Sharif Digital Repository

In the present work, the mechanical properties, in particular, the Poisson's ratio of four two-dimensional silica structures, called here α,β,γ and δ are studied by means of molecular dynamics simulations. The α structure has been synthesized experimentally and the others have been reported as the most stable low-energy structures that reveal in-plane negative Poisson's ratio based on the first principles calculations. Among these structures, β-silica exhibits the largest in-plane negative Poisson's ratio which is 2–4 times higher than penta-graphene. Our results illustrate that the classical molecular dynamics simulation reproduces results in agreement with those of the first principles... 

The effect of temperature on the short-range order (SRO) structures, deformation mechanisms and failure modes of metallic glasses (MGs) is of fundamental importance for their practical applications. However, due to lack of direct structural information at the atomistic level from experiments and the absence of previous molecular dynamics (MD) simulations to reproduce experimental observations over a wide range of temperature, this issue has not been well understood. Here, by carefully constructing the atomistic models of Cu64Zr36 and Fe80W20 MGs, we are able to reproduce the major deformation modes observed experimentally, i.e. single shear banding (SB) at low temperatures, multiple... 

The demonstration of high entropy alloys (HEAs), or more generally multi-principal-element alloys (MPEAs), which display a greater resistance to softening at elevated temperatures and embrittlement at cryogenic temperatures, has offered an accessible alternative alloying process for materials scientists and engineers. Although solidification is a fundamental process in synthesis of alloys which strongly affects their microstructure and properties, a firm understanding of this process in HEAs is scarce. Here, using molecular dynamics (MD) simulations, we study the rapid solidification of the multi-principal-element CoFeNiPd alloy as a prototypical single-phase HEA. Our simulations reveal an... 

Previous studies have shown that a small variation in the chemical composition of metallic glasses (MGs) can drastically alter their strength and ductility. However, the underlying structural origin and atomistic mechanisms remain unclear. Using large-scale molecular dynamics simulations, we studied the effect of chemical composition and affinity on the microstructure and deformation behaviour of Zr50Ni50 − xAlx MG by varying the value of x in the range of 5 ≤ x ≤ 25 (at.%). We show that an increase in x is able to strengthen and embrittle the material. In particular, a ductile (homogeneous deformation) to brittle (shear banding) transition occurs at x ~ 15. To reveal the structural origin,... 

Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two-stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average... 

In this paper we show how the higher index theory can be used to prove results concerning the non-existence of a complete Riemannian metric with uniformly positive scalar curvature at infinity. By improving some classical results due to M. Gromov and B. Lawson we show the efficiency of these methods to prove such non-existence theorems  

In this paper we state and prove delocalized Morse type inequalities for Morse functions as well as for closed differential 1-forms. These inequalities involve delocalized Betti numbers. As an immediate consequence, we prove the vanishing of delocalized Betti numbers of manifolds fibering over the circle under a vanishing condition on the delocalizing conjugacy class  

Development of novel engineering techniques that can promote new clinical treatments requires implementing multidisciplinary in-vitro and in-vivo approaches. In this study, we have implemented microfluidic devices and in-vivorat model to study the mechanism of neural stem cell migration and differentiation.These studies can result in the treatment of damages to the neuronal system. In this research, we have shown that by applying appropriate ranges of biochemical and biomechanical factors as well as by exposing the cells to electromagnetic fields, it is possible to improve viability, proliferation, directional migration and differentiation of neural stem cells. The results of this study can... 

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

Using smoothness criteria to separate smooth graph signals from their summation is an approach that has recently been proposed (Mohammadi et al., 2023) and shown to have a unique solution up to the uncertainty of the average values of source signals. In this correspondence, closed-form solutions of both exact and approximate decompositions of that approach are presented. This closed-form solution in the exact decomposition also answers the open problem of the estimation error. Additionally, in the case of Gaussian source signals in the presence of additive Gaussian noise, it is shown that the optimization problem of that approach is equivalent to the Maximum A Posteriori (MAP) estimation of... 

