Accurate prediction of relative binding affinities of a series of HIV-1 protease inhibitors using semi-empirical quantum mechanical charge

A major challenge in computer-aided drug design is the accurate estimation of ligand binding affinity. Here, a new approach that combines the adaptive steered molecular dynamics (ASMD) and partial atomic charges calculated by semi-empirical quantum mechanics (SQMPC), namely ASMD-SQMPC, is suggested to predict the ligand binding affinities, with 24 HIV-1 protease inhibitors as testing examples. In the ASMD-SQMPC, the relative binding free energy (ΔG) is reflected by the average maximum potential of mean force (<PMF>_max) between bound and unbound states. The correlation coefficient (R²) between the <PMF>_max and experimentally determined ΔG is 0.86, showing a significant improvement compared with the conventional ASMD (R² = 0.52). Therefore, this study provides an efficient approach to predict the relative ΔG and reveals the significance of precise partial atomic charges in the theoretical simulations.     

Moving boundary truncated grid method: Multidimensional quantum dynamics

The moving boundary truncated grid (TG) method is used to study wave packet dynamics of multidimensional quantum systems. As time evolves, appropriate Eulerian grid points required for propagating a wave packet are activated and deactivated with no advance information about the dynamics. This method is applied to the Henon-Heiles potential and wave packet barrier scattering in two, three, and four dimensions. Computational results demonstrate that the TG method not only leads to a great reduction in the number of grid points needed to perform accurate calculations but also is computationally more efficient than the full grid calculations.     

Tiara[5]arenes: Synthesis,Solid‐State Conformational Studies,Host–Guest Properties,and Application as Nonporous Adaptive Crystals

Tiara[5]arenes (T[5]s), a new class of five‐fold symmetric oligophenolic macrocycles that are not accessible from the addition of formaldehyde to phenol, were synthesized for the first time. These pillar[5]arene‐derived structures display both unique conformational freedom, differing from that of pillararenes, with a rich blend of solid‐state conformations and excellent host–guest interactions in solution. Finally we show how this novel macrocyclic scaffold can be functionalized in a variety of ways and used as functional crystalline materials to distinguish uniquely between benzene and cyclohexane.     

Polymer Transformers: Interdigitating Reaction Networks of Fueled Monomer Species to Reconfigure Functional Polymer States

Adaptivity is an essential trait of life. One type of adaptivity is the reconfiguration of a functional system states by correlating sensory inputs. We report polymer transformers, which can adaptively reconfigure their composition from a state of a mixed copolymer to being enriched in either monomer A or B. This is achieved by embedding and hierarchically interconnecting two chemically fueled activation/deactivation enzymatic reaction networks for both monomers via a joint activation pathway (network level) and an AB linker monomer reactive to both A and B (species level). The ratio of enzymes governing the individual deactivation pathways (our external signals) control the enrichment behavior in the dynamic state. The method shows high programmability of the reconfigured state, rejuvenation of transformation cycles, and quick in situ adaptation. As a proof‐of‐concept, we showcase this dynamic reconfiguration for colloidal surface functionalities.     

FORCE FIELDS ON INVISCID,SLENDER, ANNULAR LIQUID JETS

Regular perturbation expansions are used to analyse the fluid dynamics of unsteady, inviscid, slender, thin, incompressible (constant density), axisymmetric, upward and downward, annular liquid jets subjected to non-homogeneous, conservative body forces when both the annular jets are very thin and the gases enclosed by and surrounding the jet are dynamically passive. Both inertia- and capillarity-dominated annular jets are considered. It is shown that, for inertia-dominated jets, closure of the leading-order equations is achieved at second order in the perturbation parameter, which is the slenderness ratio, whereas closure is achieved at first order for capillarity-dominated jets. The steady leading-order equations are solved numerically by means of both an adaptive finite difference method which maps the curvilinear geometry of the jet onto a unit square and a fourth-order-accurate Runge–Kutta technique. It is shown that the fluid dynamics of steady, annular liquid jets is very sensitive to the Froude and Weber numbers and nozzle exit angle in the presence of non-homogeneous, conservative body forces. For upward jets with inwardly or axially directed velocities at the nozzle exit the effect of the non-homogeneous, conservative body forces is to increase the leading-order axial velocity component, decrease the jet's mean radius and move the stagnation point downstream. For downward jets with radially outward velocity at the nozzle exit the axial velocity component decreases monotonically as the magnitude of the non-homogeneous, conservative body forces is increased.     

