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[null,"1.","Record Nr.",null,"UNISA996466401503316"]
[null,null,"Titolo",null,"Analysis of infectious disease problems (Covid-19) and their global impact / / Praveen Agarwal [and three others], editors"]
[null,null,"Pubbl/distr/stampa",null,"Gateway East, Singapore : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"981-16-2450-X"]
[null,null,"Descrizione fisica",null,"1 online resource (635 pages)"]
[null,null,"Collana",null,"Infosys Science Foundation series in mathematical sciences"]
[null,null,"Disciplina",null,"616.241400285"]
[null,null,"Soggetti",null,"COVID-19"]
[{"$nulls":4},"Models matemàtics"]
[{"$nulls":4},"COVID-19 (Disease) - Mathematical models"]
[{"$nulls":4},"Llibres electrònics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- General Analysis -- Continued and Serious Lockdown Could Have Minimized Many Newly Transmitted Cases of Covid-19 in the U.S.: Wavelets, Deterministic Models, and Data -- 1 Introduction -- 2 Methods, Models and Data -- 3 Data -- 4 Results -- 5 Concluding Remarks -- References -- Dynamical Analysis of a Caputo Fractional Order SIR Epidemic Model with a General Treatment Function -- 1 Introduction -- 2 Mathematical Model and Preliminaries -- 3 Preliminaries -- 4 The Well-Posedness of the Model and Equilibria -- 4.1 Existence of Endemic Equilibrium -- 5 Local Stability Analysis -- 6 Global Stability Analysis -- 6.1 Infection-Free Equilibrium -- 6.2 Endemic Equilibrium -- 7 Numerical Simulations -- 8 Concluding Remarks -- References -- Protective Face Shield Effectiveness: Mathematical Modelling -- 1 Introduction -- 2 Practical Application of Face Shields -- 3 Mathematical Modelling -- 3.1 Euler Form of Equations -- 3.2 Lagrangian Form of Equations -- 3.3 Model Description -- 3.4 Numerical Methods -- 3.5 Computer Simulation -- 4 Full-Scale Experiment -- 5 Conclusion -- References -- On the Evolution Equation for Modelling the Covid-19 Pandemic -- 1 Introduction -- 2 The Evolution Equation -- 2.1 The Classical Kolmogorov-Feller Equation -- 2.2 The Generalised Kolmogorov-Feller Equation -- 2.3 Orthonormal Memory Functions -- 2.4 Time Series "]
[{"$nulls":4},"Models -- 2.5 Logarithmic Scale Analysis -- 3 Random Walk Fields -- 4 Self-Affine Random Walk Fields -- 4.1 Solution for Eq. (7) -- 4.2 Solution for Eq. (8) -- 4.3 Random Walk Analysis -- 4.4 Example Results -- 5 The Bio-Dynamics Hypothesis -- 5.1 Self-affine Structures of a Virus -- 5.2 A Parametric Self-affine Model -- 5.3 Discussion -- 6 Summary, Conclusions and Future Research -- 6.1 Summary -- 6.2 Conclusions -- 6.3 Future Research."]
[{"$nulls":4},"References -- Modelling the Dynamics of Fake News Spreading Transmission During Covid-19 Through Social Media -- 1 Introduction -- 2 Methodology/Proposal -- 2.1 SIR Model for Fake News Transmission -- 2.2 Fake News Transmission Rate Through Different Social Media Platforms -- 2.3 Fake News Transmission Rate Among Users of Different Age Groups -- 2.4 Fake News Transmission Rate Among Users of Facebook from Different Countries -- 3 Results, Interpretation and Discussion -- 4 Conclusion -- References -- Generalized Logistic Equations in Covid-Related Epidemic Models -- 1 Introduction -- 2 Logistic Coefficients Models -- 2.1 Computable Examples -- 3 Carrying Capacity Periodically Variable -- 3.1 Existence of Periodic Solution -- 3.2 Cosinusoidal Carrying Capacity -- 4 Periodic Harvesting -- 4.1 Global Features of the Solution -- 4.2 Closed-Form Integration and Examples -- 4.3 A Sample Problem -- References -- A Transition of Shared Mobility in Metro Cities-A Challenge Post-Lockdown Covid-19 -- 1 Introduction -- 2 BPR Model -- 3 Data Analysis &amp -- Implementation -- 3.1 Data Description -- 3.2 Model Application &amp -- Results -- 3.3 Prediction of Traffic Scenarios Post-Lockdown -- 4 India's Transport Growth Journey and Its Effect on Energy and Environment -- 4.1 Transport and Environment -- 4.2 Health and Social Issues -- 4.3 Personal Vehicles and Their Impact -- 4.4 Measures to Curb the Traffic Upsurge -- References -- Analysis of Covid-19 Virus Spreading Statistics by the Use of a New Modified Weibull Distribution -- 1 Introduction and Preliminaries -- 1.1 The New Model NMWB Distribution -- 1.2 The Reliability Function -- 1.3 Moments of the Distribution -- 1.4 Order Statistics -- 1.5 Parameter Estimation -- 1.6 Relationship with Weibull-Related Results -- 2 Main Results -- 2.1 Statistical Properties -- 2.2 Least Square Estimates (LSES)."]
