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Physics-informed neural networks for estimating stress transfer mechanics in single lap joints

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2021年第8期22卷 621-631页

作者： shivam sharma Rajneesh AWASTHI Yedlabala Sudhir SASTRY Pattabhi Ramaiah BUDARAPU School of Mechanical Sciences Indian Institute of TechnologyBhubaneswar 752050India Department of Aeronautical Engineering Institute of Aeronautical EngineeringHyderabad 500043India

With the explosive growth of computational resources and data generation,deep machine learning has been successfully employed in various *** important and emerging scientific application of deep learning involves solving differential ***,physics-informed neural networks(PINNs)are developed to solve the differential equations associated with a specific scientific *** such,algorithms for solving the differential equations by embedding their initial and boundary conditions in the cost function of the artificial neural networks using algorithmic differentiation must also be *** this study,various PINNs are adopted to estimate the stresses in the tablets and the interphase of a single lap *** proposed model is represented by two fourth-order non-homogeneous coupled partial differential equations,with the axial stresses in the upper and lower tablets adopted as the dependent *** axial stresses are a function of the tablet length,which presents the independent ***,the axial stresses in the tablets are estimated by solving the coupled partial differential equations when subjected to the boundary conditions,whereas the remaining stress components are expressed in terms of axial *** results obtained using the developed methodology are validated using the results obtained via MAPLE software.

关键词： Physics-informed neural networks(PINNs) Algorithmic differentiation Artificial neural networks Loss function Single lap joint

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Nonlinear Time Series Analysis of Pathogenesis of COVID-19 Pandemic Spreadin Saudi Arabia

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Computers, Materials & Continua 2021年第1期66卷 805-825页

作者： Sunil Kumar sharma shivam Bhardwaj Rashmi Bhardwaj Majed Alowaidi College of Computer and Information Sciences Majmaah UniversityMajmaah11952Saudi Arabia Maharaja Agrasen Institute of Technology Guru Gobind Singh Indraprastha UniversityDelhi110086India Non-Linear Dynamics Research Laboratory GGS Indraprastha UniversityDelhi110078India

This article discusses short–term forecasting of the novel Corona Virus(COVID-19)data for infected and recovered cases using the ARIMA method for Saudi *** COVID-19 data was obtained from the Worldometer and MOH(Ministry of Health,Saudi Arabia).The data was analyzed for the period from March 2,2020(the first case reported)to June 15,*** ARIMA(2,1,0),we obtained the short forecast up to July 02,*** statistical parameters were tested for the goodness of fit to evaluate the forecasting *** results show that ARIMA(2,1,0)gave a better forecast for the data *** 19 data followed quadratic behavior,and in the long run,it spreads with a high *** is concluded that COVID-19 will follow secondary shock waves,and it is strongly advisable to maintain social distancing with all safety measures as the pandemic situation is not in control.

关键词： COVID-19 short-term forecast ARIMA GIS

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Performance of Non-invasive Blood Parameters for Ruling Out Significant Liver Fibrosis in Patients with Chronic Hepatitis B

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Journal of Clinical and Translational Hepatology 2020年第2期8卷 143-149页

作者： shivam Khare Anil Arora Praveen sharma Shashi Dhawan Naresh Bansal Vikas Singla Ashish Kumar Institute of Liver Gastroenterology&Pancreatico-Biliary SciencesSir Ganga Ram HospitalNew DelhiIndia Department of Histopathology Sir Ganga Ram HospitalNew DelhiIndia

Background and Aims:Evaluation of significant liver fibro-sis is important for treatment decision and treatment re-sponse evaluation in patients with chronic hepatitis B. Since liver biopsy is invasive and transient elastography (TE) has limited availability, various non-invasive blood parameters need evaluation for their capabilities for detection of signifi-cant fibrosis. Methods:In this retrospective study, records of patients who had undergone liver biopsy for treatment-na?ve chronic hepatitis B were evaluated to obtain various non-in-vasive blood parameters (aspartate aminotransferase-to-pla-telet ratio index [referred to as APRI], Fibrosis-4 score [referred to as FIB-4], gamma-glutamyl transpeptidase-to-platelet ratio [referred to as GPR], and gamma-glutamyl transpeptidase-to-albumin ratio [referred to as GAR]), in ad-dition to TE, to assess significant liver fibrosis and compare these to fibrosis stage in liver biopsy. Results:A total of 113 patients were included in the study (median age 33 [inter-quartile range: 11-82 years], 74% males). Most (75%) pa-tients were HBeAg-negative. The liver biopsy revealed significant fibrosis (Ishak ≥3) in 13% of the patients and nil or mild fibrosis (Ishak<3) in 87%of the patients. TE findings were available for 85 patients, APRI and FIB-4 for 95 patients, GPR for 79 patients, and GAR for 78 patients. The median values of all the parameters were significantly higher in pa-tients with significant fibrosis, as compared to patients with non-significant fibrosis, and all the blood parameters as well as TE were able to identify patients with significant fibrosis significantly well (p<0.05). All non-invasive parameters had low positive predictive value but negative predictive value above 92%. Compared to TE, all the non-invasive blood pa-rameters had similar area under the curve for detecting sig-nificant fibrosis, with excellent negative predictive value (≥93%). Conclusions: Non-invasive blood parameters (APRI, FIB-4, GPR, and G

关键词： Hepatitis B Liver fibrosis Cirrhosis Transient elastography APRI FIB-4 GPR GAR

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Validation of Vesical Imaging Reporting and Data System score for the diagnosis of muscle-invasive bladder cancer: A prospective cross-sectional study

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Asian Journal of Urology 2022年第4期9卷 467-472页

作者： Kumawat Ghanshyam Vyas Nachiket sharma Govind Priyadarshi shivam Gupta Bhagwan Sahay Singla Mohit Kumar Ashok Department of Urology Sawai Man Singh Medical College and HospitalJaipurRajasthanIndia

Objective:Vesical Imaging Reporting and Data System(VIRADS)score was developed to standardize the reporting and staging of bladder tumors on pre-operative multiparametric magnetic resonance *** helps in avoiding unnecessary repeat transurethral resection of bladder tumor in high-risk non-muscle-invasive bladder cancer *** study was done to determine the validity of VIRADS score prospectively for the diagnosis of muscleinvasive bladder ***:This study was conducted from March 2019 to March 2020 at Sawai Man Singh Medical College and Hospital,Jaipur,Rajasthan,*** admitted with the provisional diagnosis of bladder tumor were included as *** these patients underwent a 3 Tesla mpMRI to obtain a VIRADS score before they underwent transurethral resection of bladder tumor and these data were analyzed to evaluate the correlation of pre-operative VIRADS score with mus-cle invasiveness of the tumor in final biopsy ***:A cut-off of VIRADS≥4 for prediction of detrusor muscle invasion yielded a sensitivity of 79.4%,specificity of 94.2%,positive predictive value of 90.0%,negative predictive value of 87.5%,and diagnostic accuracy of 86.4%.A cut off of VIRADS≥3 for prediction of detrusor muscle invasion yielded a sensitivity of 91.2%,specificity of 78.8%,positive predictive value of 73.8%,negative predictive value of 93.2%,and accuracy of 83.7%.The receiver operating curve showed the area under the curve to be 0.922(95%confidence interval:0.862e0.983).Conclusion:VIRADS score appears to be an excellent and effective pre-operative radiological tool for the prediction of detrusor muscle invasion in bladder cancer.

关键词： Vesical Imaging Reporting and Data System Bladder tumor Multiparametric magnetic resonance imaging Detrusor invasion

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