Hybrid nanomaterial flow and heat transport in a stretchable convergent/divergent channel:a Darcy-Forchheimer model

The flow behavior in non-parallel walls is an important factor of any physical model including cavity flow and canals, which is applicable for diverging/converging channel. The present communication explains that the flow of the hybrid nanomaterial subjected to the convergent/divergent channel has non-parallel walls. It is assumed that the hybrid nanomaterial movement is in the porous region. A Darcy-Forchheimer medium of porosity is considered to interpret the porosity features. A useful similarity function is adopted to get the strong ordinary coupled equations. Numerical solutions are achieved through the Runge-Kutta-Fehlberg(RKF) fourth-fifth order method, and they are validated with the existing results. Physical nature of the involving constraints is reported with the help of plots. It is explored that the velocity of divergent channel decreases, and convergent channel enhances for the higher solid volume faction. Further, the presence of inertia coefficient and porosity parameter amplifies the velocity at the wall.     

Xe对NO(X)微分截面和非弹性散射中的碰撞诱导旋转准直

本文对NO(X)-Xe碰撞系统在碰撞能量为519 cm^-1，测量了完全?-双峰分解的微分截面和碰撞引起的旋转准直力矩. 同时结合初始量子态选择，使用六极杆的非均质电场，借助量子态分辨的测量，利用(1+1'')共振增强的多光子电离和速度离子成像. 结果显示，微分截面以及偏振相关的微分截面均显示与从头算势能面上进行的量子力学散射计算[J. K?os etal. J. Chem. Phys. 137, 014312 (2012)]一致. 通过与准经典轨迹、硬壳势能的量子力学散射以及运动近端模型的比较，评估了势能对所测微分截面和碰撞引起的旋转准直力矩的影响.     

Some optimizations on detecting gravitational wave using convolutional neural network

This work investigates the problem of detecting gravitational wave (GW) events based on simulated damped sinusoid signals contaminated with white Gaussian noise. It is treated as a classification problem with one class for the interesting events. The proposed scheme consists of the following two successive steps: decomposing the data using a wavelet packet, representing the GW signal and noise using the derived decomposition coefficients; and determining the existence of any GW event using a convolutional neural network (CNN) with a logistic regression output layer. The characteristic of this work is its comprehensive investigations on CNN structure, detection window width, data resolution, wavelet packet decomposition and detection window overlap scheme. Extensive simulation experiments show excellent performances for reliable detection of signals with a range of GW model parameters and signal-to-noise ratios. While we use a simple waveform model in this study, we expect the method to be particularly valuable when the potential GW shapes are too complex to be characterized with a template bank.     

Comonotone approximation with interpolation at the ends on an interval

Let a function f ∈ C[-1, 1], changes its monotonisity at the finite collection Y := {y1,… ,ys} of s points yi ∈ (-1, 1). For each n ≥ N(Y), we construct an algebraic polynomial Pn, of degree ≤ n, which is comonotone with f, that is changes its monotonisity at the same points yi as f, and |f(x)-Pn(x)|≤c(s)ω2(f,(√1-x2)/n), x∈[-1,1],where N(Y) is a constant depending only on Y, c(s) is a constant depending only on s and ω2 (f, t) is the second modulus of smoothness of f.     

Folate binding protein—Outlook for drug delivery applications

Serum proteins represent an important class of drug and imaging agent delivery vectors. In this minireview, key advantages of using serum proteins are discussed, followed by the particular advantages and challenges associated with employing soluble folate binding protein. In particular, approaches employing drugs that target folate metabolism are reviewed. Additionally, the slow-onset, tightbinding interaction of folate with folate binding protein and the relationship to a natural oligomerization mechanism is discussed. These unique aspects of folate binding protein suggest interesting applications for the protein as a vector for further drug and imaging agent development.     

沸石催化剂上降冰片烯二聚（英文）

The high activity and selectivity of H‐Beta and H‐ZSM‐12 zeolites in the dimerization of norbornene was established.The norbornene conversion reached 100% in chlorinated paraffin and argon gas medium,with a selectivity of dimer formation of 88%–98%.Four stereo‐isomers of the bis‐2,2'‐norbornylidene structure were identified in the dimer fraction,with the(Z)‐anti‐bis‐2,2'‐norbornylidene prevailing over the others.     

载体对其负载的Cu-Co双金属催化剂上5-羟甲基糠醛氢解选择性生成2,5-二甲基呋喃的影响

碳-氧键氢解是生物质呋喃基化合物制备交通燃料常见的模型反应,其中5-羟甲基糠醛(HMF)转化为汽油添加剂2,5-二甲基呋喃(DMF)尤为引人关注.本文采用CeO2,ZrO2和Al2O3负载的Cu-Co双金属催化剂用于HMF选择性氢解制DMF的反应中.采用X射线衍射、N2吸附-脱附、投射电镜、H2-程序升温还原、氨-程序升温脱附和元素分析表征了新鲜的和使用过催化剂的结构,并将其与催化活性相关联.Cu-Co/CeO2催化剂通过在大的Cu颗粒上还原C=O键生成了最多的2,5双(羟甲基呋喃)(BHMF).但Cu-Co/Al2O3催化剂具有高度分散的Cu,Cu-Co复合氧化物和大量的弱酸位,因而生成DMF的选择性最高.Cu-Co/ZrO2催化剂则由于存在强酸位,DMF选择性较低,生成了各种过度氢解产物,如2,5而甲基四氢呋喃和5,5-二(亚甲基)双(2-甲基呋喃).因此,考察了Cu-Co/Al2O3催化剂上的反应路径,以及温度、氢气压力和时间等操作条件的影响,使其具有较优的HMF转化率和DMF选择性.     

Recovery of Immersions from Their Metric Tensors and Nonlinear Korn Inequalities: A Brief Survey

The authors discuss the existence and uniqueness up to isometries of Enof immersions φ : Ω  R~n→ E~n with prescribed metric tensor field(g ij) : Ω→ S~n, and discuss the continuity of the mapping(gij) →φ defined in this fashion with respect to various topologies. In particular, the case where the function spaces have little regularity is considered. How, in some cases, the continuity of the mapping(gij) →φ can be obtained by means of nonlinear Korn inequalities is shown.     

混凝土与纤维混凝土的劈裂试验及损伤描述

描述工程材料在服役期间所受到的损伤，是评估其可靠度、耐久性等指标的重要依据，本文根据混凝土与纤维混凝土劈裂试验的结果，对一些损伤模型存在的问题进行的探讨认为：对于混凝土复合材料，卸载曲线的斜率受到粗骨料和纤维等因素的干扰，卸载刚度的衰减不能精确描述损伤的演化，并且，针对不同的极限状态，损伤描述应该有不同的形式，针对损伤对混凝土抗渗性能的影响问题，本文提出了损伤描述表达式。