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RISS 인기검색어
- 검색키워드
- 저자 : Mohammad Irfan Khan (검색결과 4 건)
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Mohammad Tarique1,Badruddeen,Farogh Ahsan,Juber Akhtar,Mohammad Irfan Khan,Mohammad Khalid 경희대학교 융합한의과학연구소 2019 Oriental Pharmacy and Experimental Medicine Vol.19 No.4
The present study aims at formulation development and pharmacological evaluation of fxed dose combination of Bombyx mori (Abresham) extract, Flaxseed oil and coenzyme Q10 (CoQ10) against doxorubicin induced myocardial toxicity in rats. Formulation (emulsion) was prepared using dry gum method (continental method), by using pestle and mortar. The formulation was characterized by performing stability studies which includes focculation and creaming, cracking, phase inversion and accelerated studies (temperature and light). In-vivo pharmacological evaluation of Bombyx mori extract, Flaxseed oil, CoQ10 and its fxed dose combination (FDC) were then performed. Results obtained indicates that developed FDC and extract, Oil, CoQ10 passed all stability tests and signifcantly prevented drug induced increase in serum levels of AST, ALT, LDH, Creatinine and lipid profle (TC, LDL, VLDL and TG) and increases the levels of HDL and antioxidant parameters— SOD, GSH and CAT (in heart tissue). It also lowered the doxorubicin induced increase in heart weight due to hypertrophy. These results were also confrmed by histopathology. The results of this study strongly indicate the cardioprotective efect of fxed dose combination of BME, Flaxseed oil and CoQ10 against doxorubicin induced myocardial toxicity.
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M. Irfan Marwat,Javed Ali Khan,Dr. Mohammad Dahman Alshehri,Muhammad Asghar Ali,Hizbullah,Haider Ali,Muhammad Assam 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.3
[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.
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Measurement of Traffic-Related Air Pollution in Peshawar, Pakistan - A Pilot Study
Mohsin Khan,Mohammad Abdul Aziz Irfan,Najeeb Ullah 한국대기환경학회 2021 Asian Journal of Atmospheric Environment (AJAE) Vol.15 No.4
This pilot study measured Traffic-Related Air Pollution (TRAP) and calculated the corresponding Air Quality Index (AQI) in Peshawar. Using Libelium wireless sensors, the research measured outdoor TRAP and monitored indoor air quality for 48 days. The maximum outdoors daily mean concentration was 47 μg m-3 for PM1, 90 μg m-3 for PM2.5, 356 μg m-3 for PM10, 258 ppb for SO2, and 219 ppb for NO2, respectively. This corresponds to PM2.5 AQI of 158 (Unhealthy), PM10 AQI of 148 (Unhealthy for Sensitive Groups; USG), SO2 AQI of 181 (Unhealthy), and NO2 AQI of 123 (USG). The maximum daily average concentration for the indoor condition was 31 μg m-3 for PM1, 49 μg m-3 for PM2.5, 78 μg m-3 for PM10, 465 ppb for SO2, and 247 ppb for NO2, respectively. The corresponding AQI was 135 (USG) for PM2.5, 62 (Moderate) for PM10, 254 (Very Unhealthy) for SO2, and 129 (USG) for NO2. Data analysis shows that about 73% of the overall indoor AQI falls in the category of “USG”, while SO2 was the largest contributor to overall AQI. The study concludes that indoor AQI was slightly better than outdoor AQI because of the distance and height from the outdoor location. Moreover, Pakistan’s AQI for PM2.5 exceeds WHO’s 24-hours limit; however, it was relatively better by 23%, 65%, and 170% compared to China, India, and Bangladesh, respectively. In contrast, AQI for SO2 and NO2 was poor as compared to the same countries. The concentration and AQI for traffic-related air pollutants remain unhealthy and sometimes becomes hazardous, which means the sensitive groups are at greater risk.
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Numerical analysis of heat transfer in human head
Sarfaraz Kamangar,Mohammad Anas Khan,Irfan Anjum Badruddin,T. M. Yunus Khan,Nik. Ghazali. N 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.7
An investigation of heat transfer in human head is carried out by using finite element method. The head is modeled with different tissues having varying physical properties. The current work is focused to simulate the effect of various physical and geometrical parameters such as ambient temperature, heat transfer coefficient and variation in the thickness of different tissue layers of human head. The effect of presence of hair on human head is also investigated. It is found that the deep brain temperature remains almost constant whereas a small variation occurs in the other layers with respect to varying environmental and geometrical parameters.
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