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Search for a lighter neutral custodial fiveplet scalar in the Georgi-Machacek model

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Chinese Physics C 2022年第8期46卷 114-121页

作者： Chu Wang Jun-Quan Tao M.Aamir shahzad Guo-Ming Chen S.Gascon-Shotkin Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China Institut de Physique des 2 Infinis de Lyon Universitéde LyonUniversitéClaude Bernard Lyon 1CNRS-IN2P3Villeurbanne 69622France

Many researches from both theoretical and experimental perspectives have been performed to search for a new Higgs Boson that is lighter than the 125 GeV Higgs boson,which was discovered at the LHC in *** this study,we explore the possibility of constraining a lighter neutral custodial fiveplet scalar H_(5)^(0) in the GeorgiMachacek(GM) model using the latest results of the search for a lighter Higgs boson decaying into two photons from LHC *** custodial-singlet mass eigenstate h or H is considered to be the LHC observed 125 GeV Higgs boson.A new set of constrained parameters that is favoured by low-mass H_(5)^(0) is proposed to generate events *** production of H_(5)^(0) from a scan based on the constrained parameters is compared to the latest results of the search for a lighter Higgs boson decaying into two photons by the CMS Collaboration after applying theoretical constraints from the GM model and constraints from all existing relevant experimental measurements,including the recent results of the Higgs boson searches by the *** analyses of the surviving GM parameter space are *** tendencies and correlations of the GM input parameters from phenomenological studies are *** addition,the discovery potential of the other interesting decay channels of this low-mass neutral custodial fiveplet scalar are discussed.

关键词： Georgi-Machacek model lighter neutral custodial fiveplet scalar phenomenological studies

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

Improvement in winter wheat productivity through regulating PSⅡ photochemistry,photosynthesis and chlorophyll fluorescence under deficit irrigation conditions

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Journal of Integrative Agriculture 2022年第3期21卷 654-665页

作者： shahzad ALI XU Yue-yue MA Xiang-cheng JIA Qian-min JIA Zhi-kuan College of Pastoral Agriculture Science and Technology Lanzhou UniversityLanzhou 730000P.R.China Institute of Water Saving Agriculture in Arid Areas Yangling 712100P.R.China

Deficit irrigation is critical to global food production,particularly in arid and semi-arid regions with low *** water shortage has threatened agricultural sustainability under the dry-land farming system in China,there is an urgent need to develop effective water-saving *** carried out a field study under two cultivation techniques:(1) the ridge and furrow cultivation model(R);and(2) the conventional flat farming model(F),and three simulated precipitation levels(1,275 mm;2,200 mm;3,125 mm) with two deficit irrigation levels(150 and 75 mm).We demonstrated that under the ridge furrow(R) model,rainfall harvesting planting under 150 mm deficit irrigation combined with 200 mm simulated precipitation can considerably increase net photosynthesis rate(P_(n)),quantum yield of PSII(ΦPSⅡ),electron transport rate(ETR),performance index of photosynthetic PSII(F_(v)/F_(m)′),and transformation energy potential of PSII(F_(v)/F_(o)).In addition,during the jointing,anthesis and grain-filling stages,the grain and biomass yield in the R model are 18.9 and 11.1% higher than those in the flat cultivation model,respectively,primarily due to improved soil water *** winter wheat fluorescence parameters were significantly positively associated with the photosynthesis,biomass and wheat *** result suggests that the R cultivation model with irrigation of 150 mm and simulated precipitation of 200 mm is an effective planting method for enhancing P_(n),biomass,wheat production,and chlorophyll fluorescence parameters in dry-land farming areas.

关键词： chlorophyll fluorescence deficit irrigation photosynthesis production planting models soil moisture content

Neural Machine Translation Models with Attention-Based Dropout Layer

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Computers, Materials & Continua 2023年第5期75卷 2981-3009页

作者： Huma Israr Safdar Abbas Khan Muhammad Ali Tahir Muhammad Khuram shahzad Muneer Ahmad Jasni Mohamad Zain School of Electrical Engineering and Computer Science(SEECS) National University of Science and TechnologyIslamabadPakistan Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Kompleks Al-KhawarizmiUniversiti Teknologi MARA40450Shah AlamSelangorMalaysia

In bilingual translation,attention-based Neural Machine Translation(NMT)models are used to achieve synchrony between input and output sequences and the notion of *** model has obtained state-of-the-art performance for several language ***,there has been little work exploring useful architectures for Urdu-to-English machine *** conducted extensive Urdu-to-English translation experiments using Long short-term memory(LSTM)/Bidirectional recurrent neural networks(Bi-RNN)/Statistical recurrent unit(SRU)/Gated recurrent unit(GRU)/Convolutional neural network(CNN)and *** results show that Bi-RNN and LSTM with attention mechanism trained iteratively,with a scalable data set,make precise predictions on unseen *** trained models yielded competitive results by achieving 62.6%and 61%accuracy and 49.67 and 47.14 BLEU scores,*** a qualitative perspective,the translation of the test sets was examined manually,and it was observed that trained models tend to produce repetitive output more *** attention score produced by Bi-RNN and LSTM produced clear alignment,while GRU showed incorrect translation for words,poor alignment and lack of a clear ***,we considered refining the attention-based models by defining an additional attention-based dropout *** dropout fixes alignment errors and minimizes translation errors at the word *** empirical demonstration and comparison with their counterparts,we found improvement in the quality of the resulting translation system and a decrease in the perplexity and over-translation *** ability of the proposed model was evaluated using Arabic-English and Persian-English datasets as *** empirically concluded that adding an attention-based dropout layer helps improve GRU,SRU,and Transformer translation and is considerably more efficient in translation quality and speed.

