Evaluation of adult and offspring thiamine deficiency in salmonine species from Lake Ontario

Thiamine Deficiency Complex (TDC) is an ongoing problem impacting salmonine health in various waterbodies, including Lake Ontario. The prevalence of TDC has been variable and explanations for differences are limited. In the current study, thiamine concentrations were measured in eggs, liver tissue, and muscle tissue sampled from brown trout (Salmo trutta), Chinook salmon (Oncorhynchus tshawytscha), coho salmon (O. kisutch), lake trout (Salvelinus namaycush), and steelhead trout (O. mykiss) that were collected from Lake Ontario and its surrounding tributaries. The occurrence of TDC was measured for each species based on TDC-induced offspring mortality rates under laboratory conditions. TDC-induced offspring mortality was observed for all species except brown trout. For affected species, egg free thiamine (Th) was consistently low compared to lake trout collected from Lake Superior that are considered thiamine replete. In addition, species with the lowest percentages of Th in their eggs were the most susceptible to TDC, suggesting that limited thiamine reserves in the form of Th may cause TDC-induced offspring mortality. Lastly, our results show that egg thiamine concentrations have yearly variation and increased for all species throughout the study. Reasons for such variation are undetermined; but, if egg thiamine concentrations continue to increase, the impacts of TDC on these salmonine species may lessen. Future monitoring is needed for determining if thiamine concentrations are increasing and the potential impacts that may have on the entire Lake Ontario fishery.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

基于改进耦合增强随机共振的滚动轴承故障诊断

针对强背景噪声下经典随机共振方法对滚动轴承故障特征提取效果差的问题,提出了一种基于改进耦合增强随机共振的滚动轴承故障诊断方法。首先,利用一个定参双稳系统和一个变参双稳系统构成耦合随机共振系统,外部输入直接作用于定参双稳系统;然后,通过调节变参双稳系统参数和耦合系数实现耦合系统的随机共振控制,并借助遗传算法实现控制参数的自适应选取。实验和工程应用验证了所提方法的有效性和优越性。     

Numerical modelling of a low power non-transferred arc plasma reactor for methane conversion

Thermal flow characteristics and the methane conversion reaction in a low power arc plasma reactor for efficient storage and transport of methane, which is the main component of shale gas, were simulated. The temperature and velocity distributions were calculated according to the type of discharge gases and arc current level by a self-developed magnetohydrodynamics (MHD) code and a commercial ANSYS-FLUENT code; the transport of chemical species was analyzed as including the chemical reactions of methane conversion. The simulated results were verified by the comparison of calculated and measured arc voltages with permissible low error as under 4%. Three C₂ hydrocarbon gases with ethane (C₂H₆), ethylene (C₂H₄), and acetylene (C₂H₂) were selected as the converted species of methane from experimental data. The mass fraction of C₂ hydrocarbons and hydrogen as the product of the conversion reaction at the reactor was also calculated. Those values show good agreement with the actual experimental results in that the major conversion reaction occurred in C₂H₂ and hydrogen, and the conversions to C₂H₆, C₂H₄, and hydrogen were minor reactions of methane pyrolysis conversion.     

A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

Effect of preparation method on physicochemical properties and catalytic performances of LaCoO_3 perovskite for CO oxidation

Perovskite oxides LaCoO_3 prepared by templating, co-precipitation and sol-gel method with different complexants were systematically characterized and its catalytic performances for CO oxidation were investigated. The samples were characterized by X-ray diffraction, thermogravimetry analysis and differential scanning calorimetry, N_2 physisorption, transmission electron microscopy, temperature program reduction of hydrogen, temperature program desorption of oxygen and X-ray photoelectron spectroscopy measurement, results of which show that the properties of LaCoO_3, such as surface morphology, surface area, surface compositions, redox capability, oxygen vacancy, as well as the calcination temperature and formation mechanism, depend intimately on the preparation method. Catalytic tests indicate that the sample prepared by carbon templating method shows the best activity for CO oxidation, with full CO conversion obtained at 135 ℃. In particular, the catalyst can be activated and significant increase of activity can be obtained with the increase of reaction time. The cyclic and longterm stability of catalysts were discussed and compared.     

An improved cuckoo search algorithm for the problem of electric distribution network reconfiguration

Power loss reduction has an important role in operating electric distribution network system. There are a lot of methods for reduction power loss such as capacitor placement, distributed generation placement and electric distribution network reconfiguration (EDNR). Among these methods, the EDNR is an efficient technique to reduce power loss due to without taking any costs. However, the EDNR problem is a nonlinear, discrete problem and lots of extreme points. Therefore, it is necessary to have efficient methods for solving the EDNR problem. In this paper, an improved cuckoo search algorithm (ICSA) is proposed for solving the EDNR problem. In which, based on disadvantages of exploration and exploitation process of cuckoo search algorithm (CSA) for solving the EDNR problem, a local search mechanism is added to exploit candidate solutions existing around the current best solution. The calculated results on the simple distribution networks to complex distribution networks show that ICSA has ability for finding the global optimal solution with much smaller iterations and better quality of obtained solution compared with CSA and some other improved versions of CSA. The performance comparisons with other existing methods available in previous studies and the software of Power System Simulator/Advanced Distribution Engineering Productivity Tool (PSS/ADEPT) also lead to the better electric distribution network configuration with smaller total power losses. As a result, ICSA is a potential and reliable method for solving the EDNR problems.     

Semirigid inclusions in elastic bodies: Mechanical interplay and optimal control

The paper concerns an analysis of an equilibrium problem for 2D elastic body with two semirigid inclusions. It is assumed that inclusions have a joint point, and we investigate a junction problem for these inclusions. The existence of solutions is proved, and different equivalent formulations of the problem are proposed. We investigate a convergence to infinity of a rigidity parameter of the semirigid inclusion. It is proved that in the limit, we obtain an equilibrium problem for the elastic body with a rigid inclusion and a semirigid one. A parameter identification problem is investigated. In particular, the existence of a solution to a suitable optimal control problem is proved.     

Numerical analysis of history-dependent hemivariational inequalities and applications to viscoelastic contact problems with normal penetration

In this paper numerical approximation of history-dependent hemivariational inequalities with constraint is considered, and corresponding Céa’s type inequality is derived for error estimate. For a viscoelastic contact problem with normal penetration, an optimal order error estimate is obtained for the linear element method. A numerical experiment for the contact problem is reported which provides numerical evidence of the convergence order predicted by the theoretical analysis.