Optimal teleportation via thermal entangled states of a two-qubit Heisenberg chain

We study the optimal teleportation based on Bell measurements via the thermal states of a two-qubit Heisenberg XXX chain in the presence of the Dzyaloshinsky-Moriya (DM) anisotropic antisymmetric interaction and obtain an optimal unitary transformation. The explicit expressions of the output state and the teleportation fidelity are presented and compared with those of the standard protocol. It is shown that in this protocol the teleportation fidelity is always larger and the unit fidelity is achieved at zero temperature. The DM interaction can enhance the teleportation fidelity at finite temperatures, as opposed to the effect of the interaction in the standard protocol. Cases with other types of anisotropies are also discussed. Copyright (C) EPLA, 2009

A probabilistic model for fatigue crack propagation analysis

A simple probabilistic model for predicting crack growth behavior under random loading is presented. In the model, the parameters c and m in the Paris-Erdogan Equation are taken as random variables, and their stochastic characteristic values are obtained through fatigue crack propagation tests on an offshore structural steel under constant amplitude loading. Furthermore, by using the Monte Carlo simulation technique, the fatigue crack propagation life to reach a given crack length is predicted. The tests are conducted to verify the applicability of the theoretical prediction of the fatigue crack propagation.

Probabilistic Modeling of Rosette Formation

英文摘要: Rosetting, or forming a cell aggregate between a single target nucleated cell and a number of red blood cells (RBCs), is a simple assay for cell adhesion-mediated by specific receptor-ligand interaction. For example, rosette formation between sheep RBC and human lymphocytes has been used to differentiate T cells from B cells. Rosetting assay is commonly used to determine the interaction of Fc gamma-receptors (Fc gamma R) expressed on inflammatory cells and IgG-coated on RBCs. Despite its wide use in measuring cell adhesion, the biophysical parameters of rosette formation have not been well characterized. Here we developed a probabilistic model to describe the distribution of rosette sizes, which is Poissonian. The average rosette size is predicted to be proportional to the apparent two-dimensional binding affinity of the interacting receptor-ligand pair and their site densities. The model has been supported by experiments of rosettes mediated by four molecular interactions: Fc gamma RIII interacting with IgG, T cell receptor and coreceptor CD8 interacting with antigen peptide presented by major histocompatibility molecule, P-selectin interacting with P-selectin glycoprotein ligand 1 (PSGL-1), and L-selectin interacting with PSGL-1. The latter two are structurally similar and are different from the former two. Fitting the model to data enabled us to evaluate the apparent effective two-dimensional binding affinity of the interacting molecular pairs: 7.19x10(-5) mu m(4) for Fc gamma RIII-IgG interaction, 4.66x10(-3) mu m(4) for P-selectin-PSGL-1 interaction, and 0.94x10(-3) mu m(4) for L-selectin-PSGL-1 interaction. These results elucidate the biophysical mechanism of rosette formation and enable it to become a semiquantitative assay that relates the rosette size to the effective affinity for receptor-ligand binding.

Quantum teleportation via a two-qubit Heisenberg XXZ chain - effects of anisotropy and magnetic field

We study quantum teleportation via a two-qubit Heisenberg XXZ, chain under an inhomogeneous magnetic field. We first consider entanglement teleportation, and then focus on the teleportation fidelity under different conditions. The effects of anisotropy and the magnetic field, both uniform and inhomogeneous, are discussed. We also find that, though entanglement teleportation does require an entangled quantum channel, a nonzero critical value of minimum entanglement is not always necessary.

achieving on-time delivery: a two-stage probabilistic scheduling strategy for software projects

Chinese Academy of Sciences (ISCAS)

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Probabilistic modelling of soil moisture dynamics of irrigated cropland in the North China Plain

A probabilistic soil moisture dynamic model is used to estimate the soil moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic soil moisture dynamic model. Results showed that the model was able to capture the soil moisture dynamics and estimate long-term water balance reasonably well when little soil water deficit existed. The prediction of mean plant water stress during winter wheat and maize growing season quantified the suitability of the wheat-maize rotation to the soil and climate environmental conditions in North China Plain under the impact of irrigation. Under the impact of precipitation fluctuations, there is no significant bimodality of the average soil moisture probability density function.

