Development of a Portable Single Photon Ionization-Photoelectron Ionization Time-of-Flight Mass Spectrometer

A vacuum ultraviolet lamp based single photon ionization- (SPI-) photoelectron ionization (PEI) portable reflecting time-of-flight mass spectrometer (TOFMS) was designed for online monitoring gas samples. It has a dual mode ionization source: SPI for analyte with ionization energy (IE) below 10.6 eV and PEI for IE higher than 10.6 eV. Two kinds of sampling inlets, a capillary inlet and a membrane inlet, are utilized for high concentration and trace volatile organic compounds, respectively. A mass resolution of 1100 at m/z 64 has been obtained with a total size of 40 × 31 × 29 cm, the weight is 27 kg, and the power consumption is only 70 W. A mixture of benzene, toluene, and xylene (BTX), SO2, and discharging products of SF6 were used to test its performance, and the result showed that the limit of quantitation for BTX is as low as 5 ppbv (S/N = 10 : 1) with linear dynamic ranges greater than four orders of magnitude. The portable TOFMS was also evaluated by analyzing volatile organic compounds from wine and decomposition products of SF6 inside of a gas-insulated switchgear

Protein docking refinement by convex underestimation in the low-dimensional subspace of encounter complexes

We propose a novel stochastic global optimization algorithm with applications to the refinement stage of protein docking prediction methods. Our approach can process conformations sampled from multiple clusters, each roughly corresponding to a different binding energy funnel. These clusters are obtained using a density-based clustering method. In each cluster, we identify a smooth “permissive” subspace which avoids high-energy barriers and then underestimate the binding energy function using general convex polynomials in this subspace. We use the underestimator to bias sampling towards its global minimum. Sampling and subspace underestimation are repeated several times and the conformations sampled at the last iteration form a refined ensemble. We report computational results on a comprehensive benchmark of 224 protein complexes, establishing that our refined ensemble significantly improves the quality of the conformations of the original set given to the algorithm. We also devise a method to enhance the ensemble from which near-native models are selected.Published versio

Chemical constituents and hypoglycemic mechanisms of Dendrobium nobile in treatment of type 2 diabetic rats by UPLC-ESI-Q-Orbitrap, network pharmacology and in vivo experimental verification

Abstract: This study aimed to systematically explore the chemical constituents of D. nobile and its hypoglycemic effect by UPLC-ESI-Q-Orbitrap, network pharmacology and in vivo experiment. The chemical constituents of D. nobile were qualitatively analyzed, and the hypoglycemic compounds were quickly identified. Network pharmacological analysis and molecular docking technique were applied to assist in the elucidation of the hypoglycemic mechanisms of D. nobile. A type 2 diabetic mellitus (T2DM) rat model was established using the HFD and STZ method for in vivo experimental verification, and these T2DM rats were treated with D. nobile extract and D. nobile polysaccharide for two months by gavage. The results showed that a total of 39 chemical constituents of D. nobile, including alkaloids, bibenzyls, phenanthrenes and other types of compounds, were identified. D. nobile extract and D. nobile polysaccharide could significantly ameliorate the body weight, hyperglycemia, insulin resistance, dyslipidemia and morphological impairment of the liver and pancreas in the T2DM rats. α-Linolenic acid, dihydroconiferyl dihydro-p-coumarate, naringenin, trans-N-feruloyltyramine, gigantol, moscatilin, 4-O-methylpinosylvic acid, venlafaxine, nordendrobin and tristin were regarded as the key hypoglycemic compounds of D. nobile, along with the hypoglycemic effect on the PI3K-AKT signaling pathway, the insulin signaling pathway, the FOXO signaling pathway, the improvement of insulin resistance and the AGE-RAGE signaling pathway. The Western blotting experiment results confirmed that D. nobile activated the PI3K/AKT pathway and insulin signaling pathway, promoted glycogen synthesis via regulating the expression of glycogen synthase kinase 3 beta (GSK-3) and glucose transporter 4 (GLUT4), and inhibited liver gluconeogenesis by regulating the expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6 phosphatase (G6pase) in the liver. The results suggested that the hypoglycemic mechanism of D. nobile might be associated with liver glycogen synthesis and gluconeogenesis, contributing to improving insulin resistance and abnormal glucose metabolism in the T2DM rats

Anisotropic shear stress σxy\sigma_{xy} effects in the basal plane of Sr2_2RuO4_4

