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Tectonic Study of the Sub-Himalayas Based on Geophysical Data in Azad Jammu and Kashmir and Northern Pakistan

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Journal of Earth Science 2016年第6期27卷 981-988页

作者： Muhammad rustam khan Fahad Hameed Muhammad Saleem Mughal Muhammad Basharat Sohail Mustafa Institute of Geology University of Azad Jammu and Kashmir Muzaffarabad

The tectonic study based on geophysical data has been carried out in Sub-Himalayas in Azad Jammu and Kashmir and northern Pakistan. A series of thin skinned and thick skinned faults have been delineated in the investigated area on the basis of present study. In the study area compressional stresses caused by the collisional of Indian and Eurasian plates developed the northwestsoutheast trending faults which are Shaheed Gala thrust, Bagh basement fault, Kashmir boundary thrust and Kawai fault or Indus Kohistan seismic zone. The crustal thickness increases towards north due to the stacking of the thrust sheets along these faults. The Murree Formation thrusts over the Si- waliks molasse along the Shaheed Gala thrust. This fault dips at an angle of 43° northeast and joins the thick skinned Bagh basement fault in subsurface which are penetrated up to Moho depth. In the northeast of Bagh basement fault the northwest-southeast trending Kashmir boundary thrust has been delineated in the sedimentary-metasedimentary wedge which joins the Indus Kohistan seismic zone in the subsurface. The present study suggested that the Kawai fault which is running within Murree Formation cuts 16 km thick sedimentary-metasedimentary wedge and also joins the Indus Kohistan seismic zone in the subsurface.

关键词： tectonic study Sub-Himalayas Bouguer anomaly magnetic anomaly gravity modeling.

Regolith thickness modeling using a GIS approach for landslide distribution analysis, NW Himalayas

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Journal of Mountain Science 2018年第11期15卷 2466-2479页

作者： Muhammad BASHARAT Masood QASIM Muhammad SHAFIQUE Nasir HAMEED Muhammad Tayyib RIAZ Muhammad rustam khan Institute of Geology University of Azad Jammu and Kashmir National Center of Excellence in Geology University of Peshawar Land Use Planning and Development Department Azad Jammu and Kashmir

Regolith thickness is considered as a contributing factor for the occurrence of ***, mostly it is ignored because of complex nature and as it requires more time and resources for investigation. This study aimed to appraise the role of regolith thickness on landslide distribution in the Muzaffarabad and surrounding areas, NW *** this purpose regolith thickness samples were evenly collected from all the lithological units at representative sites within different slope and elevation classes in the field. Topographic attributes(slope, aspect, drainage, Topographic Wetness Index,elevation and curvature) were derived from the Digital Elevation Model(DEM)(12.5 m resolution).Arc GIS Model Builder was used to develop the regolith thickness model. Stepwise regression technique was used to explore the spatial variation of regolith thickness using topographic attributes and lithological units. The derived model explains about 88% regolith thickness variation. The model was validated and shows good agreement(70%) between observed and predicted values. Subsequently, the derived regolith model was used to understand the relationship between regolith thickness and landslide distribution. The analysis shows that most of the landslides were located within 1-5 m regolith thickness. However, landslide concentration is highest within 5-10 m regolith thickness, which shows that regolith thickness played a significant role for the occurrence of landslide in the studied area.

关键词：厚度变化喜马拉雅山脉 GIS 表土山崩分发模特儿土模型

Helicobacter pylori outer membrane protein Q genotypes and their susceptibility to antiadhesive phytotherapeutic agents

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Journal of Integrative Medicine 2017年第5期15卷 398-406页

作者： Javed Yakoob Zaigham Abbas Malik Hassan Mehmood Kanwal Tariq Saima Azhar Saleem Safia Awan Abdul Malik Saeed Hamid rustam khan Wasim Jafri Department of Medicine Aga Khan UniversityKarachi 74800Pakistan Department of Biological Biomedical Sciences Aga Khan UniversityKarachi 74800Pakistan

