يتناول البحث شخصية شعرية وأدبية فذة هو محمد صالح بحر العلوم الشاعر العراقي المعروف والمولود في بيت ثوري من بيوتات النجف المعادية للاستعمار البريطاني في مطلع القرن العشرين، وينحدر من أسرة عريقة مشهورة بالعلم والأدب، عاش بحر العلوم شاعراً ينقل بصوره الجمالية كل ما يقع في حواسه، وتجربته تثري من اتصاله ببيئته فنجد الشاعر اشبه بالمصور يستمد صوره من واقع بيئته المتنوع. ونحن في بحثنا هذا نحاول أن نرصد أهم المصادر

The toxicity effect of some heavy metals (Lead, Cadmium, Copper, and Zinc) on the growth of alga Scenedesmus dimorphus which belongs to the Division of Chlorophyta was studied and depended on the total cell number . The growth rate and doubling time were also calculated accordingly in present of absent of the the heavy metals . There were differences in toxic effects of the metals (p<0.05) . The growth was decreased gradually with alga when exposured to Lead at 15,20 and 25 mg/l in comparison with the control , mean while 30 mg/l caused an acute decrease in growth . Treating the alga with 0.05,0.1,0.5 mg/l concentration of Cadmium the number of cells decreased while at 1 mg/l the effect was more pronounced . As for Copper the conc

Evaluate the acute and chronic toxicity of Ruta Chalepensis aerial part aqueous extract used in folk medicine in Iraq in Albino Wistar male and female rats. The study of chronic toxicity at the doses 100, 300 and 600mg/kg body weight in male and female rats for 90 days, recorded no mortality. Treated animals showed a normal weight change compared with control. The parameters of male fertility showed a significant decrease in the weight of testis, epididymis and seminal vesicle as well as a reduction in the number and the motility of spermatozoids at treated groups by the doses 300 and 600 mg/kg body weight compared to control group.

Ciprofloxacin, which is a second generation of fluoroquinolone and one of the most effective and widely used drugs within fluoroquinolone. Unfamiliar adverse effects of ciprofloxacin such as bone marrow (BM) suppression, thrombocytopenia, anemia, agranulocytosis, renal failure, and others observed. Lutein, is a xanthophyll (an oxygenated carotenoid), was focused by most studies as it has a strong antioxidant activity in vitro; and also, it has been associated with reducing the risk of the age-related disorders. The current study was designed to describe the role of apoptosis through the measurement of Bcl-2 associated X protein (Bax) marker, as mechanisms of bone marrow toxicity induced by ciprofloxacin and to find whether lutei

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database