Prevalence and risk factors of abnormal left ventricular geometrical patterns in untreated hypertensive patients

BACKGROUND: The various prevalence of LVH and abnormal LV geometry have been reported in different populations. So far, only a few reports are available on the prevalence of LV geometric patterns in a large Chinese untreated hypertensive population. METHODS: A total of 9,286 subjects (5167 men and 4119 women) completed the survey and 1641 untreated hypertensive patients (1044 males and 597 females) enrolled in the present study. The LV geometry was classified into four patterns: normal; abnormal,defined as concentric remodeling;concentric or eccentric hypertrophy based on the values of left ventricular mass index (LVMI) and relative wall thickness (RWT). Logistic regression model was applied to determine the odds ratio (OR) and 95% confidence intervals (CI) of the risk factors of left ventricular hypertrophy. RESULTS: The prevalence of LVH was 20.2% in untreated hypertensive patients, much higher in women (30.8%) than in men (14.2%) (P < 0.01). The prevalence of LV geometrical patterns was 34.9%, 11.1%, 9.1% for concentric remodeling, concentric and eccentric hypertrophy,respectively. After adjustment by using Logistic regression model, the risk factors for LVH and abnormal LV geometry were age, female, systolic blood pressure, and body mass index. And low high density lipoprotein maybe a positive factor. CONCLUSIONS: The prevalence of LVH and abnormal LV geometric patterns was higher in women than in men and increased with age. It is crucial to improve the awareness rate of hypertension and control the risk factors of CV complications in untreated hypertensive population

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic

Experimental study on dissolution effect and water purification mechanism of broken coal and rock mass in goaf

Research on the dissolution effect and the water purification mechanism of fractured coal and rock mass in the goaf area of underground reservoir is the key to realizing the safe and efficient operation of underground reservoir in mine.This paper takes the underground water reservoir formed by the mining of 31409 working face in Jinjie coal mine as example, and selects the broken coal rock mass in the mining area and deionized water for the experimental study of pollutant release law.We analyse the law of dissolution action of broken coal rock mass in the mining area, and explore the mechanism of the influence broken coal rock mass exerts on the characteristics of the water body.We discover the law of pollutant release of broken coal rock mass under different temperature and weathering degrees, and analyse precipitation and dissolution that occurs during the water purification process in underground water reservoir.The water-rock interaction of dissolution, the adsorption and precipitation of clay mineral surfaces and soluble organic matter in the rock body constitute the water purification characteristics of the groundwater reservoir, with dissolution, adsorption and precipitation each playing a dominant role in influencing mine water quality at different time scales

Technical note: Numerical quantification of the mixing states of partially-coated black carbon based on the single-particle soot photometer: Implication for global radiative forcing

In this work, we have performed a series of numerical investigations on the mixing states of partially-coated black carbon (BC) based on the single-particle soot photometer (SP2). First, we calculated the scattering signal returned from partially-coated BC based on the SP2 measurement, and then the mixing states were determined using Mie theory, where the difference between the determined and "true" mixing states can represent the uncertainties of the SP2 measurement. We found that the SP2 measurement can provide good estimates for small, heavily coated BCs and shows better performance for fully coated BCs. However, the microphysical properties of BCs have a significant impact on the accuracy of the SP2 measurement; sometimes deviations of about -22 % to 28 % were observed for the determined particle-to-core size ratio (Dp/Dc). When considering a size distribution, the error in the effective radius is generally within about -17 % to 8.8 %. We also investigated the effects of Mie-based models using the SP2 determined and volume-mean Dp/Dc on the radiative effects of partially-coated BC. We found that both Mie models based on the volume mean and SP2 determined mixing states overestimate the absorption enhancement (Eabs) and direct radiative forcing (DRF) of BC. The Mie model based on the SP2 measurement does not necessarily provide worse estimates of radiative properties, although some errors occur in the determination of the mixing states, since the fraction of the coated core (F) in the particle scale is an important factor affecting Eabs and DRF. Sometimes the inaccurate measurements of the mixing states by SP2 would offset the influence of F. Moreover, our results based on the Mie model considering F can significantly improve the estimates for the absorption and DRF of partially-coated BC, although the morphology also has some influence. Therefore, we suggest adding a parameter F to model the radiative effect of BC in climate modeling even when a Mie-based model is used

Four New Species of Aspergillus Subgenus Nidulantes from China

Aspergillus subgenus Nidulantes includes species with emericella-like ascomata and asexual species. Subgenus Nidulantes is the second largest subgenus of Aspergillus and consists of nine sections. In this study, agricultural soils were sampled from 12 provinces and autonomous regions in China. Based on primary BLAST analyses, seven of 445 Aspergillus isolates showed low similarity with existing species. A polyphasic investigation, including phylogenetic analysis of partial ITS, &beta;-tubulin, calmodulin, and RNA polymerase II second largest subunit genes, provided evidence that these isolates were distributed among four new species (Aspergillus guangdongensis, A. guangxiensis, A. sichuanensis and A. tibetensis) in sections Aenei, Ochraceorosei, and Sparsi of subgenus Nidulantes. Illustrated morphological descriptions are provided for each new taxon