No abstract

Software fault prediction is a valuable exercise in software quality assurance to best allocate limited testing resources. Classification is one of the effective methods for software fault prediction. The classification models are trained based on the datasets obtained by mining software historical repositories. However, the performance of the models depends on the quality of datasets. In this paper, we propose a novel two-stage data preprocessing approach which incorporates both feature selection and instance reduction. Specifically, in the feature selection stage, we first perform relevance analysis, and then propose a threshold-based clustering method, called novel threshold-based clustering algorithm, to conduct redundancy control. In the instance reduction stage, we apply random under-sampling to keep the balance between the faulty and non-faulty instances. In empirical studies, we chose datasets from real-world software projects, such as Eclipse and NASA. Then we compared our approach with some classical baseline methods, and further investigated the influencing factors in our approach. The final results demonstrate the effectiveness of our approach, and provide a guideline for achieving cost-effective data preprocessing when using our two-stage approach.

No abstract

No abstract

No abstract

Background: The role of serum fibroblast growth factor 19 (FGF19) in arteriosclerosis is not well known. In the present study, we aimed to explore whether serum FGF19 levels were related to arteriosclerosis parameters, including arterial stiffness and atherogenic index of plasma (AIP), in patients with type 2 diabetes (T2D). Methods: A total of 200 patients with type 2 diabetes and 50 healthy controls were recruited for this study from Apr 2017 to Oct 2018. Serum FGF19 levels, arterial stiffness assessed by brachial ankle pulse wave velocity (baPWV), and AIP assessed by the triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio were measured in those subjects. In addition, other relevant clinical data were also collected. Results: Serum FGF19 levels in T2D patients were significantly lower than those in healthy controls (p < 0.05). The arteriosclerosis parameters, including baPWV and AIP, significantly decreased across ascending tertiles of serum FGF19 levels (all p for trend < 0.001). Moreover, the baPWV and AIP were all inversely correlated with serum FGF19 levels (r = − 0.351 and − 0.303, respectively, p < 0.001). Furthermore, after adjusting for other clinical covariates by multiple linear regression analyses, the serum FGF19 levels were independently associated with baPWV (β = − 0.20, t = − 2.23, p = 0.029) and AIP (β = − 0.28, t = − 2.66, p = 0.010). Conclusions: The serum FGF19 levels were independently and inversely associated with baPWV and AIP, which indicate that serum FGF19 may have a protective role in atherosclerosis in patients with T2D.

Background: Diabetic nephropathy (DN) is one of the common chronic microvascular complications of diabetes, and podocyte injury and dysfunction are strictly related to the pathogenesis of DN. Studies have shown that ligustilide (LIG) has anti-inflammatory, antioxidant, and anti-apoptotic activities. This study was designed to investigate the therapeutic effect of LIG in DN rats and their mechanisms.Methods: DN rat models (n=10) were induced by streptozotocin (STZ) combined with a high-fat diet. Rats in the LIG group were intragastrically administered with LIG daily for eight weeks, and animals in the positive control group were treated with Losartan potassium. The body weight and blood glucose were checked weekly during the treatment. The pathological changes of kidney tissue were observed with hematoxylin and eosin (HE) staining. Blood lipid profiles and renal function-related markers, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), blood urea nitrogen (BUN), and serum creatinine (Scr) were monitored using a biochemical analyzer. The protein expression of nephrin was determined by immunohistochemistry and Western blotting. Finally, Western blot was used to determine the protein expression of Sirtuin 1 (SIRT1) and nuclear factor-kappa B (NF-κB).Results: Compared with the healthy control group, rats in the DN group have slower weight gain, increased blood sugar level, renal lesions, and impaired renal function, along with decreased nephrin expression, abnormally activated NF-κB, and inhibited SIRT1 protein expression. All the above conditions were improved after intervention with either losartan potassium or LIG.Conclusions: LIG attenuates podocyte injury by regulating the SIRT1/NF-κB signaling pathway and thereby exerts its protective effect on renal function in DN rats.

Background and Objectives: It is important to match species needs with site conditions for sustainable forestry. In Eucalyptus urophylla × Eucalyptus grandis plantations in southern Yunnan, China, species-site mismatches have led to inappropriate expansion and management, which has degraded forests and decreased efficiency in plantation production. Further research is needed to understand the relationship between tree growth and site productivity. We empirically explored site features and classified site types within these plantations in southern Yunnan. Our objective was to develop a theoretical basis for improving site selection for afforestation, and to establish intensive management in that region. Materials and Methods: 130 standard plots were set up in 1−15-year-old eucalyptus plantations in Pu’er and Lincang. We used quantification theory to examine the relationship between dominant tree growth traits and site factors. Hierarchical cluster analysis and canonical correlation analysis were applied to classify sites and evaluate the growth potential of E. urophylla × E. grandis plantations, respectively. Results: The multiple correlation coefficient between eight site factors (altitude, slope, slope position, aspect, soil depth, texture, bulk density, and litter thickness) and the quantitative growth of the dominant tree was 0.834 (p < 0.05). Slope position, altitude, and soil depth were the main factors contributing to the variation in stand growth. Plantation growth was best on lower slopes at relatively low altitude, where thick and weathered red soil layers existed. Conversely, the poorest plantations were located on upper slopes at higher altitude, with a thin semi-weathered purple soil layer. The soil factors total nitrogen (N) and potassium (K), trace boron (B), copper (Cu), and zinc (Zn) content, available phosphorous (P), and organic matter content in the soil influenced plantation growth. Conclusions. The addition of N, P, and K fertilizer as well as trace elements such as B, Cu, and Zn can promote the productivity of these plantations.