPP in these areas would have great influence on the water and heat balance. The average NPP at different land cover was farmland > forestland > grassland > garden, increasing rate of NPP at different land cover was garden > grassland > forestland > farmland, and proportional changes of NPP was grassland > garden > forestland > farmland. The increasing percentage of NPP at three gradient ranges were 14.6% (0°-5°), 25.7% (5°-25°) and 35.9% (>25°), respectively.

Dynamic monitoring of eco-environment quality changes based on PCA:A case study of urban area of Baoji City

Dynamic monitoring of eco-environment quality changes based on PCA:A case study of urban area of Baoji City

A review of heavy metal pollution levels and health risk assessment of urban soils in Chinese cities.

This study assessed literature-based data for the period 2006-2016 regarding heavy metal (As, Cd, Cr, Cu, Pb, Ni, Zn, and Hg) concentrations in soils from 32 Chinese cities and the associated human health risks. The mean concentrations of the eight metals were lower than the soil environmental quality standards in China, but were much higher than the background values for most cities. The enrichment factor (EF) and geoaccumulation index (I geo) values showed moderate pollution levels, possibly influenced by anthropogenic activity for Cd, Hg, Pb, and Zn. The pollution levels in eastern cities were much higher than those in western cities, and heavy metals concentrations in different types of cities followed the order: industrial based cities > more developed cities > metropoles > underdeveloped cities. The human health risk assessment for heavy metals in most cities indicated that non-carcinogenic risks were within threshold values (HI <1). The total carcinogenic risk due to As, Cr, and Ni in most urban areas was in excess of 1×10-5, but was lower than 1×10-4. However, in some cities (e.g., Baoji City, Tiyuan City, and Xuzhou City), Ni and Cr have potential cancer risks for both adults and children. Compared to adults, children could be more seriously threatened by heavy metal contamination in soils. In general, we recommend that Cd, Hg, and Pb are selected as priority heavy metals pollutants that require control in Chinese cities.

Quality of case report of Japanese Encephalitis after the establishment of surveillance on acute meningitis and encephalitis syndrome in Baoji

Objective: To evaluate the quality of Japanese Encephalitis (JE) case reports based on the establishment of surveillance on acute meningitis and encephalitis syndrome (AMES) in Baoji. Methods: A surveillance network on AMES cases was set up in Baoji city of Shaanxi province between July 2013 and December 2016. All the cases met the surveillance definition of AMES cases were conducted a questionnaire, collected serum and/or cerebrospinal fluid (CSF) specimens to test JE immunoglobulin M antibodies by using enzyme-linkedimmunosorbent assay methods.The information of the incidence of JE in Shaanxi and Baoji from 2009 to 2016 originated from the China information system for disease control and prevention. Chi square test was used to compare the difference in JE incidence in Baoji, Shaanxi before and after the implementation of AMES monitoring project. Results: 75 out of 855 collected cases were laboratory confirmed as JE, Including 42 suspected JE cases and 33 other suspected cases diagnosed after hospitalization. Except 1 case occurring in December, all the other cases occurred between July and October, especially in August with a peak of 55 cases (73.3%), and 6 cases (8.0%) in July, 11 cases (14.7%) in September, 2 cases (2.7%) in October. The proportion of patients aging 0-6, 7-14 and ≥15 years old were respectively 4.0% (3 cases), 8.0% (6 cases) and 88.0% (66 cases). The biochemical test showed the cerebrospinal fluid in 13 cases (17.3%) were slightly turbid, the white blood cell in 31 cases (41.3%) elevated, the glucose levels in 24 cases (32.0%) were abnormal, and the chloride level in 23 cases (30.7%) were abnormal. A total of 103 cases of JE were diagnosed in Baoji from 2009 to 2016, with an average annual incidence rate at 0.34/100 000. The average incidence of JE in 2009-2012 and 2013-2016 was 0.21/100 000 and 0.48/100 000 respectively. From 2013 to 2016, the proportion of JE cases in Baoji, Shaanxi was 19.3% (71/369), and it was 8.9% (32/362) between 2009 and 2012 (χ(2)=4.15, P=0.040). Conclusion: The AMES surveillance project improved the quality of the JE case report in Baoji. Changes appeared in biochemistrical and epidemiological characteristics of cerebrospinal fluid. The incidence of JE was seriously underestimated in Shaanxi province and therefore the sensitivity of Japanese encephalitis surveillance cases should be further improved.

Source apportionment of VOCs and their impacts on surface ozone in an industry city of Baoji, Northwestern China

Level of surface ozone (O3) has been increasing continuously in China in recent years, while its contributors and formation pathways are less understood. In this study, distributions of volatile organic compounds (VOCs) and the roles on O3 pollution have been investigated in a typical industrial city of Baoji in Northwestern China by means of monitoring of their concentrations and other trace gases. The air samples have been collected at three sites according to urban function area. Concentration of VOCs in Weibin site, which near to industrial zone, was higher than most of other cities in China, and the ambient VOCs were dominated by aromatics and alkenes. The temporal variations of VOCs and O3 coincided with the surface wind, implying that the formation of O3 was impacted by both exports of plumes upwind and local photochemical reactions. Result of source apportionment indicated that industrial emission, vehicular exhaust, and solvent evaporation were three major pollution origins. Alkenes and aromatics contributed to the largest fractions of photochemical reactivity, suggesting the strong influences from industrial and traffic sectors. The study presents the characteristic VOCs and other factors in the contribution of O3 formation in China.

