A freshwater bivalve plays a crucial function in aquatic habitats as the filtered water and burrowing mussels mix the sediment, thus increasing oxygen content and making the ecosystem healthier. The aim of the study is to see how chlorpyrifos affects biochemical markers in freshwater mussel Unio tigridis. About 180 individuals per taxon and water samples were collected from the Qandil water resource on the Greater Zab River, Erbil Province, Iraq. Once arrived at the lab, the individuals were kept in aquaria with river water and an air-conditioned room Temperature: 25±2 and Light: 12h/12h and acclimatized to laboratory conditions for seven days in aged tap water. The mussel's identification molecularly and the DNA sequence of t

Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

The central marshes are one of the most important wetlands/ecosystems in the southern area of Iraq. This study evaluates the bed soil's mechanical, physical, and chemical properties at certain southern Iraqi central marshes sites. This was conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops and for construction purposes. Soil samples were collected from 15 sites at 10-100 cm depth. Hence, numerous parameters were determined: index properties, unconfined compressive strength, direct shear strength, consolidation, texture, and sieve analysis, water content, specific gravity, dry density, permeability, pH, total soluble salts (TSS), organic materials (OM) and total sulfate con

Unsaturated polyester was used as a matrix which was filled with different percentages of cobalt ferrite using hand lay-up method. Cobalt ferrite was synthesized using solid state ceramic method with reagent of CoO and Fe2O3. Mechanical properties such tensile strength, Young's modulus and shore D hardness of the composite have been studied. All these properties have increased by 10% with increasing cobalt ferrite contents. Also the thermal properties such thermal conductivity and specific heat capacity are highly increased as the ferrite content increased, while the thermal diffusivity increased by 22 %. On the other hand dielectric strength of composite has been measured which increased by 50% by increasing the cobalt ferrite content.&

Engineered geopolymer composite (EGC) is a high-performance material with enhanced mechanical and durability capabilities. Ground granulated blast furnace slag (GGBFS) and silica fume (SF) are common binder materials in producing EGC. However, due to the scarcity and high cost of these materials in some countries, sustainable alternatives are needed. This research focused on producing eco-friendly EGC made of cheaper and more common pozzolanic waste materials that are rich in aluminum and silicon. Rice husk ash (RHA), granite waste powder (GWP), and volcanic pumice powder (VPP) were used as partial substitutions (10–50%) of GGBFS in EGC. The effects of these wastes on workability, unit weight, compressive strength, tensile strengt

The central marshes are one of the most important wetlands/ecosystems in the southern area of Iraq. This study evaluates the bed soil's mechanical, physical, and chemical properties at certain southern Iraqi central marshes sites. This was conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops and for construction purposes. Soil samples were collected from 15 sites at 10-100 cm depth. Hence, numerous parameters were determined: index properties, unconfined compressive strength, direct shear strength, consolidation, texture, and sieve analysis, water content, specific gravity, dry density, permeability, pH, total soluble salts (TSS), organic materials (OM) and total

A solar updraft tower power plant (solar tower) is a solar thermal power plant that utilizes a combination of solar

air collector and central updraft tube to generate an induced convective flow which drives pressure staged turbines to generate electricity.

 This paper presents practical results of a prototype of a solar chimney with thermal mass, where the glass surface is replaced by transparence plastic cover. The study focused on chimney's basements kind effect on collected air temperatures. Three basements were used: concrete, black concrete and black pebbles basements. The study was conducted in Baghdad from August to November 2009.

The results show that the best chimney efficiency attaine

         The present study was undertaken to study the effect of apigenin and luteolin on physiological and histological changes in rats treated with cytarabine drugs. Thirty-five albino healthy male adult rats with equal age weighing 250 -300g were enrolled. Rats were randomly divided into seven groups according to the treatment. Group “1” was treated with normal saline and served as the control group. Groups “2,3 and 4”  received cytarabine, apigenin, and luteolin respectively, while groups 5, 6, and 7 received a combination of “apigenin + cytarabine”, “luteolin + cytarabine”, and “apigenin + luteolin + cytarabine”, respectively.  After one week of treatment, all seven groups of rats were

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature