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Comparative analysis of jet and underlying event properties across various models as a function of charged particle multiplicity at 7 TeV

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Chinese Physics C 2024年第9期48卷 118-125页

作者： Maryam Waqar Haifa I.Alrebdi muhammad Waqas K.S.Al-mugren muhammad Ajaz Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

In this study,a comprehensive analysis of jets and underlying events as a function of charged particle multiplicity in proton-proton(pp)collisions at a center-of-mass energy of √s=7 TeV is *** Monte Carlo(MC)event generators,including Pythia8.308,EPOS 1.99,EPOSLHC,EPOS4_(Hydro),and EPOS4_(noHydro),are employed to predict particle *** predictions from these models are compared with experimental data from the CMS *** charged particles are categorized into those associated with underlying events and those linked to jets,and the analysis is restricted to charged particles with|η|0.25 GeV/*** comparing the MC predictions with CMS data,we find that EPOS4_(Hydro),EPOSLHC,and Pythia8 consistently reproduce the experimental results for all charged particles,underlying events,intrajets,and leading charged *** charged jet rates with p_T^(***)>5 GeV/c,EPOS4_(Hydro)and Pythia8 perform exceptionally *** the case of charged jet rates with p_T^(***)→30 GeV/c,EPOSLHC reproduces satisfactorily good results,whereas EPOS4 Hydro exhibits good agreement with the data at higher charged particle multiplicities compared to the other *** can be attributed to the conversion of energy into flow when"Hydro=on"leading to an increase in *** EPOSLHC model describes the data better owing to the new collective flow effects,correlated flow treatment,and parameterization compared to EPOS ***,the examination of the jet p_T spectrum and normalized charged p_T density reveals that EPOS4_(Hydro),EPOS4_(noHydro),and EPOSLHC exhibit good agreement with the experimental results,whereas Pythia8 and EPOS 1.99 do not perform as well owing to the lack of correlated flow treatment.

关键词： Monte Carlo models underlying event jets charged particle multiplicity

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Attitude-adjusting dynamical behavior of cubic rover on low-gravity testbed

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Astrodynamics 2024年第1期8卷 149-159页

作者： Bowen Jiang muhammad Talha Hussain Xiangyuan Zeng School of Automation Beijing Institute of TechnologyBeijing100081China

Cubic rovers that traverse by hopping systems are promising in low-gravity *** several analyses of the control methods and mobility of the cubic rover are available,investigations of its attitude-adjusting behavior are still *** study derives the dynamic equations of the two attitude-adjusting modes of the cubic rover,referred to as walking and *** relationships between the speed threshold and rotation angle of the cubic rover were investigated in both rigid and regolith environments using a self-designed low-gravity *** studies were conducted by considering the experimental and simulated *** results of this study can be interesting for roving mission planning when exploring planetary moons and small celestial bodies.

关键词： low-gravitytestbed attitude-adjusting motion cubic rover experimental study

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Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

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Intelligent Automation & Soft Computing 2024年第3期39卷 545-566页

作者： Asad Raza shahzad Memon muhammad Ali Nizamani Mahmood Hussain shah Dr.AHS Bukhari Postgraduate Centre of Information and Communication Technology Faculty of Engineering and TechnologyUniversity of SindhJamshoro76060Pakistan Newcastle Business School Northumbria UniversityNewcastleNE1UK

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven ***,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the *** signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging ***,there is the need for an IDS which can learn from data and detect new *** Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking *** this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta *** proposed DSNN model was trained and evaluated with the next-generation dataset,TON_*** pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE ***,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble *** experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML *** addition,the model proposed for IDS has been compared with similar *** proposed DSNN achieved better performance metrics than the other *** proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

关键词： Industrial internet of things smart industrial environment cyber-attacks convolutional neural network ensemble learning

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Advances in Zika virus vaccines and therapeutics:A systematic review

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Asian Pacific Journal of Tropical Medicine 2024年第3期17卷 97-109页

作者： Shiza Malik Khalid muhammad Omar Ahsan muhammad Tahir Khan Ranjit Sah Yasir Waheed Bridging Health Foundation Rawalpindi 46000Pakistan Department of Biology College of SciencesUAE University15551Al AinUnited Arab Emirates Department of Medicine Foundation University Medical CollegeFoundation University IslamabadIslamabad 44000Pakistan INTI International University Persiaran Perdana BBN Putra Nilai71800 NilaiNegeri SembilanMalaysia Institute of Molecular Biology and Biotechnology the University of LahoreKM Defence RoadLahore 58810Pakistan Zhongjing Research and Industrialization Institute of Chinese Medicine Zhongguancun Scientific ParkNanyang 473006China Department of Microbiology Tribhuvan University Teaching HospitalInstitute of MedicineKathmandu 44600Nepal Department of Microbiology Dr.D.Y.Patil Medical CollegeHospital and Research CentreDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Department of Public Health Dentistry Dr.D.Y.Patil Dental College and HospitalDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Gilbert and Rose-Marie Chagoury School of Medicine Lebanese American UniversityByblos 1401Lebanon

