Adoption of New Irrigation Technology Under Production Risk

This paper investigates the factors affecting adoption of new irrigation technologies and also addresses the linkage between this type of technology and production risk. The risk-premium associated with the use of water is estimated by adapting a moment-based approach. Farm-level data were collected from a sample of 187 wheat farms, located in the three major districts of Fars province of Iran during the years 2002 and 2003. Results of this study demonstrate that the risk premium decrease with new irrigation technology. Also, it is concluded that the farmer-specific relative risk premium has positive and significant effect on the decision to adopt the new irrigation technologies. So, farmers that are more risk-averse with respect to their use of water are more likely to adopt new irrigation technologies that allow them to save water and decrease their production (yield) risk.     

A Comparison Between Cold-Welded and Diffusion-Bonded Al/Cu Bimetallic Rods Produced by ECAE Process

In this research, the application of equal channel angular extrusion process to produce both the cold-welded and diffusion-bonded Al/Cu bimetallic rods is assessed. The joints shear strength for both of the methods are measured and compared. The microstructure examinations were also carried out using scanning electron microscope equipped with EDX system and x-ray diffraction analysis. The results exhibit that the strength of the bond in cold-welded specimens is dependent on the amount of stretch and pressure at the materials interface. But in the diffusion-bonded specimens, it is depended on the struggle between the oxidation rate of the mating surfaces accompanied by inter-metallic compounds formation and the aluminum and copper atoms ability to diffuse in the joint interface.     

Quantitative Microstructural Analysis of Formability Enhancement in Dual Phase Steels Subject to Electrohydraulic Forming

Under certain conditions, strain rate sensitive materials such as dual phase steels, show formability improvement under high strain rate forming which is known as hyperplasticity. In this research, two commercial dual phase steel sheets, DP500 and DP780, were formed under quasi-static conditions using the Nakazima test and under high strain rate conditions by electrohydraulic forming (EHF) into a conical die. Macro-strains, measured from electro-etched circle grids with an FMTI analyzer, showed remarkable formability improvement in EHF specimens. Micro-strains, i.e., the strains in the ferrite and the martensite, were calculated by quantitative metallography of more than 7000 ferrite grains and 10,500 martensite islands. The goal was to investigate the deformation improvement of the constituents under EHF. Around 20 and 100% deformation improvements were observed in ferrite and martensite, respectively. Furthermore, as a micro-mechanical modeling technique, correlation of the micro-strains with the macro-strains was investigated by applying the mixture rule. Results showed a reasonable correlation between the macro and micro-scale strains; however in banded microstructures, the strain in the martensite should be determined precisely for more accuracy.     

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC₁’s) scores, the MSPI would be simply attained by dividing PC₁’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC₁ is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.     

Biologically‐synthesised ZnO/CuO/Ag nanocomposite using propolis extract and coated on the gauze for wound healing applications

Wound healing has long been recognised as a major clinical challenge for which stablishing more effective wound therapies is necessary. The generation of metallic nanocomposites using biological compounds is emerging as a new promising strategy for this purpose. In this study, four metallic nanoparticles (NPs) with propolis extract (Ext) and one without propolis including ZnO/Ext, ZnO/Ag/Ext, ZnO/CuO/Ext, ZnO/Ag/CuO/Ext and ZnO/W were prepared by microwave method and assessed for their wound healing activity on excision experimental model of wounds in rats. The developed nanocomposites have been characterised by physico‐chemical methods such as X‐ray diffraction, scanning electron microscopy, diffuse reflectance UV–vis spectroscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis and Brunauer–Emmett–Teller analyses. The wounded animals treated with the NPs/Ext in five groups for 18 days. Every 6 days, for measuring wound closure rate, three samples of each group were examined for histopathological analysis. The prepared tissue sections were investigated by haematoxylin and Eosin stainings for the formation of epidermis, dermis and muscular and Masson''s trichrome staining for the formation of collagen fibres. These findings toughly support the probability of using this new ZnO/Ag/Ext materials dressing for a wound care performance with significant effect compared to other NPs.Inspec keywords: nanomedicine, X‐ray diffraction, II‐VI semiconductors, visible spectra, ultraviolet spectra, nanocomposites, biomedical materials, proteins, wounds, nanoparticles, scanning electron microscopy, nanofabrication, skin, zinc compounds, silver, antibacterial activity, Fourier transform infrared spectra, copper compounds, molecular biophysicsOther keywords: propolis, wound healing applications, effective wound, metallic nanocomposites, biological compounds, metallic nanoparticles, microwave method, wound healing activity, physico‐chemical methods, Fourier transform infrared spectroscopy, diffuse reflectance UV‐vis spectroscopy, Brunauer‐Emmett‐Teller analyses, wounded animals, wound closure rate, wound care performance, histopathological analysis, scanning electron microscopy, X‐ray diffraction, thermogravimetric analysis, haematoxylin, Eosin stainings, Masson trichrome, epidermis, muscular trichrome, collagen fibres, time 18.0 d, time 6.0 d, ZnO‐CuO‐Ag     

Computer simulation of the effect of post annealing parameters on the microstructure inhomogeneity of the non-uniformly deformed copper

A computer simulation on the basis of the Finite Element Method and Monte Carlo Model is developed to simulate the microstructure of the non-uniformly deformed copper workpiece after annealing. Using the computer simulation, the effects of annealing time and temperature on the microstructure inhomogeneity of the workpiece are simulated and investigated quantitatively, by defining an Inhomogeneity Factor, to design an annealing program for reducing the microstructure inhomogeneity. The results show that with increasing the parameters of annealing time and temperature, the inhomogeneity is decreased when one of the parameters is constant. Also, at high annealing temperature, the annealing time changes the inhomogeneity slowly compared with which occurs at low annealing temperature. The simulation results agree well with the experimental values.     

Moisture susceptibility of warm mixed-reclaimed asphalt pavement containing Sasobit and Zycotherm additives

In this research, the influence of Sasobit and Zycotherm on the properties of reclaimed asphalt pavement (RAP)-warm mix asphalt (WMA) was investigated. Moisture susceptibility was evaluated applying the resilient modulus ratio, the indirect tensile strength ratio, and the fracture energy ratio. Laboratory testing results indicated that Zycotherm mixtures had more resistance to moisture damage than Sasobit WMA and hot mix asphalt (HMA) mixtures. The stiffness of mixtures increased dramatically by increasing the amount of RAP and using Sasobit exacerbated this problem.     

Prediction of hydrate equilibrium conditions using k-nearest neighbor algorithm to CO2 capture

Gas or clathrate hydrates are an important issue when they form in the oil and gas pipelines. Since the determination of the hydrate formation temperature and pressure is very difficult experimentally for every gas system and it is impossible in terms of cost and time approximately, mathematical models can be useful tools to overcome these difficulties. In this study, k-nearest neighbor model was used to predict the equilibrium conditions of hydrate formation in absorption and separation of carbon dioxide from flue gas mixture, containing carbon dioxide and nitrogen. At the training phase, temperature and composition data of nitrogen and carbon dioxide in the flue gas mixture at equilibrium conditions and the equilibrium pressures of hydrate formation were used as input and output, respectively. The error percentage less than 0.38% indicates the high accuracy of the proposed model. In this study, 80%, 85%, and 90% of the training data are examined for three numbers of nearest. For three numbers of used nearest (k = 1, k = 2 and k = 3), the value of k = 1 leads to the lowest error; so, it is selected as the best nearest in the presented model.