Sharif Digital Repository

In this letter, we study a receiver architecture technique for joint resource allocation in a downlink (DL) multi-user multi-carrier non-orthogonal multiple access (MC-NOMA) network with simultaneous wireless information and power transfer (SWIPT). In this framework, the subcarrier set is partitioned into two groups that are assigned to perform information decoding (ID) and energy harvesting (EH) at the receiver side based on the optimization problem. This letter seeks to maximize energy harvesting while meeting a minimum data-rate requirement for each user. The underlying optimization problem is mixed-integer non-linear programming (MINLP). To that end, we employ the monotonic optimization... 

Purpose. Drug release from nanosystems at the sites of either absorption or effect biophase is a major determinant of its biological action. Thus, in vitro drug release is of paramount importance in gaining insight for the systems performance in vivo. Methods. A novel in vitro in vivo correlation, IVIVC, model denoted as double reciprocal area method was presented and applied to 19 drugs from 55 nano formulations with total 336 data, gathered from literature. Results. The proposed model correlated the in vitro with in vivo parameters with overall error of 12.4 ± 3.9%. Also the trained version of the model predicted the test formulations with overall error of 15.8 ± 3.7% indicating the... 

Protein aggregation in cell membrane is vital for the majority of biological functions. Recent experimental results suggest that transmembrane domains of proteins such as α-helices and β-sheets have different structural rigidities. We use molecular dynamics simulation of a coarse-grained model of protein-embedded lipid membranes to investigate the mechanisms of protein clustering. For a variety of protein concentrations, our simulations under thermal equilibrium conditions reveal that the structural rigidity of transmembrane domains dramatically affects interactions and changes the shape of the cluster. We have observed stable large aggregates even in the absence of hydrophobic mismatch,... 

The electrodynamics of Weyl semimetals is an extension of Maxwell's theory where in addition to field strength tensor Fμν, an axion field enters the theory which is parametrized by a four-vector bμ=(b0,b). In tilted Weyl materials (TWMs) an additional set of parameters ζ=(ζx,ζy,ζz) enters the theory that can be encoded into the metric of the spacetime felt by electrons in TWMs. This allows an extension of Maxwell's electrodynamics that describes electric and magnetic fields in TWMs, and tilted Dirac materials (TDMs) that correspond to bμ=0. The tilt parameter ζ appearing as an off-diagonal metric matrix element, mixing time and space components, which mingles E and B fields, whereby the... 

This paper introduces the genetic algorithm-kernel partial least square (GA-KPLS), as a novel nonlinear feature selection method. This technique combines genetic algorithms (GAs) as powerful optimization methods with KPLS as a robust nonlinear statistical method for variable selection. This feature selection method is combined with artificial neural network to develop a nonlinear QSAR model for predicting activities of a series of substituted aromatic sulfonamides as carbonic anhydrase II (CA II) inhibitors. Eight simple one- and two-dimensional descriptors were selected by GA-KPLS and considered as inputs for developing artificial neural networks (ANNs). These parameters represent the role... 

This paper compares the Shuffling-Adaptive Neuro Fuzzy Inference System (Shuffling-ANFIS) with conventional ANFIS as the method for selecting the features of nonlinear systems. Shuffling-ANFIS technique uses the advantage of data splitting with the ANFIS as a powerful feature selection method to select the most important factors affecting nonlinear phenomena. In this technique, the features with the largest percent of frequency can be found by running the conventional ANFIS sequential forward search on the large number of training and test sets using leave-one-out validation criteria. The superiority of Shuffling-ANFIS over the conventional ANFIS was evaluated by using two synthetic and one... 