OBJECTIVE： Helicobacter pylori is a Gram-negative organism. Its outer membrane protein Q（Hop Q） mediates host-pathogen interactions; Hop Q genotypes 1 and 2 are found associating with gastroduodenal pathologies. The authors measured the anti-adhesion effects of the extracts of Abelmoschus esculentus, Zingiber officinale, Trachyspermum ammi, Glycyrrhiza glabra, Curcuma longa and Capsicum annum against Hop Q genotypes and H. pylori cytotoxin-associated gene A（Cag A）.METHODS： DNA was extracted by polymerase chain reaction of the Hop Q genotypes（i.e., type 1, type 2 and Cag A） from 115 H. pylori strains. The effect of the extracts from selected dietary ingredients was determined using a gastric adenocarcinoma cell line and a quantitative DNA fragmentation assay. The anti-adhesive effect of these extracts on H. pylori was tested using an anti-adhesion ***： C. annum, C. longa and A. esculentus showed prominent anti-adhesion effects with resultant values of 17.3% ± 2.9%, 14.6% ± 3.7%, 13.8% ± 3.6%, respectively, against Hop Q type 1 and 13.1% ± 1.7%, 12.1% ± 2%, 11.1% ± 1.6%, respectively, against Hop Q type 2. C. longa（93%）, C. annum（89%） and A. esculentus（75%） had better anti-adhesive activity against H. pylori with Hop Q type 1 compared to Hop Q type 2 with respective values of 70%, 64% and 51%. Extracts of C. annum（14.7% ± 4.1%）, A. esculentus（12.3% ± 4.1%） and Z. officinale（8.4% ± 2.8%） had an anti-adhesion effect against Cag A-positive H. pylori strains compared to Cag A-negative strains.

关键词： outer membrane protein Q Helicobacter pylori anti-adhesion Abelmoschus esculentus Capsicum annum Curcuma Ionga

Diagnostic dilemma of abdominal tuberculosis in non-HIV patients:An ongoing challenge for physicians

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World Journal of Gastroenterology 2006年第39期12卷 6371-6375页

作者： rustam khan Shahab Abid Wasim Jafri Zaigham Abbas Khalid Hameed Zubair Ahmad Section of Gastroenterology Department of Medicine The Aga Khan University Hospital Karachi Pakistan Department of Surgery The Aga Khan University Hospital Karachi Pakistan Department of pathology The Aga Khan University Hospital Karachi Pakistan

AIM: To assess the clinical features, yield of the diagnostic tests and outcome of abdominal tuberculosis in non-HIV patients. METHODS: Adult patients with discharge diagnosis of abdominal tuberculosis (based upon; positive microbiology, histo-pathology, imaging or response to trial of anti TB drugs) during the period 1999 to 2004 were analyzed. Patient’s characteristics, laboratory investigations, radiological, endoscopic and surgical findings were evaluated. Abdominal site involved (intestinal, peritoneal, visceral, and nodal) and response to treatment was also noted. RESULTS: There were 209 patients enrolled. One hundred and twenty-three (59%) were females. Symptoms were abdominal pain 194 (93%), fever 134 (64%), night sweats 99 (48%), weight loss 98 (47%), vomiting 75 (36%), ascites 74 (35%), constipation 64 (31%), and diarrhea 25 (12%). Sub-acute and acute intestinal obstruction was seen in 28 (13%) and 12 (11%) respectively. Radiological evidence of pulmonary tuberculosis was found in 134 (64%) patients. Basis of diagnosis of abdominal tuberculosis were radiology (Chest and barium X-Rays, Ultrasound and CT scan abdomen) in 111 (53%) and histo-pathology (tissue obtained during surgery, colonoscopy, CT or ultrasound guided biopsy, laparoscopy and upper gastro intestinal endoscopy) in 87 (42%) patients. Mycobacterium culture was positive in 6/87 (7%) patients and response to therapeutic trial of anti tubercular drugs was the basis of diagnosis in 5 (2.3%) patients. Predominant site of involvement by abdominal TB was intestinal in 103 (49%) patients, peritoneal in 87 (42%) patients, solid viscera in 10 (5%) and nodal in 9 (4%) patients. Response to medical treatment was found in 158 (76%) patients andadditionally 35 (17%) patients also underwent surgery. In a 425 ± 120 d follow-up period 12 patients died (eight post operative) and no case of relapse was noted. CONCLUSION: Abdominal TB has diverse and non- specific symptomatology. No single test is adequate for dia

