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Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

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

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Assessment of Sea Water Inundation Along Daboo Creek Area in Indus Delta Region, Pakistan

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Journal of Ocean University of China 2017年第6期16卷 1055-1060页

作者： ZIA Ibrahim ZAFAR hina shahzad Muhammad I. MERAJ Mohsin KAZMI Jamil H. National Institute of Oceanography (NIO) Karachi 75600 Pakistan Department of Geography University of Karachi 75270 Pakistan Earth & Atmospheric Remote Sensing Laboratory (EARL) Department of Meteorology COMSATS Institute of Information Technology (CIIT) Park Road Islamabad 45550 Pakistan

Indus Deltaic Region(IDR) in Pakistan is an erosion vulnerable coast due to the high deep water wave energy. Livelihood of millions of people depends on the fisheries and mangrove forests in IDR. IDR consists of many creeks where Daboo is a major creek located at southeast of the largest city of Pakistan, Karachi. Unfortunately, there has been no detailed study to analyze the damages of sea water intrusion at a large temporal and spatial scale. Therefore, this study is designed to estimate the effects of sea water inundation based on changing sea water surface salinity and sea surface temperature(SST). Sea surface salinity and SST data from two different surveys in Daboo creek during 1986 and 2010 are analyzed to estimate the damages and extent of sea water intrusion. Mean salinity has increased 33.33% whereas mean SST decreased 13.79% from 1987 to 2010. Spatio-temporal analysis of creek area using LANDSAT 5 Thematic mapper(TM) data for the years 1987 and 2010 shows significant amount of erosion at macro scale. Creek area has increased approximately 9.93%(260.86 m^2 per year) which is roughly equal to 60 extensive sized shrimp farms. Further Land Use Land Cover(LULC) analyses for years 2001 and 2014 using LANDSAT 7 Enhanced Thematic Mapper Plus(ETM+) has indicated 42.3% decrease in cultivated land. Wet mud flats have spread out at the inner mouth of creek with enormous increase of 123.3%. Significant sea water intrusion has increased the area of barren land by 37.9%. This also resulted in overall decrease of 6.7% in area covered by mangroves. Therefore, this study recorded a significant evidence of sea water intrusion in IDR that has caused serious damages to community living in the area, economical losses. Additionally, it has also changed the environment by reducing creek biological productivity as reported by earlier studies over other regions of the world.

关键词： sea water intrusion SST salinity Ambro creek CTD

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Spatio-temporal variations in trends of vegetation and drought changes in relation to climate variability from 1982 to 2019 based on remote sensing data from East Asia

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Journal of Integrative Agriculture 2023年第10期22卷 3193-3208页

作者： shahzad ALI Abdul BASIT Muhammad UMAIR Tyan Alice MAKANDA Fahim Ullah KHAN Siqi SHI NI Jian College of Chemistry and Life Sciences Zhejiang Normal UniversityJinhua 321004P.R.China Department of Agriculture Hazara UniversityMansehra 21120Pakistan Department of Computer Science University of PeshawarPeshawar 25000Pakistan Faculty of Geo-Information Science and Earth Observation(ITC) University of TwenteEnschede 7500 AENetherlands

Studying the significant impacts on vegetation of drought due to global warming is crucial in order to understand its dynamics and interrelationships with temperature,rainfall,and normalized difference vegetation index(NDVI).These factors are linked to excesses drought frequency and severity on the regional scale,and their effect on vegetation remains an important topic for climate change *** Asia is very sensitive and susceptible to climate *** this study,we examined the effect of drought on the seasonal variations of vegetation in relation to climate variability and determined which growing seasons are most vulnerable to drought risk;and then explored the spatio-temporal evolution of the trend in drought changes in East Asia from 1982 to *** data were studied using a series of several drought indexes,and the data were then classified using a heat map,box and whisker plot analysis,and principal component *** various drought indexes from January to August improved rapidly,except for vegetation health index(VHI)and temperature condition index(TCI).While these indices were constant in September,they increased again in October,but in December,they showed a descending *** seasonal and monthly analysis of the drought indexes and the heat map confirmed that the East Asian region suffered from extreme droughts in 1984,1993,2007,and 2012among the study *** distribution of the trend in drought changes indicated that more severe drought occurred in the northwestern region than in the southeastern area of East *** drought tendency slope was used to describe the changes in drought events during 1982–2019 in the study *** correlations among monthly precipitation anomaly percentage(NAP),NDVI,TCI,vegetation condition index(VCI),temperature vegetation drought index(TVDI),and VHI indicated considerably positive correlations,while considerably negative correlations were found among the three pairs of NDVI and VHI,TVDI and VHI,and NDV

关键词： climate change drought severity vegetation dynamics heat mapping TVDI spatial correlation East Asia

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Role of Co in formation of Ni-Ti clusters in maraging stainless steel

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Journal of Materials Science & Technology 2018年第9期34卷 1671-1675页

作者： Jialong Tian M.Babar shahzad Wei Wang Lichang Yin Zhouhua Jiang Ke Yang School of Materials Science and Engineering Northeastern University Shenyang 110004 China Institute of Metal Research Chinese Academy of Sciences Shenyang 110016 China Shenyang National Laboratoryfor Materials Science 72 Wenhua Road Shenyang 110016 China School of Metallurgy Northeastern University Shenyang 110004 China

The effect of Co addition on the formation of Ni-Ti clusters in maraging stainless steel was studied by three dimensional atom probe（3 DAP） and first-principles calculation. The cluster analysis based on the maximum separation approach showed an increase in size but a decrease in density of Ni-Ti clusters with increasing the Co content. The first-principles calculation indicated weaker Co-Ni（Co-Ti） interactions than Co-Ti（Fe-Ti） interactions, which should be the essential reason for the change of distribution characteristics of Ni-Ti clusters in bcc Fe caused by Co addition.

关键词： Maraging stainless steels Ni-Ti cluster First-principles calculation Three-dimensional atom probe

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