A barrier certificate can separate the state space of a considered hybrid system (HS) into safe and unsafe parts according to the safety property to be verified. Therefore this notion has been widely used in the verification of HSs. A stronger condition on barrier certificates means that less expressive barrier certificates can be synthesized. On the other hand, synthesizing more expressive barrier certificates often means high complexity. In [9], Kong et al considered how to relax the condition of barrier certificates while still keeping their convexity so that one can synthesize more expressive barrier certificates efficiently using semi-definite programming (SDP). In this paper, we first discuss how to relax the condition of barrier certificates in a general way, while still keeping their convexity. Particularly, one can then utilize different weaker conditions flexibly to synthesize different kinds of barrier certificates with more expressiveness efficiently using SDP. These barriers give more opportunities to verify the considered system. We also show how to combine two functions together to form a combined barrier certificate in order to prove a safety property under consideration, whereas neither of them can be used as a barrier certificate separately, even according to any relaxed condition. Another contribution of this paper is that we discuss how to discover certificates from the general relaxed condition by SDP. In particular, we focus on how to avoid the unsoundness because of numeric error caused by SDP with symbolic checking.

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Wireless capsule endoscopy (WCE) has become a widely used diagnostic technique to examine inflammatory bowel diseases and disorders. As one of the most common human helminths, hookworm is a kind of small tubular structure with grayish white or pinkish semi-transparent body, which is with a number of 600 million people infection around the world. Automatic hookworm detection is a challenging task due to poor quality of images, presence of extraneous matters, complex structure of gastrointestinal, and diverse appearances in terms of color and texture. This is the first few works to comprehensively explore the automatic hookworm detection for WCE images. To capture the properties of hookworms, the multi scale dual matched filter is first applied to detect the location of tubular structure. Piecewise parallel region detection method is then proposed to identify the potential regions having hookworm bodies. To discriminate the unique visual features for different components of gastrointestinal, the histogram of average intensity is proposed to represent their properties. In order to deal with the problem of imbalance data, Rusboost is deployed to classify WCE images. Experiments on a diverse and large scale dataset with 440 K WCE images demonstrate that the proposed approach achieves a promising performance and outperforms the state-of-the-art methods. Moreover, the high sensitivity in detecting hookworms indicates the potential of our approach for future clinical application.

IntroductionIt is inaccurate to assess blood glucose with glycated hemoglobin (HbA1c) in patients with diabetes and chronic kidney disease (CKD), and whether glycated albumin (GA) is better than HbA1c in these patients remains unclear.MethodsWe searched PubMed, Embase, Web of Science, Scopus, the Cochrane Library, and MEDLINE to July 2017 for studies that investigated the correlation between GA or HbA1c and the average glucose levels (AG) relevant to this theme. Statistical analysis was performed using RevMan5.3 and Stata12.0. The outcome was the correlation coefficient between GA or HbA1c and AG. For the first time, we made a comparison of GA and HbA1c in different CKD stages.ResultsA total of 24 studies with 3928 patients were included. Early stages of CKD refer to CKD stage 1 to 3. Advanced CKD refer to CKD stage 4 and 5 including patients receiving dialysis. The meta-analysis suggested that in early stages of CKD, the pooled R between GA and AG was 0.61 (95% CI = 0.49−0.73) and 0.71 (95% CI = 0.55−0.87) for HbA1c (P > 0.05). In advanced CKD patients, the pooled R between GA and AG was 0.57 (95% CI = 0.52−0.62), and 0.49 (95% CI = 0.45−0.52) for HbA1c (P = 0.0001).ConclusionGA is superior to HbA1c in assessing blood glucose control in diabetes patients with advanced CKD.

Gastrointestinal (GI) disease is one of the most common diseases and primarily examined by GI endoscopy. Recently, deep learning (DL), in particular convolutional neural networks (CNNs) have made achievements in GI endoscopy image analysis. This review focuses on the applications of DL methods in the analysis of GI images. We summarized and compared the latest published literature related to the common clinical GI diseases and covers the key applications of DL in GI image detection, classification, segmentation, recognition, location, and other tasks. At the end, we give a discussion on the challenges and the research directions of GI image analysis based on DL in the future.

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This review did not provide strong evidence concerning the effectiveness of TCMHs for stopping bleeding from haemorrhoids. Most of the included studies were of low quality and there was a scarcity of eligible trials and numbers of participants. Limited, weak evidence showed that some herbal formulae, when including Radix Sanguisorbae, Radix Rehmanniae, Fructus Sophorae, Radix Angelicae Sinensis, Radix Scutellariae, etc., may alleviate some symptoms caused by haemorrhoids. These include hematochezia, congestive haemorrhoidal cushions and inflammation of perianal mucosa in the short term. Well-designed clinical trials are required urgently before any confident conclusions can be drawn about the value of TCMHs for stopping bleeding from haemorrhoids.At present, the evidence is not enough that clinical practice should be changed immediately on the basis of these results.