关键词：肺结核病理机制治疗临床

Predictive factors for early aspiration in liver abscess

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World Journal of Gastroenterology 2008年第13期14卷 2089-2093页

作者： rustam khan Saeed Hamid Shahab Abid Wasim Jafri Zaigham Abbas Mohammed Islam Hasnain Shan Shaalan Beg Section of Gastroenterology Department of Medicine The Aga Khan University Hospital Karachi Pakistan

AIM: To determine the predictive factors for early aspiration in liver abscess. METHODS: A retrospective analysis of all patients with liver abscess from 1995 to 2004 was performed. Abscess was diagnosed as amebic in 661 (68%) patients, pyogenic in 200 (21%), indeterminate in 73 (8%) and mixed in 32 (3%). Multiple logistic regression analysis was performed to determine predictive factors for aspiration of liver abscess. RESULTS: A total of 966 patients, 738 (76%) male, mean age 43 ± 17 years, were evaluated: 540 patients responded to medical therapy while adjunctive percutaneous aspiration was performed in 426 patients. Predictive factors for aspiration of liver abscess were: age ≥ 55 years, size of abscess ≥ 5 cm, involvement of both lobes of the liver and duration of symptoms ≥ 7 d. Hospital stay in the aspiration group was relatively longer than in the non aspiration group. Twelve patients died in the aspiration group and this mortality was not statistically significant when compared to the non aspiration group. CONCLUSION: Patients with advanced age, abscess size > 5 cm, both lobes of the liver involvement and duration of symptoms > 7 d were likely to undergo aspiration of the liver abscess, regardless of etiology.

关键词：肝脓肿诊断前兆因子早期症状

Chi-Square and PCA Based Feature Selection for Diabetes Detection with Ensemble Classifier

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Intelligent Automation & Soft Computing 2023年第5期36卷 1931-1949页

作者： Vaibhav Rupapara Furqan rustam Abid Ishaq Ernesto Lee Imran Ashraf School of Computing and Information Sciences Florida International UniversityUSA Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Computer Science Broward CollegeBroward CountyFloridaUSA Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Diabetes mellitus is a metabolic disease that is ranked among the top 10 causes of death by the world health *** the last few years,an alarming increase is observed worldwide with a 70%rise in the disease since 2000 and an 80%rise in male *** untreated,it results in complications of many vital organs of the human body which may lead to *** detection of diabetes is a task of signiﬁcant importance to start timely *** study introduces a methodology for the classiﬁcation of diabetic and normal people using an ensemble machine learning model and feature fusion of Chi-square and principal component *** ensemble model,logistic tree classiﬁer(LTC),is proposed which incorporates logistic regression and extra tree classiﬁer through a soft voting *** are also performed using several well-known machine learning algorithms to analyze their performance including logistic regression,extra tree classiﬁer,AdaBoost,Gaussian naive Bayes,decision tree,random forest,and k nearest *** addition,several experiments are carried out using principal component analysis(PCA)and Chi-square(Chi-2)fea-tures to analyze the inﬂuence of feature selection on the performance of machine learning classiﬁ*** indicate that Chi-2 features show high performance than both PCA features and original ***,the highest accuracy is obtained when the proposed ensemble model LTC is used with the proposed fea-ture fusion framework-work which achieves a 0.85 accuracy score which is the highest of the available approaches for diabetes *** addition,the statis-tical T-test proves the statistical signiﬁcance of the proposed approach over other approaches.