In this paper, we address theoretical limitations in estimating the mixing matrix in noisy Sparse Component Analysis (SCA) in the two-sensor case. We obtain the Cramér-Rao Bound (CRB) error estimation of the mixing matrix based on the observation vector x=(x1,x2)T. Using the Bernoulli-Gaussian (BG) sparse distribution for sources, and some reasonable approximations, the Fisher Information Matrix (FIM) is approximated by a diagonal matrix. Then, the effect of off-diagonal terms in computing the CRB is investigated. Moreover, we compute an oracle CRB versus the blind uniform CRB and show that this is only 3 dB better than the blind uniform CRB. Finally, the CRB, the approximated CRB, the... 

In this paper, we address recovery of sparse signals from compressed measurements, and sparse signal approximation, which have received considerable attention over the last decade. First, we revisit smoothed L0 (SL0), a well-known sparse recovery algorithm, and give some insights into it that have not been noticed previously. Specifically, we re-derive the SL0 algorithm based on proximal methods, and using recent results in solving nonconvex problems by proximal algorithms, we provide a convergence guarantee for it. In addition, inspired by this derivation, we propose a general family of algorithms, which we call iterative sparsification-projection (ISP), having SL0 as a special member. Our... 

In this study, a detector/estimator is proposed for compressed sensing radars, which does not need to reconstruct the radar signal, and which works directly from compressive measurements. More precisely, through direct processing of the measurements, and without the need for reconstructing the original radar signal, the system performs target detection, and then estimates range, Doppler frequency shift and radar cross section in the presence of a Gaussian clutter. It can be seen that for large compression ratios, the detection performance and estimation quality is comparable with a common radar system while having a much lower data rate and with less computational load  

This letter is concerned with designing incoherent unit-norm frames, i.e., a set of vectors in a finite dimensional Hilbert space with unit norms and very low absolute pairwise correlations. Due to their widespread use in a variety of applications, including compressed sensing and coding theory, incoherent frame design has received considerable attention, and many algorithms have been proposed to this aim. In this letter, a new algorithm is presented which constructs incoherent frames by minimizing the maximum absolute pairwise correlations (mutual coherence) of the frame vectors. Our strategy is based on an alternating minimization penalty method, which admits efficient solvers using... 

Let M be a complete n-dimensional Riemannian spin manifold, partitioned by q two-sided hypersurfaces which have a compact transverse intersection N and which in addition satisfy a certain coarse transversality condition. Let E be a Hermitean bundle on M with connection. We define a coarse multi-partitioned index of the spin Dirac operator on M twisted by E. Our main result is the computation of this multi-partitioned index as the Fredholm index of the Dirac operator on the compact manifold N, twisted by the restriction of E to N. We establish the following main application: if the scalar curvature of M is bounded below by a positive constant everywhere (or even if this happens only on one of... 

The main motivation behind compressive sensing is to reduce the sampling rate at the input of a digital signal processing system. However, if for processing the sensed signal one requires to reconstruct the corresponding Nyquist samples, then the data rate will be again high in the processing stages of the overall system. Therefore, it is preferred that the desired processing task is done directly on the compressive measurements, without the need for the reconstruction of the Nyquist samples. This paper addresses the case in which the processing task is “detection” (the existence) of a sparse signal in additive white Gaussian noise, with applications e.g. in radar systems. Moreover, we will... 

This paper presents efficient algorithms for learning low-coherence dictionaries. First, a new algorithm based on proximal methods is proposed to solve the dictionary learning (DL) problem regularized with the mutual coherence of dictionary. This is unlike the previous approaches that solve a regularized problem where an approximate incoherence promoting term, instead of the mutual coherence, is used to encourage low-coherency. Then, a new solver is proposed for constrained low-coherence DL problem, i.e., a DL problem with an explicit constraint on the mutual coherence of the dictionary. As opposed to current methods, which follow a suboptimal two-step approach, the new algorithm directly... 

The copper/copper (Cu/Cu) interface has an important role in wafer-to-wafer hybrid bonding for 3D integration applications. Reports indicate the possibility of the formation of post-bonding interfacial voids and cracks which must be avoided. Here, we use molecular dynamics simulations to investigate the effect of annealing-induced tensions on the strength and deformation mechanisms of Cu/Cu interfaces. We perform tensile tests on the pristine and defective Cu/Cu interfaces including a prototypical interfacial grain boundary in two defective limits: the presence of a single (isolated) void, and an array of multiple voids. The latter resembles interfacial nanoscale roughness as a result of...