Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pres

This study was conducted to determine the ability of water treatment system (Vortisand) to reduce some chemical and physical properties for tigris river raw water, It consisted of turbidity, electrical conductivity, pH, total hardness, calcium Hardness as well as temperature in order to determine the unit`s efficiency for reducing their concentration as compared to those in the water produced by some classical potable water projects (Dora and Wathba) in Baghdad. Samples were collected during the cold months (December 2016 and January 2017) and during the hot months (May and June 2017). The results showed that this system has the ability to reduce some properties such as turbidity, the values were 215NTU in raw water and decreased to NTU

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

This study included the estimation of growth rate, viability and morphological changes in different culture media (NNN, P-Y, RPMI- 1640, and Panmed). Promastigotes cultured in RPMI-1640 showed maximal growth rate after (2, 4, 6) days of cultivation (27.26 ± 0.05), (172.20 ± 0.1) and (343.81 ± 1.48) million parasites / ml for each day respectively, while P-Y media gave the highest mean of growth rat after (8 and 10) days of cultivation (307.16 ± 1.67) and (303.5 ± 4.96) million parasites / ml for each day respectively. P-Y medium showed the maximal percentage of viability after (2, 4, 6, 8, and 10) days of cultivation (99.76 ± 0.5) %, (98.30 ± 0.17) %, (96.1 ± 0.1) %, (92.5 ± 0.52) % and (87.26 ± 0.05) % for each day respectively.

The objective of this study was shed light for cultivation and maintenance of Trichomonas vaginalis parasite growth after isolated it by vaginal swaps from females suffering vaginitis and abnormal vaginal discharges in these media CPLM and TAB media to detect growth curve, morphological changes and viability of parasite in the two culture media, together with effect of sheep and bovine serum on the growth of it. The results of this studies were showed there was abtaine differences between the two types of media , The maximum growth of parasite was in TAB medium after 72 hours incubation with use of bovine serum, while such growth was maximized after 144 hours incubation with the use of sheep serum. In CPLM medium, a maximum gro

The n-type Au thin films of 500nm thickness was evaporated by thermal evaporation method on p-type silicon wafer of [111] direction to formed Au/Si heterojunction solar cell. The AC conductivity, C-V and I-V characteristics of fabricated c-Au/Si diffusion heterojunction-(HJ) solar cell, has been studied. The first methods demonstrated that the AC conductivity due to with diffusiontunneling mechanism, while the second show that, the heterojunction profile is abrupt, the heterojunction parameters have been played out, such as the depletion width, built-in voltage, and concentration. And finally the third one show that the c-Au/Si HJ has rectification properties, and the solar cell yielded an open circuit voltage of (Vic) 0.4V, short circuit c

Silicon nanowire arrays (SiNWs) are created utilizing the metal-assisted chemical etching method with an Ag metal as a catalyst and different etching time of 15, 30, and 60 minutes using n-Si (100). Physical properties such as structural, surface morphology, and optical properties of the prepared SiNWs are studied. The diameter of prepared SiNWs ranged from 20 to 280 nm, and the reflectance in the visible part of the wavelength spectrum was less than 1% for all prepared samples. The obtained energy gap of prepared SiNWs was around 2 eV, which is higher than the energy gap of bulk silicon. X-ray diffraction (XRD) has diffraction peaks at 68.70^o for all prepared samples. The heterojunction solar cell was fabricated based on the

      In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le