تحليل محتوى مقرر الفقه 2 للمرحلة الثانوية في ضوء معايير أنماط التعلم الفورمات (4MAT) = Analysis of the Content of Jurisprudence Syllabus 2 at Secondary Stage in Light of the Standards of Learning Patterns (4MAT)

2017 ◽  
Vol 2 (2) ◽  
pp. 269-285
Author(s):  
حبة بنت أحمد محمد سعيد أكرم
Keyword(s):  
Standards Of Learning ◽  
Learning Patterns ◽  
Secondary Stage

Environmental Impact Evaluation of Istanbul Wastewater Treatment and Marine Disposal Systems

1992 ◽  
Vol 25 (9) ◽  
pp. 85-92 ◽  
Author(s):  
I. Ozturk ◽  
T. Zambal ◽  
A. Samsunlu ◽  
E. Göknel
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Environmental Impact ◽  
Quality Parameters ◽  
Sea Of Marmara ◽  
General Evaluation ◽  
Marine Outfall ◽  
Secondary Stage ◽  
Pre Treatment

Metropolitan Istanbul Wastewater Treatment System contains 14 marine outfalls, seven of which include secondary stage biological treatment processes. The others have only mechanical treatment units including bar screens and grit chambers. Only one mechanical pre-treatment and marine disposal system, Yenikapi plant, has been operated since 1988 among these 14 plants and six of them are ready for construction. In this paper, the environmental impact of Yenikapi pretreatment and marine disposal system on the water quality of the Bosphorus and the Sea of Marmara has been investigated. Long term water quality measurements which were performed in pre-and post-dischange applications have been evaluated. Water quality parameters including pH, DO, BODs, TKN, P and total coliforms were measured at various sampling stations around the discharge points. A general evaluation of marine outfall systems to be constructed in the scope of Istanbul wastewater treatment project, on the water quality of the Sea of Marmara and the Bosphorus has been presented.

Deep Learning in the Study of Protein-Related Interactions

2020 ◽  
Vol 27 (5) ◽  
pp. 359-369 ◽  
Author(s):  
Cheng Shi ◽  
Jiaxing Chen ◽  
Xinyue Kang ◽  
Guiling Zhao ◽  
Xingzhen Lao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Interactions ◽  
Physiological Data ◽  
Great Promise ◽  
Complex Data ◽  
Protein Protein Interactions ◽  
Learning Patterns ◽  
Introductory Overview ◽  
Protein Research ◽  
Neural Network Theory

: Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In recent years, advances in biological and medical technology have provided us with explosive biological and physiological data, and deep learning-based algorithms have shown great promise in extracting features and learning patterns from complex data. At present, deep learning in protein research has emerged. In this review, we provide an introductory overview of the deep neural network theory and its unique properties. Mainly focused on the application of this technology in protein-related interactions prediction over the past five years, including protein-protein interactions prediction, protein-RNA\DNA, Protein– drug interactions prediction, and others. Finally, we discuss some of the challenges that deep learning currently faces.

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