Exclusive decay of Υ\Upsilon into J/ψ+χc0,1,2J/\psi+\chi_{c0,1,2}

We study the $\Upsilon$ exclusive decay into double charmonium, specifically, the $S$-wave charmonium $J/\psi$ plus the $P$-wave charmonium $\chi_{c0,1,2}$ in the NRQCD factorization framework. Three distinct decay mechanisms, i.e., the strong, electromagnetic and radiative decay channels are included and their interference effects are investigated. The decay processes $\Upsilon(1S,2S,3S)\to J/\psi+\chi_{c1,0}$ are predicted to have the branching fractions of order $10^{-6}$, which should be observed in the prospective Super $B$ factory.Comment: 22 pages, 9 figures, 3 table

Harnessing Neuron Stability to Improve DNN Verification

Deep Neural Networks (DNN) have emerged as an effective approach to tackling real-world problems. However, like human-written software, DNNs are susceptible to bugs and attacks. This has generated significant interests in developing effective and scalable DNN verification techniques and tools. In this paper, we present VeriStable, a novel extension of recently proposed DPLL-based constraint DNN verification approach. VeriStable leverages the insight that while neuron behavior may be non-linear across the entire DNN input space, at intermediate states computed during verification many neurons may be constrained to have linear behavior - these neurons are stable. Efficiently detecting stable neurons reduces combinatorial complexity without compromising the precision of abstractions. Moreover, the structure of clauses arising in DNN verification problems shares important characteristics with industrial SAT benchmarks. We adapt and incorporate multi-threading and restart optimizations targeting those characteristics to further optimize DPLL-based DNN verification. We evaluate the effectiveness of VeriStable across a range of challenging benchmarks including fully-connected feedforward networks (FNNs), convolutional neural networks (CNNs) and residual networks (ResNets) applied to the standard MNIST and CIFAR datasets. Preliminary results show that VeriStable is competitive and outperforms state-of-the-art DNN verification tools, including $\alpha$-$\beta$-CROWN and MN-BaB, the first and second performers of the VNN-COMP, respectively.Comment: VeriStable and experimental data are available at: https://github.com/veristable/veristabl

Analysis of the Influence of Fish Behavior on the Hydrodynamics of Net Cage

In net cage hydrodynamic analysis, drag force of net is dependent on the physical dimensions of the net cage, the Solidity ratio, the Reynolds number and the projected area of the net, which is illustrated in numerous previous researches. However, rare studies attempt to investigate the effect of fish behavior. Thus a net-fluid interaction model and a simplified fish model were proposed for analyzing the effects of fish behavior on the net cage. A series of physical model tests were conducted to validate the numerical model, which indicates models can simulate the stocked net cage in the current accurately. The simulation results indicate that circular movement of fish leads to a low pressure zone at the center of net cage, which causes a strong vertical flow along the center line of the net cage. The drag force on the net cage is significantly decreased with the increasing fish stocking density

非甾体抗炎药相关的消化性溃疡并发上消化道出血

Through discussion of 1 elderly case with multiple drug application of upper gastrointestinal bleeding (UGIB), we have summarized non-steroidal anti-inflammatory drugs (NSAIDs) are responsible for peptic ulcer bleeding, then discussed the relationship between drugs and peptic ulcer bleeding, suggested current researches of the factors such as age and Helicobacter pylori infection are bleeding risk to recurrent peptic ulcer complicated with UGIB. At last, we suggested the specifec therapeutic schedule and treat focus in different periods.通过讨论1例有应用多种药物病史的老年上消化道出血病例，分析了导致该患者发生消化性溃疡进而发生上消化道出血的致病因素主要与非甾体类消炎药密切相关，同时讨论了多种药物在致病中的主要作用与促发作用。该患者年龄大，既往有胃溃疡病史，同时有幽门螺杆菌感染则是易于再发消化性溃疡并发上消化道出血的易发因素。根据上述分析提出了具体的治疗方案以及不同时期的治疗重点

(E)-2-{3-[4-(Diphenyl­amino)styr­yl]-5,5-dimethyl­cyclo­hex-2-enyl­idene}­malono­nitrile

In the title compound, C31H27N3, the cyclo­hexene ring has an envelope configuration. In the crystal structure, there is an 34 Å3 void around the inversion center, but the low electron density (0.13 e Å−3) in the difference Fourier map suggests no solvent mol­ecule occupying this void. No hydrogen bonding is found in the crystal structure