Hypoglycemic, hypolipidemic and antioxidant effects of iridoid glycosides extracted from: Corni fructus: Possible involvement of the PI3K-Akt/PKB signaling pathway

Iridoid glycosides (CIG) are the major component of Corni fructus. In this work, we researched the antioxidative, hypoglycemic and lowering blood lipids effects of CIG on diabetic mice induced by a high-fat diet (HFD) and streptozotocin (STZ). Furthermore, to investigate the molecular mechanism of action, the phosphorylation and protein expression of phosphoinositide 3-kinase (PI3K) and its downstream proteins, such as insulin receptor (INSR), protein kinase B (Akt/PKB) and glucose transporter 4 (GLUT4) have been detected. The results showed that CIG significantly improved oral glucose tolerance in diabetic mice. Biochemical indices also revealed that CIG had a positive effect on lipid metabolism and oxidative stress. In addition, CIG can significantly enhance the expression level of the PI3K-Akt/PKB pathway related proteins in skeletal muscle, which is the key pathway of insulin metabolism. These findings show that CIG can improve the hyperglycemia and hyperlipidemia of HFD-STZ-induced diabetic mice through the PI3K-Akt/PKB signaling pathway, and CIG might be a potential medicine or functional food for type 2 diabetes mellitus remedies. © 2018 The Royal Society of Chemistry

A Knowledge-Based Simulated Annealing Algorithm to Multiple Satellites Mission Planning Problems

The multiple satellites mission planning is a complex combination optimization problem. A knowledge-based simulated annealing algorithm is proposed to the multiple satellites mission planning problems. The experimental results suggest that the proposed algorithm is effective to the given problem. The knowledge-based simulated annealing method will provide a useful reference for the improvement of existing optimization approaches

Butane-1,2,3,4-tetra­carboxylic acid–4,4′-bipyridine (1/2)

The hydro­thermal reaction of butane-1,2,3,4-tetra­carboxylic acid (H4butca), 4,4′-bipyridine (bipy) and Mn(SO4)2·H2O afforded a new co-crystal, C8H10O8·2C10H8N2 or H4butca·2(bipy), in which strong O—H⋯N hydrogen-bonding and weak π–π stacking [centroid–centroid distance = 3.8459 (19) Å] inter­actions assemble the organic mol­ecules into a three-dimensional supra­molecular framework. C—H⋯O inter­actions are also present. The whole mol­ecule has inversion symmetry

Zero-shot learning via discriminative representation extraction

Zero-shot learning (ZSL) aims to recognize classes whose samples did not appear during training. Existing research focuses on mapping deep visual feature to semantic embedding space explicitly or implicitly. However, ZSL improvements led by discriminative feature transformation is not well studied. In this paper, we propose a ZSL framework that maps semantic embeddings to a discriminative representation space, which are learned in two different ways: Kernelized Linear Discriminant Analysis (KLDA) and Central-loss based Network (CLN). KLDA and CLN can both force samples to be intra-class aggregation and inter-class separation. With the learned discriminative representations, we map class embeddings to representation space using Kernelized Ridge Regression (KRR). Our experiments show that both KLDA+KRR and CLN+KRR surpass state-of-art approaches in both recognition and retrieval task

Crop insurance and agrochemical use in the Manasi Watershed, Xinjiang, China

This study investigates the environmental impact of a government subsidy program for crop insurance in China. It looks at how crop insurance scheme in Xinjiang province affects the way cotton farmers use fertilizers, pesticides and plastic agro-film. These three inputs cause significant environmental problems in the region and there is a need to ensure that their over-use is not encouraged. The study finds that crop insurance helps protect farmers from the economic impact of crop failures, with a minimal negative impact on the environment. The only significant impact is a potential slight increase in agro-film use. In fact, crop insurance helps reduce the amount of pesticides cotton growers use. In light of these findings, the study concludes that a government-subsidized crop insurance program is an acceptable policy and proposes a number of ideas for minimizing any residual environmental impact it might have

FractalAD: A simple industrial anomaly detection method using fractal anomaly generation and backbone knowledge distillation

Although industrial anomaly detection (AD) technology has made significant progress in recent years, generating realistic anomalies and learning priors of normal remain challenging tasks. In this study, we propose an end-to-end industrial anomaly detection method called FractalAD. Training samples are obtained by synthesizing fractal images and patches from normal samples. This fractal anomaly generation method is designed to sample the full morphology of anomalies. Moreover, we designed a backbone knowledge distillation structure to extract prior knowledge contained in normal samples. The differences between a teacher and a student model are converted into anomaly attention using a cosine similarity attention module. The proposed method enables an end-to-end semantic segmentation network to be used for anomaly detection without adding any trainable parameters to the backbone and segmentation head, and has obvious advantages over other methods in training and inference speed.. The results of ablation studies confirmed the effectiveness of fractal anomaly generation and backbone knowledge distillation. The results of performance experiments showed that FractalAD achieved competitive results on the MVTec AD dataset and MVTec 3D-AD dataset compared with other state-of-the-art anomaly detection methods.Comment: 12 pages, 5 figure