The experiment was conducted in the old botanical garden belong to Biology Department/ College of Education for Pure Science - Ibn Al-Haitham/Baghdad University for growing season 2015-2016 to study the effect of irrigation with four concentrations of sodium chloride (0, 50, 100, 150) mM.L-1 and spraying with selenium in three concentrations (0, 10, 20) mgL-1 on growth of broad bean plant using clay pots. The experiment was design according to completely randomized design (CRD) with three replications. Results indicated that broad bean plant irrigated with saline water and increasing concentrations of sodium chloride in growth medium caused a significant decreased in the plant growth parameters (plant height, no. of compound leaves. Plant-1, leaf area, proline acid content, concentration of nitrogen, phosphorus and potassium) whereas spraying with selenium showed significant increase in growth parameters studied, as for interference for both factors, the best values was at the concentrations 10, 20 mg.L-1 selenium which elevate the adverse effect of high sodium chloride concentration 150 mM.L-1 .
Objective : Multiple sclerosis (MS) is a common neurological disease deeply linked with the immune-inflammatory disorders whereas the term (multiple) mostly refers to the multi-focal zones of Inflammation caused by lymphocytes and macrophages infiltration besides oligodendrocytes death. Accordingly , the dysfunctional immune system able to damage myelin ( a pivotal component of the central nervous system ) which responsible for communication among neurons. The aim of the present study is to innovate a biochemical relationship between MS and thyroid hormones (THs) by highlighting immunological responses and also to examine the action of Interferon beta (IFNβ) drug on thyroid hormone (THs) and thyroid stimulation hormone (TSH). Materials and
... Show MoreThe study aimed to reveal the extent of the first intermediate grade science curriculum focus on the national values, health, environmental, economic values, in the light of the education policy in the Kingdom of Saudi Arabia, in addition to present a proposed vision to strengthen it in the science curriculum for the first intermediate grade. The study was applied to the two books student and the two books of activity on the first-second semesters for the academic year 1441 AH. To analyze the curriculum content, the study used a verified card prepared by the researchers and a criterion for interpreting percentages. The study reached the following results: environmental values ranked first with a concentration of (43%), i.e. with an avera
... Show MoreFor the design of a deep foundation, piles are presumed to transfer the axial and lateral loads into the ground. However, the effects of the combined loads are generally ignored in engineering practice since there are uncertainties to the precise definition of soil–pile interactions. Hence, for technical discussions of the soil–pile interactions due to dynamic loads, a three-dimensional finite element model was developed to evaluate the soil pile performance based on the 1 g shaking table test. The static loads consisted of 50% of the allowable vertical pile capacity and 50% of the allowable lateral pile capacity. The dynamic loads were taken from the recorded data of the Kobe e
Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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