1-[4-(4-Nitro­phen­yl)piperazin-1-yl]-2-(4,5,6,7-tetra­hydro­thieno[3,2-c]pyridin-5-yl)ethanone

The title compound, C19H22N4O3S, comprises a thienopyridine moiety which is characteristic for anti­platelet agents of the clopidogrel class of compounds. In the crystal, inversion dimers are formed through pairs of C—H⋯O inter­actions. The benzene ring plane and the nitro plane are almost coplanar, with a dihedral angle of 0.83 (2)°. The piperazine ring adopts a chair conformation

Secure Rate-Splitting Multiple Access Transmissions in LMS Systems

This letter investigates the secure delivery performance of the rate-splitting multiple access scheme in land mobile satellite (LMS) systems, considering that the private messages intended by a terminal can be eavesdropped by any others from the broadcast signals. Specifically, the considered system has an N-antenna satellite and numerous single-antenna land users. Maximum ratio transmission (MRT) and matched-filtering (MF) precoding techniques are adopted at the satellite separately for the common messages (CMs) and for the private messages (PMs), which are both implemented based on the estimated LMS channels suffering from the Shadowed-Rician fading. Then, closed-form expressions are derived for the ergodic rates for decoding the CM, and for decoding the PM at the intended user respectively, and more importantly, we also derive the ergodic secrecy rate against eavesdropping. Finally, numerical results are provided to validate the correctness of the proposed analysis models, as well as to show some interesting comparisons.Comment: 5 pages, 3 figures, 1 tabl

Anchoring the CFRP strengthening of concrete bridge decks: A comparison of methods

Debonding failures are a common problem in concrete bridge decks strengthened with adhesively attached carbon-fibre reinforced polymer (CFRP) strips. Accordingly, in this study, rectangular concrete slabs strengthened with CFRP have been experimentally evaluated to simulate the strengthening of T-beam and box girder slabs. The resulting static load data have been used to compare the effects of four different anchoring methods in terms of crack distribution, deflection, reinforcing steel strain curve, and CFRP strain distribution. The most suitable bridge deck strengthening anchoring method has been then identified and analysed using extant strengthening design methods. The results show that the most practical anchoring method is the use of open CFRP strips attached with concentrated adhesive. The findings of this study indicate that when strengthening T-girder bridges, more than two CFRP anchorage strips should be evenly spaced within the extension of the anchorage length, while for box girder bridges, even more evenly spaced strips should be used. This research and its conclusions can be used as a reference for the improved design of bridge deck strengthening

Anchoring the CFRP strengthening of concrete bridge decks: A comparison of methods

288-299Debonding failures are a common problem in concrete bridge decks strengthened with adhesively attached carbon-fibre reinforced polymer (CFRP) strips. Accordingly, in this study, rectangular concrete slabs strengthened with CFRP have been experimentally evaluated to simulate the strengthening of T-beam and box girder slabs. The resulting static load data have been used to compare the effects of four different anchoring methods in terms of crack distribution, deflection, reinforcing steel strain curve, and CFRP strain distribution. The most suitable bridge deck strengthening anchoring method has been then identified and analysed using extant strengthening design methods. The results show that the most practical anchoring method is the use of open CFRP strips attached with concentrated adhesive. The findings of this study indicate that when strengthening T-girder bridges, more than two CFRP anchorage strips should be evenly spaced within the extension of the anchorage length, while for box girder bridges, even more evenly spaced strips should be used. This research and its conclusions can be used as a reference for the improved design of bridge deck strengthening

Bidirectional Association between Major Depressive Disorder and Gastroesophageal Reflux Disease:Mendelian Randomization Study

