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| 1 | Cigarette Smoke-Induced Changes to Alveolar Macrophage Phenotype and Function Are Improved by Treatment with Procysteine显示文摘 | Hodge Sandra Matthews Geoffrey Mukaro Violet Ahern Jessica Shivam Aruna Hodge Greg Holmes Mark Jersmann Hubertus Reynolds Paul N | 2011 | American Journal of Respiratory Cell and Molecular Biology2011，，5： | 1 |
| 2 | Prediction and analysis of blast parameters using artificial neural network显示文摘 | M. Monjezi T.N. Singh Manoj Khandelwal Shivam Sinha Vishal Singh I. Hosseini | 2009 | Noise & Vibration Worldwide2009，，5： | 1 |
| 3 | Culture conditions for the production ofα-galactosidase by Aspergillus parasiticus MTCC-2796: a novel source 显示文摘 | Shivam K Tripathi C P M Mishra S K | 2009 | ElectronicJournal of Biotechnology2009，12，4： | 1 |
| 4 | Static and dynamic characteristics of short wavy journal bearing显示文摘 | Leela Meena Stayam Shivam Gautam Mihir Kumar Ghosh | 2010 | Lubrication Science2010，22，： | 1 |
| 5 | Two-dimensional magnetic materials for spintronic applications显示文摘Spintronic devices are driving new paradigms of bio-inspired,energy efficient computation like neuromorphic stochastic computing and in-memory computing.They have also emerged as key candidates for non-volatile memories for embedded systems as well as alternatives to persistent memories.To meet the growing demands from such diverse applications,there is need for innovation in materials and device designs which can be scaled and adapted according to the application.Two-dimensional(2D)magnetic materials address challenges facing bulk magnet systems by offering scalability while maintaining device integrity and allowing efficient control of magnetism.In this review,we highlight the progress made in experimental studies on 2D magnetic materials towards their integration into spintronic devices.We provide an account of the various relevant material discoveries,demonstrations of current and voltage-based control of magnetism and reported device systems,while also discussing the challenges and opportunities towards integration of 2D magnetic materials in commercial spintronic devices. | Shivam N.Kajale Jad Hanna Kyuho Jang Deblina Sarkar | 2024 | Nano Research2024，17，2： | 1 |
| 6 | Govindaraju On selection of kernelparametes in relevance vector machines for hydrologic appli-cations显示文摘 | Shivam Tripathi Rao S | 2007 | Stoch Environ Res Risk Assess2007，，21： | 1 |
| 7 | Low-cost design of stealthy hardware trojan for bit-level fault attacks on block ciphers显示文摘Fault analysis is a very powerful technique to break cryptographic implementations.In particular,bitlevel fault analysis(BLFA),where faults are injected by flipping one or a few isolated bits,are among the most efficient of the lot.BLFA requires both precise fault injection capabilities and sophisticated key extraction skills.Algebraic fault analysis(AFA)[1]is a good analysis technique for BLFA.Compared with differential fault analysis(DFA),AFA relies on the automation from machine solvers.Since it fully utilizes the | Fan ZHANG Xinjie ZHAO Wei HE Shivam BHASIN Shize GUO | 2017 | Science China(Information Sciences)2017，60，4： | 1 |
| 8 | Watershed reliability, resilience and vulnerability analysis under uncertainty using water quality data显示文摘 | Yamen M. Hoque Shivam Tripathi Mohamed M. Hantush Rao S. Govindaraju | 2012 | Journal of Environmental Management2012，，： | 1 |
| 9 | Watershed reliability,resilience and vulnerability analysis under uncertainty using water quality data显示文摘 | YAMEN M H SHIVAM T MOHAMED M H | 2012 | J Environ Manage2012，109，： | 1 |
| 10 | Special Section on Attacking and Protecting Artificial Intelligence显示文摘Modern Artificial Intelligence(AI)systems largely rely on advanced algorithms,including machine learning techniques such as deep learning.The research community has invested significant efforts in understanding these algorithms,optimally tuning them,and improving their performance,but it has mostly neglected the security facet of the problem.Recent attacks and exploits demonstrated that machine learning‐based algorithms are susceptible to attacks targeting computer systems,including backdoors,hardware Trojans and fault attacks,but are also susceptible to a range of attacks specifically targeting them,such as adversarial input perturbations. | Shivam Bhasin Siddharth Garg Francesco Regazzoni | 2021 | CAAI Transactions on Intelligence Technology2021，6，1： | 0 |
| 11 | Physics-informed neural networks for estimating stress transfer mechanics in single lap joints显示文摘With the explosive growth of computational resources and data generation,deep machine learning has been successfully employed in various applications.One important and emerging scientific application of deep learning involves solving differential equations.Here,physics-informed neural networks(PINNs)are developed to solve the differential equations associated with a specific scientific problem.As 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 developed.In this study,various PINNs are adopted to estimate the stresses in the tablets and the interphase of a single lap joint.The 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 variables.The axial stresses are a function of the tablet length,which presents the independent variable.Therefore,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 stresses.The results obtained using the developed methodology are validated using the results obtained via MAPLE software. | Shivam SHARMA Rajneesh AWASTHI Yedlabala Sudhir SASTRY Pattabhi Ramaiah BUDARAPU | 2021 | Journal of Zhejiang University-Science A(Applied Physics & Engineering)2021，22，8： | 0 |