The purpose of this study was to develop the structure-toxicity relationships for a large group of 268 substituted benzene to the ciliate Tetrahymena pyriformis using mechanistically interpretable descriptors. The shuffling-adaptive neuro fuzzy inference system (Shuffling-ANFIS) has been successfully applied to select the important factors affecting the toxicity of substituted benzenes to T. pyriformis. The results of the proposed model were compared with the model of linear-free energy response surface and also the principal component analysis Bayesian-regularized neural network (PCA-BRANN) trained using the same data. The presented model shows a better statistical parameter in comparison... 

Katsnelson has shown that, within the Fermi-liquid approach, the optical conductivity of Dirac electrons in graphene is not affected by many-body interactions [M. I. Katsnelson, Eur. Phys. Lett. 84, 37001 (2008)EULEEJ0295-507510.1209/0295-5075/84/37001]. We show that, when the Dirac cone is tilted, the Fermi-liquid corrections arise in the optical conductivity in a manner that the correction depends on the angle between the electric field of the incident light and the tilt direction. Therefore the mapping of the optical conductivity for various directions of the incident light enables a determination of the many-body effect in the optical conductivity spectrum of the two-dimensional tilted... 

A hybrid method consisting of principal component analysis (PCA), multiple linear regressions (MLR), and artificial neural network (ANN) was developed to predict the retention time of 149 C3 - C12 volatile organic compounds for a DB-1 stationary phase. PCA and MLR methods were used as feature-selection tools, and a neural network was employed for predicting the retention times. The regression method was also used as a calibration model for calculating the retention time of VOCs and investigating their linear characteristics. The descriptors of the total information index of atomic composition, IAC, Wiener number, W, solvation connectivity index, Xlsol, and number of substituted aromatic... 

A total of 21 833 inhibitors of the central nervous system (CNS) were collected from Binding-database and analyzed using discriminant analysis (DA) techniques. A combination of genetic algorithm and quadratic discriminant analysis (GA-QDA) was proposed as a tool for the classification of molecules based on their therapeutic targets and activities. The results indicated that the one-against-one (OAO) QDA classifiers correctly separate the molecules based on their therapeutic targets and are comparable with support vector machines. These classifiers help in charting the chemical space of the CNS inhibitors and finding specific subspaces occupied by particular classes of molecules. As a next... 

This paper deals with the stability problem in LTI fractional order systems having fractional orders between 1 and 1.5. Some sufficient algebraic conditions to guarantee the BIBO stability in such systems are obtained. The obtained conditions directly depend on the coefficients of the system equations, and consequently using them is easier than the use of conditions constructed based on solving the characteristic equation of the system. Some illustrations are presented to show the applicability of the obtained conditions. For example, it is shown that these conditions may be useful in stabilization of unstable fractional order systems or in taming fractional order chaotic systems  

Energy harvesters are used in today's Wireless Sensor Networks (WSNs) to harvest energy from the environment. Although an energy harvester can provide a supply source with a much greater lifetime than a battery, the amount of available energy for an energy harvesting system is a random variable. Furthermore, the proper management of energy harvesters has a considerable impact on reliability. It has been observed that cooperative error control mechanisms like Cooperative Automatic Repeat Request (C-ARQ) and Cooperative Hybrid ARQ (C-HARQ) can be used for improving the energy management and reliability in Energy Harvesting WSNs (EH-WSNs). Recently, the impact of C-ARC mechanism has been... 

A total of 6289 drug-like anticancer molecules were collected from Binding database and were analyzed by using the classification techniques. The collected molecules were encoded to a diverse set of descriptors, spanning different physical and chemical properties of the molecules. A combination of genetic algorithms and counterpropagation artificial neural networks was used for navigating the generated drug-like chemical space and selecting the most relevant molecular descriptors. The proposed method was used for the classification of the molecules according to their therapeutic targets and activities. The selected molecular descriptors in this work define discrete areas in chemical space,... 

