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Analysis of b→cτν¯_(τ)anomalies using weak effective Hamiltonian with complex couplings and their impact on various physical observables

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Chinese Physics C 2024年第8期48卷 56-75页

作者： Muhammad Arslan Tahira Yasmeen Saba Shafaq ishtiaq Ahmed Muhammad Jamil Aslam Department of Physics Quaid-i-Azam UniversityIslamabad 45320Pakistan Department of Physics International Islamic UniversityIslamabad 44000Pakistan National Center for Physics Islamabad 44000Pakistan

Recently,the experimental measurements of the branching ratios and different polarization asymmetries for processes occurring through flavor-changing-charged current(b→cτν¯_(τ))transitions by BABAR,Belle,and LHCb have revealed some significant differences from the corresponding Standard Model(SM)*** has triggered an interest to search for physics beyond the SM in the context of various new physics(NP)models and using the model-independent weak effective Hamiltonian(WEH).Assuming left-handed neutrinos,we add the dimension-six vector,(pseudo-)scalar,and tensor operators with complex Wilson coefficients(WCs)to the SM *** 60%,30%,and 10%constraints resulting from the branching ratio of B_(c)→τν¯_(τ),we reassess the parametric space of these new physics WCs accommodating the current anomalies based on the most recent HFLAV data of R_(τ/μ,e)(D)and R_(τ/μ,e)(D^(*))and Belle data of F_(L)(D^(*))and P_(τ)(D^(*)).We find that the allowed parametric region of left-handed scalar couplings strongly depends on the constraints of the B_(c)→τν¯_(τ)branching ratio,and the maximum pull from the SM predictions results from the<60%branching ratio ***,the parametric region changes significantly if we extend the analysis by adding LHCb data of R_(τ/μ)(J/ψ)and R_(τ/ℓ)(Λ_(c)).Furthermore,due to the large uncertainties in the measurements of R_(τ/μ)(J/ψ)and R_(τ/ℓ)(X_(c)),we derive the sum rules which complement them with R_(τ/μ,e)(D)and R_(τ/μ,e)(D^(*)).Using the best-fit points of the new complex WCs along with the latest measurements of R_(τ/μ,e)(D(^(*))),we predict the numerical values of the observable R_(τ/ℓ)(Λ_(c)),R_(τ/μ)(J/ψ),and R_(τ/ℓ)(X_(c))from the sum *** simultaneous dependence of abovementioned physical observables on the NP WCs is established by plotting their correlation with R_(D) and R_(D^(*)),which are useful to discriminate between various NP *** find that the most significant impact of NP results from the WC C^(S)_(L)=4C^(T).Fi

关键词： B meson anomalies new physics complex coupling HFLAV

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

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Journal of Mountain Science 2024年第1期21卷 200-217页

作者： Hamza DAUD Javed Iqbal TANOLI Sardar Muhammad ASIF Muhammad QASIM Muhammad ALI Junaid KHAN Zahid Imran BHATTI ishtiaq Ahmad Khan JADOON Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-R Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

Impact of COVID-19 on liver transplant recipients: A nationwide cohort study evaluating hospitalization, transplant rejection, and inpatient mortality

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World Journal of Transplantation 2024年第2期14卷 62-75页

作者： Faisal Inayat Pratik Patel Hassam Ali Arslan Afzal Hamza Tahir Ahtshamullah Chaudhry Rizwan ishtiaq Attiq Ur Rehman Kishan Darji Muhammad Sohaib Afzal Gul Nawaz Alexa Giammarino Sanjaya K Satapathy Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Division of Gastroenterology Mather Hospital and Zucker School of Medicine at Hofstra UniversityPort JeffersonNY 11777United States Division of Gastroenterology and Hepatology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine Jefferson Einstein HospitalPhiladelphiaPA 19141United States Department of Internal Medicine St.Dominic's HospitalJacksonMS 39216United States Department of Internal Medicine Saint Francis Hospital and Medical CenterHartfordCT 06105United States Division of Hepatology Geisinger Wyoming Valley Medical CenterWilkes-BarrePA 18711United States Department of Internal Medicine Campbell University and Cape Fear Valley Medical CenterFayettevilleNC 28301United States Department of Internal Medicine North Shore University Hospital and Zucker School of Medicine at Hofstra UniversityManhassetNY 11030United States Division of Hepatology North Shore University Hospital and Zucker School of Medicine at Hofstra UniversityManhassetNY 11030United States