Zika virus(ZIKV)is the causative agent of a viral infection that causes neurological complications in newborns and adults *** wide transmission route and alarming spread rates are of great concern to the scientific *** trials have been conducted to develop treatment options for ZIKV *** review highlights the latest developments in the fields of vaccinology and pharmaceuticals developments for ZIKV infection.A systematic and comprehensive approach was used to gather relevant and up-to-date data so that inferences could be made about the gaps in therapeutic *** results indicate that several therapeutic interventions are being tested against ZIKV infection,such as DNA vaccines,subunit vaccines,live-attenuated vaccines,virus-vector-based vaccines,inactivated vaccines,virus-like particles,and mRNA-based *** addition,approved anti-ZIKV drugs that can reduce the global burden are *** many vaccine candidates for ZIKV are at different stages of development,none of them have received Food and Drug Authority approval for use up to *** issue of side effects associated with these drugs in vulnerable newborns and pregnant women is a major obstacle in the therapeutic pathway.

关键词： Zika virus Infection Therapeutics Antiviral agents Vaccines Therapies Treatment Novel therapeutic Clinical management

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Data Information integrated Neural Network (DINN) algorithm for modelling and interpretation performance analysis for energy systems

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Energy and AI 2024年第2期16卷 306-315页

作者： Waqar muhammad Ashraf Vivek Dua The Sargent Centre for Process Systems Engineering Department of Chemical EngineeringUniversity College LondonTorrington PlaceLondon WC1E 7JEUK

Developing a well-predictive machine learning model that also offers improved interpretability is a key challenge to widen the application of artificial intelligence in various application domains. In this work, we present a Data Information integrated Neural Network (DINN) algorithm that incorporates the correlation information present in the dataset for the model development. The predictive performance of DINN is also compared with a standard artificial neural network (ANN) model. The DINN algorithm is applied on two case studies of energy systems namely energy efficiency cooling (ENC) & energy efficiency heating (ENH) of the buildings, and power generation from a 365 MW capacity industrial gas turbine. For ENC, DINN presents lower mean RMSE for testing datasets (RMSE_test = 1.23 %) in comparison with the ANN model (RMSE_test = 1.41 %). Similarly, DINN models have presented better predictive performance to model the output variables of the two case studies. The input perturbation analysis following the Gaussian distribution for noise generation reveals the order of significance of the variables, as made by DINN, can be better explained by the domain knowledge of the power generation operation of the gas turbine. This research work demonstrates the potential advantage to integrate the information present in the data for the well-predictive model development complemented with improved interpretation performance thereby opening avenues for industry-wide inclusion and other potential applications of machine learning.

关键词： Explainable AI Model interpretation Scientific machine learning Artificial neural network Loss function

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A novel fractional case study of nonlinear dynamics via analytical approach

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 276-290页

作者： Hassan Khan Adnan Khan Rasool shah Dumitru Baleanu Department of Mathematics Abdul Wali khan UniversityMardan 23200Pakistan Department of Mathematics Faculty of Arts and SciencesCankaya UniversityAnkara 06530Turkey Institute of Space Sciences Magurele-BucharestRomania

The present work describes the fractional view analysis of Newell-Whitehead-Segal equations,using an innovative *** work is carried with the help of the Caputo operator of fractional *** analytical solutions of some numerical examples are presented to confirm the reliability of the proposed *** derived results are very consistent with the actual solutions to the problems.A graphical representation has been done for the solution of the problems at various fractional-order ***,the solution in series form has the desired rate of convergence and provides the closed-form *** is noted that the procedure can be modified in other directions for fractional order problems.