Background: Observational research has found a bidirectional relationship between major depressive disorder and gastroesophageal reflux disease; however, the causal association of this relationship is undetermined. Aims: A bidirectional Mendelian randomization study was performed to explore the causal relationships between major depressive disorder and gastroesophageal reflux disease. Methods: For the instrumental variables of major depressive disorder and gastroesophageal reflux disease, 31 and 24 single-nucleotide polymorphisms without linkage disequilibrium (r(2) <= 0.001) were selected from relevant genome-wide association studies, respectively, at the genome-wide significance level (p <= 5 x 10(-8)). We sorted summary-level genetic data for major depressive disorder, gastroesophageal reflux disease, gastroesophageal reflux disease without esophagitis, and reflux esophagitis from meta-analysis study of genome-wide association studies involving 173,005 individuals (59,851 cases and 113,154 non-cases), 385,276 individuals (80,265 cases and 305,011 non-cases), 463,010 individuals (4360 cases and 458,650 non-cases), and 383,916 individuals (12,567 cases and 371,349 non-cases), respectively. Results: Genetic liability to major depressive disorder was positively associated with gastroesophageal reflux disease and its subtypes. Per one-unit increase in log-transformed odds ratio of major depressive disorder, the odds ratio was 1.31 (95% confidence interval [CI], 1.19-1.43; p = 1.64 x 10(-8)) for gastroesophageal reflux disease, 1.51 (95% CI, 1.15-1.98; p = 0.003) for gastroesophageal reflux disease without esophagitis, and 1.21 (95% CI, 1.05-1.40; p = 0.010) for reflux esophagitis. Reverse-direction analysis suggested that genetic liability to gastroesophageal reflux disease was causally related to increasing risk of major depressive disorder. Per one-unit increase in log-transformed odds ratio of gastroesophageal reflux disease, the odds ratio of major depressive disorder was 1.28 (95% confidence interval, 1.11-1.47; p = 1.0 x 10(-3)). Conclusions: This Mendelian randomization study suggests a bidirectional causal relationship between major depressive disorder and gastroesophageal reflux disease

Measurement of Temperature Distribution Based on Optical Fiber-Sensing Technology and Tunable Diode Laser Absorption Spectroscopy

Temperature is an important physical quantity in most industrial processes. Distributed temperature sensor (DTS), fiber Bragg grating (FBG), and tunable diode laser absorption spectroscopy (TDLAS) are three primary techniques for temperature measurement using fiber optic sensing and spectrum technology. The DTS system can monitor space temperature field along the fiber in real time. In addition, it also can locate a fire source using two sections of optical fibers which are placed orthogonally to each other. The FBG temperature sensor is used to measure the point temperature. The temperature sensitivity of the bare FBG is 10.68 pm/°C and the linearity is 0.99954 in the range of 30–100°C. Based on tunable diode laser absorption spectroscopy (TDLAS), two-dimensional (2D) distribution reconstructions of gas temperature are realized using an algebraic reconstruction technique (ART). The results are in agreement with the simulation results, and the time resolution is less than 1 s

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ϵ\epsilon-Greedy Exploration

This paper provides a theoretical understanding of Deep Q-Network (DQN) with the $\varepsilon$-greedy exploration in deep reinforcement learning. Despite the tremendous empirical achievement of the DQN, its theoretical characterization remains underexplored. First, the exploration strategy is either impractical or ignored in the existing analysis. Second, in contrast to conventional Q-learning algorithms, the DQN employs the target network and experience replay to acquire an unbiased estimation of the mean-square Bellman error (MSBE) utilized in training the Q-network. However, the existing theoretical analysis of DQNs lacks convergence analysis or bypasses the technical challenges by deploying a significantly overparameterized neural network, which is not computationally efficient. This paper provides the first theoretical convergence and sample complexity analysis of the practical setting of DQNs with $\epsilon$-greedy policy. We prove an iterative procedure with decaying $\epsilon$ converges to the optimal Q-value function geometrically. Moreover, a higher level of $\epsilon$ values enlarges the region of convergence but slows down the convergence, while the opposite holds for a lower level of $\epsilon$ values. Experiments justify our established theoretical insights on DQNs