Sharif Digital Repository

A diffusion tensor imaging (DTI) -based statistical micromechanical model was developed to study the effect of axonal fiber architecture on the inter- and intra-regional mechanical heterogeneity of the white matter. Three characteristic regions within the white matter, i.e., corpus callosum, brain stem, and corona radiata, were studied considering the previous observations of locations of diffuse axonal injury. The embedded element technique was used to create a fiber-reinforced model, where the fiber was characterized by a Holzapfel hyperelastic material model with variable dispersion of axonal orientations. A relationship between the fractional anisotropy and the dispersion parameter of... 

In recent years, the city of Tehran, Iran's capital, has encountered numerous dust events so that the dust concentration of PM10 has reached even more than 800 μg m−3. This emphasizes the importance of the statistical study of dust in Tehran and the development of correlations for estimating dust concentration of PM10. In the present study, by evaluating the data measured during dust observations over the years 2013–2016 in Tehran, new statistical models are established for estimating PM10 concentration in terms of horizontal visibility and MODIS AOD. Firstly, simple nonlinear regression models between dust concentration of PM10 and horizontal visibility as well as MODIS AOD are developed.... 

Background: SApeptides have growing applications in tissue engineering and regenerative medicine. The application of SApeptide-based hydrogels depends strongly on their viscoelastic properties. Optimizing the properties is of importance in tuning the characteristics of the hydrogels for a variety of applications. Methods: In this study, we employed statistical modeling, conducted with the RSM and particle tracking microrheology, to investigate the effects of self-assembling SPG-178 peptide and added NaCl salt concentrations and milieu type (DI water or blood serum) on the viscoelastic properties of SPG-178 hydrogels. A central composite RSM model was employed for finding the optimum value of... 

Background: Oral rehydration solution (ORS) is a form of oral rehydration therapy (ORT) for diarrhoea that has the potential to drastically reduce child mortality; yet, according to UNICEF estimates, less than half of children younger than 5 years with diarrhoea in low-income and middle-income countries (LMICs) received ORS in 2016. A variety of recommended home fluids (RHF) exist as alternative forms of ORT; however, it is unclear whether RHF prevent child mortality. Previous studies have shown considerable variation between countries in ORS and RHF use, but subnational variation is unknown. This study aims to produce high-resolution geospatial estimates of relative and absolute coverage of... 

Evaluating the statistical dimension is a common tool to determine the asymptotic phase transition in compressed sensing problems with Gaussian ensemble. Unfortunately, the exact evaluation of the statistical dimension is very difficult and it has become standard to replace it with an upper-bound. To ensure that this technique is suitable, [1] has introduced an upper-bound on the gap between the statistical dimension and its approximation. In this work, we first show that the error bound in [1] in some low-dimensional models such as total variation and ell _{1} analysis minimization becomes poorly large. Next, we develop a new error bound which significantly improves the estimation gap... 

A statistical algorithm is introduced to improve the false inference of active loci, in the population in which members are admixture. The algorithm uses an advanced clustering algorithm based on a Bayesian approach. The proposed algorithm simultaneously infers the hidden structure of the population. In this regard, the Monte Carlo Markov Chain (MCMC) algorithm has been used to evaluate the posterior probability distribution of the model parameters. The proposed algorithm is implemented in a bundle, and then its performance is widely evaluated in a number of artificial databases. The accuracy of the clustering algorithm is compared with the STRUCTURE method based on certain criterion. © 2019... 

The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15–30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, "optical properties extraction (OPE)," which improves the... 

Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability... 

In this study, impact of initial ensembles on posterior distribution of ensemble-based assimilation methods is statistically analyzed. Along with, sampling performance as well as uncertainty quantification of these methods are compared in terms of their ability to accurately and consistently evaluate unknown reservoir model parameters and reservoir future performance. For this purpose, a synthetic test problem, which is a small but highly nonlinear reservoir model under two-phase flow, is utilized. Subsequently, different initial ensemble sets are considered and are updated through the assimilation process performed on the test problem using ensemble-based assimilation methods. Afterwards,... 

Asphaltene precipitation is known as one of the challenging problems in petroleum industries which have significant effects on production such as formation damage and wellbore plugging. To solve this problem, calculation of precipitated asphaltene becomes highlighted so in the present study a novel approach is proposed based on ANFIS algorithm to estimate precipitated asphaltene in terms of dilution ration, carbon number of precipitants and temperature. The particle swarm optimization (PSO) method is applied to optimize ANFIS algorithm parameters. The proposed model was evaluated based on statistical parameters and the calculated R2, AARD and RMSE for the total data are 0.90309, 9.4908 and... 

