Rational Design of Potent Inhibitors of a Metallohydrolase Using a Fragment-Based Approach

Metallohydrolases form a large group of enzymes that have fundamental importance in a broad range of biological functions. Among them, the purple acid phosphatases (PAPs) have gained attention due to their crucial role in the acquisition and use of phosphate by plants and also as a promising target for novel treatments of bone-related disorders and cancer. To date, no crystal structure of a mammalian PAP with drug-like molecules bound near the active site is available. Herein, we used a fragment-based design approach using structures of a mammalian PAP in complex with the Maybridge^TM fragment CC063346, the amino acid L-glutamine and the buffer molecule HEPES, as well as various solvent molecules to guide the design of highly potent and efficient mammalian PAP inhibitors. These inhibitors have improved aqueous solubility when compared to the clinically most promising PAP inhibitors available to date. Furthermore, drug-like fragments bound in newly discovered binding sites mapped out additional scaffolds for further inhibitor discovery, as well as scaffolds for the design of inhibitors with novel modes of action.     

防气窜固井技术研究

从气窜机理、气窜预测方法、提高水泥浆防气窜性能、防气窜固井工艺技术四个方面进行研究,为固井防气窜提供理论依据,进而提升防气窜固井技术。     

自重湿陷性黄土地基预钻孔浸水处理的可靠度设计方法

为解决传统预浸水法存在的浸水时间长、浸水处理范围难以确定等不足,基于土体中水分运移规律,依据可靠度理论、极限状态设计方法及复合 Poisson 过程原理,提出一种消除黄土湿陷性的处理浸水方法——预钻孔浸水法。给出了利用预钻孔浸水法对自重湿陷性黄土地基进行浸水时,水平向及竖直向浸水影响范围的确定模型;在此基础上结合达西定律给出了浸水孔设计参数如孔深、孔间距及浸水孔个数的确定方法。结合铜川某工程,设计进行了现场预钻孔浸水试验,对该方法的合理性进行了验证,并通过现场钻探、现场勘探、室内湿陷性试验等方法对该方法的处理效果进行了评价。该浸水方法具有浸水时间短、浸水影响范围可根据浸水孔布设进行控制等优点,且浸水处理效果良好,完全符合施工要求。     

Frequency response data-based peak filter design applied to MIMO large-scale high-precision scan stage

A large-scale high-precision scan stage is important equipment in the industrial productions of micro-fabrication such as flat panel display (FPD) lithography systems. Designing controllers for multi-input multi-output (MIMO) systems is time-consuming and needs experience because of the interaction between each axis and many controller tuning parameters. The aim of this study is to develop a peak filter design method based on frequency response data to reduce repetitive disturbance. This data-based approach does not use the model and only uses the frequency response data of the controlled system and the disturbance spectrum calculated from the scanning error data (Contribution 1). The peak filter is designed by convex optimization and satisfies robust stability conditions for six-degree-of-freedom systems (Contribution 2). The control performance of the designed peak filter is experimentally demonstrated with an industrial MIMO large-scale high-precision scan stage in reducing the scanning error of the main stroke of the translation along the $x$-axis (Contribution 3).     

Proton exchange membrane from the blend of poly(vinylidene fluoride) and functional copolymer: Preparation,proton conductivity,methanol permeability,and stability

A polymer electrolyte membrane is considered as the heart of fuel cells. Here we report the preparation of proton exchange membranes (PEMs) of poly (vinylidene fluoride) (PVDF) blend poly (methyl methacrylate)-co-poly (sodium-4-styrene sulfonate) (PMMA-co-PSSNa) by solvent evaporation method. Three different types of PEMs have been prepared by using different ratios of PVDF and PMMA-co-PSSNa copolymer. We have investigated the effect of concentration of PVDF on water uptake, ion exchange capacity, mechanical, thermal, and oxidative stability, proton conductivity (K^m), and methanol permeability (P_M) of the blend membranes. These blend PEMs showed good physicochemical and electrochemical properties along with thermal and oxidative stability. The membrane prepared from PVDF (45% w/w) to PMMA-co-PSSNa (55% w/w) exhibited optimum P_M at room temperature (8.38 × 10^?7 cm²s^?1). This low fuel crossover and high relative selectivity can make our prepared blend membranes a potential candidate in polymer electrolyte membrane fuel cells (PEMFCs) or direct methanol fuel cells (DMFCs).     

Study on ice-melting performance of gradient gas diffusion layer in proton exchange membrane fuel cell

In this study, a three-dimensional model was established using the lattice Boltzmann method (LBM) to study the internal ice melting process of the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC). The single-point second-order curved boundary condition was adopted. The effects of GDL carbon fiber number, growth slope of the number of carbon fibers and carbon fiber diameter on ice melting were studied. The results were revealed that the temperature in the middle and lower part of the gradient distribution GDL is significantly higher than that of the no-gradient GDL. With the increase of the growth slope of the number of carbon fiber, the temperature and melting rate gradually increase, and the position of the solid-liquid interface gradually decreases. The decrease in the number of carbon fibers has a similar effect as the increase in the growth slope of the number of carbon fibers. In addition, as the diameter of the carbon fiber increases, the position of the solid-liquid interface gradually decreases first and then increases.     

Sorption kinetics in metal hydrides by leaky coating

The 3D geometry of a hydrogen absorbing metal grain (Pd) is mimicked by a membrane made of the metal with identical properties, which is sealed on one side with a hydrogen semi-impermeable surface (Cu). The hydrogen loss through the sealed membrane surface is negligible, i.e., the hydrogen uptake measurement is that of a bulk material (Sieverts measurement), but the surface desorbs sufficient hydrogen to be detected by a mass spectrometer. With this, two independent spatial and temporal kinetic properties are defined which allow the reconstruction of the time dependent hydrogen distribution inside the membrane. As proof of concept, the mechanism of hydride formation in Pd is analyzed, corroborating the formation and growth of incoherent interfaces during hydrogen sorption.     

Optimization of PEMFC system operating conditions based on neural network and PSO to achieve the best system performance

PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power.     

Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.