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Background The present study aimed to compare four hepatic fibrosis markers [i.e., hyaluronic acid (HA), laminin (LN), procollagen III N-terminal peptide (PIIINP), and collagen type IV (CIV)] and 16 hepatic function indices in patients with liver cirrhosis of varying etiology. Methods The hepatic function indices and hepatic fibrosis markers were measured in 108 patients with liver cirrhosis and hepatoma using an automatic biochemical analyzer and luminescent immune analyzer. Twenty healthy controls were enrolled to compare the differences between liver cirrhosis and hepatoma of varying etiology and to analyze the correlations between the hepatic function indices and fibrosis markers. Results There was no correlation between alanine aminotransferase (ALT), total protein (TP), alkaline phosphatase (ALP), or the four markers of hepatic fibrosis in liver cirrhosis caused by hepatitis B (P>0.05). Aspartate aminotransferase (AST) was positively correlated with HA (r=0.428, P=0.007), LN (r=0.458, P=0.004), and CIV (r=0.374, P=0.021). Total bilirubin (TBIL) and direct bilirubin (DBIL) were positively correlated with LN (TBIL: r=0.480, P=0.002; DBIL: r=0.457, P=0.004), PIIINP (TBIL: r=0.380, P=0.017; DBIL: r=0.406, P=0.011), and CIV (TBIL: r=0.415, P=0.010; DBIL: r=0.400, P=0.013). Total bile acid (TBA) and γ-glutamyltranspeptidase (GGT) were positively correlated with PIIINP (TBA: r=0.363, P=0.025; GGT: r=0.353, P=0.029) and CIV (TBA: r=0.419, P=0.009; GGT: r=0.335, P=0.040). Leucine aminopeptidase (LAP) was positively correlated with LN (r=0.482, P=0.002). Cholinesterase (CHE) (HA: r=-0.452, P=0.004, LN: r=-0.336, P=0.039; PIIINP: r=-0.468, P=0.003; CIV: r=-0.485, P=0.002), prealbumin (PA) (HA: r=-0.575, P=0.000, LN: r=-0.413, P=0.010; PIIINP: r=-0.344, P=0.035; CIV: r=-0.371, P=0.022), albumin (ALB) (HA: r=-0.541, P=0.000, LN: r=-0.373, P=0.021; PIIINP: r=-0.353, P=0.030; CIV: r=-0.415, P=0.010), and superoxide dismutase (SOD) (HA: r=-0.334, P=0.040, LN: r=-0.347, P=0.033; PIIINP: r=-0.487, P=0.002; CIV: r=-0.536, P=0.001) were negatively correlated with the four markers of hepatic fibrosis. There was no correlation between ALT, AST, TBIL, TP, ALP, GGT, or the four hepatic fibrosis markers in hepatoma caused by hepatitis B (P>0.05). Meanwhile, DBIL and TBA were positively correlated with CIV (DBIL: r=0.519, P=0.023; TBA: r=0.563, P=0.012), while CHE (r=-0.604, P=0.006), ALB (r=-0.564, P=0.012), and SOD (r=-0.489, P=0.034) were negatively correlated with CIV. Moreover, PA was negatively correlated with LN (r=-0.510, P=0.026) and CIV (r=-0.696, P=0.001). Conclusions The concentrations of the serological indices differed significantly based on the specific liver cirrhosis etiology. There was a strong correlation between the hepatic function indices and four hepatic fibrosis markers. Thus, the detection of these markers might improve the diagnosis and treatment of hepatoma.

Background Angiotensin-converting enzyme (ACE) plays a major role in blood pressure regulation and cardiovascular homeostasis. The wide distribution and multifunctional properties of ACE suggest it’s involvement in various pathophysiological conditions. Results In this study, a novel visual detection method for ACE I/D polymorphisms was designed by integrating direct PCR without the need for DNA extraction using gold magnetic nanoparticles (GMNPs)-based lateral flow assay (LFA) biosensor. The entire detection procedure could enable the genotyping of clinical samples in about 80 min. The detection limit was 0.75 ng and results could be obtained in 5 min using the LFA device. Three hundred peripheral blood samples were analyzed using the direct PCR-LFA system and then verified by sequencing to determine accuracy and repeatability. A clinical preliminary study was then performed to analyze a total of 633 clinical samples. Conclusions After grouping based on age, we found a significant difference between the genotypes and the age of patients in the CHD group. The introduction of this method into clinical practice may be helpful for the diagnosis of diseases caused by large fragment gene insertions/deletions.

