710 research outputs found
Contact angle of spherical drops inside a smooth and homogeneous cylindrical capillary with hemispherical head
To investigate the wettability of spherical drops in a smooth and homogeneous cylindrical capillary with hemispherical head, based on Gibbs’s method of dividing surface and Rusanov’s concept of dividing line, the contact angle of spherical droplets has been successfully derived considering the effects of the line tension. Additionally, under the condition of ignoring the line tension, the equation describing the contact angle is simplified as the classical Young equation
The valley filter efficiency of monolayer graphene and bilayer graphene line defect model
In addition to electron charge and spin, novel materials host another degree
of freedom, the valley. For a junction composed of valley filter sandwiched by
two normal terminals, we focus on the valley efficiency under disorder with two
valley filter models based on monolayer and bilayer graphene. Applying the
transfer matrix method, valley resolved transmission coefficients are obtained.
We find that: i) under weak disorder, when the line defect length is over about
, it functions as a perfect channel (quantized conductance) and
valley filter (totally polarized); ii) in the diffusive regime, combination
effects of backscattering and bulk states assisted intervalley transmission
enhance the conductance and suppress the valley polarization; iii) for very
long line defect, though the conductance is small, polarization is indifferent
to length. Under perpendicular magnetics field, the characters of charge and
valley transport are only slightly affected. Finally we discuss the efficiency
of transport valley polarized current in a hybrid system.Comment: 6 figure
Online Regularization for High-Dimensional Dynamic Pricing Algorithms
We propose a novel \textit{online regularization} scheme for
revenue-maximization in high-dimensional dynamic pricing algorithms. The online
regularization scheme equips the proposed optimistic online regularized maximum
likelihood pricing (\texttt{OORMLP}) algorithm with three major advantages:
encode market noise knowledge into pricing process optimism; empower online
statistical learning with always-validity over all decision points; envelop
prediction error process with time-uniform non-asymptotic oracle inequalities.
This type of non-asymptotic inference results allows us to design safer and
more robust dynamic pricing algorithms in practice. In theory, the proposed
\texttt{OORMLP} algorithm exploits the sparsity structure of high-dimensional
models and obtains a logarithmic regret in a decision horizon. These
theoretical advances are made possible by proposing an optimistic online LASSO
procedure that resolves dynamic pricing problems at the \textit{process} level,
based on a novel use of non-asymptotic martingale concentration. In
experiments, we evaluate \texttt{OORMLP} in different synthetic pricing problem
settings and observe that \texttt{OORMLP} performs better than \texttt{RMLP}
proposed in \cite{javanmard2019dynamic}
(2′-Amino-4,4′-bi-1,3-thiazol-2-aminium-κ2 N,N′)aqua[citrato(4−)-κ3 O,O′,O′′)chromium(III) dihydrate
In the title compound, [Cr(C6H7N4S2)(C6H4O7)(H2O)]·2H2O, the CrIII atom is in a distorted octahedral environment, coordinated by one water molecule, two N atoms from a protonated diaminobithiazole ligand and three O atoms from a citrate(4−) anion. The complex is zwitterionic, with the H atom from the uncoordinated carboxylate group of the citrate anion transferred to one amino group of the diaminobithiazole ligand. O—H⋯O and N—H⋯O hydrogen bonds link the complexes into layers including the two uncoordinated water molecules
Research on Wavelet Based Autofocus Evaluation in Micro-vision
AbstractThis paper presents the construction of two kinds of focusing measure operators defined in wavelet domain. One mechanism is that the Discrete Wavelet Transform (DWT) coefficients in high frequency subbands of in-focused image are higher than those of defocused one. The other mechanism is that the autocorrelation of an in-focused image filtered through Continuous Wavelet Transform (CWT) gives a sharper profile than blurred one does. Wavelet base, scaling factor and form to get the sum of high frequency energy are the key factors in constructing the operator. Two new focus measure operators are defined through the autofocusing experiments on the micro-vision system of the workcell for micro-alignment. The performances of two operators can be quantificationally evaluated through the comparison with two spatial domain operators Brenner Function (BF) and Squared Gradient Function (SGF). The focus resolution of the optimized DWT-based operators is 14% higher than that of BF and its computational cost is 52% approximately lower than BF's. The focus resolution of the optimized CWT-based operators is 41% lower than that of SGF whereas its computational cost is approximately 36% lower than SGF's. It shows that the wavelet based autofocus measure functions can be practically used in micro-vision applications
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