AN ADAPTIVE UNSTRUCTURED TRI-TREE ITERATIVE SOLVER FOR MIXED FINITE ELEMENT FORMULATION OF THE STOKES EQUATIONS

An iterative adaptive equation solver for solving the implicit Stokes equations simultaneously with tri-tree grid generation is developed. The tri-tree grid generator builds a hierarchical grid structure which is mapped to a finite element grid at each hierarchical level. For each hierarchical finite element grid the Stokes equations are solved. The approximate solution at each level is projected onto the next finer grid and used as a start vector for the iterative equation solver at the finer level. When the finest grid is reached, the equation solver is iterated until a tolerated solution is reached. In order to reduce the overall work, the element matrices are integrated analytically beforehand. The efficiency and behaviour of the present adaptive method are compared with those of the previously developed iterative equation solver which is preconditioned by incomplete LU factorization with coupled node fill-in. The efficiency of the incomplete coupled node fill-in preconditioner is shown to be largely dependent on the global node numbering. The preconditioner is therefore tested for the natural node ordering of the tri-tree grid generator and for different ways of sorting the nodes.     

A control volume finite element method for three-dimensional three-phase flows

A novel control volume finite element method with adaptive anisotropic unstructured meshes is presented for three-dimensional three-phase flows with interfacial tension. The numerical framework consists of a mixed control volume and finite element formulation with a new P₁DG-P₂ elements (linear discontinuous velocity between elements and quadratic continuous pressure between elements). A “volume of fluid” type method is used for the interface capturing, which is based on compressive control volume advection and second-order finite element methods. A force-balanced continuum surface force model is employed for the interfacial tension on unstructured meshes. The interfacial tension coefficient decomposition method is also used to deal with interfacial tension pairings between different phases. Numerical examples of benchmark tests and the dynamics of three-dimensional three-phase rising bubble, and droplet impact are presented. The results are compared with the analytical solutions and previously published experimental data, demonstrating the capability of the present method.     

Flume testing of passively adaptive composite tidal turbine blades under combined wave and current loading

The tidal energy industry is progressing rapidly, but there are still barriers to overcome to realise the commercial potential of this sector. Large magnitude and highly variable loads caused by waves acting on the turbine are of particular concern. Composite blades with in-built bend-twist elastic response may reduce these peak loads, by passively feathering with increasing thrust. This could decrease capital costs by lowering the design loads, and improve robustness through the mitigation of pitch mechanisms. In this study, the previous research is extended to examine the performance of bend-twist blades in combined wave–current flow, which will frequently be encountered in the field. A scaled 3 bladed turbine was tested in the flume at IFREMER with bend-twist composite blades and equivalent rigid blades, sequentially under current and co-directional wave–current cases. In agreement with previous research, when the turbine was operating in current alone at higher tip speed ratios the bend-twist blades reduced the mean thrust and power compared to the rigid blades. Under the specific wave–current condition tested the average loads were similar on both blade sets. Nevertheless, the bend-twist blades substantially reduced the magnitudes of the average thrust and torque fluctuations per wave cycle, by up to 10% and 14% respectively.     

语音通信降噪研究

语音通信系统中,语音通过信道传输将不可避免地引入码间串扰和信号畸变,同时受到噪声污染。本文在分析自适应盲均衡算法CMA(constant modulus algorithm）和改进盲均衡算法的基础上,考虑到自适应盲均衡技术在语音噪声控制方面能力有限,将自适应盲均衡技术与小波包掩蔽阈值降噪算法联合使用,形成一种基带语音增强新方法。仿真试验结果显示自适应盲均衡技术可以使星座图变得清晰而紧凑,有效减小误码率。研究证实该方法在语音信号ISI和畸变严重情况下,在白噪及有色噪声不同的噪声环境中都具有稳定的降噪能力,消噪同时可获得汉语普通话良好的听觉效果。     

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

The accurate prediction of the solar diffuse fraction (DF), sometimes called the diffuse ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse irradiance research is discussed and then three robust, machine learning (ML) models are examined using a large dataset (almost eight years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid adaptive network-based fuzzy inference system (ANFIS), a single multi-layer perceptron (MLP) and a hybrid multi-layer perceptron grey wolf optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various solar and DF irradiance data, from Spain. The results were then evaluated using frequently used evaluation criteria, the mean absolute error (MAE), mean error (ME) and the root mean square error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance in both the training and the testing procedures.