Near-Field Radar Microwave Imaging as an Add-on Modality to Mammography

According to global statistics, there is a high incidence of cancer in western countries; and, due to the limited resources available in most health care systems, it seems like one of the most feasible options to fight against cancer might be strict prevention policies—such as eliminating carcinogens in people’s daily lives. Nevertheless, early cancer detection and effective treatment are still necessary, and understanding their efficacy and limitations are important issues that need to be addressed in order to ultimately enhance patients’ survival rate. In the case of breast cancer, some of the problems faced by conventional mammography have been addressed in the literature; they include high rate of false-positive and false-negative results, as well as the possibility of overdiagnosis. New technologies, such as digital breast tomosynthesis (DBT), have been able to improve the sensitivity and specificity by using 3D imaging. However, the low contrast (1%) existing between tumors and healthy fibroglandular tissue at X-ray frequencies has been identified as one of the main causes of misdiagnosis in both conventional 2D mammography and DBT. Near-field radar imaging (NRI) provides a unique opportunity to overcome this problem, since the contrast existing between the aforementioned tissues is intrinsically higher (10%) at microwave frequencies. Moreover, the low resolution and highly complex scattering patterns of microwave systems can be enhanced by using prior information from other modalities, such as the DBT. Therefore, a multimodal DBT/NRI imaging system is proposed to exploit their individual strengths while minimizing their weaknesses. In this work, the foundation of this idea is reviewed, and a preliminary design and experimental validation of the NRI system, used as a DBT complement, is introduced

A Multi-Objective Optimization for Supply Chain Network Using the Bees Algorithm

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem

Effect of Amniotic Membrane Homogenate on Ischemic Skin Flap Survival in Rat Model

Bachground: Surgical skin flaps are frequently used in plastic and reconstructive surgery to repair acquired or congenital defects. Necrosis is a common complication associated with these flaps postoperatively as a result of inadequate blood supply. This study was designed to evaluate the effectiveness of amniotic membrane homogenate in healing the dorsal skin of the rat as an ischemic flap model. Materials and Methods: In this experimental study, twenty male Wistar rats weighing between 350 and 400 g were used in the study. For all rats 3*10 cm, full-thickness, caudally based pattern dorsal skin flaps were elevated. The rats were randomized into 2 groups: control (I) and experimental (II). Then in 10 point,0.1 mL amniotic membrane homogenate was injected with with equal interval in experimental group and normal salin administered in control group. Seven days later all skin flaps were examined mechanically (necrosis) and histologically. Results: Tissue flap necrosis showed significantly reduced in amniotic membrane homogenate group (p=0.032), and tissue flap survival showed significantly increased in amniotic membrane homogenate group (p=0.036). There were no significant differences in the histology analysis heling proccess between two groups (p>0.05). Conclusion: It seems that, the administration of amniotic membrane homogenate is an effective and safe method that improves the survival of ischemic skin flaps in a rat model

Effect of Amniotic Membrane Homogenate Homogenate on Ischemic Skin Flap Survival in Rat Model

Bachground: Surgical skin flaps are frequently used in plastic and reconstructive surgery to repair acquired or congenital defects. Necrosis is a common complication associated with these flaps postoperatively as a result of inadequate blood supply. This study was designed to evaluate the effectiveness of amniotic membrane homogenate in healing the dorsal skin of the rat as an ischemic flap model. Materials and Methods: In this experimental study, twenty male Wistar rats weighing between 350 and 400 g were used in the study. For all rats 3 * 10 cm, full-thickness, caudally based pattern dorsal skin flaps were elevated. The rats were randomized into 2 groups: control (I) and experimental (II). Then in 10 point,0.1 mL amniotic membrane homogenate was injected with with equal interval in experimental group and normal salin administered in control group. Seven days later all skin flaps were examined mechanically (necrosis) and histologically. Results: Tissue flap necrosis showed significantly reduced in amniotic membrane homogenate group (p=0.032), and tissue flap survival showed significantly increased in amniotic membrane homogenate group (p=0.036). There were no significant differences in the histology analysis heling proccess between two groups (p>0.05). Conclusion: It seems that, the administration of amniotic membrane homogenate is an effective and safe method that improves the survival of ischemic skin flaps in a rat model

A multi-objective optimisation for supply chain network using the bees algorithm

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem