Sharif Digital Repository

The screen-printed gold electrode (SPGE) modified with the formation of self-assembly monolayer (SAM) of cysteine (Cys) on gold-nanoparticles (Au nano) was utilized for rapid and simultaneous determination of tetracycline and cefixime antibiotics by square wave voltammetry (SWV). Electrochemical investigation and characterization of the modified electrode was achieved using cyclic voltammetry (CV) and scanning electron microscopy (SEM). A principal component artificial neural network (PCANN) with three layer back-propagation network was utilized for the analysis of the voltammogram data. It is possible to simultaneously determine the tetracycline and cefixime concentrations in the ranges of... 

Multivariate curve resolutions (MCR) along with other chemometric techniques are proposed to improve the analysis of Iranian Elettaria cardamomum (E. cardamom) essential oil with gas chromatography-mass spectrometry (GC-MS). In addition, multivariate curve resolution-alternating least squares (MCR-ALS) is used to obtain pure elution and mass spectral profiles for the components present in each chromatographic segment as well as their relative concentrations. This strategy was also used to overcome the problems of baseline offset, asymmetric peaks, retention time shifts, and overlapped and embedded peaks occurring during GC-MS analysis. The analysis of GC-MS data revealed that 42 components... 

The present work focuses on the development of an interpretable quantitative structure-activity relationship (QSAR) model for predicting the anti-HIV activities of 67 thiazolylthiourea derivatives. This set of molecules has been proposed as potent HIV-1 reverse transcriptase inhibitors (RT-INs). The molecules were encoded to a diverse set of molecular descriptors, spanning different physical and chemical properties. Monte Carlo (MC) sampling and multivariate adaptive regression spline (MARS) techniques were used to select the most important descriptors and to predict the activity of the molecules. The most important descriptor was found to be the aspherisity index. The analysis of variance... 

In this paper we introduce a new ordering policy for inventory control in a two-echelon inventory system consisting of one central warehouse and a number of non-identical retailers. The warehouse uses a modified one-for-one policy, but the retailers apply a new policy which is different from the traditional inventory policies described in the literature of inventory and production control systems. In this system, each retailer constantly places an order for one unit of product to the central warehouse in a pre-determined time interval; i.e., the time interval between any two consecutive orders from each retailer is a fixed number and the quantity of each order is one. We then show how the... 

Quantitative structure-activity relationship (QSAR) approach was carried out for the prediction of inhibitory activity of some novel quinazolinone derivatives on serotonin (5-HT7) using modified ant colony (ACO) method and adaptive neuro-fuzzy interference system (ANFIS) combined with shuffling cross-validation technique. A modified ACO algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict 5-HT7 receptor binding activities of quinazolinone derivatives. The best descriptors describing the inhibition mechanism are Qmax, Se, Hy, PJI3 and DELS which are among electronic, constitutional, geometric and... 

There is a growing concern, in the last decade, about the environment and social footprint of business operations. The subject of supply chain sustainability, simultaneously considering economic, environment and/or social values, has gained attention in the academia and from the industry. Particularly for deteriorating and seasonal products, such as fresh produce, the issues of timely supply and disposal of the deteriorated products are of high concerns. This research develops a new replenishment policy in a centralized sustainable supply chain for the deteriorating items. The model considers inventory and transportation costs, as well as the environmental and social impacts, with several... 

Quantitative Structure - Activity Relationship (QSAR) models for the inhibition action of some 1-phenylbenzimidazoles on platelet-derived growth are constructed using Genetic Algorithm and Artificial Neural Network (GA-ANN) method. The statistical parameters of R2 and root-mean-square error are 0.82 and 0.21, respectively using this method. These parameters show a considerable improvement compared to the stepwise multiple linear regression combined with ANN (stepwise MLR-ANN). Ten-fold shuffling crossvalidations are carried out to select the most important descriptors. Five descriptors of index of Balaban (J), average molecular weight (AMW), 3D-Wiener index (W3D), mean atomic van der Waals... 

Polymeric membrane technology has received extensive attention in the field of gas separation, recently. However, the tradeoff between permeability and selectivity is one of the biggest problems faced by pure polymer membranes, which greatly limits their further application in the chemical and petrochemical industries. To enhance gas separation performances, recent works have focused on improving polymeric membranes selectivity and permeability by fabricating mixed matrix membranes (MMMs). Inorganic zeolite materials distributed in the organic polymer matrix enhance the separation performance of the membranes well beyond the intrinsic properties of the polymer matrix. This concept combines... 

This paper considers a two-level supply chain consisting of one warehouse and one retailer. In this model we determine the optimal ordering policy according to inventory and transportation costs. We assume that the demand rate by the retailer is known. Shortages are allowed neither at the retailer nor at the warehouse. We study this model in two cases; decentralized and centralized. In the decentralized case the retailer and the warehouse independently minimize their own costs; while in the centralized case the warehouse and the retailer are considered as a whole firm. We propose an algorithm to find economic order quantities for both the retailer and the warehouse which minimize the total... 

