Mode mixing induced by disorder in graphene PNP junction in a magnetic field

We study the electron transport through the graphene PNP junction under a magnetic field and show that modes mixing plays an essential role. By using the non-equilibrium Green's function method, the space distribution of the scattering state for a specific incident modes as well the elements of the transmission and reflection coefficient matrixes are investigated. All elements of the transmission (reflection) coefficient matrixes are very different for a perfect PNP junction, but they are same at a disordered junction due to the mode mixing. The space distribution of the scattering state for the different incident modes also exhibit the similar behaviors, that they distinctly differ from each other in the perfect junction but are almost same in the disordered junction. For a unipolar junction, when the mode number in the center region is less than that in the left and right regions, the fluctuations of the total transmission and reflection coefficients are zero, although each element has a large fluctuation. These results clearly indicate the occurrence of perfect mode mixing and it plays an essential role in a graphene PNP junction transport

Three-dimensional structures of the spatiotemporal nonlinear Schrödinger equation with power-law nonlinearity in PT-symmetric potentials

The spatiotemporal nonlinear Schrödinger equation with power-law nonlinearity in PT-symmetric potentials is investigated, and two families of analytical three-dimensional spatiotemporal structure solutions are obtained. The stability of these solutions is tested by the linear stability analysis and the direct numerical simulation. Results indicate that solutions are stable below some thresholds for the imaginary part of PT-symmetric potentials in the self-focusing medium, while they are always unstable for all parameters in the self-defocusing medium. Moreover, some dynamical properties of these solutions are discussed, such as the phase switch, power and transverse power-flow density. The span of phase switch gradually enlarges with the decrease of the competing parameter k in PT-symmetric potentials. The power and power-flow density are all positive, which implies that the power flow and exchange from the gain toward the loss domains in the PT cell.Funded by the National Natural Science Foundation of China (Grant No. 11375007), the Zhejiang Provincial Natural Science Foundation of China (Grant No. LY13F050006)

Clear Cell Renal Cell Carcinoma: Deep Learning-Based Prediction of Tumor Grade from Contrast-Enhanced CT

Tumor grading is an important prognostic parameter for renal cell carcinoma (RCC). However, current grading schemes require an invasive surgical procedure, putting patients at risks including increased risk of hemorrhage, infection, renal failure, or death. Furthermore, low grade RCC is indolent with low mortality risk and may not require treatment. Therefore, a pre-operative and non-invasive assessment of malignancy grade may be beneficial and facilitate optimal timing of treatment. In recent years, deep learning-based image analysis has gained wide popularity in cancer prognosis and prediction. The goal of this study is to investigate the feasibility and performance of a deep-learning-based model for clear cell RCC grading prediction from contrast-enhance computed tomography (CECT). After institutional review board approval, an institutional pathology database was queried for all renal biopsies between December 2002 and October 2018. All included patients received a CT with a non-contrast and at least one post-contrast series. All patients have Fuhrman grade confirmation from surgical pathology, with CT scan prior to the procedure. Tumors were manually annotated by a radiologist on either the corticomedullary or nephrographic phase CECT. Rectangular regions of interest (ROI) were drawn on each slice throughout the tumor and used as inputs to the Deep CNN ResNet50. A binary label of low grade or high grade was assigned to each patient. Sensitivity, specificity, accuracy, and AUC were calculated based on a five-fold cross-validation. Preliminary results from a small subset of data suggests that a deep learning model can be used to predict clear cell RCC grading based on CT imaging prior to surgical procedures

Detecting monopole charge in Weyl semimetals via quantum interference transport

Topological Weyl semimetals can host Weyl nodes with monopole charges in momentum space. How to detect the signature of the monopole charges in quantum transport remains a challenging topic. Here, we reveal the connection between the parity of monopole charge in topological semimetals and the quantum interference corrections to the conductivity. We show that the parity of monopole charge determines the sign of the quantum interference correction, with odd and even parity yielding the weak anti-localization and weak localization effects, respectively. This is attributed to the Berry phase difference between time-reversed trajectories circulating the Fermi sphere that encloses the monopole charges. From standard Feynman diagram calculations, we further show that the weak-field magnetoconductivity at low temperatures is proportional to $+\sqrt{B}$ in double-Weyl semimetals and $-\sqrt{B}$ in Weyl semimetals, respectively, which could be verified experimentally.Comment: published versio

Monitoring the synthesis and composition analysis of microsilica encapsulated acetylacetonatocarbonyl triphenylphosphinerhodium catalyst by inductively coupled plasma (ICP) techniques

Journal ArticleAbstract-A novel technique to monitor the synthesis process of encapsulated acetylacetonatocarbonyl triphenylphosphinerhodium within a microsilica nanoshell has been studied using inductively coupled plasma (ICP) techniques. Nanospheres sized around 50-100 nm were obtained and ICP was used to quantify the exact composition of rhodium, phosphorous, and silicon with differing digestion solvents. In addition, ICP was used to detect rhodium and phosphorous in the nano core-shell catalysts as a quality control procedure. Index Terms-Encapsulation, inductively coupled plasma (ICP), nanotechnology, Rh catalyst, silica nanoshell

Pole analysis on the hadron spectroscopy of Λb→J/ΨpK−\Lambda_b\to J/\Psi p K^-

In this paper we study the $J/\Psi p$ spectroscopy in the process of $\Lambda_b\to J/\Psi p K^-$. The final state interactions of coupled channel $J/\Psi p$ ~-~ $\bar{D} \Sigma_c$~-~$\bar{D}^{*} \Sigma_c$ are constructed based on K-matrix with the Chew-Mandelstam function. We build the $\Lambda_b\to J/\Psi p K^-$ amplitude according to the Au-Morgan-Pennington method. The event shape is fitted and the decay width of $\Lambda_b\to J/\Psi p K^-$ is used to constrain the parameters, too. With the amplitudes we extract out the poles and their residues. Our amplitude and pole analysis suggest that the $P_c(4312)$ should be $\bar{D}\Sigma_c$ molecule, the $P_c(4440)$ could be an S-wave compact pentaquark state, and the structure around $P_c(4457)$ is caused by the cusp effect. The future experimental measurement of the decays of $\Lambda_b\to \bar{D}\Sigma_c K^-$ and $\Lambda_b\to \bar{D}^*\Sigma_c K^-$ would further help to study the nature of these resonances.Comment: updated to the published versio