脉冲LDA泵浦Nd∶YVO4/GaAs被动调Q锁模激光器

用脉冲激光二极管阵列（LDA）作为泵浦源、微柱透镜阵列和透镜导管作为耦合系统,以As＋注入GaAs可饱和吸收片作为被动调Q锁模元件,实现了Nd∶YVO4激光器调Q锁模运转.调Q运转阶段,激光器每泵浦脉宽内输出一个调Q脉冲,调Q脉宽7ns.调Q锁模运转阶段,初始透过率60％的GaAs晶片对调Q包络内的锁模脉冲的调制深度达到95％以上,锁模脉冲重复频率991 MHz.研究了加在LDA上的电压、方波脉冲的脉宽和重复频率对调Q锁模脉冲特性的影响,并对实验结果进行了讨论.     

Pulverized coal swirl flames in oxy-fuel conditions: Effects of oxidizer O2 concentration on flow field and local gas composition

In an experimental study the effects of varied oxygen concentrations in the oxidizer gas on resulting flow fields, combustion products and general behavior of pulverized coal swirl flames under oxy-fuel conditions have been investigated. Experiments were carried out in a small scale down-fired cylindrical combustion chamber equipped with an annular swirl burner. Studied flames had a constant power output of 40 kW_th and O₂/CO₂ oxidizer gas mixtures with O₂ concentrations ranging from 23 to 33 vol%. Detailed two-dimensional flow field measurements are obtained from laser Doppler anemometry (LDA). Velocity profiles (Mean and RMS) have been obtained for all conditions investigated and serve as basis for identification of flow field characteristics. Velocity RMS values are provided as supplementary material. To complement flow field measurements, in-flame gas composition measurements were also conducted using a sampling probe combined with infrared gas absorption analysis via Fourier-transform infrared (FTIR) spectrometry. The results obtained show increased velocities, particularly along the main vortex for flames with increased oxygen contents, while lower velocities are found to occur inside the recirculation regions. The opposite occurs with lower O₂ concentrations, showing significantly reduced velocities in the main vortex, but stronger recirculation than the high oxygen counterparts. This effect is attributed to a modification of the swirl level introduced by the expansion of product gases. Measured NO and CO in-flame concentrations showed significant variations under different O₂ concentrations in the oxidizer.     

Multiclass Probability Estimation With Support Vector Machines

Multiclass classification and probability estimation have important applications in data analytics. Support vector machines (SVMs) have shown great success in various real-world problems due to their high classification accuracy. However, one main limitation of standard SVMs is that they do not provide class probability estimates, and thus fail to offer uncertainty measure about class prediction. In this article, we propose a simple yet effective framework to endow kernel SVMs with the feature of multiclass probability estimation. The new probability estimator does not rely on any parametric assumption on the data distribution, therefore, it is flexible and robust. Theoretically, we show that the proposed estimator is asymptotically consistent. Computationally, the new procedure can be conveniently implemented using standard SVM softwares. Our extensive numerical studies demonstrate competitive performance of the new estimator when compared with existing methods such as multiple logistic regression, linear discrimination analysis, tree-based methods, and random forest, under various classification settings. Supplementary materials for this article are available online.     

Comparison of HF,HF + MP2, LDA,BLYP, and B3LYP band structures of the homopolypeptides

Ab initio HF, HF + MP2, LDA DFT, BLYP DFT, and B3LYP DFT calculations are compared in the case of 19 homopolypeptides in their β pleated sheet conformation. The results show that the B3LYP method provides good results for the fundamental gaps, as compared with the values estimated on the basis of available UV spectra and intermediate exciton calculations for PolyGly and PolyAla. The HF method gives the best agreement, using Koopman's theorem for the ionization potential, taking the calculated VB_max values in the HF case if one compares them with the experimental ionization potentials of the 19 amino acids measured by mass spectroscopy. Finally, how these methods might be improved to determine the most stable conformations of the homopolypeptides is outlined. © 2004 Wiley Periodicals, Inc. Int J Quantum Chem, 2004     

