On the Newtonian Anisotropic Configurations

In this paper we are concerned with the effects of anisotropic pressure on the boundary conditions of anisotropic Lane-Emden equation and homology theorem. Some new exact solutions of this equation are derived. Then some of the theorems governing the Newtonian perfect fluid star are extended taking the anisotropic pressure into account

Design of Adiabatic MTJ-CMOS Hybrid Circuits

Low-power designs are a necessity with the increasing demand of portable devices which are battery operated. In many of such devices the operational speed is not as important as battery life. Logic-in-memory structures using nano-devices and adiabatic designs are two methods to reduce the static and dynamic power consumption respectively. Magnetic tunnel junction (MTJ) is an emerging technology which has many advantages when used in logic-in-memory structures in conjunction with CMOS. In this paper, we introduce a novel adiabatic hybrid MTJ/CMOS structure which is used to design AND/NAND, XOR/XNOR and 1-bit full adder circuits. We simulate the designs using HSPICE with 32nm CMOS technology and compared it with a non-adiabatic hybrid MTJ/CMOS circuits. The proposed adiabatic MTJ/CMOS full adder design has more than 7 times lower power consumtion compared to the previous MTJ/CMOS full adder

Designing Precoding and Receive Matrices for Interference Alignment in MIMO Interference Channels

Interference is a key bottleneck in wireless communication systems. Interference alignment is a management technique that align interference from other transmitters in the least possibly dimension subspace at each receiver and provides the remaining dimensions for free interference signal. An uncoordinated interference is an example of interference which cannot be aligned coordinately with interference from coordinated part; consequently, the performance of interference alignment approaches are degraded. In this paper, we propose a rank minimization method to enhance the performance of interference alignment in the presence of uncoordinated interference sources. Firstly, to obtain higher multiplexing gain, a new rank minimization based optimization problem is proposed; then, a new class of convex relaxation is introduced which can reduce the optimal value of the problem and obtain lower rank solutions by expanding the feasibility set. Simulation results show that our proposed method can obtain considerably higher multiplexing gain and sum rate than other approaches in the interference alignment framework

Improving Indoor Localization Using Mobile UWB Sensor and Deep Neural Networks

Accurate localization in indoor environments with ultra-wideband (UWB) technology has long attracted much attention. However, due to the presence of multipath components or non-line of sight (NLOS) propagation of the radio signals, it has been converted to a critical challenge. Existing solutions use many fixed anchors in the indoor environment. Particularly, large areas require many anchor points and in the case of unexpected events that lead to the destruction of existing infrastructures, the fixed anchor points cannot be used. In this paper, a novel localization framework based on the transmitting signal from a mobile UWB sensor on the outside of the building and its received signal regarding the modified Saleh Valenzuela (SV) channel model is presented. After preprocessing the received signals, two new procedures to reduce the ranging error caused by multipath components are proposed. In the first procedure, two machine learning algorithms including multi-layer perceptron (MLP) and support vector machine (SVM) using the extracted features from the received UWB signal time and power vectors are implemented. Moreover, in the second procedure, two deep learning algorithms including MLP and convolutional neural networks (CNNs) using the received UWB signal time and power vectors are implemented to improve the performance of the indoor localization system. The simulation results show that the architecture designed for the convolutional neural network based on the hybrid dataset (the combination of the dataset related to received UWB signal time and power vectors) provides a mean absolute error (MAE) of about 3 cm

Evaluation and Determination of the Appropriate Method for Assessing Optimum Utilisation Rate of \u3cem\u3eEurotia Ceratoides\u3c/em\u3e in Upland Grasslands of Iran

Determination of optimum utilisation rate for different range species is an important factor in assessing range grazing capacity. The vast rangelands in Iran with diverse vegetation types require an accurate, economic and quick method to determine the optimum utilisation rate for different range species. This experiment was conducted to determine the most appropriate method to determine the optimum utilisation rate for Eurotia ceratoides, which is one of the important grass species in upland grasslands in Iran

Did female prisoners with mental disorders receive psychiatric treatment before imprisonment?

© 2015 Mundt et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.BackgroundThroughout the world, high prevalence rates of mental disorders have been found in prison populations, especially in females. It has been suggested that these populations do not access psychiatric treatment. The aim of this study was to establish rates of psychiatric in- and outpatient treatments prior to imprisonment in female prisoners and to explore reasons for discontinuation of such treatments.Methods150 consecutively admitted female prisoners were interviewed in Berlin, Germany. Socio-demographic characteristics, mental disorders, and previous psychiatric in- and outpatient treatments were assessed by trained researchers. Open questions were used to explore reasons for ending previous psychiatric treatment.ResultsA vast majority of 99 prisoners (66%; 95% CI: 58¿73) of the total sample reported that they had previously been in psychiatric treatment, 80 (53%; 95 CI: 45¿61) in inpatient treatment, 62 (41%; 95 CI: 34¿49) in outpatient treatment and 42 (29%; 21¿39) in both in- and outpatient treatments. All prisoners with psychosis and 72% of the ones with any lifetime mental health disorder had been in previous treatment. The number of inpatient treatments and imprisonments were positively correlated (rho¿=¿0.27; p¿<¿0.01). Inpatient treatment was described as successfully completed by 56% (N¿=¿41) of those having given reasons for ending such treatment, whilst various reasons were reported for prematurely ending outpatient treatments.ConclusionThe data do not support the notion of a general `mental health treatment gap¿ in female prisoners. Although inpatient care is often successfully completed, repeated inpatient treatments are not linked with fewer imprisonments. Improved transition from inpatient to outpatient treatment and services that engage female prisoners to sustained outpatient treatments are needed