The dynamic characterisation of disk geometry particle dampers

Particle dampers (PDs) have the advantages of being simple in geometry, small in volume and applicable in extreme temperature environments. Experimental studies have shown that PDs can offer considerable potential for suppressing structural resonant conditions over a wide frequency range. In this paper, the nonlinear characteristics of PDs are studied experimentally in a series of response-level-controlled tests. The effect of the geometry is studied and a method is developed to model the nonlinear damping of PDs as equivalent viscous dampers that can be applied directly to engineering structures at the design stage

A construction scheme for linear and non-linear codes

AbstractA scheme for construcing linear and non-linear codes is presented. It constructs a code of block length 2n from two constituent codes of block length n. Codes so constructed can be either linear or non-linear even when the constituent codes are linear. The construction of many known linear and non-linear codes using this scheme will be shown

Surfactant Assisted Synthesis of LiFePO4 Nanostructures via Hydrothermal Processing

LiFePO4 is a potential cathode candidate for of secondary lithium batteries due to its low-cost, out-standing thermal stability and innocuity. In this paper, pure LiFePO4 obtained by hydrothermal method using cetyltrimethyl ammonium bromide (CTAB) as surfactant. LiFePO4 particles produced without any surfactant showed typical morphologies of perfect octahedral with size of ~1μm. For products prepared with addition CTAB, the amount of surfactant controlled the growth of LiFePO4 crystals, with which dif-ferent morphologies of plate, grains and flower-like structures were produced. Plate products displayed a capacity of 145.70 mAh•g-1 at 0.1C, which was superior to others. The results indicated the electrochemical performance depends crucially on the size and structure of active materials. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3520

Preparation of Nanostructured Li2MnO3 Cathode Materials by Single-Step Hydrothermal Method

Nanosized (10~50 nm) cathode material Li2MnO3 was prepared for with MnSO4·H2O，KMnO4 and Li- OH aqueous solution as the precursor via single-step hydrothermal reaction by controlling the reaction time, proportion of processor, and the reagent concentration. The prepared materials were well crystallized and exhibited a monoclinic Li2MnO3 structure with a space group of C2/m phase. The electrochemical performance of the material was tested at current density of 60 mAg-1 (1/4 C) between 4.3V and 2.0 V at room temperature, showing good electrochemical properties with the initial discharge capacity of 243 mAh·g-1, because it was more exposed to the electrolyte due to its nanostructure. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3519

Structure and Electrochemical Performance of Li[Li0.2Co0.4Mn0.4]O2 Cathode Material for Lithium Ion Battery by Co-precipitation Method

The nano-structured Li[Li0.2Co0.4Mn0.4]O2 cathode material is synthesized by a co-precipitation method. X-ray diffraction shows that the synthesized material has a hexagonal α-NaFeO2 type structure with a space group R-3m. Scanning electron microscopy and transmission electron microscopy images show the homogeneous distribution with 100-200 nm. X-ray photoelectron spectroscopy results indicate that the oxi-dation states of Co and Mn in Li[Li0.2Co0.4Mn0.4]O2 are present in trivalence and tetravalence, respectively. The charge-discharge curves and cycling performance are analyzed in detail. The initial charge and dis-charge capacities are respectively 236.5 mAh g-1 and 140.3 mAh g-1 at the current density of 100 mA g-1 in the voltage range of 2.0-4.6 V. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3520

Regularization of point vortices for the Euler equation in dimension two

In this paper, we construct stationary classical solutions of the incompressible Euler equation approximating singular stationary solutions of this equation. This procedure is carried out by constructing solutions to the following elliptic problem [ -\ep^2 \Delta u=(u-q-\frac{\kappa}{2\pi}\ln\frac{1}{\ep})_+^p, \quad & x\in\Omega, u=0, \quad & x\in\partial\Omega, ] where $p>1$, $\Omega\subset\mathbb{R}^2$ is a bounded domain, $q$ is a harmonic function. We showed that if $\Omega$ is simply-connected smooth domain, then for any given non-degenerate critical point of Kirchhoff-Routh function $\mathcal{W}(x_1,...,x_m)$ with the same strength $\kappa>0$, there is a stationary classical solution approximating stationary $m$ points vortex solution of incompressible Euler equations with vorticity $m\kappa$. Existence and asymptotic behavior of single point non-vanishing vortex solutions were studied by D. Smets and J. Van Schaftingen (2010).Comment: 32page

Comparison of Volatile Compounds in Two Brandies Using HS-SPME Coupled with GC-O, GC-MS and Sensory Evaluation

The aim of this study was to compare the volatile compounds between Changyu XO and Hennessy XO. Sensoryevaluation was performed by a panel of tasters. Qualitative and semi-quantitative analysis was achieved byheadspace solid phase micro-extraction (HS-SPME), coupled with gas chromatography-mass spectrometry (GCMS)and gas chromatography-olfactometry (GC-O). A total of 160 volatile compounds were identified in the twobrands of brandy. Of these, 118 compounds were common to both Changyu XO and Hennessy XO; 18 compoundswere specific to Changyu XO and 24 were specific to Hennessy XO. A total of 85 aroma compounds responsiblefor brandy flavour were identified by GC-O, of which 68 were common to both brands, while seven and tenwere specific to Changyu XO and Hennessy XO, respectively. The study provided detailed information aboutthe compounds responsible for the characteristic flavour of specific brandies. According to statistical analysis,significant differences were recorded between Changyu XO and Hennessy XO. Most volatile compounds inChangyu XO occurred at lower concentrations than those in Hennessy XO. Based on sensory evaluation analysis,the floral, alcohol and rancid aroma descriptors achieved higher scores in Changyu XO and Hennessy XO, whilethe lime aroma seemed specific to Hennessy XO. Herb and almond aromas were specific to Changyu XO

Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications

Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints. Recent developments in support vector machine and metaheuristics show many advantages of these techniques. In particular, particle swarm optimization is now widely used in solving tough optimization problems. In this paper, we use a combination of a recently developed Accelerated PSO and a nonlinear support vector machine to form a framework for solving business optimization problems. We first apply the proposed APSO-SVM to production optimization, and then use it for income prediction and project scheduling. We also carry out some parametric studies and discuss the advantages of the proposed metaheuristic SVM.Comment: 12 page

A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei

Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most existing deep learning based approaches in neuroimaging do not investigate the specific difficulties that exist in segmenting extremely small but important brain regions such as the subnuclei of the amygdala. To tackle this challenging task, we developed a dual-branch dilated residual 3D fully convolutional network with parallel convolutions to extract more global context and alleviate the class imbalance issue by maintaining a small receptive field that is just the size of the regions of interest (ROIs). We also conduct multi-scale feature fusion in both parallel and series to compensate the potential information loss during convolutions, which has been shown to be important for small objects. The serial feature fusion enabled by residual connections is further enhanced by a proposed top-down attention-guided refinement unit, where the high-resolution low-level spatial details are selectively integrated to complement the high-level but coarse semantic information, enriching the final feature representations. As a result, the segmentations resulting from our method are more accurate both volumetrically and morphologically, compared with other deep learning based approaches. To the best of our knowledge, this work is the first deep learning-based approach that targets the subregions of the amygdala. We also demonstrated the feasibility of using a cycle-consistent generative adversarial network (CycleGAN) to harmonize multi-site MRI data, and show that our method generalizes well to challenging traumatic brain injury (TBI) datasets collected from multiple centers. This appears to be a promising strategy for image segmentation for multiple site studies and increased morphological variability from significant brain pathology