In this short note, we repeat the calculations the jumps for the specific heat C$_{\sigma_{xy}}$, the elastic compliance S$_{xyxy}^{\sigma_{xy}}$ and the thermal expansion $\alpha_{\sigma_{xy}}$ due to a shear stress $\sigma_{xy}$ in the basal plane of $Sr_2RuO_4$. Henceforth we clarify some issues regarding the elastic theoretical framework suitable to explain the sound speed experiments of Lupien et al. (2001,2002), and partially the strain experiments of Hicks et al. (2014), and Steppke et al. (2016) in strontium ruthenate. We continue to propose that the discontinuity in the elastic constant C$_{xyxy}$ of this tetragonal crystal gives unambiguous experimental evidence that the superconducting order parameter $\Psi$ has two components with a broken time-reversal symmetry state, and that the $\gamma$ band couples the anisotropic electron-phonon interaction to the $[xy]$ in-plane shear stress according to Walker and collaborators [4] and [3]. Some importants words about the roll of the spin equal to one for the transversal phonons are added in the conclusion following Levine [34].Comment: 11 pages, for section 5: added figure 2 and figure 3 replaced. One reference and typos added. figure 4 added. arXiv admin note: text overlap with arXiv:1812.0649

Tackling unemployment in China: state capacity and governance issues

This paper considers China's state capacity and changing governance as revealed through its policies to tackle unemployment. Despite high levels of growth, economic restructuring has resulted in rising unemployment over the last decade. The Chinese state has been able to manage job losses from state enterprises, demonstrating some state capacity in relation to this sector and some persistent command economy governance mechanisms. However both design and implementation of policies to compensate and assist particular groups among the unemployed have been shaped by weak state capacity in several other areas. First, capacity to gather accurate employment data is limited, meaning local and central governments do not have a good understanding of the extent and nature of unemployment. Second, the sustainability of supposedly mandatory unemployment insurance schemes is threatened by poor capacity to enforce participation. Third, poor central state capacity to ensure local governments implement policies effectively leads to poor unemployment insurance fund capacity, resulting in provision for only a narrow segment of the unemployed and low quality employment services. Although the adoption of unemployment insurance (and its extension to employers and employees in the private sector), the introduction of a Labour Contract Law in 2007, and the delivery of employment services by private businesses indicate a shift towards the use of new governance mechanisms based on entitlement, contract and private sector delivery of public-sector goods, that shift is undermined by poor state capacity in relation to some of these new mechanisms

Motion Design and Learning of Autonomous Robots Based on Primitives and Heuristic Cost-to-Go

The task of trajectory design of autonomous vehicles is typically two-fold. First, it needs to take into account the intrinsic dynamics of the vehicle, which are sometimes termed local constraints. Second, on a higher level, the designed trajectories must allow the vehicle to achieve some application-specific task. The specification of the task results in the so-called global constraints. Both of these two components of trajectory design are generally nontrivial problems, and very often, they are pursued as two parallel areas. When the results drawn from the two areas are applied in conjunction, the synthesis is usually somewhat arbitrary. In this paper, we assume some optimal control strategy that addresses the vehicle dynamics is available as a set of motion primitives. The trajectories that achieve the task are determined solely through the primitives and do not reference the vehicle dynamics directly. For the higher level, we translate the task into a very special type of cost-to-go function, which is partially specified artificially, and partially determined by an admissibility condition imposed by the set of primitives. The optimality feature of the primitives is formally extended to the final trajectory design. We illustrate our result with the example of a mobile robot retrieving an object, which is an interesting problem of its own right. Both a direct design approach and a learning approach are presented

Videos of Trajectory Design Based on Motion Primitives: Direct Design and Learning

The enclosed videos demonstrate an approach of integrating the optimality of two layers of autonomous vehicle trajectory design. We assume that some optimal control laws are available as a set of motion primitives (the lower layer) to address the vehicle dynamics. For the upper layer, the trajectories that achieve the task are determined solely through the primitives and do not reference the vehicle dynamics directly. We translate the task into a very special type of cost-to-go function, which is partially specified artificially and partially determined by an admissibility condition imposed by the set of primitives. The optimality feature of the primitives is formally extended to the final trajectory design. Four videos are enclosed. In two of them, the solutions were derived analytically in closed form. As a result, the designs require little computation for real-time implementations. The other two videos demonstrate learning based on our approach. For more details, please look for the upcoming paper of the authors in the Robotics and Autonomous Systems journal.The Air Force under grant F49620-02-1-0388 and the NSF under grant ECS-0329743.1_c3e2dvzc1_vxvt90zv1_p909mfcd1_vvx9jec