关键词： Natural language processing neural machine translation word embedding attention perplexity selective dropout regularization Urdu Persian Arabic BLEU

Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning

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Computers, Materials & Continua 2022年第2期70卷 2743-2760页

作者： Mehdi Hassan Safdar Ali Muhammad Sanaullah Khuram shahzad Sadaf Mushtaq Rashda Abbasi Zulqurnain Ali Hani Alquhayz Department of Computer Science Air UniversityIslamabad44000Pakistan Directorate General National Repository Islamabad44000Pakistan Department of Computer Science Bahauddin Zakariya UniversityMultan60000Pakistan Department of Physics Air UniversityIslamabad44000Pakistan Department of Biotechnology Quaid-i-Azam University Islamabad44000Pakistan Institute of Biomedical and Genetic Engineering Islamabad44000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Cancer is the second deadliest human disease worldwide with high mortality *** and treatment of this disease requires precise and automatic assessment of effective drug response and control *** of treated and untreated cancerous cell line is one of the most challenging problems for precise and targeted drug delivery and response.A novel approach is proposed for prediction of drug treated and untreated cancer cell line automatically by employing modified Deep neural *** hepatocellular carcinoma(HepG2)cells are exposed to anticancer drug functionalized CFO@BTO nanoparticles developed by our *** models are developed by modifying ResNet101 and exploiting the transfer learning *** three layers of ResNet101 are re-trained for the identification of drug treated cancer *** learning approach in an appropriate choice especially when there is limited amount of annotated *** proposed technique is validated on acquired 203 fluorescentmicroscopy images of human HepG2 cells treated with drug functionalized cobalt ferrite@barium titanate(CFO@BTO)magnetoelectric nanoparticles in *** developed approach achieved high prediction with accuracy of 97.5%and sensitivity of 100%and outperformed other *** high performance reveals the effectiveness of the *** is scalable and fully automatic prediction approach which can be extended for other similar cell diseases such as lung,brain tumor and breast cancer.

关键词： Drug delivery in vitro transfer learning microscopic images deep learning

Preparation and Properties of Evaporated CdTe and All Thin Film CdTe/CdS Solar Cells

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Chinese Physics Letters 1991年第5期8卷 255-258页

作者： shahzad Naseem Centre for Solid State Physics University of the PunjabQuaid-e-Azam CampusLahore(PAKISTAN)

Cadmium telluride thin films were prepared by vacuum evaporation of CdTe powder in an attempt to fabricate all thin film solar cells of the type CdTe/*** of CdTe has shown it to have a band gap of 1.522eV and a resistivity of 22Ω-*** prepared,solar cells exhibited low values of output *** quantity of copper was then deposited on top of the CdTe/CdS solar cells and the whole system was annealed at 350℃.This copper doping changed the output parameters favorably with a maximum efficiency of 1.9%.

关键词： CdTe/CdS CdTe copper

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

Automatic Detection of Weapons in Surveillance Cameras Using Efficient-Net

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Computers, Materials & Continua 2022年第9期72卷 4615-4630页

作者： Erssa Arif Syed Khuram shahzad Muhammad Waseem Iqbal Muhammad Arfan Jaffar Abdullah S.Alshahrani Ahmed Alghamdi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Informatics&Systems University of Management&TechnologyLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Faculty of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Department of Computer Science&Artificial Intelligence College of Computer Science&EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia

The conventional Close circuit television(CCTV)cameras-based surveillance and control systems require human resource *** all the criminal activities take place using weapons mostly a handheld gun,revolver,pistol,swords ***,automatic weapons detection is a vital requirement now a *** current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–*** time datasets,from local surveillance department’s test sessions are used for model training and *** consist of local environment images and videos from different type and resolution cameras that minimize the *** research also contributes in the making of Efficient-Net that is experimented and results in a positive *** results are also been represented in graphs and in calculations for the representation of results during training and results after training are also shown to represent our research ***-Net algorithm gives better results than existing *** using Efficient-Net algorithms the accuracy achieved 98.12%when epochs increase as compared to other algorithms.

关键词： Detection algorithms machine learning machine vision video surveillance

Drug-eluting stents: is it the beginning of the end for coronary artery bypass surgery?

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Chinese Medical Journal 2004年第9期117卷 1377-1387页

作者： shahzad G Raja Department of Cardiac Surgery Royal Hospital for Sick Children Yorkhill NHS TrustGlasgow G3 8SJScotland

Myocardial revascularization therapy of coronary artery disease is one of the most important medical advances of the past 50 years.1 Coronary revascularization by either bypass surgery or coronary angioplasty relieves angina and may improve the prognosis in patients with coronary artery disease.2,3 Randomized comparisons reveal no difference in survival free from myocardial infarction (MI) between surgery and balloon angioplasty.4,5 Stenting significantly improved the long-term outcome, while surgery is still associated with fewer reinterventions during follow-up.6-10 However, subsequent improvements in both percutaneous and surgical techniques may now limit the validity of any conclusions that have been drawn from the earlier studies. In fact, the lines of demarcation for patients suited for bypass or angioplasty are becoming blurry with each passing day.

关键词： coronary arteriosclerosis · percutaneous coronary interventions · drug-eluting stents