Chemical composition, sources and secondary processes of aerosols in Baoji city of northwest China

Particulate air pollution is a severe environmental problem in China, affecting visibility, air quality, climate and human health. However, previous studies focus mainly on large cities such as Beijing, Shanghai, and Guangzhou. In this study, an Aerodyne Aerosol Chemical Speciation Monitor was deployed in Baoji, a middle size inland city in northwest China from 26 February to 27 March 2014. The non-refractory submicron aerosol (NR-PM1) was dominated by organics (55%), followed by sulfate (16%), nitrate (15%), ammonium (11%) and chloride (3%). A source apportionment of the organic aerosol (OA) was performed with the Sofi (Source Finder) interface of ME-2 (Multilinear Engine), and six main sources/factors were identified and classified as hydrocarbon-like OA (HOA), cooking OA (COA), biomass burning OA (BBOA), coal combustion OA (CCOA), less oxidized oxygenated OA (LO-OOA) and more oxidized oxygenated OA (MO-OOA), which contributed 20%, 14%, 13%, 9%, 23% and 21% of total OA, respectively. The contribution of secondary components shows increasing trends from clean days to polluted days, indicating the importance of secondary aerosol formation processes in driving particulate air pollution. The formation of LO-OOA and MO-OOA is mainly driven by photochemical reactions, but significantly influenced by aqueous-phase chemistry during periods of low atmospheric oxidative capacity.

Radical mastectomy and conservative surgery for breast cancer patients: comparative analysis of postoperative recurrence, complications, quality of life and cosmetic results

Objective Comparing the difference in postoperative recurrence, complications, quality of life and cosmetic results between patients receiving radical mastectomy and breast conserving surgery, provides an evidence of breast conserving surgery superior to radical mastectomy. Methods A retrospective analysis of 477 breast cancer patients cases in Department of General Surgery, Third People′s Hospital of Baoji City from January 2009 to January 2012. These patients were divided into two groups: the control group 229 cases (48%) underwent conservative surgery treatment and the observation group 248 patients (52%) underwent radical surgery. Using SPSS15.0 statistical software analysis and compare with recurrence, postoperative complications, breast cosmetic effect and quality of life for these two groups of patients. Results In breast-conserving group compared with radical mastectomy group, the one and two year recurrence or metastasis rate were not statistically different between the two groups (P>0.05), the incidence of postoperative complications was significantly decreased (P 0.05) and progression free survival (χ2＝4.243, P>0.05) as two indicator of long-term efficacy. Conclusions Conservative surgery compared with radical mastectomyhave less clinical complications, more breast cosmetic effect, better survival quality, and both of them share the same recurrence or metastasis and survival rate, so conservative surgery should be preferable in the clinical application. Key words: Breast neoplasms; Cosmetic techniques; Comparative effectiveness research; Surgical procedures, operative

The correlation of ALT, HbsAg and HCV-Ab and the effect of different detection modes on the results in blood donors

Objective To investigate the effects of different detection methods on the results for alanine aminotransferase (ALT), HBsAg and hepatitis C virus antibody (HCV-Ab) through testing the blood of 273 316 person time blood donors from 2009 to June2015, and to investigate the distribution of HBsAg, HCV-Ab and ALT and their correlation in blood donors, detection mode of nucleic acid detection in negative samples used enzyme-linked immunosorbent assay (ELISA), the results of blood donors, who were single reagent HBsAg, HCV-Ab positive, were detected again after for 24 weeks (maximum window period), and necessity of ALT screening before collecting blood sample, which provided a basis for the optimization of blood detection methods. Methods The rate method was used to detect ALT, detection of HCV-Ab and HBsAg was used ELISA, nucleic acid detection was performed on HBsAg and HCV-Ab negative blood by enzyme immunoassay, and dry chemistry complete automatic biochemistry analyzer were used for ALT screening before blood sampling in street. The enumeration data were analyzed by the χ2 test with P<0.05 for statistically significant. Results The total ALT positive rate of 273 316 people was 4.09% in Baoji city, the single ALT positive was main (98.17%, 11 185/273 316). The ALT positive rate (5.20%) of male was higher than that of women (1.79%) (χ2=1780.94, P<0.05), and the ALT positive rate of 18~44 years old group (4.48%) was higher than that of 45~55 years old groups (3.26%) (χ2=223.87, P<0.05). The positive rate of ALT before carring out ALT screening (4.90%, 8 448/172 472) was higher than that of after carrying ALT screening (2.71%, 2 737/100 844) (χ2=773.43, P<0.05). Through nucleic acid detection for serums of 143 815 ELISA negative blood donors, there were no HCV-Ab positive and 75 HbsAg positive. The Kappa value was 0.049 between ELISA and nucleic acid examination in single reagent HBsAg positive blood donors after 24 weeks. Conclusions The ALT positive and HBV, HCV had no correlation, and the ALT single positive were main in blood donors. Carrying out ATL blood screening, two times of ELISA detection and one times the nucleic acid detection may improve the blood safety level. HBsAg and HCV-Ab positive blood donors in 24 weeks (maximum window period) after ELISA and nucleic acid detection can be negative. Return blood donation team. The HbsAg and HCV-Ab positive blood donors, who were negative by the ELISA and nucleic acid detection after the 24 week (maximum window period), can return to the blood donation team. Key words: Blood donors; Blood transfusion; Alanine transaminase/BL; Hepatitis B surface antigens/BL; Hepatitis C antibodies/BL

