A new Monte Carlo model for predicting the mechanical properties of fiber yarns

Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.     

Multiplexed therapeutic drug monitoring of antipsychotics in dried plasma spots by LC‐MS/MS

In this work, a convenient method for the therapeutic monitoring of seven common antipsychotic drugs in “dried plasma spot” samples has been developed. It is based on the liquid chromatography tandem mass spectrometry technique, operating in multiple reaction monitoring mode, and a straightforward procedure for the simultaneous extraction of all antipsychotics in a single step, with high extraction yield. The method was fully validated with proper accuracy, precision, selectivity and sensitivity, for all the drugs. Limits of quantification were 0.12, 1.09, 1.46, 1.47, 5.70, 1.32, 1.33 µg/L for haloperidol, aripiprazole, olanzapine, quetiapine, clozapine, risperidone, and paliperidone, respectively. Accuracy, intra‐ and interday precision values were <10% for all drugs at all concentration levels examined. The method was tested in the analysis of 30 plasma samples from real patients for each drug. The proposed analytical approach, by combining practical and logistical advantages of microsampling with liquid chromatography tandem mass spectrometry analytical performance, could offer an ideal strategy for accurate and timely therapeutic drug monitoring of antipsychotic drugs in most clinical settings, even in remote centers and/or in out‐patient settings, bringing so many potential improvements in psychiatric patient care.     

One-pot reactions of nitroenamines with anilines and ethyl glyoxylate

In a simple, one-pot, catalyst-free procedure starting from heterocyclic nitroenamines, substituted anilines and ethyl glyoxylate new ethyl 2-arylamino-3-nitro-propionates were prepared in good to excellent yields. Depending on the substituent pattern of the anilines applied, two routes for the one-pot reaction are suggested. Additionally, it was demonstrated that these multifunctional compounds of aza-Morita–Baylis–Hillman type were also formed in two-step protocols either from imines and nitroenamines or from the adducts of nitroenamines and ethyl glyoxylate with anilines.     

Topic tracking with Bayesian belief network

The task of topic tracking is to monitor a stream of stories and find all subsequent stories that discuss the same topic. Using Bayesian belief network we give three topic tracking models: a static topic model BSTM and two dynamic topic models BDTM-I, BDTM-II. BDTM-II merges the advantages of BSTM and BDTM-I, has better tracking performance than the former two, and effectively alleviates topic drift phenomenon. Applying unrelated coming stories to update BDTM-I and BDTM-II can filter noises existed in topics. Experiments on TDT corpora show that BSTM decreases (C_det)_norm by 5.5% comparing to VSM, BDTM-II decreases (C_det)_norm by 6.3% and 6.0% comparing to BSTM and BDTM-I respectively, using unrelated stories can improve the tracking performance.     

Thermodynamic description of the viscosity of liquid solder alloys with minor Co impurities

Because of the increasing complexity and cost of experiments carried out, the data for the multi-component alloy systems have frequently been obtained by numerical modelling. It is clear that the related calculations require reliable data dealing with the pure components and binary alloy systems. Selecting the reliable data concerning the pure components from the literature, the viscosities for the SAC and (SAC)_1?x Co_x solder alloys have been calculated using different viscosity models (geometric and physical). The viscosity decreases as the amount of tin content increases in the SAC387 alloy while the addition of the cobalt to SAC387 solder results in the increasing of the viscosity. Moreover, by computing the root mean square values between theoretical and experimental viscosities, it can be concluded that the lowest value among all models is that of obtained by Kaptay equation.     

An embedded boundary framework for compressible turbulent flow and fluid–structure computations on structured and unstructured grids

The finite volume method with exact two‐phase Riemann problems (FIVER) is a two‐faceted computational method for compressible multi‐material (fluid–fluid, fluid–structure, and multi‐fluid–structure) problems characterized by large density jumps, and/or highly nonlinear structural motions and deformations. For compressible multi‐phase flow problems, FIVER is a Godunov‐type discretization scheme characterized by the construction and solution at the material interfaces of local, exact, two‐phase Riemann problems. For compressible fluid–structure interaction (FSI) problems, it is an embedded boundary method for computational fluid dynamics (CFD) capable of handling large structural deformations and topological changes. Originally developed for inviscid multi‐material computations on nonbody‐fitted structured and unstructured grids, FIVER is extended in this paper to laminar and turbulent viscous flow and FSI problems. To this effect, it is equipped with carefully designed extrapolation schemes for populating the ghost fluid values needed for the construction, in the vicinity of the fluid–structure interface, of second‐order spatial approximations of the viscous fluxes and source terms associated with Reynolds averaged Navier–Stokes (RANS)‐based turbulence models and large eddy simulation (LES). Two support algorithms, which pertain to the application of any embedded boundary method for CFD to the robust, accurate, and fast solution of FSI problems, are also presented in this paper. The first one focuses on the fast computation of the time‐dependent distance to the wall because it is required by many RANS‐based turbulence models. The second algorithm addresses the robust and accurate computation of the flow‐induced forces and moments on embedded discrete surfaces, and their finite element representations when these surfaces are flexible. Equipped with these two auxiliary algorithms, the extension of FIVER to viscous flow and FSI problems is first verified with the LES of a turbulent flow past an immobile prolate spheroid, and the computation of a series of unsteady laminar flows past two counter‐rotating cylinders. Then, its potential for the solution of complex, turbulent, and flexible FSI problems is also demonstrated with the simulation, using the Spalart–Allmaras turbulence model, of the vertical tail buffeting of an F/A‐18 aircraft configuration and the comparison of the obtained numerical results with flight test data. Copyright © 2014 John Wiley & Sons, Ltd.     

盐析辅助液液萃取交联聚维酮净化-靶向单一离子监测/高分辨质谱法测定蜂蜜中新烟碱类农药残留

基于盐析辅助液液萃取(LLE)交联聚维酮(PVPP)净化技术,建立了蜂蜜中7种新烟碱类农药的靶向单一离子监测(TSIM)/高分辨质谱检测方法。样品用乙腈基于盐析辅助LLE-PVPP提取净化,采用BEH C18色谱柱为分析柱,甲醇-水体系(两相均含0.1%甲酸和5 mmol/L甲酸铵)作为流动相,梯度洗脱,采用高分辨质谱TSIM模式检测目标化合物,内标法定量。结果表明,盐析辅助LLE-PVPP净化技术可实现提取净化一步式样品制备,TSIM扫描模式则显示了更宽的线性动态范围和更高的灵敏度与准确度。7种新烟碱类农药在0.01~100μg/L或0.02~100μg/L范围内具有良好的线性关系(r20.999);方法检出限为0.03~0.07μg/kg,定量下限为0.1~0.2μg/kg。在0.2、2、20μg/kg 3种加标水平下,7种新烟碱类农药在蜂蜜中的平均回收率为84.8%~112.7%,日内精密度(RSDr)为0.9%~5.7%,日间精密度(RSDR)为3.7%~9.7%。该方法前处理简单快速、成本较低,灵敏度高、重现性好,可广泛应用于蜂蜜中新烟碱类农药残留的快速检测。     

Multivalent neuraminidase hydrolysis resistant triazole-sialoside protein conjugates as influenza-adsorbents

Triazole-sialoside tailored proteins with high hemagglutinin (HA) and neuraminidase (NA) binding affinity are prepared. Dynamic light scattering shows that these pseudo-sialylated proteins are ideal virus capture macromolecules.