Sharif Digital Repository

It is known that no quantum process can produce a predetermined superposition of unknown arbitrary states. It has already been shown that with some partial information about the states, one can produce with some probability such superpositions. In general the success probability of these machines, even for orthogonal states, are less than unity. Here we show that there are specific machines that can produce superpositions of orthogonal qubit states with unit probability. © 2017 American Physical Society  

Nowadays, the issue of e-cigarettes gaining popularity among never-smokers and teenagers, thus becoming an emergent public health problem. Consequently, developing methods to monitor the toxic compounds in their smoke is a lucrative object. Herein, two coordination polymers (CPs) with nanorod and microsphere morphology are proposed as extractive phases in a needle trap device (NTD). The two synthesized CPs were characterized by FT-IR, SEM, BET, EDS, XPS and TGA. The extraction efficiency of two synthesized CPs was compared for polyaromatic hydrocarbons (PAHs) and as a result, the nanorods exhibited higher extraction and desorption efficiency. The prepared NTD filled with the nanorod CP was... 

In this letter, the sequency domain is introduced as a novel resource to propose a new index modulation, which is named sequency index modulation (SeIM). In SeIM, information bits are implicitly conveyed through the indices of the activated sequencies enabling bit error rate (BER), spectral efficiency, and power efficiency enhancement. Also, two strategies are proposed to allocate power among the activated sequencies revealing a trade-off between BER and power efficiency. Moreover, results are analytically derived for the BER of SeIM decoder. Finally, the recently proposed orthogonal time sequency multiplexing modulation is utilized to evaluate the performance of SeIM over doubly-spread... 

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

In the eld of supply chain, selecting a suitable green supplier could signi cantly help us decrease the cost and risks of the operations and increase the quality of green supply. This paper develops an integrated two-stage approach based on Fuzzy Analytic Hierarchy Process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and allocate order in the green supply chain. In the rst stage, suppliers are evaluated using FAHP method and in the second stage, a multi-product multi-period supply chain is developed considering green location-routing problem, discounting, and time window under uncertainty. Then, a fuzzy solution approach is applied to solve the proposed... 

The increasing level of customer awareness and application of environmental laws by governments, on the one hand, and the increasing number of competitors, on the other hand, has obliged industry owners to include green activities in the design of the supply chain network. Green activities include any type of action that reduces environmental degradation. Hence, this study seeks to develop a bi-objective, mixed integer linear programming (MILP) model for designing a green supply chain network. In the proposed model, the minimisation of costs and detrimental environmental effects are discussed. LP metric method is used to solve the bi-objective model and the proposed model is run by using... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a... 

Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously,... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a... 

Many cities are struggling to keep pace with limited budgets and rapid growth. Economic development models involving public-private partnerships (P3s) can help drive economic revitalization. The choice of partners plays a vital role in the success or failure of sustainable P3 initiatives. In this study, we propose a novel integrated sustainable private partner selection framework in P3s. The proposed model is composed of the best-worst method (BWM), the weighted influence non-linear gauge system (WINGS), and the technique of order preference similarity to the ideal solution (TOPSIS). The BWM is used to identify the importance weights of the economic, environmental, social, and technological...