Application of YLD Calculation in Assessing Disease Data──An Analysis of 4 Diseases in 2 Regions

The objective of the curtent study is to discuss the problems related to how data is used to calculate Yeare Lost with Disability (YLD) with the method recommended by the World Bank. The study includes collecting useful data, estimating disease duration and average age of disease onset,adjusting incidence and prevalence data by means of a software programme, DISMOD (Harvard University Incidence & Prevalence Model), and assessing the importance of YLD calculation for different diseases.Remission and fatality rates of 3 diseases were estimated by experts at 2 round consultations.Incidence rates, disease duration and average age of disease onset were calculated and adjusted by DISMOD. YLD due to schizothrenia is the highest among 4 diseases in two regions. YLD is 18. 88 % in disability adjusted life year for 4 diseases in Xiacheng District, and 19 .97 % in Fuyang County.Available data can be used for the calculation of YLD after being adjusted. DISMOD is a useful instrument to test the internal consistency of incidence, prevalence, rendssion and fatality rate. The adjusted data are acceptable to experts and DISMOD. To get rational remission and fatality rates, we can use a cohort method through expert consultations. To renect overall burden of disease, YLD calculation should be used.

Regional Frequency Analysis of Observed Sub-Daily Rainfall Maxima over Eastern China

Based on hourly rainfall observational data from 442 stations during 1960-2014, a regional frequency analysis of the annual maxima （AM） sub-daily rainfall series （1-, 2-, 3-, 6-, 12-, and 24-h rainfall, using a moving window approach） for eastern China was conducted. Eastern China was divided into 13 homogeneous regions： Northeast （NE1, NE2）, Central （C）, Central North （CN1, CN2）, Central East （CE1, CE2, CE3）, Southeast （SE1, SE2, SE3, SE4）, and Southwest （SW）. The generalized extreme value performed best for the AM series in regions NE, C, CN2, CE1, CE2, SE2, and SW, and the generalized logistic distribution was appropriate in the other regions. Maximum return levels were in the SE4 region, with value ranges of 80-270 mm （1-h to 24-h rainfall） and 108-390 mm （1-h to 24-h rainfall） for 20- and 100 yr, respectively. Minimum return levels were in the CN1 and NE1 regions, with values of 37-104 mm and 53-140 mm for 20 and 100 yr, respectively. Comparing return levels using the optimal and commonly used Pearson-III distribution, the mean return-level differences in eastern China for 1-24-h rainfall varied from -3-4 mm to -23-11 mm （- 10%-10%） for 20-yr events, reaching -6-26 mm （-10%-30%） and -10-133 mm （-10%-90%） for 100-yr events. In view of the large differences in estimated return levels, more attention should be given to frequency analysis of sub-daily rainfall over China, for improved water management and disaster reduction.

Regional Frequency Analysis of Significant Wave Heights Based onL-moments

L-moments are defined as linear combinations of probability-weighted moments, They are, virtually unbiased for small samples, and perform well in parameter estimation, choice of the distribution type and regional analysis. The traditional methods of determining the design wave heights for planning marine structures use data only from the site of interest. Regional frequency analysis gives a new approach to estimate quantile by use of the homogeneous neighborhood informatian. A regional frequency analysis based on L-moments with a case study of the California coast is presented. The significant wave height data for the California coast is offered by NDBC. A 6-site region without 46023 is considered to be a homogeneous region, whose optimal regional distribution is Pearson Ⅲ. The test is conducted by a simulation process. The regional quantile is compared with the at-site quantile, and it is shown that efficient neighborhood information can be used via regional frequency analysis to give a reasonable estimation of the site without enough historical data.

Temperature Trend Analysis in the North Pacific Watershed in Mexico

Through the monthly data of 71 meteorological stations of the North Pacific Watershed in northwest Mexico, the annual trends of nine temperature variables were estimated using the non-parametric Mann-Kendall test and the Q Sen’s slope estimator. Annual Q Sen’s slopes were analyzed in spatial terms using geographic variables as independent factors and likewise with Moran’s I index. Three major physiographic zones were used to perform a regional analysis using pooled data. The monthly trends were also analyzed. Divergent annual trends were found for the nine proposed variables and warming trends were predominant in almost all of them. Latitude is the most relevant factor in the spatial distribution of the Q Sen’s slopes. Four temperature variables were found statistically clustered, as depicted by the Moran’s I index. The largest regional Q Sen’s slopes values were found in the Coastal Plains. In this area a larger increase in minimum temperatures was observed, in contrast with the Sierra Madre regions, where the largest rate of increasing change was found in maximum temperatures. The monthly analysis indicates warming trends in the first six months of the year with a sudden decrease in July and also a noticeable decrease in the slope values in December.