General expression for probabilistic estimation of multiphase structure invariants in the case of a native protein and multiple derivatives. Application to estimates of the three-phase structure invariants

Concise probabilistic formulae with definite crystallographic implications are obtained from the distribution for eight three-phase structure invariants (3PSIs) in the case of a native protein and a heavy-atom derivative [Hauptman (1982). Acta Cryst. A38, 289-294] and from the distribution for 27 3PSIs in the case of a native and two derivatives [Fortier, Weeks & Hauptman (1984). Acta Cryst. A40, 646-651]. The main results of the probabilistic formulae for the four-phase structure invariants are presented and compared with those for the 3PSIs. The analysis directly leads to a general formula of probabilistic estimation for the n-phase structure invariants in the case of a native and m derivatives. The factors affecting the estimated accuracy of the 3PSIs are examined using the diffraction data from a moderate-sized protein. A method to estimate a set of the large-modulus invariants, each corresponding to one of the eight 3PSIs, that has the largest \Delta\ values and relatively large structure-factor moduli between the native and derivative is suggested, which remarkably improves the accuracy, and thus a phasing procedure making full use of all eight 3PSIs is proposed.

Probabilistic distribution of one-phase structure seminvariants for an isomorphous pair of structures: Theoretical basis and initial applications

Given a special type of triplet of reciprocal-lattice vectors in the monoclinic and orthorhombic systems, there exist eight three-phase structure seminvariants (3PSSs) for a pair of isomorphous structures. The first neighborhood of each of these 3PSSs is defined by the six magnitudes and the joint probability distribution of the corresponding six structure factors is derived according to Hauptman's neighborhood principle. This distribution leads to the conditional probability distribution of each of the 3PSSs, assuming as known the six magnitudes in its first neighborhood. The conditional probability distributions can be directly used to yield the reliable estimates (0 or pi) of the one-phase structure seminvariants (1PSSs) in the favorable case that the variances of the distributions happen to be small [Hauptman (1975). Acta Cryst. A31, 680-687]. The relevant parameters in the formulas for the monoclinic and orthorhombic systems are given in a tabular form. The applications suggest that the method is efficient for estimating the 1PSSs with values of 0 or pi.

PROBABILISTIC ESTIMATION OF THE STRUCTURE SEMINVARIANTS IN THE MONOCLINIC AND ORTHORHOMBIC SYSTEMS WHEN ANOMALOUS SCATTERERS ARE PRESENT

The estimate formulas for the two-phase structure seminvariants (TPSSs) in the presence of anomalous scattering are obtained from the estimate of the two-phase structure invariants [Hauptman (1982). Acta Cryst. A38, 632-641; Giacovazzo (1983). Acta Cryst.

A nonlinear model for assessing multiple probabilistic risks: A case study in South five-island of Changdao National Nature Reserve in China

Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors. (C) 2006 Elsevier Ltd. All rights reserved.

Two-Dimensional Kinetics Of Beta(2)-Integrin And Icam-1 Bindings Between Neutrophils And Melanoma Cells In A Shear Flow

Cell adhesion, mediated by specific receptor-ligand interactions, plays an important role in biological processes such as tumor metastasis and inflammatory cascade. For example, interactions between beta(2)-integrin ( lymphocyte function-associated antigen-1 and/or Mac-1) on polymorphonuclear neutrophils (PMNs) and ICAM-1 on melanoma cells initiate the bindings of melanoma cells to PMNs within the tumor microenvironment in blood flow, which in turn activate PMN-melanoma cell aggregation in a near-wall region of the vascular endothelium, therefore enhancing subsequent extravasation of melanoma cells in the microcirculations. Kinetics of integrin-ligand bindings in a shear flow is the determinant of such a process, which has not been well understood. In the present study, interactions of PMNs with WM9 melanoma cells were investigated to quantify the kinetics of beta(2)-integrin and ICAM-1 bindings using a cone-plate viscometer that generates a linear shear flow combined with a two-color flow cytometry technique. Aggregation fractions exhibited a transition phase where it first increased before 60 s and then decreased with shear durations. Melanoma-PMN aggregation was also found to be inversely correlated with the shear rate. A previously developed probabilistic model was modified to predict the time dependence of aggregation fractions at different shear rates and medium viscosities. Kinetic parameters of beta(2)-integrin and ICAM-1 bindings were obtained by individual or global fittings, which were comparable to respectively published values. These findings provide new quantitative understanding of the biophysical basis of leukocyte-tumor cell interactions mediated by specific receptor-ligand interactions under shear flow conditions.

Beam splitter entangler for light fields

We propose an experimentally feasible scheme to generate various types of entangled states of light fields by using beam splitters and single-photon detectors. Two beams of light fields are incident on two beam splitters respectively with each beam being asymmetrically split into two parts in which one part is supposed to be so weak that it contains at most one photon. We let the two weak output modes interfere at a third beam splitter. A conditional joint measurement on both weak output modes may result in an entanglement between the other two output modes. The conditions for the maximal entanglement are discussed based on the concurrence. Several specific examples are also examined.