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic has posed a major public health concern *** with comorbid conditions are at risk of adverse outcomes following *** organ transplant recipients with concurrent immunosuppression and comorbidities are more susceptible to a severe COVID-19 *** could lead to higher rates of inpatient complications and mortality in this patient ***,studies on COVID-19 outcomes in liver transplant(LT)recipients have yielded inconsistent *** To evaluate the impact of the COVID-19 pandemic on hospital-related outcomes among LT recipients in the United *** We conducted a retrospective cohort study using the 2019–2020 National Inpatient Sample *** with primary LT hospitalizations and a secondary COVID-19 diagnosis were identified using the International Classi-fication of Diseases,Tenth Revision coding *** primary outcomes included trends in LT hospitalizations before and during the COVID-19 *** outcomes included comparative trends in inpatient mortality and transplant rejection in LT *** A total of 15720 hospitalized LT recipients were *** 0.8% of patients had a secondary diagnosis of COVID-19 *** both cohorts,the median admission age was 57 *** linear trends for LT hospitalizations did not differ significantly before and during the pandemic(P=0.84).The frequency of in-hospital mortality for LT recipients increased from 1.7% to 4.4% between January 2019 and December *** to the pre-pandemic period,a higher association was noted between LT recipients and in-hospital mortality during the pandemic,with an odds ratio(OR)of 1.69[95% confidence interval(CI):1.55-1.84),P<0.001].The frequency of transplant rejections among hospitalized LT recipients increased from 0.2%to 3.6% between January 2019 and December *** hospitalizations during the COVID-19 pandemic had a higher associ

关键词： Liver transplant recipients Solid organ transplantation COVID-19 Hospitalization Transplant rejection Mortality

Energy Theft Detection in Smart Grids with Genetic Algorithm-Based Feature Selection

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Computers, Materials & Continua 2023年第3期74卷 5431-5446页

作者： Muhammad Umair Zafar Saeed Faisal Saeed Hiba ishtiaq Muhammad Zubair Hala Abdel Hameed Faculty of Information Technology University of Central PunjabLahore54590Pakistan DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirmingham B47XGUK Faculty of Computer and Information Systems Fayoum University63514Egypt Khaybar Applied College Taibah UniversitySaudi Arabia

As big data,its technologies,and application continue to advance,the Smart Grid(SG)has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology(ICT)and cloud *** a result of the complicated architecture of cloud computing,the distinctive working of advanced metering infrastructures(AMI),and the use of sensitive data,it has become challenging tomake the SG *** of the SG are categorized into two main categories,Technical Losses(TLs)and Non-Technical Losses(NTLs).Hardware failure,communication issues,ohmic losses,and energy burnout during transmission and propagation of energy are ***’s are human-induced errors for malicious purposes such as attacking sensitive data and electricity theft,along with tampering with AMI for bill reduction by fraudulent *** research proposes a data-driven methodology based on principles of computational intelligence as well as big data analysis to identify fraudulent customers based on their load *** our proposed methodology,a hybrid Genetic Algorithm and Support Vector Machine(GA-SVM)model has been used to extract the relevant subset of feature data from a large and unsupervised public smart grid project dataset in London,UK,for theft detection.A subset of 26 out of 71 features is obtained with a classification accuracy of 96.6%,compared to studies conducted on small and limited datasets.

关键词： Big data data analysis feature engineering genetic algorithm machine learning

Performance Evaluation of Virtualization Methodologies to Facilitate NFV Deployment

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Computers, Materials & Continua 2023年第4期75卷 311-329页

作者： Sumbal Zahoor ishtiaq Ahmad Ateeq Ur Rehman Elsayed Tag Eldin Nivin AGhamry Muhammad Shafiq Department of Electrical Engineering The University of LahoreLahore54000Pakistan Department of Electrical Engineering Government College UniversityLahore54000Pakistan Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Faculty of Computers and Artificial Intelligence Cairo UniversityGiza3750010Egypt Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The development of the Next-Generation Wireless Network(NGWN)is becoming a *** conduct specialized processes more,rapid network deployment has become *** like Network Function Virtualization(NFV),Software-Defined Networks(SDN),and cloud computing will be crucial in addressing various challenges that 5G networks will face,particularly adaptability,scalability,and *** motivation behind this work is to confirm the function of virtualization and the capabilities offered by various virtualization platforms,including hypervisors,clouds,and containers,which will serve as a guide to dealing with the stimulating environment of *** is particularly crucial when implementing network operations at the edge of 5G networks,where limited resources and prompt user responses are *** results prove that containers outperform hypervisor-based virtualized infrastructure and cloud platforms’latency and network throughput at the expense of higher virtualized processor *** contrast to public clouds,where a set of rules is created to allow only the appropriate traffic,security is still a problem with containers.

