Inventory control and pricing for perishable products under age and price dependent stochastic demand

Multistage stochastic programming (SP) with both endogenous and exogenous uncertainties is a novel problem in which some uncertain parameters are decision-dependent and others are independent of decisions. The main difficulty of this problem is that nonanticipativity constraints (NACs) make up a significantly large constraint set, growing very fast with the number of scenarios and leading to an intractable model. Usually, a lot of these constraints are redundant and hence, identification and elimination of redundant NACs can cause a significant reduction in the problem size. Recently, a polynomial time algorithm has been proposed in the literature which is able to identify all redundant NACs in an SP problem with only endogenous uncertainty. In this paper, however, we extend the algorithm proposed in the literature and present a new method which is able to make the upper most possible reduction in the number of NACs in any SP with both exogenous and endogenous uncertain parameters. Proving the validity of this method is another innovation of this study. Computational results confirm that the proposed approach can significantly reduce the problem size within a reasonable computation time.     

Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al₂O₃, and TiO₂) are loaded into the TO. To measure the thermal performance of nanoparticle-based TO nanofluids at laminar flow and under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, the heat transfer coefficient of the abovementioned two-phase systems is increased upon increasing both the volume concentration and the flow rate. An adaptive neuro-fuzzy inference system (ANFIS) is applied for modeling the effect of critical parameters on the heat transfer coefficient of nanoparticle-TO based nanofluids numerically. The results are compared with experimental ones for training and test data. The results suggest that the developed model is valid enough and promising for predicting the extant of the heat transfer coefficient. R² and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modeling by ANFIS is efficient and valid, which can be expanded for more general states.     

A Simple Synthesis of Stable Phosphorus Ylides from Indole and Some of Its Derivatives

Stable crystalline phosphorus ylides were obtained in excellent yields from the 1:1:1 addition reaction between triphenylphosphine and dialkyl acetylenedicarboxylates in the presence of strong NH acids, such as indole and 2-methyl indole, 3-methyl indole, and 5-boromo indole. These stable ylides exist in a solution as a mixture of two geometrical isomers as a result of the restricted rotation around the carbon–carbon partial double bond resulting from the conjugation of the ylide moiety with the adjacent carbonyl group.     

Offline estimation of 2D crystal lattice parameters by processing the electron diffraction image

Electron diffraction provides useful information about the internal composition of materials and has been in the use of material scientists for more than fifty years. In order to extract useful information from offline diffraction images, they are manually analyzed by using some photometric technique. Manual analysis is however a cumbersome, laborious and difficult task. To reduce the labors of material scientists one can employ image processing techniques to perform automated analysis, due to the well established popularity and clear evidence of widely used image processing techniques. In this work an image processing technique is being proposed for the extraction of 2D unit cell information from diffraction images on one hand and finding the 2D point group contained by the lattices on the other. The technique employs a morphological shrinking operation to find the center of each spot in the underlying preprocessed diffraction image. This is followed by the extraction of eight points with reference to the spot produced by the transmitted electron beam. The resultant nine points, i.e. the extracted eight plus the reference spot generated by the transmitted electron beam, are then subjected to symmetry operations, rotation symmetry and mirror symmetry, in polar coordinate system, to classify the point group of the lattice produced by the electron diffraction. One of the difficult task, even in manual analysis, is to ascertain the exact spot where the transmitted electron beam hit the sample at the time of realization of the image. This has been accurately and intuitively done by employing the notion that the transmitted spot must have greater number of pixels, with the highest gray value, among the diffracted spots. The proposed strategy has been applied to a sample set of various images and the results shows that the technique is efficient in determining the unit cell in 2D and classify the point group with good accuracy.     

Formulation and Optimization of Alkaline Extracted Ispaghula Husk Microscopic Reservoirs of Isoniazid by Box-Behnken Statistical Design

The main objective of the present work was to formulate and optimize a microparticulate sustained release drug delivery system of isoniazid by using a novel, alkaline extracted ispaghula husk as a polymer. Isoniazid microspheres of alkaline extracted ispaghula husk were prepared by emulsification internal ionic gelation method. Results of preliminary trials indicated that the polymer concentration, cross-linking agent and stirring speed had a noticeable effect on size and surface morphology. A four-factor three-level Box-Behnken design was employed to study the effect of independent variables on dependent variables. The particle size and entrapment efficiency varied from 30.75 to 61.78 µm and 62.27% to 85.80% respectively, depending on the polymer concentration, concentration of cross-linker and stirring speed. Optimized microspheres batch based on point prediction tool of design software exhibited 83.43% drug entrapment and 51.53 µm particle size with 97.80% and 96.37% validity, respectively at the following conditions: sodium alginate (3.55% w/v), alkaline extracted ispaghula husk (3.60% w/v), cross-linker concentration (7.82% w/v), and stirring speed (1200 rpm). The optimized formulation showed controlled drug release for more than 12 hours. The drug release followed Higuchi kinetics via a non-Fickian diffusion.     

Synthesis, Characterization, Spectroscopy and Study of Antimicrobial Properties of Two New Substituted Trichloroaluminate（Ⅲ） Complexes [AlCl3X]- （X = SCN-, CN-）

The synthesis and characterization of two new aluminate(Ⅲ) complexes with general formula K[AlCl3X] are reported. These compounds derived from aluminate trichloride and related salts. Potassium trichlorothiocyanoaluminate, PCTA, and potassium trichlorocyanatoalu-minate, PCCA, are two new ionic aluminate complexes. They can be easily synthesized in a nearly quantitative yield by using the direct reaction of AlCl3 and KX. The complexes were characterized by physico-chemical and spectroscopic methods. Theoretical calculations have been used for the extraction of structural and spectroscopic data of these new synthesized complexes. The antibacterial activities of such compounds were studied against the Staphylococcus aureus, Escherichia coli, Staphylococcus Epidermidis, Estreptococo B and Shigella.     

Phenylpropanoids from Tanacetum baltistanicum with Nematocidal and Insecticidal Activities

Chemistry of Natural Compounds - One new and seven known secondary metabolites 1–8 were isolated, and the nematocidal and insecticidal activities of major compounds from Tanacetum...