In recent years, much more attentions have been focused on siRNA-based gene therapy. This approach is based on PTGS (Post-transcriptional gene silencing). Due to some defects in viral vectors, non-viral vectors have been used to deliver nucleic acids into target cells. Although, transfection efficiency in non-viral vectors is less than viral ones, but safety of non-viral vectors is much more. Characteristic features of siRNA, such as high compatibility, application in low doses and its versatility make it suitable in the gene therapy field. However, some challenges, such as stimulating immune system and Off-target silencing will be remain. In this review article, we express bottlenecks existing in siRNA delivery into target cells. According to the information, with further development of siRNA delivery in the future, it could be a promising approach in treatment for a variety of genetic diseases.

This paper develops Order Acceptance for an Integrated Production-Distribution Problem in which Batch delivery is implemented. The aim of this problem is to coordinate: (1) rejecting some of the orders (2) production scheduling of the accepted orders and (3) Batch delivery to maximize Total Net Profit. A Mixed Integer Programming is proposed for the problem. In addition, a hybrid meta-heuristic algorithm is developed. For a quick exploration around a solution, a Local search is proposed. Two simple heuristics for initial population and a heuristic for Batching are proposed. Besides, data is generated to evaluate the performance of algorithms and compare with each other based on comprehensive experiments.

Batch sizing in different planning period is categorized as a classical problem in production planning, that so many exact & heuristic methods have been proposed to solve this problem, each of which considering various aspects of the original problem. The solution obtained from majority – e.g. MRP – is in this format that there may be some periods of idleness or each period should produce as needed in different adjacent periods. If there are more the one final independent product to be produced in a factory, this makes the production planning experience strong variations in Batch sizes for different periods, which production managers are opposed to these proposed production plans. In this paper, some of the models are proposed to solve this shortcoming of the production plan to smooth the variation of Batch sizes and consequently to meet the managers ideal. Finally all of the proposed models are used in a real case problem and the best model is introduced in that case.

Nine commercial almond cultivars ('Sahand', 'Yalda', 'Shukofeh', 'Azar', 'Ferragnes', 'Nonpareil', 'Monagga', 'A200' and 'A230') were used for determination of the flower initiation time, stages of morphological development of flower bud, flower buds density in spur, branch spur number of and pistil length. The experiment was conducted in 'Sahand' Horticultural Station during three years. For determination of flower initiation, buds were sampled weekly since 15 August. Results showed a positive correlation between initiation and flowering times. The first flower initiation period was observed in 'Monagha' (27 August) and the last flower organogenesis period was observed in 'Sahand' (26 November). Analysis of variance showed significant differences among cultivars in all studied characteristice (P≤5%). 'Sahand' produced the highest spur in each meter of branches with average of 46 spurs and 'Monagha' produced the highest pistil length with average of 1.85 cm. The important point in all the cultivars used was normal fruit setting despite short pistil production in some of them.

A structured unsegregated cybernetic model is able to describe diauxic growth phenomena of cells colony in aerobic condition. This model shows that the metabolic activity of the cells is regulated by internal cellular controls which direct the micro-organism towards the most convenient metabolic pathway able to optimize the use of available resources. In this paper, for proving this reality, a structured unsegregated cybernetic model have been used for describing of the growth stages of Saccharomyces cerevisiae on mixed substrates. The results of simulation of baker’s yeast in Batch and fed-Batch bioreactor show that agreements are quite satisfactory between experimental data and simulation results. And it well performs in the simulation of the lag-phases and the diauxic growth. Finally, for preventing of oxygen starvation that causes ethanol production, oxygen mass transfer coefficient is simulated on the function of impeller speed and air flow rate and the effect of this parameter on biomass yield have been discussed.

In this paper, just-in-time scheduling problem with Batch delivery and due date assignment for hybrid ow shop robotic cells is considered. A mixed integer linear programming (MILP) model is presented to determine the sequence of jobs and robot moves. Two meta-heuristic algorithms including Arti cial Immune System (AIS) and Tabu Search (TS) are proposed. The results show that AIS performs well for this problem.

This paper presents a comparison between Batch and three different sets of fed Batch fermentations for rhamnolipid production by Pseudomonas aeruginosa.The Batch run was performed with 500 ml of culture medium having the initial glycerol and sodium nitrate concentrations of 30 and 8.3 g/l, respectively. For a fed Batch run with nitrogen source in feed, 250 ml of the nitrogen excluded culture medium was in the bioreactor initially, and 250 ml culture medium containing 16.6 g/l sodium nitrate was fed to the bioreactor continuously.A similar procedure was repeated for fed Batch runs with carbon, and phosphorus source in feed. Statistical analysis showed that fed Batch runs were better than Batch in term of rhamnolipid production, and among the fed Batch runs the maximum amount of rhamnolipid.(4.12 g Rhamnose Equivalent/l) was for the fed Batch run with the carbon source in feed.

This paper addresses a practical but complicated version of Just in Time (JIT) problem in which a set of available jobs with known processing times and due dates are processed on a single machine and delivered in Batches of arbitrary size. A new mathematical model is developed to minimize the non-convex sum of earliness-tardiness and delivery costs criteria. Due to the limitations imposed by the large size complexity of the proposed model and its nonlinear nature, we use the recently proposed league championship algorithm (LCA) to solve arbitrary test problem instances of the problem on hand. Since LCA works in continuous space, we use several representational schemes to map the solutions generated by LCA to discrete space and compare the output of the algorithm under each mapping scenario. To measure how effective LCA is in comparison with the mathematical modeling approach and other heuristic methods, we use the Lingo system and a discrete version of the Imperialistic Competitive Algorithm (ICA) as the comparator algorithms, respectively. Experimental results show that LCA is strongly efficient and dominates the comparator algorithms. At the same time, the time saved by LCA to report the final output is significant, which recommends the use of this algorithm for other practical optimization problems.