Ordered mesoporous Pd/SnO2 synthesized by a nanocasting route for high hydrogen sensing performance

Ordered mesoporous SnO₂ and mesoporous Pd/SnO₂ have been successfully synthesized via nanocasting method using the hexagonal mesoporous SBA-15 as template. Two different procedures, impregnation technique and direct synthesis, were utilized for the doping of Pd in the mesoporous SnO₂. The results of small angle X-ray diffraction (SAXD), nitrogen adsorption–desorption and transmission electron microscopy (TEM) demonstrate that the SnO₂ and Pd/SnO₂ display ordered mesoporous structures and high surface areas. Wide angle X-ray diffraction (WAXD) and X-ray photoelectron spectroscopy (XPS) reveal tetragonal structure of SnO₂ and the existence of Pd element. The sensing properties of mesoporous SnO₂ and mesoporous Pd/SnO₂ for H₂ were detected. The sensor utilizing mesoporous Pd/SnO₂ via direct synthesis method exhibits excellent response and recovery behavior and much higher sensitivity to H₂, compared to those using mesoporous SnO₂ and mesoporous Pd/SnO₂ via impregnation technique. It is believed that its high gas sensing performance is derived from the large surface area, high activity and well dispersion of Pd additive, as well as high porosity, which lead to highly effective surface interaction between the target gas molecules and the surface active sites.     

Illumination robust single sample face recognition based on ESRC

Multimedia Tools and Applications - The extended sparse representation classifier (ESRC) is one of the state-of-the-art solutions for single sample face recognition, but it performs...     

Refined entanglement concentration for electron-spin entangled cluster states with quantum-dot spins in optical microcavities

We present a refined entanglement concentration protocol (ECP) for an arbitrary unknown less-entangled four-electron-spin cluster state by exploring the optical selection rules derived from the quantum-dot spins in one-sided optical microcavities. In our ECP, the parties obtain not only the four-electron-spin systems in the partial entanglement with two unknown parameters, but also the less-entangled two-electron-spin systems in the first step. Utilizing the above preserved systems as the resource for the second step of our ECP, the parties can obtain a standard cluster state by keeping the robust odd-parity instances with two parity-check gates. Meanwhile, the systems in the rest three instances can be used as the resource in the next round of our ECP. The success probability of our ECP is largely increased by iteration of the ECP process. Moreover, all the coefficients of our ECP are unknown for the parties without assistance of extra single electron-spin, so our ECP maybe has good applications in quantum communication network in the future.     

Stability radius of implicit dynamic equations with constant coefficients on time scales

This paper deals with the stability radii of implicit dynamic equations on time scales when the structured perturbations act on both the coefficient of derivative and the right-hand side. Formulas of the stability radii are derived as a unification and generalization of some previous results. A special case where the real stability radius and the complex stability radius are equal is studied. Examples are derived to illustrate results.     

单件小批量生产排产逆序递推法应用研究

针对单件小批量型生产企业,为了保证交货期和控制原材料、在制品库存,提出一种生产排产算法--逆序递推算法.本文在算法中考虑到了生产扰动对交货期的影响,并结合实例作出逆序递推排产甘特图来指导生产.     

3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor beta (TRbeta), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q(2) (cross-validated) values 0.600 and 0.616 and non-cross-validated r(2) values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)(2)) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRbeta. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor beta but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.     

Symbolic gray code as a multikey hashing function

In this paper, we extend the binary Gray code to symbolic Gray code. We then show that this symbolic Gray code can be used as a multikey hashing function for storing symbolic records. The record stored at location k and the record stored at location k + 1 will be nearest neighbors if this hashing function is used. Thus, this symbolic Gray code hashing function exhibits some kind of clustering property which will group similar records together. This property is a desirable property for designing nearest neighbor searching (also called best match searching) systems. There are many other interesting properties of this hashing function. For instance, there exists an address-to-key transformation which can be used to determine the record stored at certain location k if this hashing function is used. Besides, if there are totally M records, we only have to reserve exactly M locations; there are no collisions and wasting of memory storage. At the end of this paper, it is shown that the resulting file exhibits the multiple-attribute tree structure.     

An adaptive model-free resource and power management approach for multi-tier cloud environments

With the development of cloud environments serving as a unified infrastructure, the resource management and energy consumption issues become more important in the operations of such systems. In this paper, we investigate adaptive model-free approaches for resource allocation and energy management under time-varying workloads and heterogeneous multi-tier applications. Specifically, we make use of measurable metrics, including throughput, rejection amount, queuing state, and so on, to design resource adjustment schemes and to make control decisions adaptively. The ultimate objective is to guarantee the summarized revenue of the resource provider while saving energy and operational costs. To validate the effectiveness, performance evaluation experiments are performed in a simulated environment, with realistic workloads considered. Results show that with the combination of long-term adaptation and short-term adaptation, the fluctuation of unpredictable workloads can be captured, and thus the total revenue can be preserved while balancing the power consumption as needed. Furthermore, the proposed approach can achieve better effect and efficiency than the model-based approaches in dealing with real-world workloads.