Managing and preventing the credit risk in Peer-to-Peer lending has become a crucial problem in China’s internet finance market. The influencing factors of the credit risk in P2P lending are identified from three aspects including P2P lending platform, borrowers and environment. The internal relation between these influencing factors is also explored by using the method of Interpretative Structural Modeling. Results show that factors such as the audit mechanism of P2P lending platform could affect the credit risk in P2P lending directly. In addition, borrowers’ moral level, their job stability, and the policy environment will affect the credit risk in P2P lending comprehensively through influencing other factors.

This paper made the investigation and analysis to the desk and chair for the primary and secondary students. So from the ergonomics and product semantics,mechanical principle, design psychology as the starting point, also basing on the satisfaction for the economic costs and environmental protection and others, we had design a set of chair and desk accord with the ergonomics, which can keep the normal physiology curve of students and good for growing, but also can improve the learning efficiency. This design method is one of the important development directions of desk and chair in the future, also has important reference significance on the ordinary design for desks and chairs.

Before and after pouring the concrete for a dam, how to predict and obtain the accurate temperature and stress of the various parts of the dam, is the key to prevent cracks in concrete. The stresses calculated from the parameters of the laboratory under the ideal conditions have obvious difference with the value calculated from site measured strain. As for such problem, based on the measured temperature and strain data of rolled compact concrete gravity dam engineering, the thermal and mechanics parameters of the concrete materials are inversed. The dam stress of construction period is simulated and analyzed separately based on the site parameters and lab parameters. The results show that although the stress development law from different ways is near, their values are different obviously because of three aspects. The site measured values should be more real. So it is necessary to inverse the thermal and mechanics parameters according to the site measured data.

Pier concrete is vulnerable to cracking when using concrete rapid construction after long off period. In order to solve this problem, crack mechanism and effects of several temperature control measures of thin-walled structure concrete is analyzed. Through analyzing the temperature and stress time-space variation using 3D finite element method, it can be found that stress is more sensitive to controlling concrete placing temperature than other measures. It also shows that under the condition of taking other proper temperature control measures, low placing temperature can not be spared.

Currently, there exists billions of files on the Internet, such as pictures, web pages, audio and video files, etc., and the number is still growing rapidly. These huge amount of files need to be processed by some applications as quickly as possible with parallel processing. With the increasing of cores in processors, parallel programming becomes more complex. The behavior that multiple parallel processes/threads access files simultaneously may interfere with each other and cause extra performance loss. Consequently, this paper proposes a pipeline-based parallel framework for mass file processing, in which file processing is divided into multiple stages to compose a pipeline. Files flow through these stages one by one, and the interferences in file-accessing are avoided. Moreover, the parallel programming can be simplified by means of parallel frameworks and programming interfaces. Experiments with one real-world application and some micro-benchmarks show that the framework can efficiently improve system performance.

Autoregressive moving average (ARMA) was one of the popular linear models in financial time series forecasting in the past. Generalized regression neural network (GRNN) is a branch of RBF neural network. Recent research activities in forecasting with GRNN suggest that GRNN can be a promising alternative to the traditional time series model. It has shown great ability in modeling and forecasting nonlinear time series. This paper proposes an ARMA-GRNN model that combines ARMA and GRNN models. The combined model is proposed to make use of the advantage of ARMA and GRNN models in linear and nonlinear modeling. And ARMA model aids in improving the combined model performance by capturing statistical information of the time series. The relative tests testify that the combined model can be an effective way to improve forecasting accuracy achieved by either of the models used separately.