Regional Distribution and Prospects of Potash in China

China was formed by amalgamation of several small continental blocks （cratons）, micro, blocks and orogenic belts in different paleoclimatic settings. It may be correlated with other continental blocks but has its own specific characteristics; therefore the tectonic environments of China＇s marine and continental saline basins and salt, and potash, forming environment have some specific characteristics： multiple phases of salt formation, difference in salt, forming ages, migration and concentration of salt, forming processes and diversity of component materials, as well as small sizes of marine saline basins and great changes of saline basins in the late stage and occurrence of abundant liquid mineral resources. The nature of the tectonic basement exerted a key controlling effect on the formation of potash basins. The stable tectonic region was favorable for potash concentration in a quasi, stable region, and quasi, and the quasi-stable region was favorable for salt concentration and potash formation in a local stable tectonic region. Most China＇s major ancient saline basins occur in ＂quasi, cratons （continental block）＂; especially all the marine saline basins occur in continental blocks with the Precambrian basement. These regions are the key ones for potash search. Most relatively large, scale soluble salt deposits are developed in relatively stable continental nuclei. According to the characteristics of the tectonic domains where China＇s salt, forming basins are located, the North China, Yangtze and Tarim, Qaidam salt minerogenetic domains and the northern Qiangtang, western Yunnan salt minerogenetic belt may be distinguished. Their salt and potash prospects will be discussed separately.

Automatic recognition of damaged town buildings caused by earthquake using remote sensing information: Taking the 2001 Bhuj, India, earthquake and the 1976 Tangshan, China, earthquake as examples

In the high-resolution images, the undamaged buildings generally show a natural textural feature, while the dam- aged or semi-damaged buildings always exhibit some low-grayscale blocks because of their coarsely damaged sections. If we use a proper threshold to classify the grayscale of image, some independent holes will appear in the damaged regions. By using such statistical information as the number of holes in every region, or the ratio between the area of holes and that of the region, etc, the damaged buildings can be separated from the undamaged, thus automatic detection of damaged buildings can be realized. Based on these characteristics, a new method to auto- matically detect the damage buildings by using regional structure and statistical information of texture is presented in the paper. In order to test its validity, 1-m-resolution iKonos merged image of the 2001 Bhuj earthquake and grayscale aerial photos of the 1976 Tangshan earthquake are selected as two examples to automatically detect the damaged buildings. Satisfied results are obtained.

Classifiers fusion for improved vessel recognition with application in quantification of generalized arteriolar narrowing

This paper attempts to estimate diagnostically relevant measure,i.e.,Arteriovenous Ratio with an improved retinal vessel classification using feature ranking strategies and multiple classifiers decision-combination scheme.The features exploited for retinal vessel characterization are based on statistical measures of histogram,different filter responses of images and local gradient in-formation.The feature selection process is based on two feature ranking approaches(Pearson Correlation Coefficient technique and Relief-F method)to rank the features followed by use of maximum classification accuracy of three supervised classifiers(κ-Nearest Neighbor,Support Vector Machine and Naïve Bayes)as a threshold for feature subset selection.Retinal vessels are labeled using the selected feature subset and proposed hybrid classification scheme,i.e.,decision fusion of multiple classifiers.The comparative analysis shows an increase in vessel classification accuracy as well as Arteriovenous Ratio calculation performance.The system is tested on three databases,a local dataset of 44 images and two publically available databases,INSPIRE-AVR containing 40 images and VICAVR containing 58 images.The local database also contains images with pathologically diseased structures.The performance of the proposed system is assessed by comparing the experimental results with the gold standard estimations as well as with the results of previous methodologies.Overall,an accuracy of 90.45%,93.90%and 87.82%is achieved in retinal blood vessel separation with 0.0565,0.0650 and 0.0849 mean error in Arte-riovenous Ratio calculation for Local,INSPIRE-AVR and VICAVR dataset,respectively.

