The practical picture was clear in the statement of the foundations of moderation and its impact on the future of the nation, and in it a statement of the foundations on which moderation is based as the foundations for building moderation, the goals that moderation seeks and the desired results as a result of the applications of moderation. It was about the positive impact of moderation on the future of the nation in maintaining social balances such as economic, cultural and political balance and preserving freedoms.

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In this work, porous Silicon structures are formed with photochemical etching process of n-type Silicon(111) wafers of resistivity (0.02.cm) in hydrofluoric acid (HF) of concentration (39%wt) under light source of tungeston halogen lamp of (100 Watt) power. Samples were anodized in a solution of 39%HF and ethanol at 1:1 for 15 minutes. The samples were realized on n-type Si substrates Porous Silicon layers of 100m thickness and 30% of porousity. Frequency dependence of conductivity for Al/PSi/Si/Al sandwich form was studied. A frequency range of 102-106Hz was used allowing an accurate determination of the impedance components. Their electronic transport parameters were determined using complex impedance measurements. These measu

This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a