Three-dimensional Turbulent Boundary Layer in a Shrouded Rotating System

A thre-dimensional direct numerical simulation is combined with a laboratory study to describe the turbulent flow in an enclosed annular rotor-stator cavity characterized by a large aspect ratio G = (b − a)/h = 18.32 and a small radius ratio a/b = 0.152, where a and b are the inner and outer radii of the rotating disk and h is the interdisk spacing. The rotation rate Ω considered is equivalent to the rotational Reynolds number Re = Ωb ²/ν= 9 .5 × 10⁴ (ν the kinematic viscosity of water). This corresponds to a value at which experiment has revealed that the stator boundary layer is turbulent, whereas the rotor boundary layer is still laminar. Comparisons of the computed solution with velocity measurements have given good agreement for the mean and turbulent fields. The results enhance evidence of weak turbulence by comparing the turbulence properties with available data in the literature (Lygren and Andersson, J Fluid Mech 426:297–326, 2001). An approximately self-similar boundary layer behavior is observed along the stator. The wall-normal variations of the structural parameter and of characteristic angles confirm that this boundary layer is three-dimensional. A quadrant analysis (Kang et al., Phys Fluids 10:2315–2322, 1998) of conditionally averaged velocities shows that the asymmetries obtained are dominated by Reynolds stress-producing events in the stator boundary layer. Moreover, Case 1 vortices (with a positive wall induced velocity) are found to be the major source of generation of special strong events, in agreement with the conclusions of Lygren and Andersson (J Fluid Mech 426:297–326, 2001).     

Turbulent pipe flow of a drag-reducing rigid “rod-like” polymer solution

Fully developed turbulent pipe flow of an aqueous solution of a rigid “rod-like” polymer, scleroglucan, at concentrations of 0.005% (w/w) and 0.01% (w/w) has been investigated experimentally. Fanning friction factors were determined from pressure-drop measurements for the Newtonian solvent (water) and the polymer solutions and so levels of drag reduction for the latter. Mean axial velocity u and complete Reynolds normal stress data, i.e. u′, v′ and w′, were measured by means of a laser Doppler anemometer at three different Reynolds numbers for each fluid. The measurements indicate that the effectiveness of scleroglucan as a drag-reducing agent is only mildly dependent on Reynolds number. The turbulence structure essentially resembles that of flexible polymer solutions which also lead to low levels of drag reduction.     

搅拌槽流场的实验研究

利用二维激光多普勒测速仪在内径为２５０ｍｍ的搅拌槽内对ＤＴ叶轮和ＰＴ叶轮进行了流场测试，获得了不同几何参数的叶轮在不同工况下的二维时均速度场和湍流强度、雷诺应力、剪切速率分布。为进一步研究搅拌器的流动特性，开发新型搅拌叶轮提供了可靠的实验依据。     

Direct numerical simulation of turbulent pipe flow

Fully developed turbulent pipe flow at low Re-number is studied by means of direct numerical simulation (DNS). In contrast to many previous DNS's of turbulent flows in rectangular geometries, the present DNS code, developed for a cylindrical geometry, is based on the finite volume technique rather than being based on a spectral method. The statistical results are compared with experimental data obtained with two different experimental techniques. The agreement between numerical and experimental results is found to be good which indicates that the present DNS code is suited for this kind of numerical simulations.     

MS/MS-Based Molecular Networking: An Efficient Approach for Natural Products Dereplication

Natural products (NPs) have historically played a primary role in the discovery of small-molecule drugs. However, due to the advent of other methodologies and the drawbacks of NPs, the pharmaceutical industry has largely declined in interest regarding the screening of new drugs from NPs since 2000. There are many technical bottlenecks to quickly obtaining new bioactive NPs on a large scale, which has made NP-based drug discovery very time-consuming, and the first thorny problem faced by researchers is how to dereplicate NPs from crude extracts. Remarkably, with the rapid development of omics, analytical instrumentation, and artificial intelligence technology, in 2012, an efficient approach, known as tandem mass spectrometry (MS/MS)-based molecular networking (MN) analysis, was developed to avoid the rediscovery of known compounds from the complex natural mixtures. Then, in the past decade, based on the classical MN (CLMN), feature-based MN (FBMN), ion identity MN (IIMN), building blocks-based molecular network (BBMN), substructure-based MN (MS2LDA), and bioactivity-based MN (BMN) methods have been presented. In this paper, we review the basic principles, general workflow, and application examples of the methods mentioned above, to further the research and applications of these methods.