The survey was carried out From January to April of 2018 on macrofungi samples collected from different places in Halabja province located in north eastern parts of Iraq-Kurdistan region. This region is rich in forest trees and pasture lands with diversity of shrubs and herbs and is expected to support the growth of several macro fungal species. However, this part of Kurdistan in Iraq is still unexplored from macrofungal point of view. In this paper three species from Pezizaceae and Pyronemataceae families that belonging to (Pezizales, Ascomycota), were reported from Iraqi Kurdistan. These macrofungal species are recorded for the first time from Iraq. Also the species were identified and showing their locations distributed on a map prepared

Oryza sativa japonica (ofada rice) is largely grown in Aramoko, Abakaliki and Ofada are communities and consumed by both the poor and rich in Nigeria. A total of twenty ofada rice farmlands were identified in each study area and rice samples were randomly collected, thoroughly mixed to make a representative sample from each farmland. Soil samples were collected in each farm to a depth of 5-15cm from at least eight different points and thoroughly mixed together to form a representative sample. The samples were thereafter taken to the laboratory for preparation and spectroscopic analysis. A well-calibrated NaI(Tl) gamma-ray detector was used in spectrometric analysis of the samples and descriptive statistics was used to analyze th

In this research, the results of x-ray diffraction method were used to determine the uniform stress deformation and microstructure parameters of CuO nanoparticles to determine the lattice strain obtained and crystallite size and then to compare the results obtained by two model Halder Wagner and Size Strain Plot with the results of these methods of the same powder using equations during which the calculation of the size of the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (19.81nm) and the lattice strain (0.004065) of the Halder-wagner model respectively and for the ssp method were the results of the crystallite size (17.20nm) and lattice strain (0.000305) respectively. The sa

Industrial effluents loaded with heavy metals are a cause of hazards to the humans and other forms of life. Conventional approaches, such as electroplating, ion exchange, and membrane processes, are used for removal of copper, cadmium, and lead and are often cost prohibitive with low efficiency at low metal ion concentration. Biosorption can be considered as an option which has been proven as more efficient and economical for removing the mentioned metal ions. Biosorbents used are fungi, yeasts, oil palm shells, coir pith carbon, peanut husks, and olive pulp. Recently, low cost and natural products have also been researched as biosorbent. This paper presents an attempt of the potential use of Iraqi date pits and Al-Khriet (i.e. substances l

Two field experiments were conducted at two different texture sites. The first site of the fields of AlMed-hateya Agriculture Division / Babil Governorate. The second site of the fields of Al-Nouriah Research Station / Ministry of Agriculture, the factors of the study in the two sites included several factors. The first factor includes two irrigation systems: sprinkler irrigation and surface irrigation. The second factor is the method of cultivation which includes the method of cultivation with basin and furrowing. The third factor is the type of the cultivated crop which includes a local variety (Fajr 3) and a hybrid variety (Drakma). The actual water consumption for the sprinkler irrigation system reached (587.13 and 637.62) mm season-1 f

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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