Abstract:
The evolution of three-dimensional, cellular convective flows in a plane horizontal layer of a Boussinesq fluid heated from below is well studied. Here we review results from the investigation of this system as well as a number of related and novel numerical findings. We present theoretical results for pattern formation in Rayleigh-B\'enard convection with solving NS equation under the Boussinesq approximation . System of equations were reduced to 2-dimension form to simplify the analysis.The evolution of the flow agree with the idea of the flow achieving an optimal form.

The effect of different types of surface preparation
with SiC abrasive paper on the shear bond strength (SBS) of superficial
bovine dentin obtained from the incisal, middle and cervical thirds were
evaluated. Dentin substrates were obtained with twenty specimens for each
locationgrit combination. Superficial dentin was exposed and prepared to 120-, 320-, or 600-grit SiC; the
dentin surfaces were treated with Optibond Solo Plus (Kerr) and polymerized
for 20 s. The specimens were
placed in a jig, filled with resin composite Z100 (3M-ESPE), polymerized for 40
s according to manufacturer’s
instructions, and stored for 24 h at 37℃ and 100% humidity. After 24 h, SBS was measured using a
loading testing machine (Ul-tradent) and expressed in megapascals. A two-way
ANOVA and Tukey test were used for data analysis. No statistically significant effect of the location (P = 0.254) or interaction
grit-location (P = 0.629) were observed on SBS. Statistically
significant effect of the grit on the SBS was detected (P < 0.001) with
320-grit being statistically different from 600-grit (P = 0.011) and 120-grit
(P < 0.001). No significant differences were observed between 600-grit and
120-grit (P = 0.413). Regardless of the location, 320-grit consistently
showed the lowest SBS indicating that different surface grit preparations have
an effect on dentin SBS values.

Abstract:
Recently, Xiao et al. proposed a nonsmooth equations-based method to solve the -norm minimization problem (2011). The advantage of this method is its simplicity and lower storage. In this paper, based on new nonsmooth equations reformulation, we investigate new nonsmooth equations-based algorithms for solving -norm minimization problems. Under mild conditions, we show that the proposed algorithms are globally convergent. The preliminary numerical results demonstrate the effectiveness of the proposed algorithms. 1. Introduction We consider the -norm minimization problem where , , , and is a nonnegative parameter. Throughout the paper, we use and to denote the Euclidean norm and the -norm of vector , respectively. Problem (1.1) has many important practical applications, particularly in compressed sensing (abbreviated as CS) [1] and image restoration [2]. It can also be viewed as a regularization technique to overcome the ill-conditioned, or even singular, nature of matrix , when trying to infer from noiseless observations or from noisy observations , where is the white Gaussian noise of variance [3–5]. The convex optimization problem (1.1) can be cast as a second-order cone programming problem and thus could be solved via interior point methods. However, in many applications, the problem is not only large scale but also involves dense matrix data, which often precludes the use and potential advantage of sophisticated interior point methods. This motivated the search of simpler first-order algorithms for solving (1.1), where the dominant computational effort is a relatively cheap matrix-vector multiplication involving and . In the past few years, several first-order algorithms have been proposed. One of the most popular algorithms falls into the iterative shrinkage/thresholding (IST) class [6, 7]. It was first designed for wavelet-based image deconvolution problems [8] and analyzed subsequently by many authors, see, for example, [9–11]. Figueiredo et al. [12] studied the gradient projection and Barzilai-Borwein method [13] (denoted by GPSR-BB) for solving (1.1). They reformulated problem (1.1) as a box-constrained quadratic program and solved it by a gradient projection and Barzilai-Borwein method. Wright et al. [14] presented sparse reconstruction algorithm (denoted by SPARSA) to solve (1.1). Yun and Toh [15] proposed a block coordinate gradient descent algorithm for solving (1.1). Yang and Zhang [16] investigated alternating direction algorithms for solving (1.1). Quite recently, Xiao et al. [17] developed a nonsmooth equations-based algorithm (called

