In order to predict the behavior of soil-related phenomena, it is necessary to have knowledge about unsaturated flow and using models that provide optimal estimates of the retention curve and hydraulic Conductivity of soils. Despite the widespread use of the classic van Genuchten-Mualem model (VGM), this model usually performs poorly in predicting hydraulic Conductivity and modification of some of its parameters seems necessary. In this research, 283 soils from different textures of the UNSODA bank were selected and divided into two sections of calibration and validation and their soil parameters were exported and categorized. Then, by defining the modified unsaturated hydraulic Conductivity (Ksc) instead of the saturated hydraulic Conductivity (Ks) and determining the limits for l and n parameters, the hydraulic Conductivity-moisture function of VGM were solved using 24600 pairs of points li and nj for each soil of the three main soil texture classes. In the following, the optimal l value (l̂) of each texture class was selected based on the minimum value of the hydraulic Conductivity estimation error using the root mean square error (RMSE) index and the n values that had created the minimum errors, were selected as the optimal pore size distribution coefficients of the hydraulic Conductivity-moisture function (n̂opt). In order to create pedotransfer functions for estimating n̂opt, we ran stepwise regression in MATLAB software considering the condition of statistical significance (P-value=0.05) for independent variables and functions for each soil texture class. After creating pedotransfer functions, the results of the proposed method of this research (MVGM) were compared with the VGM results using RMSE and Nash-Sutcliffe (NSE) indices. The results showed that in both sections of creation and validation functions, the MVGM performed better in estimating hydraulic Conductivity and had a higher efficiency index in all textural classes of soil.

Application of feed pellets in animal and aquatic farming industries has grown because of both the physical and the nutritional benefits it provides. Development of feed pellets manufacturing industry is also considerable. Steam conditioning process, which plays an important role in pelleting production, includes heating feed particles, adding moisture, and mixing the mash. Pellets cooling and drying processes are also involved in heat transfer phenomena. In this study, thermal Conductivity of feed pellets was determined at different temperatures ranging from 25 to 85oC and moisture contents of 11.8 to 18.2% wb. It was measured by the transient technique using the line heat source method assembled in a thermal Conductivity probe. It turned out that decreasing moisture contents from 18.2 to 11.8% (wb) produced non-linear reduction in thermal Conductivity.The average values of thermal Conductivity changed from 0.1509 to 0.2143 W m-1 oC-1 at different moisture contents. Tests conducted on two pellet size categories (based on nominal diameter) revealed a significant difference in thermal Conductivity between these categories. The thermal conductivities of the first category (minor than nominal dia.) appeared to be 8.5% higher than those of the second category (superior to nominal dia.).Average values of thermal Conductivity changed from 0.1538 to 0.2333 W m-1 oC-1 for the first category and from 0.1235 to 0.2456 W m-1 oC-1 for the second category (in 25oC). In addition, some empirical models were developed to express thermal properties as a function of moisture content and temperature.

In this study, spin Conductivity of gapped graphene using Hubbard model is calculated. We obtain spin Conductivity for two cases: in the absence of coulomb interaction and in the presence of coulomb interaction between electrons. It can be seen that for the non-itercting case, by increasing the magnetization, the peaks of spin Conductivity will be shifted towards lower frequencies and the height of them rises. By increasing the energy gap, the peaks of spin Conductivity will be shifted towards higher frequencies and the height of them rises. In the interacting case, plots of spin Conductivity versus frequency have two peaks. One of them belongs to spin up electrons and the other belongs to spin down electrons. By increasing magnetization, the peaks of spin up electrons will be shifted towards lower frequencies and the peaks of spin down electrons will be shifted towards higher frequencies. By increasing the repulsion coulomb interaction and the energy gap, spin up and spin down peaks will be shifted towards higher frequencies.

An empirical electrical Conductivity assessment of nanofluids comprising CuO nanoparticles water-based in different concentrations, particles size and various temperatures of nanofluids has been carried out in this paper. These experimentations have been done in deionized water with nanoparticles sizes such as 89, 95, 100 and 112 nm and concentrations of 0.12 g/l, 0.14 g/l, 0.16 g/l and 0.18 g/l so nanofluids obtain in temperatures such as 25oC, 35oC, 45oC and 50oC for investigation of their electrical Conductivity. It is observed that, in water-based nanofluids, the electrical Conductivity increases with increasing in both nanofluids temperatures and concentration respectively in the range 25-50oC and 0.12-0.18g/l. But in nanoparticles size rising in nanofluids we observe that electrical Conductivity has a few increase when nanoparticles have 95nm diameters, so decrease for biggest nanoparticles such as 100 and 112nm. It seems that there is an optimum in electrical Conductivity with resize of nanoparticles.

In this paper, we aim to investigate the electric Conductivity of an out of equilibrium system of QCD at low temperatures. One way to study such systems is to apply a time dependent electric field and examine the out of equilibrium behavior of the system. The electric field produces pairs of quarks and antiquarks from the field theory vacuum leading to an electric current. By using the relation between the applied electric field and its relevant current, the electric Conductivity of the field theory can be obtained. We use a non-critical holographic model of QCD to study the time dependent out of equilibrium solution of the system non-perturbatively and examine the effects of parameters such as electric field magnitude and frequency as well as the charge density on electric Conductivity. Finally, we compare our results with those from other holographic models.

Liquid paraffin as a coolant fluid can be applied in electronic devices as a result to its suitable capabilities such as electrical insulating, high heat capacity, chemical and thermal stability, and high boiling point. However, the poor thermal Conductivity of paraffin has been confined its thermal cooling application. Addition of high conductor nanoparticles to paraffin can fix this drawback properly. In this article, the influence of the nanoparticles on the thermal Conductivity of base material was assessed. Temperature (20-50° C) and volume fractions (0-3%) effect on the thermal Conductivity of paraffin/alumina nanofluids have been considered. Nanofluid samples were prepared applying the two-step method. The thermal Conductivity was measured by a KD2 pro instrument. The results indicated the thermal Conductivity augments smoothly with an increase in volume fraction of nanoparticles as well as temperature. Moreover, it observed that for nanofluids with more volume-fraction the temperature affection is more remarkable. Thermal Conductivity enhancement (TCE) and effective thermal Conductivity (ETC) of the nanofluid was calculated and new correlations were reported to predict the values of them based on the volume fraction of nanoparticles and temperature of nanofluid accurately.

Time domain reflectometry (TDR) is a widely used method for measuring the dielectric constant (Ka) and bulk electrical Conductivity (σa) in soils. The TDR- measured σa and Ka can be used to calculate the soil solution electrical Conductivity, (σp). A theoretical model describing a linear relationship between bulk electrical Conductivity, σa, and dielectric constant, Ka, in moist soil was already presented. By using this linear relationship, the pore water electrical Conductivity, σp, can be estimated in a wide range of soil types without soil- specific calibration. The objective of this study was to evaluate the linear model presented previously for TDR. The previous study was on light texture soils but in this study we used clay, clay loam, loam, silty clay and silty clay loam textures. The results showed that the linear model performed well for light texture soils but not for heavy textures. Such poor result for heavy texture is mainly due to this fact that dielectric constant pore water was lower than 80 which was proposed as default by model. This study showed that for heavy texture soils dielectric constant of pore water is smaller than light textured soils.