| 12 | A dual-mode image sensor using an all-inorganic perovskite nanowire array for standard and neuromorphic imaging显示文摘The high-density,vertically aligned retinal neuron array provides effective vision,a feature we aim to replicate with electronic devices.However,the conventional complementary metal-oxide-semiconductor(CMOS)image sensor,based on separate designs for sensing,memory,and processing units,limits its integration density.Moreover,redundant signal communication significantly increases energy consumption.Current neuromorphic devices integrating sensing and signal processing show promise in various computer vision applications,but there is still a need for frame-based imaging with good compatibility.In this study,we developed a dual-mode image sensor based on a high-density all-inorganic perovskite nanowire array.The device can switch between frame-based standard imaging mode and neuromorphic imaging mode by applying different biases.This unique bias-dependent photo response is based on a well-designed energy band diagram.The biomimetic alignment of nanowires ensures the potential for high-resolution imaging.To further demonstrate the imaging ability,we conducted pattern reconstruction in both modes with a 10×10 crossbar device.This study introduces a novel image sensor with high compatibility and efficiency,suitable for various applications including computer vision,surveillance,and robotics. | Zhenghao Long Yucheng Ding Xiao Qiu Yu Zhou Shivam Kumar Zhiyong Fan | 2023 | Journal of Semiconductors2023，44，9： | 0 |
| 13 | Nonlinear Time Series Analysis of Pathogenesis of COVID-19 Pandemic Spreadin Saudi Arabia显示文摘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 Arabia.The 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 15,2020.Using ARIMA(2,1,0),we obtained the short forecast up to July 02,2020.Several statistical parameters were tested for the goodness of fit to evaluate the forecasting methods.The results show that ARIMA(2,1,0)gave a better forecast for the data system.COVID 19 data followed quadratic behavior,and in the long run,it spreads with a high peak.It 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. | Sunil Kumar Sharma Shivam Bhardwaj Rashmi Bhardwaj Majed Alowaidi | 2021 | Computers, Materials & Continua2021，，1： | 0 |
| 14 | Transistor level SCA-resistant scheme based on fluctuating power logic显示文摘Appendix A Experiment Results In order to establish topological design rules and to recognize possible obstructions for securing an encryption block module against DPA at the cell level,we take fundamental components(SBox module)of Advanced Encryption Standard(AES) | Liang GENG Fan ZHANG Jizhong SHEN Wei HE Shivam BHASIN Xinjie ZHAO Shize GUO | 2017 | Science China(Information Sciences)2017，60，10： | 0 |
| 15 | Metastatic inguinal lymph nodes with two different histological types in a case of carcinoma of unknown primary site显示文摘Cancer of unknown primary site is a group of uncommon cancers where patients present with metastatic disease and the primary site is not identifi ed,even after a complete workup to establish the diagnosis.Inguinal metastasis with unknown primary is even more uncommon,and histological type is the most important guiding factor to look for the primary.This report describes the rare situation of inguinal metastasis with an unknown primary site where a combination of squamous and transitional cell carcinoma was found on fi nal histopathology.It highlights the importance of multimodality approach including an aggressive surgical resection combined with adjuvant radiation therapy to achieve an optimal outcome. | Mukur Dipi Ray Shivam Vatsal Sunil Kumar | 2015 | Journal of Cancer Metastasis and Treatment2015，1，1： | 0 |
| 16 | Validation of Vesical Imaging Reporting and Data System score for the diagnosis of muscle-invasive bladder cancer: A prospective cross-sectional study显示文摘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 imaging.It helps in avoiding unnecessary repeat transurethral resection of bladder tumor in high-risk non-muscle-invasive bladder cancer patients.This study was done to determine the validity of VIRADS score prospectively for the diagnosis of muscleinvasive bladder cancer.Methods:This study was conducted from March 2019 to March 2020 at Sawai Man Singh Medical College and Hospital,Jaipur,Rajasthan,India.Patients admitted with the provisional diagnosis of bladder tumor were included as participants.All 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 report.Results: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. | Kumawat Ghanshyam Vyas Nachiket Sharma Govind Priyadarshi Shivam Gupta Bhagwan Sahay Singla Mohit Kumar Ashok | 2022 | Asian Journal of Urology2022，9，4： | 0 |
| 17 | A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data显示文摘Modern diagnostic tools in turbulent combustion allow for highly-resolved measurements of reacting flows;however,they tend to generate massive data-sets,rendering conventional analysis intractable and inefficient.To alleviate this problem,machine learning tools may be used to,for example,discover features from the data for downstream modeling and prediction tasks.To this end,this work applies generative adversarial networks(GANs)to generate realistic flame images based on a time-resolved data set of hydroxide concentration snapshots obtained from planar laser induced fluorescence measurements of a model combustor.The generative model is able to generate flames in attached,lifted,and intermediate configurations dictated by the user.Using��-means clustering and proper orthogonal decomposition,the synthetic image set produced by the GAN is shown to be visually similar to the real image set,with recirculation zones and burned/unburned regions clearly present,indicating good GAN performance in capturing the experimental data statistical structure.Combined with techniques for controlling the configuration of generated flames,this work opens new avenues towards tractable statistical analysis and modeling of flame behavior,as well as rapid and inexpensive flame data generation. | Anthony Carreon Shivam Barwey Venkat Raman | 2023 | Energy and AI2023，13，3： | 0 |
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