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Enhancing Trade Competitiveness of Pakistan through Trade Facilitation Measures
( Muhammad Hassan Farid ) 한국EU학회 2011 Asia-Pacific Journal of EU Studies Vol.9 No.2
Impasse in Doha Development Agenda has been generating new alternatives which can drive a wedge between export and import prices and the role of trade facilitation policies in bridging that wedge has been recognized among economic and trade pundits. Trade facilitation is multi-faceted area which can shape the competitiveness of trade by interacting with multidimensional spheres of increasing complexity of trade by reducing trade transaction cost.In the case of Pakistan, its global share of export is decreasing since 1999 and export growth is stagnant. Many factors and policies are stayed responsible owing to external and internal environment, political and economic reasons and regional and national policies. Since 1970s, she has not prioritized trade development agenda especially trade facilitation measures aggressively. Many regional as well as East-Asian countries adopted trade facilitation measures vigorously besides trade policies and results have been yielded in the form of elevated share of their products in world markets. Trade facilitation measures particularly custom efficiency, port and logistic efficiency, regulatory environment and e-business usages apart from other traditional trade policies needs to be improved to enhance trade competitiveness in Pakistan.
Hassan, Mubashir,Abbasi, Muhammad Athar,Aziz-ur-Rehman, Muhammad Athar,Siddiqui, Sabahat Zahra,Hussain, Ghulam,Shah, Syed Adnan Ali,Shahid, Muhammad,Seo, Sung-Yum Elsevier 2018 Journal of theoretical biology Vol.458 No.-
<P><B>Abstract</B></P> <P>A new series of multifunctional amides has been synthesized having moderate enzyme inhibitory potentials and mild cytotoxicity. 2-Furyl(1-piperazinyl)methanone (<B>1</B>) was coupled with 3,5-dichloro-2-hydroxybenzenesulfonyl chloride (<B>2</B>) to form {4-[(3,5-dichloro-2-hydroxyphenyl)sulfonyl]-1-piperazinyl}(2-furyl)methanone (<B>3</B>). Different elecrophiles were synthesized by the reaction of various un/substituted anilines (<B>4a-o</B>) with 2-bromoacetylbromide (<B>5</B>), 2‑bromo‑<I>N</I>-(un/substituted-phenyl)acetamides (<B>6a-o</B>). Further, equimolar ratios of <B>3</B> and <B>6a-o</B> were allowed to react in the presence of K<SUB>2</SUB>CO<SUB>3</SUB> in acetonitrile to form desired multifunctional amides (<B>7a-o</B>). The structural confirmation of all the synthesized compounds was carried out by their EI-MS, IR, <SUP>1</SUP>H NMR and <SUP>13</SUP>C NMR spectral data. Enzyme inhibition activity was performed against acetyl and butyrylcholinestrase enzymes, whereby <B>7e</B> showed very good activity having IC<SUB>50</SUB> value of 5.54 ± 0.03 and 9.15 ± 0.01 <I>μ</I>M, respectively, relative to eserine, a reference standard. Hemolytic activity of the molecules was checked to asertain their cytotoxicity towards red blood cell membrance and it was observed that most of the compounds were not toxic up to certain range. Moreover, chemoinformatic protepties and docking simulation results also showed the significance of <B>7e</B> as compared to other compounds. Based on <I>in vitro</I> and <I>in silico</I> analysis <B>7e</B> could be used as a template for the development of new drugs against Alzheimer's disease.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Designing of multifunctional amides derivatives as acetyl and butyrylcholinesterase inhibitors. </LI> <LI> Chemoinformatic, molecular docking and simulation analysis was against most potent inhibitor <B>7e.</B> </LI> <LI> In vitro and in silico results showed the significance of <B>7e</B> and could be used as a template for novel drugs against Alzheimer's disease. </LI> </UL> </P>
Hassan, Mubashir,Abbasi, Muhammad Athar,Aziz-ur-Rehman, Muhammad Athar,Siddiqui, Sabahat Zahra,Shahzadi, Saba,Raza, Hussain,Hussain, Ghulam,Shah, Syed Adnan Ali,Ashraf, Muhamamd,Shahid, Muhammad,Seo, Academic Press 2019 Bioorganic chemistry Vol.91 No.-
<P><B>Abstract</B></P> <P>In the designed research work, a series of 2-furoyl piperazine based sulfonamide derivatives were synthesized as therapeutic agents to target the Alzheimer’s disease. The structures of the newly synthesized compounds were characterized through spectral analysis and their inhibitory potential was evaluated against butyrylcholinesterase (BChE). The cytotoxicity of these sulfonamides was also ascertained through hemolysis of bovine red blood cells. Furthermore, compounds were inspected by Lipinki Rule and their binding profiles against BChE were discerned by molecular docking. The protein fluctuations in docking complexes were recognized by dynamic simulation. From our <I>in vitro</I> and <I>in silico</I> results <B>5c</B>, <B>5j</B> and <B>5k</B> were identified as promising lead compounds for the treatment of targeted disease.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Sulfonamide derivatives were synthesized as therapeutic agents to target the Alzheimer’s disease. </LI> <LI> The inhibitory potential of newly synthesized compounds were evaluated against butyrylcholinesterase (BChE). </LI> <LI> The cytotoxicity of these sulfonamides was also ascertained through hemolysis of bovine red blood cells. </LI> <LI> Computational analysis was performed to check their binding profile against target protein. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Muhammad Ali Shamim,Muhammad Hassan,Sameel Ahmad,Muhammad Zeeshan 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.2
Storage dams play a very important role in irrigation especially during lean periods. For proper regulation one should make sure the availability of water according to needs and requirements. Normally regression techniques are used for the estimation of a reservoir level but this study was aimed to account for a non-linear change and variability of natural data by using Gamma Test, for input combination and data length selection, in conjunction with Artificial Neural Networking (ANN) and Local Linear Regression (LLR) based models for monthly reservoir level prediction. Results from both training and validation phase clearly indicate the usefulness of both ANN and LLR based prediction techniques for Water Management in general and reservoir level forecasting in particular, with LLR outperforming the ANN based model with relatively higher values of Nash-Sutcliffe model efficiency coefficnet (R2) and lower values of Root Mean Squared Error (RMSE) and Mean Biased Error (MBE). The study also demonstrates how Gamma test can be effectively used to determine the ideal input combination for data driven model development.