Research on practical power system stability analysis algorithm based on modified SVM

Stable and safe operation of power grids is an important guarantee for economy development.Support Vector Machine(SVM)based stability analysis method is a significant method started in the last century.However,the SVM method has several drawbacks,e.g.low accuracy around the hyperplane and heavy computational burden when dealing with large amount of data.To tackle the above problems of the SVM model,the algorithm proposed in this paper is optimized from three aspects.Firstly,the gray area of the SVM model is judged by the probability output and the corresponding samples are processed.Therefore the clustering of the samples in the gray area is improved.The problem of low accuracy in the training of the SVM model in the gray area is improved,while the size of the sample is reduced and the efficiency is improved.Finally,by adjusting the model of the penalty factor in the SVM model after the clustering of the samples,the number of samples with unstable states being misjudged as stable is reduced.Test results on the IEEE 118-bus test system verify the proposed method.

Regional moment-independent sensitivity analysis with its applications in engineering

Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function（RIMPDF） and Regional Importance Measure based on Cumulative Distribution Function（RIMCDF）,are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

Genetic climatic regionalization of the Balkan Peninsula using cluster analysis

Sea Level Pressure（SLP） data for the period 1950–2012 at 61 stations located in or around the Balkan Peninsula was used. The main concept is that intra-annual course of SLP represents the best different air masses that are situated over the Balkan Peninsula during the year. The method for differentiation of climatic zones is cluster analysis. A hierarchical clustering technique–average linkage between groups with Pearson correlation for measurement of intervals was employed in the research. The climate of the Balkan Peninsula is transitional between oceanic and continental and also between subtropical and temperate climates. Several major changes in atmospheric circulation over the Balkan Peninsula have happened over the period 1950–2012. There is a serious increase of the influence of the Azores High in the period January–Marchwhich leads to an increase of SLP and enhances oceanic influence. There is an increase of the influence of the north-west extension of the monsoonal low in the period June–September. This leads to more continental climatebut also to more tropical air masses over the Balkan Peninsula. Accordinglythe extent of subtropical climate widens in northern direction. There is an increase of the influence of the Siberian High in the period October–December. This influence covers central and eastern part of the peninsula in October and Novemberand it reaches western parts in December. Thusthe climate becomes more continental.

Chemical characteristics of trace metals in PM10 and their concentrated weighted trajectory analysis at Central Delhi,India

Trace metals associated with PM10 aerosols and their variation during day and nighttime as well as during different seasons have been studied for the year 2012. PCA analysis suggested5 PCs,which accounted for 86.8% cumulative variance. PC1 accounted for 30% with a significant loading of metals of anthropogenic origin,while PC2 showed 28% variance with the loading of metals of crustal origin. These trace metals showed seasonal distinct day and night time characteristics. The concentrations of Cu,Pb,and Cd were found to be higher during nighttime in all the seasons. Only Fe was observed with significantly higher mean concentrations during daytime of all seasons except monsoon. The highest mean values of Cu,Cd,Zn,and Pb during post-monsoon might be attributed to winds advection over the regions of waste/biomass burning and industrial activities in Punjab and Haryana regions.Furthermore,concentration weighted trajectory analysis suggested that metals of crustal origin were contributed by long-range transport while metals of anthropogenic and industrial activities were contributed by regional/local source regions.

STATISTICAL ANALYSIS OF CYCLONE TRACKS IN WESTERN ANTARCTIC REGION

The paper shows the statistical analysis of cyclone tracks that have influence on the western Antarctic region.Based on the conditions of cyclone movement and its impact upon the weather,cyclone tracks are classified into three categories,i.e.,the track moving towards the northern tip of the Antarctic Peninsula, southern track,and northern track. Moreover,in this paper,the frequency distributions of cyclone tracks,the major tracks with higher frequencies,the original region of Antarctic cyclones and the seasonal features of Antarctic cyclones have been analyzed.The results show that there are higher cyclogeneses in summer,whereas relatively fewer cycloge- neses in winter,and cyclone numbers in transitional seasons are close to the climatological average.The analysis also shows that the moving velocity of Antarctic cyclone is about the same in winter and summer. It obviously speed up during the transitional season.

CO_2 Emissions Embodied in China's Foreign Trade:An Investigation from the Perspective of Global Vertical Specialization

In light of the growth in vertically specialized in global trade, the present paper uses input output tables from the World Input-Output Database to construct an environmental multi regional input-output model to calculate the CO2 emissions embodied in China＇s international trade during 1995-2009. The advantage of this model lies in its incorporation of the re exported CO2 emissions component embodied in trade and its ability to differentiate domestic sourced CO2 emissions from foreign-sourced CO2 emissions in trade. The results show that carbon emissions embodied in both China＇s exports and imports increased significantly during 1995-2009. One important reason for this is that the re-exported carbon emissions embodied in China＇s imported intermediate inputs increased substantially during this period. Our research reveals that accelerating the transformation of trade pattern and upgrading processing trade should be emphasized in the formulation of policy to prompt CO 2 emissions abatement in China.