Statistical process control provides useful tools to improve the quality of multistage machining processes, specifically in continuous manufacturing lines, where product characteristics are measured at the final station. In order to reduce process errors, variation source identification has been widely applied in machining processes. Although statistical estimation and pattern matching-based methods have been utilized to monitor and diagnose machining processes, most of these methods focus on stage-by-stage inspection using complex models and patterns. However, because of the existence of high rate alarms and the complexity of the machining processes, a surrogate modelling is needed to solve... 

A method is developed to calculate the critical line of two dimensional (2D) anisotropic Ising model including nearest-neighbor interactions. The method is based on the real-space renormalization group (RG) theory with increasing block sizes. The reduced temperatures, Ks (where K=J/kBT and J, kB, and T are the spin coupling interaction, the Boltzmann constant, and the absolute temperature, respectively), are calculated for different block sizes. By increasing the block size, the critical line for three types of lattice, namely: triangular, square, and honeycomb, is obtained and found to compare well with corresponding results reported by Onsager in the thermodynamic limit. Our results also... 

A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises... 

Conventional models of cardiovascular system frequently lack required detail and focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the cardiovascular system. It utilizes noninvasive blood flow and pressure seed data and temporal cardiac muscle regional activity to predict the operation of the heart under normal and congestive heart failure conditions. The analysis considers specific regions of the heart, namely, base, mid and apex of left ventricle. The proposed method of parameter estimation for hydraulic electric analogy model is recursive least squares algorithm. Based on simulation results and comparison... 

Employing a biharmonic boundary integral method with linear elements, coarsening dynamics of nanodroplets on topographical step heterogeneity is investigated. It is shown that the step height and droplet configuration have an influential effect on the dynamics. Increasing the step height slows down the process while locating the droplets close to the step boosts the coarsening rate. Considering a slip boundary condition enhances the dynamics and reveals a transition in the droplet migration direction. Our results reveal that increasing the surface wettability weakens the dynamics. Various types of the disjoining pressure over the step are also considered and their effects on the coarsening... 

Considering high temperature and pressure during single bubble sonoluminescence collapse, a hot plasma core is generated at the center of the bubble. In this paper a statistical mechanics approach is used to calculate the core pressure and temperature. A hydrochemical model alongside a plasma core is used to study the bubble dynamics in two host liquids of water and sulfuric acid 85 wt % containing Ar atoms. Calculation shows that the extreme pressure and temperature in the plasma core are mainly due to the interaction of the ionized Ar atoms and electrons, which is one step forward to sonofusion. The thermal bremsstrahlung mechanism of radiation is used to analyze the emitted optical energy... 

This paper deals with the average consensus problem in a multi-agent system with switching interaction topology modeled as a weighted digraph. The convergence analysis is performed in both discrete-time and continuous-time dynamics based on the theory of infinite matrix products. Conditions for system convergence to average consensus are derived in the form of constraints on direct and reverse graphs and the structure of adjacency elements among the agents. Furthermore, a sufficient condition is provided for convergence to average consensus in systems in which the interaction topology is balanced over infinite contiguous non-overlapping time intervals instead of being balanced continuously.... 

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational... 

An HMM-based speech enhancement in Mel-frequency domain is introduced and improved. It is shown that hidden Markov modeling in the Mel-frequency domain is beneficial due to its effective representation of the speech spectrum; however, speech enhancement in this domain requires an inversion from the Mel-frequency to the spectral domain which introduces distortion artifacts for spectrum estimation. To reduce the distortion effects of the inversion and employ the advantages of robustness modeling in the Mel-frequency domain, a parallel cepstral and spectral (PCS) modeling is proposed. In PCS, a concurrent modeling in both cepstral and spectral domains is performed. The performances of the... 

In this paper the characteristic ratios and generalized time constant are defined for all-pole commensurate fractional order systems. The sufficient condition for stability of these systems in terms of their characteristic ratios is obtained. Also an analytical approach for characteristic ratio assignment (CRA) to have a non-overshooting fast closed loop step response is introduced. The proposed CRA method is then employed to design a fractional order controller. Computer simulation results are presented to illustrate the performance of the CRA based designed fractional order controllers