Abstract:
We study the continuous-time mean-variance portfolio selection problem in the situation when investors must pay margin for short selling. The problem is essentially a nonlinear stochastic optimal control problem because the coefficients of positive and negative parts of control variables are different. We can not apply the results of stochastic linearquadratic (LQ) problem. Also the solution of corresponding Hamilton-Jacobi-Bellman (HJB) equation is not smooth. Li et al. (2002) studied the case when short selling is prohibited; therefore they only need to consider the positive part of control variables, whereas we need to handle both the positive part and the negative part of control variables. The main difficulty is that the positive part and the negative part are not independent. The previous results are not directly applicable. By decomposing the problem into several subproblems we figure out the solutions of HJB equation in two disjoint regions and then prove it is the viscosity solution of HJB equation. Finally we formulate solution of optimal portfolio and the efficient frontier. We also present two examples showing how different margin rates affect the optimal solutions and the efficient frontier. 1. Introduction Modern portfolio theory was introduced by Markowitz in 1952 [1, 2]. It is a theory of finance which attempts to minimize risk for a given level of expected return, by carefully choosing the proportions of various assets. In the theory variance of portfolio return was chosen as measure of the risk by Markowitz. Markowitz also established concept of the efficient frontier of the optimal portfolio: it is a curve showing the relation of the best possible expected level of return with respect to its level of risk (the standard deviation of the portfolio's return). This theory has been widely accepted both in financial industry and academy. There are lots of extensions and applications in the discrete time models [3]. Relatively there are less discussions of the mean-variance portfolio problem about continuous-time model [4–6]. In 2000, Zhou and Li [5] solved the continuous time mean-variance problem without short selling constraint by using the stochastic linear quadratic optimal control theory. Li et al. [6] in 2002 considered mean-variance portfolio selection with short selling prohibiting condition by solving HJB equation. In financial market, the potential loss on a short sale can be huge when the price of the security goes up, therefore in practice the short seller will be required to post margin or collateral to cover possible losses.

Abstract:
We study the evolution of nearest-neighbor entanglement in the one dimensional Ising model with an external transverse field. The system is initialized as the so called "thermal ground state" of the pure Ising model. We analyze properties of generation of entanglement for different regions of external transverse fields. We find that the derivation of the time at which the entanglement reaches its first maximum with respect to the reciprocal transverse field has a minimum at the critical point. This is a new indicator of quantum phase transition.

Abstract:
Aiming at the solving FJSP (Flexible job-shop scheduling problem), a scheduling algorism combined gene and tabu algorism were proposed. Firstly, the FJSP problem model was defined, then the improve gene algorism was used to obtain the solution, the chromosome was coded as double-stranded and the NEH algorism was used to get the initial solution. And the adaptive selection strategy, compound cross strategy and mutation strategy were introduced to protect the optimum chromosome and renew. When the gene algorism got the local optimum solution, the tabu algorism was used to get the global solution. The simulation experiment shows our method in this paper can resolve the FJSP effectively and get the optimal solution, compared with the other methods; the method has the rapid convergence and high solution efficiency.

Abstract:
Bi has a good modification effect on the hypoeutectic Al-Si alloy, and the morphology of eutectic Si changes from coarse acicular to fine fibrous. Based on the similarity between Mg2Si and Si phases in crystalline structure and crystallization process, the present study investigated the effects of different concentrations of Bi on the microstructure, tensile properties, and fracture behavior of cast Al-15wt.%Mg2Si in-situ metal matrix composite. The results show that the addition of the proper amount of Bi has a significant modification effect on both primary and eutectic Mg2Si in the Al-15wt.%Mg2Si composite. With an increase in Bi content from 0 to 1wt.%, the morphology of the primary Mg2Si is changed from irregular or dendritic to polyhedral shape; and its average particle size is significantly decreased from 70 to 6 μm. Moreover, the morphology of the eutectic Mg2Si phase is altered from flake-like to very short fibrous or dot-like. When the Bi addition exceeds 4.0wt.%, the primary Mg2Si becomes coarse again. However, the eutectic Mg2Si still exhibits the modified morphology. Tensile tests reveal that the Bi addition can improve the tensile strength and ductility of the material. Compared with those of the unmodified composite, the ultimate tensile strength and percentage elongation after fracture with 1.0wt.% Bi increase 51.2% and 100%, respectively. At the same time, the Bi addition changes the fracture behavior from brittle to ductile.

