Sharif Digital Repository

In this study, we demonstrated a straightforward method for the easy access of chromeno[4,3-b]quinolin-6-ones via a one-pot three-component reaction of 4-hydroxycoumarin, aldehydes and aryl amines in the presence of halloysite nanoclay as an eco-friendly, inexpensive and green heterogeneous catalyst under solvent-free conditions. Moreover, symmetric and unsymmetric bis-chromeno[4,3-b]quinolin-6-ones were obtained from dialdehyde or diamines in good yields by this method. To date, this is the first report on the synthesis of symmetric and unsymmetric bis-chromeno[4,3-b]quinolin-6-ones via such a one-pot, multicomponent reaction. Some prepared chromeno[4,3-b]quinolin-6-ones displayed as... 

In the present study, an in-situ, two-step, highly controllable, fast, green, and facile strategy for fabricating the bimetallic cobalt-zinc-based metal-organic frameworks (MOFs) is employed for designing a non-enzymatic glucose sensing platform. The structural characterization, as well as the phase investigation of materials in each step, are assessed by X-ray diffraction, energy-dispersive X-ray spectroscopy, elemental mapping, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy. Furthermore, the electrocatalytic activity of the CoZn-BTC/GC fabricated electrode toward the electro-oxidation of glucose is examined by various electrochemical techniques,... 

In this paper, we propose a new derivative-free preconditioned conjugate gradient method in order for solving large-scale square and under-determined nonlinear systems of equations. The proposed method is also equipped with a relaxed nonmonotone line search technique. Under some suitable assumptions, the global convergence property is established. Numerical results on some square and under-determined test systems show the efficiency and effectiveness of the new method in practice. An application of the new method for solving nonlinear integro-differential equations is also provided. © 2016 Elsevier Ltd  

In this paper, we suggest to use a steepest descent algorithm for learning a parametric dictionary in which the structure or atom functions are known in advance. The structure of the atoms allows us to find a steepest descent direction of parameters instead of the steepest descent direction of the dictionary itself. We also use a thresholded version of Smoothed- ℓ0 (SL0) algorithm for sparse representation step in our proposed method. Our simulation results show that using atom structure similar to the Gabor functions and learning the parameters of these Gabor-like atoms yield better representations of our noisy speech signal than non parametric dictionary learning methods like K-SVD, in... 

Having a prime significance in diagonsing and predicting the dangerous symptoms of chronic diseases in the early stages, special attention has been drawn by wearable glucose-sensing platforms in recent years. Herein, modified commercial cotton fabrics, decorated with binary Ni–Co metal-organic frameworks (NC-MOFs) through a one-pot scalable hydrothermal route, were directly utilized as flexible electrodes for non-enzymatic glucose amperometric sensing. Glucose sensitivities of 105.2 μA mM−1 cm−2 and 23 μA mM−1 cm−2 were acheived within two distinct linear dynamic ranges of 0.04–3.13 mM and 3.63–8.28 mM, respectively. Receiving benefits from a remarkable glucose sensitivity behavior in... 

In this study, Ni-Fe/SiC nanocomposite coatings with smooth and crack-free surface were successfully prepared by means of the conventional electrodeposition in the presence of saccharin in electrolyte. The goal of this work was to investigate the effect of SiC nanoparticles and saccharin on the structure and properties of permalloy nanocomposite coatings. The nanocomposite coatings were characterized using optical and scanning electron microscopy, energy dispersive X-ray (EDX) analysis and X-ray diffraction (XRD) technique. The significant variation in the crystallographic texture of the coatings was observed due to the addition of SiC nanoparticles and saccharin in the electrodeposition... 

A highly controllable, green, and rapid strategy is demonstrated for fabricating of highly sensitive non-enzymatic glucose sensing platforms. Carbon nanohorns (CNHs) were decorated onto the screen-printed electrodes. Binary nickel-cobalt sulfide (NiCo-S) nanosheets (NSs) were then deposited on CNH-casted electrodes by a facile and scalable method. Following detailed structural characterization and the electrocatalytic activity of the fabricated NiCo-S/CNH electrodes towards electro-oxidation of glucose was examined in detail. The proposed electrodes operated within two distinct linear dynamic ranges of 0.001- 0.330 mM and 0.330 - 4.53 mM with sensitivities of 1842 µA.mM−1.cm−2 and 854... 

We theoretically study a Kitaev chain with a quasiperiodic potential, where the quasiperiodicity is introduced by a Fibonacci sequence. Based on an analysis of the Majorana zero-energy mode, we find the critical p-wave superconducting pairing potential separating a topological phase and a non-topological phase. The topological phase diagram with respect to Fibonacci potentials follow a self-similar fractal structure characterized by the box-counting dimension, which is an example of the interplay of fractal and topology like the Hofstadter's butterfly in quantum Hall insulators. © 2017 The Physical Society of Japan  

Transferring large models in federated learning (FL) networks is often hindered by clients' limited bandwidth. We propose $ extsf {FedAA}$ , an FL algorithm which achieves fast convergence by exploiting the regularized Anderson acceleration (AA) on the global level. First, we demonstrate that FL can benefit from acceleration methods in numerical analysis. Second, $ extsf {FedAA}$ improves the convergence rate for quadratic losses and improves the empirical performance for smooth and strongly convex objectives, compared to FedAvg, an FL algorithm using gradient descent (GD) local updates. Experimental results demonstrate that employing AA can significantly improve the performance of FedAvg,... 

Natural convection in a porous enclosure in the presence of thermal dispersion is investigated. The Fourier–Galerkin (FG) spectral element method is adapted to solve the coupled equations of Darcy’s flow and heat transfer with a full velocity-dependent dispersion tensor, employing the stream function formulation. A sound implementation of the FG method is developed to obtain accurate solutions within affordable computational costs. In the spectral space, the stream function is expressed analytically in terms of temperature, and the spectral system is solved using temperature as the primary unknown. The FG method is compared to finite element solutions obtained using an in-house code... 

Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

Object-oriented frameworks are widely used to develop new applications. They provide reusable concepts that are instantiated in application code through potentially complex implementation steps such as subclassing, implementing interfaces, and calling framework operations. Unfortunately, many modern frameworks are difficult to use because of their large and complex APIs and frequently incomplete user documentation. To cope with these problems, developers often use existing framework applications as a guide. However, locating concept implementations in those sample applications is typically challenging due to code tangling and scattering. To address this challenge, we introduce the notion of... 

This paper studies the energy-limited performance of multi-relay networks. Taking the properties of the power amplifiers (PAs) into account, we derive closed-form expressions for the optimal power allocation, the outage probability and the throughput in the cases with a sum consumed energy constraint. Moreover, we analyze the diversity and the multiplexing gains of the PA-aware systems. Finally, we investigate the performance of large-scale multi-relay networks and develop efficient multi-relay systems with low cooperation overhead. The numerical and the analytical results show that the inefficiency of the PAs affects the outage probability and the throughput of the multi-relay systems... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to... 

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference–based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference–based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number...