A novel self consistent calculation approach for the capacitance-voltage characteristics of semiconductor quantum wire transistors based on a split-gate configuration

Purpose - The purpose of this paper is to develop an efficient numerical algorithm for the self-consistent solution of Schrodinger and Poisson equations in one-dimensional systems. The goal is to compute the charge-control and capacitance-voltage characteristics of quantum wire transistors. Design/methodology/approach - The paper presents a numerical formulation employing a non-uniform finite difference discretization scheme, in which the wavefunctions and electronic energy levels are obtained by solving the Schrodinger equation through the split-operator method while a relaxation method in the FTCS scheme ("Forward Time Centered Space") is used to solve the two-dimensional Poisson equation. Findings - The numerical model is validated by taking previously published results as a benchmark and then applying them to yield the charge-control characteristics and the capacitance-voltage relationship for a split-gate quantum wire device. Originality/value - The paper helps to fulfill the need for C-V models of quantum wire device. To do so, the authors implemented a straightforward calculation method for the two-dimensional electronic carrier density n(x,y). The formulation reduces the computational procedure to a much simpler problem, similar to the one-dimensional quantization case, significantly diminishing running time.

Monitoring Drug Use Among HIV/AIDS Patients in Brazil: Should we Combine Self-Report and Urinalysis?

Illicit drug use in HIV-infected patients can be linked to impairment of physical and mental health, low health-related quality of life, and suboptimal adherence to HIV treatment. This study aimed to evaluate the correlation of self-report illicit drug use, urinalysis for cocaine and cannabis metabolites, and severity of dependence among HIV-infected patients on antiretroviral therapy (ART) in a treatment center in Brazil. Four hundred and thirty-eight outpatients of an HIV referral center were interviewed and assessed for drug use (lifetime, last year and last month). Urinalysis was performed to detect the presence of cocaine and cannabis metabolites in urine samples. Overall agreement between self-report and urinalysis was almost 68% for cannabis and higher than 85% for cocaine. Positive urinalysis was significantly associated with more than once a week cannabis (p < .0001) and cocaine (p <.0001) use during the last-month. Severity of Dependence Scale (SDS) properly predicted positive cocaine urinalysis results (area under the curve [AUC] = .81, p = .0001). Frequency of cannabis and cocaine use, SDS score degree and positive urinalysis for both drugs were correlated. Our findings suggest that positive self-report is a reliable predictor of positive urine sample both for cannabis and cocaine, but since the agreement was not perfect, there is a role for urine drug screening in the care of patients with HIV-related conditions.

Self-potential signals from an analog biogeobattery mode

A tank experiment was conducted to check if self-potential (SP) signals can be generated when buried organic matter is wire-connected to a near-surface, oxygen-rich, sediment layer. This experiment demonstrated that once wired, there was a flux of electrons (hence an electric current) between the lower and upper layers of the sandbox with the system responding as a large-scale microbial fuel cell (a type of bioelectrochemical system). An electric current was generated by this process in the wire and the SP method was used to monitor the associated electric potential distribution at the top of the tank.. The electric field was controlled by the flux of electrons through the wire, the oxidation of the organic matter, the reduction of oxygen used as a terminal electron acceptor, and the distribution of the DC resistivity in the tank. The current density through the wire was limited by the availability of oxygen and not by the oxidation of the organic matter. This laboratory experiment incorporated key elements of the biogeobattery observed in some organic-rich contaminant plumes. This analogy includes the generation of SP signals associated with a flux of electrons, the capacity of buried organic matter in sustaining anodic reactions, network resistance connecting terminal redox reactions spatially separated in space, and the existence of anodic secondary coupled reactions. A resistivity tomogram of the tank, after almost a year in operation, suggests that oxidative processes triggered by this geobattery can be imaged with this method to determine the radius of influence of the bioelectrochemical system.

Texture descriptor based on partially self-avoiding deterministic walker on networks

Texture image analysis is an important field of investigation that has attracted the attention from computer vision community in the last decades. In this paper, a novel approach for texture image analysis is proposed by using a combination of graph theory and partially self-avoiding deterministic walks. From the image, we build a regular graph where each vertex represents a pixel and it is connected to neighboring pixels (pixels whose spatial distance is less than a given radius). Transformations on the regular graph are applied to emphasize different image features. To characterize the transformed graphs, partially self-avoiding deterministic walks are performed to compose the feature vector. Experimental results on three databases indicate that the proposed method significantly improves correct classification rate compared to the state-of-the-art, e.g. from 89.37% (original tourist walk) to 94.32% on the Brodatz database, from 84.86% (Gabor filter) to 85.07% on the Vistex database and from 92.60% (original tourist walk) to 98.00% on the plant leaves database. In view of these results, it is expected that this method could provide good results in other applications such as texture synthesis and texture segmentation. (C) 2012 Elsevier Ltd. All rights reserved.