关键词： NFV hypervisors cloud computing containers

On the stacking fault forming probability and stacking fault energy in carbon-doped 17 at%Mn steels via transmission electron microscopy and atom probe tomography

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Journal of Materials Science & Technology 2022年第20期115卷 177-188页

作者： Hyo Ju Bae Kwang Kyu Ko Muhammad ishtiaq Jung Gi Kim Hyokyung Sung Jae Bok Seol Department of Materials Engineering and Convergence Technology Center for K-metalGyeongsang National University(GNU)Jinju 52828South Korea

Assessing the stacking fault forming probability(P_(sf)) and stacking fault energy(SFE)in medium-or highMn base structural materials can anticipate and elucidate the microstructural evolution before and after ***,these two parameters have been determined from theoretical calculations and empirical ***,the estimation of SFE values in Fe–Mn–C ternary systems is a longstanding debate due to the complicated nature of carbon:that is,whether the carbon doping indeed plays an important role in the formation of stacking faults;and how the amount of carbon atoms exist at grain boundaries or at internal grains with respect to the nominal carbon doping ***,the use of atom probe tomography and transmission electron microscopy(TEM)unveils the influence of carbondoping contents on the structural properties of dual-phase Fe–17 Mn–x C(x=0–1.56 at%)steels,such as carbon segregation free energy at grain boundaries,carbon concentration in grain interior,interplanar D-spacings,and mean width of intrinsic stacking faults,which are essential for SFE *** next determined the Psfvalues by two different methods,viz.,reciprocal-space electron diffraction measurements and stacking fault width measurements in real-space TEM ***,SFEs in the Fe–17 Mn–x C systems were calculated on the basis of the generally-known SFE *** found that the high amount of carbon doping gives rise to the increased SFE from 8.6 to 13.5 m J/m^(2)with non-linear *** SFE trend varies inversely with the mean width of localized stacking faults,which pass through both other stacking faults and pre-existingε-martensite plates without much difficulty at their intersecting *** high amount of carbon doping acts twofold,through increasing the segregation free energy(due to more carbon at grain boundaries)and large lattice expansion(due to increased soluble carbon at internal grains).The experimental data obtained here strengthens the composition-

关键词： Stacking fault formation probability Stacking fault energy High-Mn steel Electron diffraction

Order selection in fractional Fourier transform based beamforming

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Journal of Systems Engineering and Electronics 2010年第3期21卷 361-369页

作者： Muhammad ishtiaq Ahmad School of Information and Electronics Beijing Institute of Technology

Traditionally,beamforming using fractional Fourier transform（FrFT） involves a trial-and-error based FrFT order selection which is impractical.A new numerical order selection scheme is presented based on fractional power spectra（FrFT moment） of the linear chirp *** method can adaptively determine the optimum FrFT order by maximizing the second-order central FrFT *** makes the desired chirp signal substantially concentrated whereas the noise is rejected *** improves the mean square error minimization beamformer by reducing effectively the signal-noise cross terms due to the finite data length de-correlation *** results show that the new method works well under a wide range of signal to noise ratio and signal to interference ratio.

关键词： adaptive beamforming fractional Fourier transform (FrFT) fractional moments chirp signal.

Design of Latency-Aware IoT Modules in Heterogeneous Fog-Cloud Computing Networks

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Computers, Materials & Continua 2022年第3期70卷 6057-6072页

作者： Syed Rizwan Hassan ishtiaq Ahmad Jamel Nebhen Ateeq Ur Rehman Muhammad Shafiq Jin-Ghoo Choi Department of Electrical Engineering The University of LahoreLahore54000Pakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The modern paradigm of the Internet of Things(IoT)has led to a significant increase in demand for latency-sensitive applications in Fog-based cloud ***,such applications cannot meet strict quality of service(QoS)*** large-scale deployment of IoT requires more effective use of network infrastructure to ensure QoS when processing big ***,cloud-centric IoT application deployment involves different modules running on terminal devices and cloud *** devices with different computing capabilities must process the data generated by the end device,so deploying latency-sensitive applications in a heterogeneous fog computing environment is a difficult *** addition,when there is an inconsistent connection delay between the fog and the terminal device,the deployment of such applications becomes more *** this article,we propose an algorithm that can effectively place application modules on network nodes while considering connection delay,processing power,and sensing data *** with traditional cloud computing deployment,we conducted simulations in iFogSim to confirm the effectiveness of the *** simulation results verify the effectiveness of the proposed algorithm in terms of end-to-end delay and network ***,latency and execution time is insensitive to the number of sensors.

关键词： IoT fog-cloud computing architecture module placement latency sensitive application resource aware placement

Reinforcing Artificial Neural Networks through Traditional Machine Learning Algorithms for Robust Classification of Cancer

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Computers, Materials & Continua 2023年第5期75卷 4293-4315页

作者： Muhammad Hammad Waseem Malik Sajjad Ahmed Nadeem ishtiaq Rasool Khan Seong-O-Shim Wajid Aziz Usman Habib Department of Computer Sciences and Information Technology University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Computer Science and AI College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of AI&DS School of ComputingNational University of Computer and Emerging SciencesIslamabad44000Pakistan

Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or *** ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification *** network weights and the activation functions are the two crucial elements in the learning process of an *** weights affect the prediction ability and the convergence efficiency of the *** traditional settings,ANNs assign random weights to the *** research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random *** proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer *** system computes the confusion matrix-based metrics for traditional and proposed *** proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other *** results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research ***,the proposed framework is of use to predict and classify cancer patients ***,this will facilitate the effective management of cancer patients.

关键词： ANN decision support systems gene-expression data hybrid classification machine learning predictive analytics