To scavenge the energy from the environment and extend the network lifetime, some wireless sensor networks (WSNs) have been equipped with energy harvesters recently. However, the variable amount of environmental energy can affect the reliability of energy harvesting wireless sensor networks (EH-WSNs). In addition, data transmission over a wireless media is vulnerable. Hence, utilizing suitable error control schemes are necessary to improve the reliability. Regarding this point, Automatic Repeat Request (ARQ) and Cooperative ARQ (C-ARQ) schemes are applied in this generation of WSNs. Conventional ARQ as well as C-ARQ scheme are considered and examined through simulation. A comparative... 

Bayesian regularised genetic neural network (BRGNN) has been used for modelling the inhibition activity of 141 biphenylalanine derivatives as integrin antagonists. Three local pattern search (PS) methods, simulated annealing and threshold acceptance were combined with BRGNN in the form of a hybrid genetic algorithm (HGA). The results obtained revealed that PS is a suitable method for improving the ability of BRGNN to break out from the local minima. The proposed HGA technique is able to retrieve important variables from complex systems and nonlinear search spaces for optimisation. Two models with 8-3-1 artificial neural network (ANN) architectures were developed for describingα 4β 7 and α 4β... 

This study deals with developing a quantitative structure-activity relationship (QSAR) model for describing and predicting the inhibition activity of 1-(3,3-diphenylpropyl)-piperidinyl derivatives as CCR5 modulators. Applying the multiple linear regressions (MLR) and its inability in predicting the inhibition behavior showed that the interaction has no linear characteristics. To assess the nonlinear characteristics of the inhibition activity artificial neural networks (ANN) was used for data modeling. In order to select the variables needed for developing ANNs, three variable selection algorithms were used: Stepwise-MLR, genetic algorithm-partial least squares (GA-PLS), and Bayesian... 

The list of two-dimensional Dirac systems with a tilt in their Dirac cone spectrum is expanding, and now, in addition to the organic system α(BEDT-TTF)2I3, it includes the two-dimensional 8Pmmn-borophene sheet, which allows for controlled doping by the gate voltage. We analytically calculate the polarization function of tilted Dirac cone for an arbitrary tilt parameter, 0≤η<1, and arbitrary doping. This enables us to find two interesting plasmonic effects solely caused by the tilt. (i) In addition to the standard plasmon oscillations, a strong enough tilt induces an additional linearly dispersing overdamped branch of plasmons, which is strongly Landau damped due to overlap with a large... 

The rich structure of solid state physics provides us with Dirac materials the effective theory of which enjoys the Lorentz symmetry. In nonsymmorphic lattices, the Lorentz symmetry can be deformed in a way that the null energy-momentum vectors will correspond to the on-shell condition for tilted Dirac cone dispersion. In this sense, tilted Dirac/Weyl materials can be viewed as solid state systems where the effective spacetime is non-Minkowski. In this work, we show that the polarization tensor for tilted Dirac cone systems acquires a covariant form only when the spacetime is considered to be an appropriate deformation of the Minkowski spacetime that is compatible with the dispersion. As a... 

In systems with substantial spin fluctuations, dressing the polarization function by ladder diagram of Stoner (spin-flip) excitations can drastically modify the electromagnetic response. As a case study, we provide the detailed analysis of the corrections to the non-local optical conductivity of both doped and undoped graphene. While the resummation of ladder diagram of Stoner excitations does not affect the TE mode in doped graphene, it allows for a new undamped TM mode in undoped graphene. This is the sole effect of corrections arising from ladder diagrams and is dominated by Stoner excitations along the ladder rung which goes away by turning off the source of spin-flip interactions. In... 

This paper explores software design methodologies in the context of creating a simulator and proposes a methodology to design and implement an event-based simulator namely Sim Met. SimMet is explored in the context of the development of a complex simulator for simulating real world conditions to use in science, technology and medicine and other simulations. In this paper we interested in event-based approach to create a real world with variety range of event possibilities. The paper first discusses the role of time concept as the cornerstone of a methodical analysis and design phase. In Sim Met we use an adaptation of object-oriented methodology to meet time and event concepts in creating a...