Human prion diseases are a group of transmissible, progressive, and invariably fatal neurodegenerative disorders, which include Kuru, Creutzfeldt-Jakob disease (CJD), Gerstmann-Sträussler-Scheinker syndrome, and fatal familial insomnia. Human prion diseases affect approximately 1–2 persons per million worldwide annually, occurring in sporadic, inherited, and acquired forms. These diseases have attracted both scientific and public attention not only because of their mysterious pathogen, but also due to their considerable threat to public health since the emergence of the variant CJD.There are still no specific therapeutic and prophylactic interventions available for prion diseases, thus active surveillance of human prion diseases is critical for disease control and prevention. Since 1993, CJD surveillance systems have been established in many countries and regions, and several long-term multinational cooperative projects have been conducted.In this paper, the epidemiological characteristics of various human prion diseases and the active surveillance systems pertaining to them in different countries and regions are summarized and reviewed.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-016-0143-8) contains supplementary material, which is available to authorized users.

This study focused on producing flash flood hazard susceptibility maps (FFHSM) using frequency ratio (FR) and statistical index (SI) models in the Xiqu Gully (XQG) of Beijing, China. First, a total of 85 flash flood hazard locations (n = 85) were surveyed in the field and plotted using geographic information system (GIS) software. Based on the flash flood hazard locations, a flood hazard inventory map was built. Seventy percent (n = 60) of the flooding hazard locations were randomly selected for building the models. The remaining 30% (n = 25) of the flooded hazard locations were used for validation. Considering that the XQG used to be a coal mining area, coalmine caves and subsidence caused by coal mining exist in this catchment, as well as many ground fissures. Thus, this study took the subsidence risk level into consideration for FFHSM. The ten conditioning parameters were elevation, slope, curvature, land use, geology, soil texture, subsidence risk area, stream power index (SPI), topographic wetness index (TWI), and short-term heavy rain. This study also tested different classification schemes for the values for each conditional parameter and checked their impacts on the results. The accuracy of the FFHSM was validated using area under the curve (AUC) analysis. Classification accuracies were 86.61%, 83.35%, and 78.52% using frequency ratio (FR)-natural breaks, statistical index (SI)-natural breaks and FR-manual classification schemes, respectively. Associated prediction accuracies were 83.69%, 81.22%, and 74.23%, respectively. It was found that FR modeling using a natural breaks classification method was more appropriate for generating FFHSM for the Xiqu Gully.

This study focused on landslide susceptibility analysis mapping of the Xulong hydropower station reservoir, which is located in the upstream of Jinsha River, a rapidly uplifting region of the Tibetan Plateau region. Nine factors were employed as landslide conditioning factors in landslide susceptibility mapping. These factors included the slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation, bedrock uplift and annual precipitation. The rapid bedrock uplift factor was represented by the slope angle. The eight factors were processed with the information content model. Since this area has a significant vertical distribution law of precipitation, the annual precipitation factor was analyzed separately. The analytic hierarchy process weighting method was used to calculate the weights of nine factors. Thus, this study proposed a component approach to combine the normalized eight-factor results with the normalized annual precipitation distribution results. Subsequently, the results were plotted in geographic information system (GIS) and a landslide susceptibility map was produced. The evaluation accuracy analysis method was used as a validation approach. The landslide susceptibility classes were divided into four classes, including low, moderate, high and very high. The results show that the four susceptibility class ratios are 12.9%, 35.06%, 34.11%and 17.92% of the study area, respectively. The red belt in the high elevation area represents the very high susceptibility zones, which followed the vertical distribution law of precipitation. The prediction accuracy was 85.74%, which meant that the susceptibility map was confirmed to be reliable and reasonable. This susceptibility map may contribute to averting the landslide risk in the future construction of the Xulong hydropower station.

In view of the effect of water on the physical and mechanical parameters of natural gypsum rock, in this study, gypsum rock in the goaf of a gypsum mine was selected as the research object, and gypsum rock samples were prepared with different immersion times. In addition, uniaxially tests were performed separately on the gypsum rock samples. Compression and scanning electron microscopy experiments were carried out to analyze the effects of immersion time on the uniaxial compressive strength, elastic modulus, Poisson's ratio, and microstructure of gypsum. The results show that the uniaxial compressive strength and elastic modulus of gypsum are inversely proportional to the water content. However, the Poisson's ratio is direly proportional to the water content, and the failure mode is destroyed by the brittle fracture of a single crack and is transformed into the shear ductile failure of the Y-shaped crack. Microscopically, with increasing immersion time, the bonds in the crystal of the microporous cracks and microcrack tips are weakened by hydrolysis, and the macroscopic structure is complicated by the internal structure of gypsum, and the end of the crack is expanded by the compressive action of water. Based on the damage mechanics, the evolution equation of gypsum soaking softening damage based on time factor was derived. The relationship between the brittleness coefficient and softening damage variable is revealed, providing a theoretical basis for the determination of the softening degree of gypsum in the goaf. INDEX TERMS Gypsum rock, water immersion, softening damage, brittleness coefficient.