Abstract:
We present a joint source-channel multiple description (JSC-MD) framework for resource-constrained network communications (e.g., sensor networks), in which one or many deprived encoders communicate a Markov source against bit errors and erasure errors to many heterogeneous decoders, some powerful and some deprived. To keep the encoder complexity at minimum, the source is coded into K descriptions by a simple multiple description quantizer (MDQ) with neither entropy nor channel coding. The code diversity of MDQ and the path diversity of the network are exploited by decoders to correct transmission errors and improve coding efficiency. A key design objective is resource scalability: powerful nodes in the network can perform JSC-MD distributed estimation/decoding under the criteria of maximum a posteriori probability (MAP) or minimum mean-square error (MMSE), while primitive nodes resort to simpler MD decoding, all working with the same MDQ code. The application of JSC-MD to distributed estimation of hidden Markov models in a sensor network is demonstrated. The proposed JSC-MD MAP estimator is an algorithm of the longest path in a weighted directed acyclic graph, while the JSC-MD MMSE decoder is an extension of the well-known forward-backward algorithm to multiple descriptions. Both algorithms simultaneously exploit the source memory, the redundancy of the fixed-rate MDQ, and the inter-description correlations. They outperform the existing hard-decision MDQ decoders by large margins (up to 8dB). For Gaussian Markov sources, the complexity of JSC-MD distributed MAP sequence estimation can be made as low as that of typical single description Viterbi-type algorithms.

Abstract:
Background Numerous studies examining the relationship between Cyclooxygenase-2 (COX-2) immunoexpression and clinical outcome in osteosarcoma patients have yielded inconclusive results. Methods We accordingly conducted a meta-analysis of 9 studies (442 patients) that evaluated the correlation between COX-2 immunoexpression and clinical prognosis (death). Pooled odds ratios (OR) and risk ratios (RR) with 95% confidence intervals (95% CI) were calculated using the random-effects or fixed-effects model. Results Meta–analysis showed no significant association between COX-2 positivity and age, gender, tumor location, histology, stage, metastasis or 90% necrosis. Conversely, COX-2 immunoexpression was associated with overall survival rate (RR=2.12; 95% CI: 1.10–3.74; P=0.009) and disease-free survival rate (RR=1.63; 95% CI: 1.17–2.28; P=0.004) at 2 years. Sensitivity analysis performed by omitting low quality studies showed that the pooled results were stable. Conclusions COX-2 positivity was associated with a lower 2-year overall survival rate and disease-free survival rate. COX-2 expression change is an independent prognostic factor in patients with osteosarcoma.

Abstract:
The effect of curing age on chloride diffusion coefficient of recycled aggregate concrete subjected to different compressive stresses was investigated. A compression loading setup was both designed and fabricated. The chloride diffusion coefficients of recycled aggregate concrete under compressive stresses were measured by the rapid chloride ion migration (RCM) method. The experimental results show that the chloride diffusion coefficients of recycled aggregate concrete (RAC) under different compressive stress ratios generally decrease with the increase of curing age. For RAC subjected to the same compressive stress ratios, the chloride diffusion coefficients approximately have power functions with curing ages and the relationship models are proposed. Moreover, the influence of curing age on chloride diffusion coefficient firstly decreases and then increases as the compressive stress ratio increases.