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Ambrin Fatima,Muhammad Farooq,Uzma Abdullah,Muhammad Tariq,Tanveer Mustafa,Muhammad Iqbal,Niels Tommerup,Shahid Mahmood Baig 대한신경정신의학회 2017 PSYCHIATRY INVESTIGATION Vol.14 No.5
Objective: Schizophrenia is a chronic neuropsychiatric disease afflicting around 1.1% of the population worldwide. Recently, MIR137, CACNA1C, CSMD1, DRD2, and GRM3 have been reported as the most robustly emerging candidates involved in the etiology of schizophrenia. In this case control study, we performed an association analysis of rs1625579 (MIR137), rs1006737, rs4765905 (CACNA1C), rs10503253 (CSMD1), rs1076560 (DRD2), rs12704290, rs6465084, and rs148754219 (GRM3) in Pakistani population. Methods: Schizophrenia was diagnosed on the basis of the Diagnostic and Statistical Manual of Mental Disorders 4th ed (DSM-IV). Detailed clinical information, family history of all patients and healthy controls were collected. RFLP based case control association study was performed in a Pakistani cohort of 508 schizophrenia patients and 300 healthy control subjects. Alleles and genotype frequencies were calculated using SPSS. Results: A significant difference in the genotype and allele frequencies for rs4765905, rs1076560 and rs6465084 were found between the patients and controls (p=0.000). Conclusion: This study provides substantial evidence supporting the role of CACNA1C, GRM3 and DRD2 as schizophrenia susceptibility genes in Pakistani population.
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Challenges and Issues of Resource Allocation Techniques in Cloud Computing
( Adnan Abid ),( Muhammad Faraz Manzoor ),( Muhammad Shoaib Farooq ),( Uzma Farooq ),( Muzammil Hussain ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.7
In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.
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Structural and Electromechanical Behavior Evaluation of Polymer-Copper Nanocomposites
Gulfam Nasar,Muhammad Azhar Khan,Muhammad Farooq Warsi,Muhammad Shahid,Uzma Khalil,Muhammad Saleem Khan 한국고분자학회 2016 Macromolecular Research Vol.24 No.4
Copper nanoparticles were prepared by chemical reduction of copper nitrate by sodium borohydride as a reducing agent in de-ionized water/acetonitrile mixture. The prepared nanoparticles were incorporated in poly(vinyl alcohol) (PVA) by physical dispersion method to obtain PVA/copper nanocomposites. Various compositions of nanocomposites were obtained by changing the w/w ratio of nanoparticles with the polymeric material. The prepared nanocomposites cast into films of uniform thickness. The composite films were subjected to the electrical, mechanical and surface morphology characterization. AC Impedance was figured out by AC Impedance analyser. The results illustrated that copper nanoparticles impart electrical conductivity in poly(vinyl alcohol). Moreover, electrical conductivity of the composites exhibited an increase with an increase of w/w% of the copper nanoparticles in poly(vinyl alcohol). Tensile properties were studied in terms of tensile strength, elongation at break and Young’s modulus. Elongation at break and Young’s modulus values demonstrated an increase while tensile strength displayed a decrease at higher concentration of the copper nanoparticles in the composites. AFM results unfolded the surface morphology of the composites illustrating a smooth surface with evenly distributed copper nanoparticles in the polymer matrix. The dimensions of the uneven surface is attributed to the copper nanoparticles were estimated to be of a range less than 100 nm. The prepared nanocomposites are suggested as potential candidates in charge storing devices.
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