Sharif Digital Repository

Responsible sustainable consumer behavior might serve as a complex pattern of social and environmental issues, consistent with the perspective of sustainability as a construct with both social and environmental pillars. Anchored on signaling theory and attribution theory, this study seeks to unearth a hitherto unexplored mechanism that might translate sustainability marketing into elevated responsible sustainable consumer behavior through the mediating role of brand image. Besides, this study aims to examine the impact of corporate social responsibility, as an intervening variable, to underpin the association between sustainability marketing and brand image. This study analyzes data from... 

The fabrication of supported noble metal nanocrystals (NCs) with well-controlled morphologies have been attracted considerable interests due to their merits in a wide variety of applications. Photodeposition is a facile and effective method to load metals over semiconductors in a simple slurry reactor under irradiation. By optimizing the photodeposition process, the size, chemical states, and the geometrical distribution of metal NCs have been successfully tuned. However, metal NCs with well-controlled shapes through the photodeposition process have not been reported until now. Here, we report our important advances in the controlled photodeposition process to load regular noble metal NCs.... 

Transportation electrification is an undeniable trend for moving towards sustainable energy systems. Therefore, electric intelligent parking lots (IPL) enhanced with renewable energy sources (RESs) and hydrogen storage systems (HSSs) play an essential role in reaching multiple techno-environmental purposes. In this regard, this paper proposes a novel energy management framework for HSS-based IPL considering risk management approach and demand response programs. The uncertainties of input parameters such as solar irradiation and its temperature, wind speed, energy tariff of the upper grid, and IPL's demand are captured into the model through two strategies; the stochastic optimization method... 

As an important precursor of crystalline phases, amorphous calcium carbonate (ACC), especially ultrasmall ACC clusters, have been attracting great interest in fundamental research, materials chemistry, as well as industrial applications. However, it is still challenging to synthesize stable ACC clusters in water that can be isolated and concentrated without severe aggregation. Herein, we report a facile dialysis method for producing colloidally stable ACC clusters that are well dispersed in water with the protection of specific polycarboxylic acids, which could be also easily deprotected by small-molecule acids like sodium citrate. Inherent proto-calcite short-range order is found to be... 

As an important precursor of crystalline phases, amorphous calcium carbonate (ACC), especially ultrasmall ACC clusters, have been attracting great interest in fundamental research, materials chemistry, as well as industrial applications. However, it is still challenging to synthesize stable ACC clusters in water that can be isolated and concentrated without severe aggregation. Herein, we report a facile dialysis method for producing colloidally stable ACC clusters that are well dispersed in water with the protection of specific polycarboxylic acids, which could be also easily deprotected by small-molecule acids like sodium citrate. Inherent proto-calcite short-range order is found to be... 

Dye-sensitized upconversion nanoparticles (UCNPs) have gained significant interest in biological applications. However, previous attempts to utilize these dye-sensitized UCNPs in the aqueous environment suffer from dramatic decline in the upconversion luminescence (UCL) intensity and problems with nanoparticles aggregation and water quenching. By employing indocyanine green (ICG) as a hydrophobic amplifier and energy harvester for UCNPs, we use a general, facile, and kinetically controlled mixing technology—flash nanoprecipitation (FNP)—to prepare aqueous stable ICG-sensitized UCNPs encapsulated by a biocompatible block copolymer poly (ethylene glycol)-b-poly (lactic-co-glycolic acid... 

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... 

We address the noninvasive temperature estimation from pulse-echo radio frequency signals from standard diagnostic ultrasound imaging equipment. In particular, we investigate the use of a high-resolution spectral estimation method for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach, employing generalized second-order statistics, is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods Seip and Ebbini (1995). Furthermore, temperature estimates from the new algorithm are compared with results from the more commonly used echo shift method described in Simon... 

Designers and manufacturers of cryptographic devices are always worried about the vulnerability of their implementations in the presence of power analysis attacks. This article can be categorized into two parts. In the first part, two parameters are proposed to improve the accuracy of the latest hypothetical power consumption model, so-called toggle-count model, which is used in power analysis attacks. Comparison between our proposed model and the toggle-count model demonstrates a great advance, i.e., 16%, in the similarity of hypothetical power values to the corresponding values obtained by an analog simulation. It is supposed that the attacker would be able to build such an accurate power... 

Partial discharge (PD) measurement and identification have great importance to condition monitoring of power transformers. In this paper a new method for recognition of single and multi-source of PD based on extraction of high level image features have been introduced. A database, involving 365 samples of phase-resolved PD (PRPD) data, is developed by measurement carried out on transformer artificial defect models (having different sizes of defect) under a specific applied voltage, to be used for proposed algorithm validation. In the first step, each set of PRPD data is converted into grayscale images to represent different PD defects. Two “image feature extraction” methods, the Local Binary...