Spin correlations for an Anderson impurity in conventional and unconventional superconductors

We present a theoretical study of the spin-spin correlation functionC(r) in a superconductor, whereC(r) = S · s(r);S is an impurity spin operator, ands(r) is the conduction electron spin density operator. We model the impurity using the Anderson Hamiltonian, and use the U , 1/N expansion to do the calculations. In addition to conventional superconductors, we consider unconventional superconductors, in which the order parameter (k) has a lower rotational symmetry, and has vanishing angular average. Of particular interest is the way that the behavior ofC(r) reflects two length scales, the Kondo length _k and the superconducting coherence length, ₀, and the way that its behavior is affected by the angular dependence of unconventional gaps.     

Surface modification of polyetherurethaneureas and their antithrombogenicity

Polyetherurethaneurea (PU) films were treated by oxygen plasma discharge followed by acrylic acid (AA) grafting. The carboxyl groups of the AA-grafted PU (PU-AA) surface were coupled with bovine serum albumin and heparin via water soluble carbodiimide. Surface characterization of the modified PUs was carried out by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and electron spectroscopy for chemical analysis (ESCA). The amount of immobilized albumin and heparin on the PU surface was 1.8 and 1.5 g/cm², respectively, as determined by the dye interaction method. Interactions between the surface-modified PUs and blood components such as plasma proteins and platelets were investigated to evaluate the blood compatibility of the samples. Plasma recalcification time (PRT) and activated partial thromboplastin time (APTT) of the albumin-immobilized PU (PU-Al) were almost the same as those of PU, while platelets were less adhered on the PU-Al than on PU. On the other hand, PRT and APTT of the PU-He were significantly longer than those of the PU, PU-AA, and PU-Al. Moreover, adhesion of platelets was effectively suppressed on the PU-He, leading to good in vitro blood compatibility.     

A study of a new data association and track initiation method with normalized distance squared ordering

In an underwater environment, measurements regarding true targets and false targets (clutter) can be made. Therefore, a suitable data association method to exactly detect and track a target and an efficient track initiation method for judging tracks formed by the target should be selected in this environment. This paper attempts to propose a new data association method and track initiation method to detect and track targets more effectively. Also, the performance of the new method is tested in a series of Monte Carlo simulation runs and is compared with the existing data association and track initiation methods in a cluttered environment.     

数据中心安全管理的创新构想

与运动员都渴望追求好成绩一样,人们都期待数据中心能够实现高性能运转。然而,无论在什么时候,实现成功都需要遵循一个既有的过程：目标设定、设计、规划、培训、执行和维护,这些都是必要的步骤。勾画成功的蓝图是实现预期结果的重要部分,但如果没有有效的措施加以支持,     

Betweenness parameterized above tight lower bound

We study ordinal embedding relaxations in the realm of parameterized complexity. We prove the existence of a quadratic kernel for the Betweenness problem parameterized above its tight lower bound, which is stated as follows. For a set V of variables and set C of constraints “vi is between vj and vk”, decide whether there is a bijection from V to the set {1,…,|V|} satisfying at least |C|/3+κ of the constraints in C. Our result solves an open problem attributed to Benny Chor in Niedermeier's monograph “Invitation to Fixed-Parameter Algorithms”. The betweenness problem is of interest in molecular biology. An approach developed in this paper can be used to determine parameterized complexity of a number of other optimization problems on permutations parameterized above or below tight bounds.     

Memory effects of all‐solution‐processed oxide thin‐film transistors using ZnO nanoparticles

Abstract— Non‐volatile memory effects of an all‐solution‐processed oxide thin‐film transistor (TFT) with ZnO nanoparticles (NPs) as the charge‐trapping layer are reported. The device was fabricated by using a soluble MgInZnO active channel on a ZrHfO^x gate dielectric. ZnO NPs were used as the charge‐trapping site at the gate‐insulator—channel interface, and Al was used for source and drain electrodes. Transfer characteristics of the device showed a large clockwise hysteresis, which can be used to demonstrate its memory function due to electron trapping in the ZnO NP charge‐trapping layer. This memory effect has the potential to be utilized as a memory application on displays and disposable electronics.     

Modeling,simulation, and practice of floor control for synchronous and ubiquitous collaboration

Floor control refers to the need for coordinating activities occurred in synchronously cooperating applications shared among collaborators. We address this for ubiquitous collaboration—the capability of multiple users to link together with disparate access device anytime and anywhere. Floor control has been studied for years but most researchers focus on relaxed coordination mechanisms with stationary devices that allow updates by any user on any object and resolve the uncoordinated updates. In this paper we present a floor control mechanism, called XGSP-Floor, which implements a coordination mechanism at application level for enabling users to consistently share the same resource in real time (synchronous collaboration) in ubiquitous collaboration environment. The implementation platform on cell phone devices may not be new. But we believe the implementation and experiment for XGSP-Floor on cell phone devices is a new challenge in ubiquitous collaboration environment even though the coordination mechanism can intuitively impose a tremendous overhead in worst case. We also describe the results of the modeling of XGSP-Floor and formal verification to prove the correctness of the modeling using Colored Petri Nets. We describe lessons learned and discuss future work.     

The effect of the aspect ratio on the hydrophobicity of microstructured polydimethylsiloxane (PDMS) robust surfaces

In this study, we have designed and fabricated robust hydrophobic surfaces that are composed of various micropillar arrays and investigated the effect of the aspect ratio (feature height/feature size) of the micropillar on the wettability of the fabricated surfaces. The robust, micropillar-arrayed surfaces were designed to yield the same Wenzel and Cassie water contact angles (CAs). According to our design rule, one can achieve an enhanced hydrophobic surface by increasing the height of the micropillars. The designed hydrophobic surfaces were fabricated by polydimethylsiloxane (PDMS) replica molding with photolithographically micropatterned SU-8 masters. The hydrophobicity properties of the fabricated PDMS surfaces were fully characterized theoretically and experimentally. From the theoretical and experimental results, it was found that the micropillars of an intrinsically hydrophobic material with a high aspect ratio enhance the hydrophobicity of the surface by increasing the surface roughness (in view of the Wenzel state) and the opportunities for the entrapment of air beneath a water droplet (the Cassie state).     

Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

A scanning electron microscope (SEM) is a sophisticated equipment employed for fine imaging of a variety of surfaces. In this study, prediction models of SEM were constructed by using a generalized regression neural network (GRNN) and genetic algorithm (GA). The SEM components examined include condenser lens 1 and 2 and objective lens (coarse and fine) referred to as CL1, CL2, OL-Coarse, and OL-Fine. For a systematic modeling of SEM resolution (R), a face-centered Box–Wilson experiment was conducted. Two sets of data were collected with or without the adjustment of magnification. Root-mean-squared prediction error of optimized GRNN models are GA 0.481 and 1.96×10^-12 for non-adjusted and adjusted data, respectively. The optimized models demonstrated a much improved prediction over statistical regression models. The optimized models were used to optimize parameters particularly under best tuned SEM environment. For the variations in CL2 and OL-Coarse, the highest R could be achieved at all conditions except a larger CL2 either at smaller or larger OL-Coarse. For the variations in CL1 and CL2, the highest R was obtained at all conditions but larger CL2 and smaller CL1.