关键词： Homotopy Perturbation method Shehu transform Newell-Whitehead-Segel Equation Caputo operator

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Unveiling the Nexus the link between water quality index and phthalic acid ester concentrations in Tigris River

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Emerging Contaminants 2024年第1期10卷 108-116页

作者： Shaymaa arif Shukur Fikrat M.Hassan Saad Sabah Fakhry Department of Biology College of Science for WomenUniversity of BaghdadIraq Ministry of Science and Technology/Food Contamination Research Center Iraq

Monitoring water quality in an aquatic system is a crucial objective in pursuing sustainable development,despite the challenges posed by water scarcity and the impact of climate *** objective of the present study was to examine the water quality of the Tigris River along its course from the point of entry into Baghdad city to its exit,particularly in the presence of Phthalic Acid Esters(PAEs).In both dry and wet seasons and from five sites of the river,nine environmental factors(Turbidity,Total dissolved solids,pH,dissolved oxygen,Chloride,nitrate,phosphate,sulfate,and Biological oxygen demand)and three PAEs(di-n-butyl phthalate(DBP),di-isononyl phthalate(DiNP),and di-2-ethyl hexyl phthalate(DEHP))were *** revealed that the river has high levels of turbidity and Total dissolved solids,slightly alkaline,and well-aerated(dissolved oxygen>7 mg/L).Chloride,nitrate,phosphate,and sulfate values varied between seasons,as high values were recorded in the wet *** oxygen demand levels were higher during the dry *** highest value of total PAEs(2.20μg/L)was observed during the dry season,and the lowest value was in the wet season(1.16μg/L).The HQ results revealed that the river was ranked as a moderate risk *** the water quality index and environmental risk index classified the water quality as a poor category,with a high-risk score in the study sites within Baghdad ***,despite the acceptable limit of PAEs in the river's water(<3μg/L),its presence is an early alarm to withdraw attention to its environmental *** findings highlight the need for appropriate measures to control and remove pollutants to ensure a safe and healthy water supply in the Tigris River.

关键词： Phthalic acid esters di-n-butyl phthalate(DBP) di-isononyl phthalate(DiNP) di-2-ethyl hexyl phthalate(DEHP) Environmental risk index Tigris River Water pollution

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ROBO-SPOT:Detecting Robocalls by Understanding User Engagement and Connectivity Graph

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Big Data Mining and Analytics 2024年第2期7卷 340-356页

作者： muhammad Ajmal Azad Junaid Arshad Farhan Riaz College of Comnputer Science Birmingham City UniversityBirminghamB55JUUK School of Computer Science University of LincolnLincolnLN67TSUK

Robo or unsolicited calls have become a persistent issue in telecommunication networks,posing significant challenges to individuals,businesses,and regulatory *** calls not only trick users into disclosing their private and financial information,but also affect their productivity through unwanted phone ringing.A proactive approach to identify and block such unsolicited calls is essential to protect users and service providers from potential ***,this paper proposes a solution to identify robo-callers in the telephony network utilising a set of novel features to evaluate the trustworthiness of callers in a *** trust score of the callers is then used along with machine learning models to classify them as legitimate or *** use a large anonymized dataset(call detailed records)from a large telecommunication provider containing more than 1 billion records collected over 10 *** have conducted extensive evaluation demonstrating that the proposed approach achieves high accuracy and detection rate whilst minimizing the error ***,the proposed features when used collectively achieve a true-positive rate of around 97%with a false-positive rate of less than 0.01%.

关键词： social network analysis reputation unwanted calls robo-callers telephone network Spam Over Internet Technology(SPIT)

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PETG:Applications in Modern Medicine

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Engineered Regeneration 2024年第1期5卷 45-55页

作者： Catherine Yan Corinne Kleiner Aaron Tabigue Veer shah Gregory Sacks Darshi shah Vincent DeStefano Renaissance School of Medicine at Stony Brook University Stony BrookNYUSA Department of Biology Niagara UniversityLewistonNYUSA Stony Brook University Stony BrookNYUSA Department of Mechanical and Industrial Engineering Northeastern UniversityBostonMAUSA

Polyethylene terephthalate glycol,PETG,is a miscible,transparent thermoplastic known to have strong tensile properties,high ductility,as well as resistance to heat and chemical *** may be manufactured in several ways,most notably 3D printing *** such,PETG has emerged as a viable biomaterial for a variety of medical applications such as tissue engineering,dentistry,optometry,vascular health,cardiology,orthopedics,neurology,gynecology,and *** also serves a valuable role in biomedical research and engineering by offering improvements in cell studies,drug carriers,and anti-bacterial *** medical research and innovation utilizing PETG will better characterize its value as an inexpensive and versatile biomaterial.

关键词： Polyethylene terephthalate glycol Tissue Engineering 3D Printing Clinical Applications Biomedical Research

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Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

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Computers, Materials & Continua 2024年第8期80卷 3221-3242页

作者： Ayesha Khaliq Salman Afsar Awan Fahad Ahmad muhammad Azam Zia muhammad Zafar Iqbal Department of Computer Science University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan School of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics and Statistics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original *** approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent *** study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical *** approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text *** model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and *** results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document *** research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

关键词： Summarization graph attention network bidirectional encoder representations from transformers Latent Dirichlet Allocation term frequency-inverse document frequency

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