This paper considers a two-level supply chain consisting of one warehouse and one retailer. Unlike the most similar models which determine the optimal ordering policy according to inventory cost only, in this model, we also consider the transportation cost. We assume that the demand rate at the retailer is known and the demand is confined to a single item. Shortages are allowed neither at the retailer nor at the warehouse. The objective is to find the economic order quantities for both the retailer and the warehouse which minimize the total cost. That is. the sum of the holding and ordering cost at the retailer and warehouse as well as the transportation cost from warehouse to retailer.... 

In unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over... 

A linear and non-linear quantitative structure-activity relationship (QSAR) study is presented for modeling and predicting heparanase inhibitors' activity. A data set that consisted of 92 derivatives of 2,3-dihydro-1,3-dioxo-1H-isoindole-5-carboxylic acid, furanyl-1,3-thiazol-2-yl and benzoxazol-5-yl acetic acids is used in this study. Among a large number of descriptors, four parameters classified as physico-chemical, topological and electronic indices are chosen using stepwise multiple regression technique. The artificial neural networks (ANNs) model shows superiority over the multiple linear regressions (MLR) by accounting 87.9% of the variances of antiviral potency of the heparanase... 

Artificial neural networks (ANN) have not been used in chronic subdural hematoma (CSDH) outcome prediction following surgery. We used two methods, namely logistic regression and ANN, to predict using eight variables CSDH outcome as assessed by the Glasgow outcome score (GOS) at discharge. We had 300 patients (213 men and 87 women) and potential predictors were age, sex, midline shift, intracranial air, hematoma density, hematoma thickness, brain atrophy, and Glasgow coma score (GCS). The dataset was randomly divided to three subsets: (1) training set (150 cases), (2) validation set (75 cases), and (3) test set (75 cases). The training and validation sets were combined for regression... 

A computational investigation was conducted to optimize the fluidic injection angle effects on thrust vectoring. Numerical simulation of fluidic injection for shock vector control, with a convergent-divergent nozzle concept was performed, using URANS approach with Spalart-Allmaras turbulence model. The fluidic injection angles from 60° to 120° were investigated at different aerodynamic and geometric conditions. The current investigation demonstrated that secondary injection angle is an essential parameter in fluidic thrust vectoring. Computational results indicated that, optimizing secondary injection angle would have positive impact on thrust vectoring performance. Furthermore, in most... 

The current research attempted to apply a numerical investigation for external freestream-flow influence on thrust-vector control. The freestream-flow Mach numbers varying from 0.05 to 1.1 were studied at different flow conditions. Computational modeling and simulation of a converging diverging nozzle with shock-vector control structure was achieved with utilizing the Unsteady-RANS approach and Spalart-Allmaras turbulence model. The present investigation has shown that, freestream-flow is an essential parameter on performance of shock-vector nozzle. Numerical results demonstrate that, increasing freestream Mach number would reduce the thrust-vectoring effectiveness. Furthermore, optimizing... 

The present study attempted to utilize a computational investigation to optimize the external freestream flow influence on thrust-vector control. The external flow with different Mach numbers from 0.05 to 1.1 and with optimum injection angles from 60° to 120° were studied at variable flow conditions. Simulation of a converging-diverging nozzle with shock-vector control method was performed, using the unsteady Reynoldsaveraged Navier-Stokes approach with Spalart-Allmaras turbulence model. This research established that freestream flow and fluidic-injection angle are the significant parameters on shock-vector control performance. Computational results indicate that, increasing freestream Mach... 

This paper presents a novel model for designing a reliable network of facilities in closed-loop supply chain under uncertainty. For this purpose, a bi-objective mathematical programming formulation is developed which minimizes the total costs and the expected transportation costs after failures of facilities of a logistics network. To solve the model, a new hybrid solution methodology is introduced by combining robust optimization approach, queuing theory and fuzzy multi-objective programming. Computational experiments are provided for a number of test problems using a realistic network instance  

In this work, the inhibitory activity of pyridine N-oxide derivatives against human severe acute respiratory syndrome (SARS) is predicted in terms of quantitative structure-activity relationship (QSAR) models. These models were developed with the aid of multivariate adaptive regression spline (MARS) and adaptive neuro-fuzzy inference system (ANFIS) combined with shuffling cross-validation technique. A shuffling MARS algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict SARS inhibitory activities of pyridine N-oxide derivatives. A data set of 119 drug-like compounds was coded with over hundred calculated... 

The efficient planning of search and rescue (SAR) operations is highly impactful in the disaster response phase, which offers a limited time window with a declining chance for saving trapped people. The present paper introduces a new robust decision support framework for planning SAR resource deployment in post-disaster districts. A two-stage decomposition approach is applied to formulate the problem as iterative interrelated stages of mixed-integer programming (MIP) models. The first stage presents a robust multi-period allocation model for maximizing fair and effective demand coverage in the affected districts during the entire planning horizon. It takes into account the time-sensitiveness... 

The efficient planning of search and rescue (SAR) operations is highly impactful in the disaster response phase, which offers a limited time window with a declining chance for saving trapped people. The present paper introduces a new robust decision support framework for planning SAR resource deployment in post-disaster districts. A two-stage decomposition approach is applied to formulate the problem as iterative interrelated stages of mixed-integer programming (MIP) models. The first stage presents a robust multi-period allocation model for maximizing fair and effective demand coverage in the affected districts during the entire planning horizon. It takes into account the time-sensitiveness...