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Positive functional synergy of structurally integrated artificial protein dimers assembled by Click chemistry
Abstract<p>Construction of artificial higher order protein complexes allows sampling of structural architectures and functional features not accessible by classical monomeric proteins. Here, we combine in silico modelling with expanded genetic code facilitated strain promoted azide-alkyne cycloaddition to construct artificial complexes that are structurally integrated protein dimers and demonstrate functional synergy. Using fluorescent proteins sfGFP and Venus as models, homodimers and heterodimers are constructed that switched ON once assembled and display enhanced spectral properties. Symmetrical crosslinks are found to be important for functional enhancement. The determined molecular structure of one artificial dimer shows that a new long-range polar network comprised mostly of organised water molecules links the two chromophores leading to activation and functional enhancement. Single molecule analysis reveals the dimer is more resistant to photobleaching spending longer times in the ON state. Thus, genetically encoded bioorthogonal chemistry can be used to generate truly integrated artificial protein complexes that enhance function.</p>
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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Integrated Problem Based Learning (PBL) Evaluation by Students in Kerbala Medical College

Background: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students

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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
First record of click Beetle Agriotes lineatus (Linneaus ) (Coleoptera : Elateridae )In the middle of Iraq

Trials were carried out in the middle of Iraq ( 3 different sites ) during 2009 to detecation and determined the seasonal occurrence of Agriotes lineatus L. Three YATOR funnel traps were used in each of these sites which baited with the specific pheromone of A. lineatus from the first of March to the end of October in the College of Agriculture - Abu- Ghraib / Provenance of Baghdad and AL-Nile / Provenance of Babylon , while in AL-Radhwania was used through May- June. Pheromone dispenser were changed every 6 weeks in each of these traps . Males of A. lineatus were found in all of the three sites , and the total number capture were 208 , 897 and 57 male / 3 traps / season in College of Agriculture , AL-Nile and AL-Radhwania respectiv

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Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
Mass Transfer Study for Bio-Synergy in Dairy Wastewater Treatment Plant

The present study addresses the behavior of gases in cultivation media as an essential factor to develop the relationship between the microorganisms that are present in the same environment. This relationship was explained via mass transfer of those gases to be a reasonable driving force in changing biological trends. Stripping and dissolution of oxygen and carbon dioxide in water and dairy wastewater were investigated in this study. Bubble column bioreactor under thermal control system was constructed and used for these processes. The experimental results showed that the removal of gases from the culture media requires more time than the dissolution. For example, the volumetric mass transfer coefficient for the removal

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained were 96.5%

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Publication Date
Tue Jan 01 2019
Journal Name
Marine And Petroleum Geology
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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Tue Sep 19 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Density and Approximation by Using Feed Forward Artificial Neural Networks

I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

 

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Pointwise Estimates for Finding the Error of Best Approximation by Spline, Positive Algebraic Polynomials and Copositive

     The first step in this research is to find some of the necessary estimations in approximation by using certain algebraic polynomials, as well as we use certain specific points in approximation. There are many estimations that help to find the best approximation using algebraic polynomials and geometric polynomials. Throughout this research, we deal with some of these estimations to estimate the best approximation error using algebraic polynomials where the basic estimations in approximation are discussed and proven using algebraic polynomials that are discussed and proven using algebraic polynomials that are specified by the following points and  if   as well as if   .

  For the second step of the work, the estimatio

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
On a Subclass of Analytic and Univalent Functions with Positive Coefficients Defined by a Differential Operator

In this paper, a differential operator is used to generate a subclass of analytic and univalent functions with positive coefficients. The studied class of the functions includes:  

 

which is defined in the open unit disk  satisfying the following condition

This leads to the study of properties such as coefficient bounds, Hadamard product, radius of close –to- convexity, inclusive properties, and (n, τ) –neighborhoods for functions belonging to our class.

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