On the Simulatability Condition in Key Generation Over a Non-authenticated Public Channel

Simulatability condition is a fundamental concept in studying key generation over a non-authenticated public channel, in which Eve is active and can intercept, modify and falsify messages exchanged over the non-authenticated public channel. Using this condition, Maurer and Wolf showed a remarkable "all or nothing" result: if the simulatability condition does not hold, the key capacity over the non-authenticated public channel will be the same as that of the case with a passive Eve, while the key capacity over the non-authenticated channel will be zero if the simulatability condition holds. However, two questions remain open so far: 1) For a given joint probability mass function (PMF), are there efficient algorithms (polynomial complexity algorithms) for checking whether the simulatability condition holds or not?; and 2) If the simulatability condition holds, are there efficient algorithms for finding the corresponding attack strategy? In this paper, we answer these two open questions affirmatively. In particular, for a given joint PMF, we construct a linear programming (LP) problem and show that the simulatability condition holds \textit{if and only if} the optimal value obtained from the constructed LP is zero. Furthermore, we construct another LP and show that the minimizer of the newly constructed LP is a valid attack strategy. Both LPs can be solved with a polynomial complexity

Deep Learning Based Prediction of Transfer Probability of Shared Bikes Data

In the pile-free bicycle sharing scheme, the parking place and time of the bicycle are arbitrary. The distribution of the pile does not constrain the origin and destination of the journey. The travel demand of the user can be derived from the use of the shared bicycle. The goal of this article is to predict the probability of transition for a shared bicycle user destination based on a deep learning algorithm and a large amount of trajectory data. This study combines eXtreme Gradient Boosting (XGBoost) algorithm, stacked Restricted Boltzmann Machines (RBM), support vector regression (SVR), Differential Evolution (DE) algorithm, and Gray Wolf Optimization (GWO) algorithm. In an experimental case, the destinations of the cycling trips and the probability of traffic flow transfer for shared bikes between traffic zones were predicted by computing 2.46 million trajectory points recorded by shared bikes in Beijing. The hybrid algorithm can improve the accuracy of prediction, analyze the importance of various factors in the prediction of transfer probability, and explain the travel preferences of users in the pile free bicycle-sharing scheme

Two DsbA Proteins Are Important for Vibrio parahaemolyticus Pathogenesis

Bacterial pathogens maintain disulfide bonds for protein stability and functions that are required for pathogenesis. Vibrio parahaemolyticus is a Gram-negative pathogen that causes food-borne gastroenteritis and is also an important opportunistic pathogen of aquatic animals. Two genes encoding the disulfide bond formation protein A, DsbA, are predicted to be encoded in the V. parahaemolyticus genome. DsbA plays an important role in Vibrio cholerae virulence but its role in V. parahaemolyticus is largely unknown. In this study, the activities and functions of the two V. parahaemolyticus DsbA proteins were characterized. The DsbAs affected virulence factor expression at the post-translational level. The protein levels of adhesion factor VpadF (VP1767) and the thermostable direct hemolysin (TDH) were significantly reduced in the dsbA deletion mutants. V. parahaemolyticus lacking dsbA also showed reduced attachment to Caco-2 cells, decreased β-hemolytic activity, and less toxicity to both zebrafish and HeLa cells. Our findings demonstrate that DsbAs contribute to V. parahaemolyticus pathogenesis

Alleviation of DSS-induced colitis in mice by a new-isolated Lactobacillus acidophilus C4

IntroductionProbiotic is adjuvant therapy for traditional drug treatment of ulcerative colitis (UC). In the present study, Lactobacillus acidophilus C4 with high acid and bile salt resistance has been isolated and screened, and the beneficial effect of L. acidophilus C4 on Dextran Sulfate Sodium (DSS)-induced colitis in mice has been evaluated. Our data showed that oral administration of L. acidophilus C4 remarkably alleviated colitis symptoms in mice and minimized colon tissue damage.MethodsTo elucidate the underlying mechanism, we have investigated the levels of inflammatory cytokines and intestinal tight junction (TJ) related proteins (occludin and ZO-1) in colon tissue, as well as the intestinal microbiota and short-chain fatty acids (SCFAs) in feces.ResultsCompared to the DSS group, the inflammatory cytokines IL-1β, IL-6, and TNF-α in L. acidophilus C4 group were reduced, while the antioxidant enzymes superoxide dismutase (SOD), glutathione (GSH), and catalase (CAT) were found to be elevated. In addition, proteins linked to TJ were elevated after L. acidophilus C4 intervention. Further study revealed that L. acidophilus C4 reversed the decrease in intestinal microbiota diversity caused by colitis and promoted the levels of SCFAs.DiscussionThis study demonstrate that L. acidophilus C4 effectively alleviated DSS-induced colitis in mice by repairing the mucosal barrier and maintaining the intestinal microecological balance. L. acidophilus C4 could be of great potential for colitis therapy

Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis B-related fibrosis: a leading meta-analysis

<p>Abstract</p> <p>Background</p> <p>The aspartate aminotransferase-to-platelet ratio index (APRI), a tool with limited expense and widespread availability, is a promising noninvasive alternative to liver biopsy for detecting hepatic fibrosis. The objective of this study was to systematically review the performance of the APRI in predicting significant fibrosis and cirrhosis in hepatitis B-related fibrosis.</p> <p>Methods</p> <p>Areas under summary receiver operating characteristic curves (AUROC), sensitivity and specificity were used to examine the accuracy of the APRI for the diagnosis of hepatitis B-related significant fibrosis and cirrhosis. Heterogeneity was explored using meta-regression.</p> <p>Results</p> <p>Nine studies were included in this meta-analysis (n = 1,798). Prevalence of significant fibrosis and cirrhosis were 53.1% and 13.5%, respectively. The summary AUCs of the APRI for significant fibrosis and cirrhosis were 0.79 and 0.75, respectively. For significant fibrosis, an APRI threshold of 0.5 was 84% sensitive and 41% specific. At the cutoff of 1.5, the summary sensitivity and specificity were 49% and 84%, respectively. For cirrhosis, an APRI threshold of 1.0-1.5 was 54% sensitive and 78% specific. At the cutoff of 2.0, the summary sensitivity and specificity were 28% and 87%, respectively. Meta-regression analysis indicated that the APRI accuracy for both significant fibrosis and cirrhosis was affected by histological classification systems, but not influenced by the interval between Biopsy & APRI or blind biopsy.</p> <p>Conclusion</p> <p>Our meta-analysis suggests that APRI show limited value in identifying hepatitis B-related significant fibrosis and cirrhosis.</p

Modelling and application of a spectral clustering method for shared bicycle trajectories

AbstractGeographic flow clustering analysis can effectively reveal human behavioral patterns in movement. Traditional methods for studying human movement patterns are mostly based on first-order quantity analyses of point data, such as hotspots, density or clustering. Currently, relatively few second-order spatial analysis methods based on geographic flows exist. Thus, we developed a new geographic flow method based on spectral clustering and applied it to trajectory data analysis. This article uses the bike-sharing trajectories data in Shanghai in August 2016, spectral clustering analysis was conducted on the group flow patterns before, during and after rainfall, on weekdays and weekends and in the morning and evening peak. Spectral clustering was verified to exhibit better clustering effect by comparing the clustering indices of different clustering methods. This study enriches the analysis method of geographical flows, and the human mobility patterns revealed by its analysis can provide references for formulating urban green travel policies