Sharif Digital Repository

A titanium dioxide nanotube (TNT) and CuO-doped TNT (TNT-CuO) were synthesized using a hydrothermal method and incorporated into carrageenan-based films. The SEM results confirmed the formation of uniform nanocomposite films. The addition of nanoparticles imparted UV-blocking properties to the carrageenan film and increased the mechanical strength, surface hydrophobicity, and water vapor barrier properties. The modified TiO2 (TNT and TNT-CuO)-incorporated carrageenan films showed significantly higher antibacterial activity than the TiO2-added film under visible light. Bananas packaged with the neat carrageenan and TiO2-added films were degraded considerably after 12 days of storage at 20 °C.... 

Titanium dioxide (TiO2) and Cu-doped TiO2 (Cu–TiO2) were synthesized using a sol-gel method and used as nanofillers to prepare CMC-based functional packaging films. The Cu–TiO2 was spherical particles with a size range of 66.1 ± 9.0 nm TiO2 and Cu–TiO2 nanoparticles had good compatibility with CMC and were evenly distributed in the CMC polymer matrix to form a composite film. The TiO2-added film did not show significant antibacterial activity, but the Cu–TiO2-added film exhibited high antibacterial activity against foodborne pathogenic bacteria (L. monocytogenes and E. coli) under visible light. When bananas were packaged with the CMC-based films, the CMC/Cu–TiO2 film effectively delayed the... 

Human bodies use the electrical currents to make the muscles move. Disconnection of the electrical signals between the brain and the muscles as a result of spinal cord injuries, causes paralysis below the level of injury. Functional electrical stimulation (FES) is used to stimulate the peripheral nerves of the disabled limbs. The level of these electrical signals should be selected so that the desired tasks are done successfully. Applying the appropriate controller which can result a human like behaviour and the accomplishment of the desired tasks has become a significant research area. In this paper, the multi-input multi-output (MIMO) musculoskeletal model of human arm with six muscles is... 

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...