宝鸡市区公众对雾霾风险感知与应对行为研究

为了解宝鸡市区公众对雾霾天气的风险感知能力，本文以宝鸡市四个地区的公众为调查对象，采用调查问卷的方式对不同人群进行随机调查，结果表明：在公众对雾霾风险的现状感知方面，公众所得的雾霾信息无法较准确与科学地区分雾和霾以及PM2.5的含义与区别，但对宝鸡市雾霾集中的季节感知能力很高。在公众对雾霾灾害的影响感知方面，宝鸡市公众对雾霾影响的感知能力较高，但是多停留在对雾霾认识的表层，所以还有待深化。在雾霾天气严重时期，公众会适度调节出行的活动以及日常生活，都具有良好且积极的防霾意识。 To understand the public risk awareness to haze weather in Baoji city, this article is the survey of the public in four regions of Baoji, with the method of questionnaires for different groups of random investigation, the results show that in the public on the present situation of the haze risk awareness. Public information on haze cannot more accurately and scientifically distinguish between fog and haze and the meaning and difference of PM2.5, but the concentration of haze on the season in Baoji is very high. In the public’s perception of the impact of smog, the public's perception of the haze’s impact is relatively high, but it still remains on the surface of haze recognition and has to be deepened. During the severe haze days, the public will moderately adjust the activity of travel and daily life, and have a good and positive awareness of haze prevention.

Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China

The main purpose of this study is to produce reliable susceptibility maps using GIS-based support vector machine (SVM) models and compare their performances for the Qianyang County of Baoji City, Shaanxi Province, China. In this paper, with kernel classifiers of linear, polynomial, radial basis function and sigmoid, the four various types were applied in landslide susceptibility mapping. The important input parameters for the landslide susceptibility assessment were acquired from different sources. Firstly, 81 landslide sites were obtained by aerial photographs, earlier reports and field surveys. Then, the landslide inventory was randomly classified into two datasets: 70 % (56 landslides) for training the models and 30 % (25 landslides) for validation purpose. Secondly, 15 landslide conditioning factors were selected (i.e., slope angle, slope aspect, altitude, plan curvature, profile curvature, distance to faults, distance to rivers, distance to roads, NDVI, STI, SPI, TWI, geomorphology, rainfall, and lithology). Subsequently, with four types of kernel function classifiers based on landslide conditioning factors, landslide susceptibility parameters were obtained using SVM models. Finally, the rationality of landslide susceptibility maps was verified using the receiver operating characteristics with both success rate curve and prediction rate curve. The validation results showed that success rates for the four SVM models were 83.15 % (RBF-SVM), 82.72 % (PL-SVM), 81.77 % (LN-SVM), and 79.99 % (SIG-SVM). The prediction rates for the four SVM models were 77.98 % (RBF-SVM), 77.50 % (PL-SVM), 77.07 % (LN-SVM), and 76.08 % (SIG-SVM), respectively. The results showed that the RBF-SVM model had the highest overall performance.

A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping

The aim of this study is to generate reliable susceptibility maps using frequency ratio (FR), statistical index (SI), and weights-of-evidence (WoE) models based on geographic information system (GIS) for the Qianyang County of Baoji City, China. At first, landslide locations were identified by earlier reports, aerial photographs, and field surveys, and a total of 81 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70 % (56 landslides) for training the models, and the remaining 30 % (25 landslides) was used for validation purpose. In this case study, 13 landslide-conditioning factors were exploited to detect the most susceptible areas. These factors are slope angle, slope aspect, curvature, plan curvature, profile curvature, altitude, distance to faults, distance to rivers, distance to roads, Sediment Transport Index (STI), Stream Power Index (SPI), Topographic Wetness Index (TWI), and lithology. Subsequently, landslide-susceptible areas were mapped using the FR, SI, and WoE models based on landslide-conditioning factors. Finally, the accuracy of the landslide susceptibility maps produced from the three models was verified by using areas under the curve (AUC). The AUC plot estimation results showed that the susceptibility map using FR model has the highest training accuracy of 83.62 %, followed by the SI model (83.45 %), and the WoE model (82.51 %). Similarly, the AUC plot showed that the prediction accuracy of the three models was 79.40 % for FR model, 79.35 % for SI model, and 78.53 % for WoE model, respectively. According to the validation results of the AUC evaluation, the map produced by FR model exhibits the most satisfactory properties.