Magnetic micro-particle conditioning–pressurized vertical electro-osmotic dewatering(MPEOD) of activated sludge： Role and behavior of moisture and organics

In this study, a magnetic micro-particle conditioning–pressurized vertical electro-osmotic dewatering（MPEOD） process with magnetic micro-particle conditioning–drainage under gravity–mechanical compression–electrical compression（MMPC–DG–MC–EC） stages was established to study the distribution and migration of water, extracellular polymeric substances（EPS）, and other organic matter in the activated sludge（AS） matrix at each stage.Results showed that the MPEOD process could attain 53.52% water content（WC） in dewatered AS with bound water（BW） and free water（FW） reduction rates of 82.97% and 99.67%,respectively. The coagulation and time-delayed magnetic field effects of magnetic microparticles（MMPs） along the MMPC–DG–MC stages initiated the transformation of partial BW to FW in AS. EC had a coupling driving effect of electro-osmosis and pressure on BW, and the changes in pH and temperature at EC stage induced the aggregation of AS flocs and the release of partial BW. Additionally, MMPs dosing further improved the dewatering performance of AS by acting as skeleton builders to provide water passages. Meanwhile, MMPs could disintegrate sludge cells and EPS fractions, thereby reducing tryptophan-like protein and byproduct-like material concentrations in LB-EPS as well as protein/polysaccharide ratio in AS matrix, which could improve AS filterability. At EC stage, the former four Ex/Em regions of fluorescence regional integration analysis for EPS were obviously reduced, especially the protein-like substances in LB-and TB-EPS, which contributed to improvement of AS dewaterability.

Climate change on the southern slope of Mt. Qomolangma （Everest） Region in Nepal since 1971

Based on monthly mean, maximum, and minimum air temperature and monthly mean precipitation data from 10 meteorological stations on the southern slope of the Mt. Qomolangma region in Nepal between 1971 and 2009, the spatial and temporal characteristics of climatic change in this region were analyzed using climatic linear trend, Sen＇s Slope Estimates and Mann-Kendall Test analysis methods. This paper focuses only on the southern slope and attempts to compare the results with those from the northern slope to clarify the characteristics and trends of climatic change in the Mt. Qomolangma region. The results showed that： （1） between 1971 and 2009, the annual mean temperature in the study area was 20.0℃, the rising rate of annual mean temperature was 0.25℃/10a, and the temperature increases were highly influenced by the maximum temperature in this region. On the other hand, the temperature increases on the northern slope of Mt. Qomolangma region were highly influenced by the minimum temperature. In 1974 and 1992, the temperature rose noticeably in February and September in the southern region when the increment passed 0.9℃. （2） Precipitation had an asymmetric distribution; between 1971 and 2009, the annual precipitation was 1729.01 mm. In this region, precipitation showed an increasing trend of 4.27 mm/a, but this was not statistically significant. In addition, the increase in rainfall was mainly concentrated in the period from April to October, including the entire monsoon period （from June to September） when precipitation accounts for about 78.9% of the annual total. （3） The influence of altitude on climate warming was not clear in the southern region, whereas the trend of climate warming was obvious on the northern slope of Mt. Qomolangma. The annual mean precipitation in the southern region was much higher than that of the northern slope of the Mt. Qomolangma region. This shows the barrier effect of the Himalayas as a whole and Mt. Qomolangma in particular.

Region-based structure line detection for cartoons

Cartoons are a worldwide popular visual entertainment medium with a long history. Nowadays,with the boom of electronic devices, there is an increasing need to digitize old classic cartoons as a basis for further editing, including deformation,colorization, etc. To perform such editing, it is essential to extract the structure lines within cartoon images.Traditional edge detection methods are mainly based on gradients. These methods perform poorly in the face of compression artifacts and spatially-varying line colors,which cause gradient values to become unreliable. This paper presents the first approach to extract structure lines in cartoons based on regions. Our method starts by segmenting an image into regions, and then classifies them as edge regions and non-edge regions. Our second main contribution comprises three measures to estimate the likelihood of a region being a non-edge region.These measure darkness, local contrast, and shape.Since the likelihoods become unreliable as regions become smaller, we further classify regions using both likelihoods and the relationships to neighboring regions via a graph-cut formulation. Our method has been evaluated on a wide variety of cartoon images, and convincing results are obtained in all cases.