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    Explicit Versus Implicit Instruction: the Case of Request and Apology Speech Acts

    , M.Sc. Thesis Sharif University of Technology Bana, Zahra (Author) ; Salehi, Mohammad (Supervisor)
    Abstract
    The present study was conducted to examine the effect of explicit and implicit teaching of the speech acts of apologies and requests with 40 students. They were given a discourse completion test (DCT) which was designed by the researcher. The students came up with situations that embodied apologies and requests. After exemplar generation and likelihood investigation some 16 items were retained and used with students. The participants of the study consisted of two groups of implicit and explicit. The two groups were intact and randomization was not a possibility. The design was quasi-experimental. To investigate the relationship between grammatical competence and pragmatic competence, the... 

    The effects of postural difficulty conditions on variability of joint kinematic patterns during sit to stand task in normals and patients with non-specific chronic low back pain

    , Article 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, 21 February 2011 through 24 February 2011, Sharjah ; 2011 , Pages 300-303 ; 9781424470006 (ISBN) Tajali, S ; Negahban, H ; Yazdi, M. J. S ; Salehi, R ; Mehravar, M ; Parnianpour, M ; Sharif University of Technology
    2011
    Abstract
    Sit to stand (STS) is one of the most important activities of daily living that is shown to be affected in low back pain (LBP) patients. It requires a fundamental coordination action among all segments (DOFs) of the body in order to control important performance variables such as body's center of mass (CM) within base of support (BOS). In this study, possible differences in joint coordination and variability patterns between chronic LBP and healthy control subjects were investigated during STS task. Eleven adults with nonspecific chronic LBP and 12 healthy controls were recruited in the study. The participants performed the task in 3 exerimental conditions including: rigid surface, open eyes... 

    Parallel nonlinear analysis of weighted brain's gray and white matter images for Alzheimer's dementia diagnosis

    , Article 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, 31 August 2010 through 4 September 2010, Buenos Aires ; 2010 , Pages 5573-5576 ; 9781424441235 (ISBN) Razavian, S. M. J ; Torabi, M ; Kim, K ; Sharif University of Technology
    2010
    Abstract
    In this study, we are proposing a novel nonlinear classification approach to discriminate between Alzheimer's Disease (AD) and a control group using T1-weighted and T2- weighted Magnetic Resonance Images (MRI's) of brain. Since T1-weighted images and T2-weighted images have inherent physical differences, obviously each of them has its own particular medical data and hence, we extracted some specific features from each. Then the variations of the relevant eigenvalues of the extracted features were tracked to pick up the most informative ones. The final features were assigned to two parallel systems to be nonlinearly categorized. Considering the fact that AD defects the white and gray regions... 

    Design and application of (Fe3O4)-GOTfOH based AgNPs doped starch/PEG-poly (acrylic acid) nanocomposite as the magnetic nanocatalyst and the wound dress

    , Article Journal of Molecular Structure ; Volume 1214 , 2020 Forouzandehdel, S ; Meskini, M ; Rami, M. R ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    As a novel, recyclable nanocatalyst, (Fe3O4)-GOTfOH based Ag nanoparticles doped Starch/PEG-poly (acrylic acid) nanocomposite (Fe3O4@GOTfOH/Ag/St-PEG-AcA) was applied for one-pot synthesis of 2,4,6-triarylpyridine derivatives under water solvent conditions. The prepared nanocomposite was also evaluated in terms of biocompatibility for wound healing. Fe3O4@GOTfOH/Ag/St-PEG-AcA could be easily removed from the mixture of the reaction by an external magnet and recycled without a considerable decrease of activity even after 10 runs. The new nanocatalyst offered better efficiencies than other commercially available sulfonic acid catalysts. In terms of the bioactivity of nanocatalyst, good... 

    Fabrication of a novel 3D scaffold for cartilage tissue repair: In-vitro and in-vivo study

    , Article Materials Science and Engineering C ; Volume 128 , 2021 ; 09284931 (ISSN) Haghighi, P ; Shamloo, A ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Self-repairing is not an advanced ability of articular cartilage. Tissue engineering has provided a novel way for reconstructing cartilage using natural polymers because of their biocompatibility and bio-functionality. The purpose of cartilage tissue engineering is to design a scaffold with proper pore structure and similar biological and mechanical properties to the native tissue. In this study, porous scaffolds prepared from gelatin, chitosan and silk fibroin were blended with varying ratios. Between the blends of chitosan (C), gelatin (G) and silk fibroin (S), the scaffold with the weight per volume ratio of 2:2:3 (w/v) showed the most favorable and higher certain properties than the... 

    Discrimination between Alzheimer's disease and control group in MR-images based on texture analysis using artificial neural network

    , Article ICBPE 2006 - 2006 International Conference on Biomedical and Pharmaceutical Engineering, Singapore, 11 December 2006 through 14 December 2006 ; 2006 , Pages 79-83 ; 8190426249 (ISBN); 9788190426244 (ISBN) Torabi, M ; Ardekani, R. D ; Fatemizadeh, E ; Sharif University of Technology
    2006
    Abstract
    In this study, we have proposed a novel method investigates MR-Images for normal and abnormal brains which effected by Alzheimer's Disease (AD) to extract 336 number of different features based on texture analysis. Before applying this algorithm, we have to use a registration method because of variety in size of normal and abnormal images. Consequently, the output of Texture Analysis System (TAS) is a vector containing 336 elements that are features extracted from texture. This vector is considered as the input of the Artificial Neural Network (ANN) which is feed-forward one. The features extracted from the Gray-level Co-occurrence Matrix (GLCM) have been interpreted and compared with normal...