Survival Analysis and Prognostic Factors for Colorectal Cancer Patients in Malaysia
Hassan, Muhammad Radzi Abu,Suan, Mohd Azri Mohd,Soelar, Shahrul Aiman,Mohammed, Noor Syahireen,Ismail, Ibtisam,Ahmad, Faizah Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.7
Background: Cancer survival analysis is an essential indicator for effective early detection and improvements in cancer treatment. This study was undertaken to document colorectal cancer survival and associated prognostic factors in Malaysians. Materials and Methods: All data were retrieved from the National Cancer Patient Registry-Colorectal Cancer. Only cases with confirmed diagnosis through histology between the year 2008 and 2009 were included. Retrieved data include socio-demographic information, pathological features and treatment received. Survival curves were plotted using the Kaplan-Meier method. Univariate analysis of all variables was then made using the Log-rank test. All significant factors that influenced survival of patients were further analysed in a multivariate analysis using Cox' regression. Results: Total of 1,214 patients were included in the study. The overall 3- and 5-year survival rates were 59.1% and 48.7%, respectively. Patients with localized tumours had better prognosis compared to those with advanced stage cancer. In univariate analysis, staging at diagnosis (p<0.001), primary tumour size (p<0.001), involvement of lymph nodes (p<0.001) and treatment modalities (p=0.001) were found to be predictors of survival. None of the socio-demographic characteristics were found to exert any influence. In Cox regression analysis, staging at diagnosis (p<0.001), primary tumour size (p<0.001), involvement of lymph nodes (p<0.001) and treatment modalities (p<0.001) were determined as independent prognostic factors of survival after adjusted for age, gender and ethnicity. Conclusions: The overall survival rate for colorectal cancer patients in Malaysia is similar to those in other Asian countries, with staging at diagnosis, primary tumor size, involvement of lymph node and treatment modalities having significant effects. More efforts are needed to improve national survival rates in future.
Improving Artificial Neural Network Based Streamflow Forecasting Models through Data Preprocessing
Muhammad Hassan,Ishtiaq Hassan 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.9
The real time hydrological data may contain noise, missing information and deviation from its original scale due to complex and nonlinear nature of hydrological processes. The data when used as it is in hydrological forecasting may create uncertainty in hydrological models, especially in data-driven models which fully rely upon the input-output data. The current research provides a simple preprocessing approach to improve the performance of ANN-based streamflow estimation models through providing a better input state. The two-step preprocessing approach includes; the data transformation through a family of power transformation, the Box-Cox transformation, and the selection of appropriate input variables through the Gamma Test. The original data, which is essentially antecedent upland catchment information of thirteen stations located in Upper Indus Basin (UIB), comprises of twenty inputs, including precipitation, solar radiation and discharge. The Box-Cox transformation has been applied to prepare a transformed data-set and the power factor, λ, (with best value of 0.005), for this transformation, has been determined using probability plots and histogram characteristics. Input combination selection procedure is carried out in WinGamma environment with the help of Genetic Algorithm (GA). Two-layer ANN models have been trained through Broyden, Fletcher and Goldfrab Shano (BFGS) training algorithm for both original and transformed data-sets. The comparison of models clearly indicate that the models developed through transformed data-set showed better performance in both training and testing phases with high values of NSE and R2 which is above 90% in most of the cases, and less other statistical errors including RMSE, VARIANCE and BIAS. Simple preprocessing options, could significantly reduce the uncertainty in ANN based hydrological models through improving the quality of real time hydrological data.
Chorea as a Presentation of SARS-CoV-2 Encephalitis: A Clinical Case Report
Muhammad Hassan,Fibhaa Syed,Liaqat Ali,Haris Majid Rajput,Farhan Faisal,Waleed Shahzad,Mazhar Badshah 대한파킨슨병및이상운동질환학회 2021 Journal Of Movement Disorders Vol.14 No.3
Central nervous system (CNS) involvement in SARS-CoV-2 is now a known fact, likely due to viral transmission through the olfactory nerve and high brainstem viral load, which also suggests dissemination in the ambiguus and solitary nuclei from the respiratory tract via the vagus nerve