Effect of long-range structural corrugations on magnetotransport properties of phosphorene in tilted magnetic field

Rippling is an inherent quality of two-dimensional materials playing an important role in determining their properties. Here, we study the effect of structural corrugations on the electronic and transport properties of monolayer black phosphorus (phosphorene) in the presence of tilted magnetic field. We follow a perturbative approach to obtain analytical corrections to the spectrum of Landau levels induced by a long-wavelength corrugation potential. We show that surface corrugations have a non-negligible effect on the electronic spectrum of phosphorene in tilted magnetic field. Particularly, the Landau levels are shown to exhibit deviations from the linear field dependence. The observed effect become especially pronounced at large tilt angles and corrugation amplitudes. Magnetotransport properties are further examined in the low temperature regime taking into account impurity scattering. We calculate magnetic field dependence of the longitudinal and Hall resistivities and find that the nonlinear effects reflecting the corrugation might be observed even in moderate fields (\mbox{$B<10$ T})

A New Method For Increasing the Accuracy of EM-based Channel Estimation

It was recently shown that the detection performance can be significantly improved if the statistics of channel estimation errors are available and properly used at the receiver. Although in pilot-only channel estimation it is usually straightforward to characterize the statistics of channel estimation errors, this is not the case for the class of data-aided (semi-blind) channel estimation techniques. In this paper, we focus on the widely-used data-aided channel estimation techniques based on the expectation-maximization (EM) algorithm. This is achieved by a modified formulation of the EM algorithm which provides the receiver with the statistics of the estimation errors and properly using this additional information. Simulation results show that the proposed data-aided estimator outperform its classical counterparts in terms of accuracy, without requiring additional complexity at the receiver

Many body effects on the transport properties of a doped nano device

In this article, we study the effect of electron-electron interaction in a doped nano cluster sandwich between two electrodes. The Hamiltonian of the cluster is written in the tight-binding model and electrodes are described in the wide-band approximation. The GW approximation has been used for the calculation of the exchange-correlation term in the cluster region. Our results showed that in the presence of the electronelectron interaction the transmittance gap increases and current decreases. Also, in a doped nano structure the transmission decreases and many body effect becomes more important. By considering the exchange-correlation in a doped nano cluster in the GW approximation the transmission and current decrease drastically. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2056

Depression Affects Recovery Following Distal Radius Fracture: A Latent Class Analysis

Background: Most people recover within six months following distal radius fractures (DRFs) but some experience pain and disability for one year or longer. Therefore, it is important to understand the factors that can help predict recovery. According to the biopsychosocial model of pain, psychological aspects of a condition can play important roles in explaining recovery. Objectives: To identify the recovery trajectories of patients with DRFs and to determine the degree to which depression affects these trajectories. Methods: Recovery was assessed in 318 patients using the Patient-Rated Wrist Evaluation scale at baseline, three, six, and 12 months. Demographic information was collected in addition to the Self-Administered Comorbidity Questionnaire, from which data regarding the single item pertaining to depression were extracted. Latent class analysis was used to identify the recovery trajectories. Comparisons of proportion between the emergent classes were then conducted using chi-square and Kruskal-Wallis tests. Results: The latent class analysis revealed three trajectories: rapid-recovery, slow-recovery, and non-recovery as the best fit to the data. The proportion of people that had depression was significantly greater in the non-recovery class (24%) compared to the rapid-recovery (8%) and slow-recovery classes (16%) (p Discussion: Patients who appear to be in the non-recovery class may require additional assessments, closer monitoring, supervised therapy, or other interventions to improve outcomes