Sharif Digital Repository

Development of predictive multi-organ models before implementing costly clinical trials is central for screening the toxicity, efficacy, and side effects of new therapeutic agents. Despite significant efforts that have been recently made to develop biomimetic in vitro tissue models, the clinical application of such platforms is still far from reality. Recent advances in physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD) modeling, micro- and nanotechnology, and in silico modeling have enabled single- and multi-organ platforms for investigation of new chemical agents and tissue-tissue interactions. This review provides an overview of the principles of designing... 

Organ-on-chip (OOC) platforms have attracted attentions of pharmaceutical companies as powerful tools for screening of existing drugs and development of new drug candidates. OOCs have primarily used human cell lines or primary cells to develop biomimetic tissue models. However, the ability of human stem cells in unlimited self-renewal and differentiation into multiple lineages has made them attractive for OOCs. The microfluidic technology has enabled precise control of stem cell differentiation using soluble factors, biophysical cues, and electromagnetic signals. This study discusses different tissue- and organ-on-chip platforms (i.e., skin, brain, blood–brain barrier, bone marrow, heart,... 

In this paper, we consider the coherent radar detection of rapid fluctuating signals in the Gaussian noise. This problem has been previously solved by employing the GLR technique, but we use the ALR to improve the detection performance. So, after deriving an approximate ALR detector, we compare the new detector with the GLR and ' Square-law detectors and we show its superiority  

The goal of this paper is to develop a model to integrate "pricing" and "advertisement" for short life cycle products, such as branded fashion clothing products. To achieve this goal, we apply the concept of "Dynamic Pricing". There are two classes of advertisements, for the brand (regardless of product) and for a particular product. Advertising the brand affects the demand and price of all the products. Thus, the model considers all these products in relation with each other. We develop two different methods to integrate both types of advertisement and pricing. The first model is developed within the framework of dynamic programming. However, due to the complexity of the model, this method... 

To formulate stochastic capacity allocation problems in a manufacturing system, the concept and techniques of revenue management is applied in this research. It is assumed the production capacity is stochastic and hence its exact size cannot be forecasted in advance, at the time of planning. There are two classes of "frequent" and "occasional" customers demanding this capacity. The price rate as well as the penalty for order cancellation caused by overbooking is different for each class. The model is developed mathematically and we propose an analytical solution method. The properties of the optimal solution as well as the behavior of objective function are also analyzed. The objective... 

This paper provides a framework to study the integration of network marketing in a dual-channel distribution system. We develop an approach to optimize the main decision variables of this system simultaneously. These decision variables include the price paid by the customers of both channels, confidence level, the effort level of active distributors of network marketing, and wholesale price. Although both channels compete with each other, it is vital to have a balanced pricing system to keep them motivated. However, the prices in network marketing and traditional retailer system are not necessarily equal due to the differences in their nature. Furthermore, it is also required to develop an... 

In this paper, a new approach to formulate a class of scheduling problems is introduced, which can be applied to many other discrete problems with complicated structures. The concept of graph circular coloring is applied to develop a model for the special case of an open shop scheduling problem. In this problem, there are some independent jobs to be processed in a shop with dedicated renewable resources. Each job consists of several tasks with no precedence restriction. Each task is processed without preemption. The processing time of the tasks is given. Processing each task requires using some multiple specified types of resource, while no more than one task can use each resource,... 

Network theory and Saaty's analytic heirarchy process (AHP) are considered to be effective methods for estimating a city's traffic pattern during the emergency period of an earthquake, and for evaluating the urban transportation network of that city. A graph is created in which the nodes are land uses (or a group of land uses), crossroads or junctions represent the city, and the arcs are the streets. AHP is used to determine the priority of trips, and shortest path techniques identify the fastest routes for daily trips, and the safest ones during earthquakes. A pareto diagram then shows those streets that play an important role in satisfying both criteria. On the basis of the trip patterns... 

In this paper, the optimization of long term operation and determination of the reliability level of a hydro-thermal power system are integrated into a unified model. Inflow to reservoirs is modeled as a random variable. Furthermore, the demand for energy is also assumed to be a random variable with normal distribution. In order to minimize the total cost, the reliability level of the system is determined, rather than considering it as a priori input data. Since the resulting model is a large-scale stochastic nonlinear programming, it is necessary to develop a special method to solve it. This method, which provides an optimal solution within three stages, consists of a decomposition... 

This article investigates optimization of long-term operation of hydrothermal power systems consisting of cascaded reservoirs. Due to stochasticity of reservoir inflows, demand for energy, and unit forced outages, the uncertainty of this system is so significant that reliability of demand satisfaction becomes an indispensable component of the modelling process. On the other hand, existence of stochastic parameters, especially in the case of cascaded reservoirs, makes the problem very difficult to solve by applying existing optimization techniques. A hybrid genetic algorithm with dynamic tuning of its control parameters is developed that incorporates real number encoding and an analytical...