关键词： Diabetes mellitus prediction feature fusion ensemble classiﬁer principal component analysis chi-square

Malicious Traffic Detection in IoT and Local Networks Using Stacked Ensemble Classifier

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Computers, Materials & Continua 2022年第4期71卷 489-515页

作者： R.D.Pubudu L.Indrasiri Ernesto Lee Vaibhav Rupapara Furqan rustam Imran Ashraf School of Computing and Mathematics Charles Sturt UniversityAustralia Department of Computer Science Broward CollegeBroward CountyFloridaUSA School of Computing and Information Sciences Florida International UniversityUSA Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar KhanPakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Malicious traffic detection over the internet is one of the challenging areas for researchers to protect network infrastructures from any malicious *** shortcomings of a network system can be leveraged by an attacker to get unauthorized access through malicious *** from such attacks requires an efficient automatic system that can detect malicious traffic timely and avoid system ***,many automated systems can detect malicious activity,however,the efficacy and accuracy need further improvement to detect malicious traffic from multi-domain *** present study focuses on the detection of malicious traffic with high accuracy using machine learning *** proposed approach used two datasets UNSW-NB15 and IoTID20 which contain the data for IoT-based traffic and local network traffic,*** datasets were combined to increase the capability of the proposed approach in detecting malicious traffic from local and IoT networks,with high *** merging both datasets requires an equal number of features which was achieved by reducing feature count to 30 for each dataset by leveraging principal component analysis(PCA).The proposed model incorporates stacked ensemble model extra boosting forest(EBF)which is a combination of tree-based models such as extra tree classifier,gradient boosting classifier,and random forest using a stacked ensemble *** results show that EBF performed significantly better and achieved the highest accuracy score of 0.985 and 0.984 on the multi-domain dataset for two and four classes,respectively.

关键词： Stacked ensemble PCA malicious traffic detection classification machine learning

Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

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Computer Systems Science & Engineering 2023年第6期45卷 3053-3077页

作者： Ernesto Lee Furqan rustam Hina Fatima Shahzad Patrick Bernard Washington Abid Ishaq Imran Ashraf Department of Computer Science Broward CollegeBroward CountFloridaUSA Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Division of Business Administration and Economics Morehouse CollegeAtlantaGAUSA Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

With the increasing usage of drugs to remedy different diseases,drug safety has become crucial over the past few *** medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different *** diversification is both helpful and danger-ous as such medicine proves to be more effective or shows side effects to different *** clinical trials,side effects are reported when the medicine is used by the mass public,of which several such experiences are shared on social media platforms.A system capable of analyzing such reviews could be very helpful to assist healthcare professionals and companies for evaluating the safety of drugs after it has been *** analysis of drug reviews has a large poten-tial for providing valuable insights into these ***,this study proposes an approach to perform analysis on the drug safety reviews using lexicon-based and deep learning techniques.A dataset acquired from the‘***’contain-ing reviews of drug-related side effects and reactions,is used for experiments.A lexicon-based approach,Textblob is used to extract the positive,negative or neu-tral sentiment from the review *** classification is achieved using a novel hybrid deep learning model of convolutional neural networks and long short-term memory(CNN-LSTM)*** CNN is used at thefirst level to extract the appropriate features while LSTM is used at the second *** well-known machine learning models including logistic regression,random for-est,decision tree,and AdaBoost are evaluated using term frequency-inverse docu-ment frequency(TF-IDF),a bag of words(BoW),feature union of(TF-IDF+BoW),and lexicon-based *** analysis with machine learning models,long short term memory and convolutional neural network models,and state-of-the-art approaches indicate that the proposed CNN-LSTM model shows superior performance with an 0.96 *** also

关键词： Drug safety analysis lexicon-based techniques drug reviews sentiment analysis machine learning CNN-LSTM