[{"$nulls":4},"2.3 Order Statistics -- 2.4 Parameter Estimation -- 3 Applications -- 4 Conclusion -- References -- Lifting Lockdown Control Measure Assessment: From Finite-to Infinite-Dimensional Epidemic Models for Covid-19 -- 1 Introduction -- 2 Data Collection -- 3 Basic Covid-19 Model -- 3.1 Reproduction Numbers -- 3.2 Parameter and Initial Data Estimation -- 4 Discrete Age-Structured Covid-19 Model -- 4.1 Reproduction Numbers -- 4.2 Parameter and Initial Data Estimation -- 5 Covid-19 Model with Constant Delay -- 5.1 Reproduction Numbers -- 5.2 Parameter and Initial Data Estimation -- 6 Covid-19 Model with Threshold-Type Delay -- 7 Models with Demographic Effects -- 7.1 Covid-19 Model with Constant Delay -- 7.2 Covid-19 Model with Threshold-Type Delay -- 8 Discussion -- References -- Introduction to the Grey Systems Theory and Its Application in Mathematical Modeling and Pandemic Prediction of Covid-19 -- 1 A Brief Introduction to the Grey Systems Theory -- 2 Description of the Traditional Linear and Nonlinear Univariate Grey Models GM(1, 1) and NGBM(1, 1) -- 2.1 Building the Traditional Grey Model GM(1, 1) -- 2.2 The Nonlinear Grey Bernoulli Model NGBM(1, 1) -- 3 Optimization of the Univariate Grey Models -- 3.1 Optimization of Hyper-parameters -- 3.2 Rolling Mechanism -- 3.3 Optimization of the Initial Condition -- 4 Applications of Univariate Grey Models in Predicting Total Covid-19 Infected Cases -- 5 Description of the Existing GM(1, N) and GMC(1, N) "]
[{"$nulls":4},"Models -- 5.1 The Traditional GM(1, N) Model -- 5.2 The Grey Model with Convolution Integral GMC(1, N) -- 5.3 Variations of the Current GMC(1, N) and GMC(1, N) Models -- 5.4 Representation of the Nonlinear Grey Model with Convolution Integral NGMC(1, N) -- 6 Grey System Models with Fractional Order Accumulation -- 6.1 Definition of the Fractional Order Accumulation -- 6.2 The Fractional GMpq(1, 1) Model."]
[{"$nulls":4},"6.3 The Fractional Multivariate Grey Model with Convolutional Integral GMC pq(1, N) -- 6.4 Optimization of the Fractional Order r -- 7 Introduction to the Grey Relational Analysis -- 7.1 Data Preprocessing -- 7.2 Grey Relational Coefficient and Grey Relational Grade -- 8 Applications of Grey Relational Analysis In medicine -- 8.1 General Applications of Grey Relational Analysis in Medical Data Analysis -- 8.2 Application in Telecare -- 8.3 Grey Data Management in Medicine -- References -- Mathematical Analysis of Diagnosis Rate Effects in Covid-19 Transmission Dynamics with Optimal Control -- 1 Introduction -- 2 Model Formulation -- 3 Mathematical Analysis -- 3.1 The Disease-Free Equilibrium and Control Reproduction Number -- 3.2 Global Stability of DFE -- 3.3 Existence and Local Stability of the Endemic Equilibrium -- 3.4 Sensitivity Analysis -- 3.5 Numerical Simulation -- 4 Optimal Control -- 4.1 Building the Optimal Control Problem -- 4.2 Characterization of the Optimal Control -- 4.3 Numerical Simulation of the Optimal Control Problem -- 5 Conclusion -- References -- Development of Epidemiological Modeling RD-Covid-19 of Coronavirus Infectious Disease and Its Numerical Simulation -- 1 Introduction -- 2 Infectious Disease Epidemiology Components -- 2.1 Timelines of Infection -- 2.2 Estimation of Transmission Probability -- 2.3 The SAR is a Proportion, Not a Rate -- 3 Estimation of Basic Reproduction Number/ Proliferation Number -- 3.1 Estimation of R0 -- 3.2 Virulence of R0 and the Case Fatality Ratio (CFR) -- 4 Incidence Rate as a Function of Prevalence and Contact Rate -- 5 Dynamic Epidemic Process in a Closed Population -- 6 RD-Covid-19 Epidemiological Model -- 7 Numerical Simulation of RD-Covid-19 Model -- 7.1 PART-1: Numerical Outcome of RD-Covid-19 Model Outcome for INDIA."]
[{"$nulls":4},"7.2 PART-2: Numerical Outcome of RD-Covid-19 Model Outcome for CHINA -- 7.3 PART-3: Numerical Outcome of RD-Covid-19 Model Outcome for BRAZIL -- 7.4 PART-4: Numerical Outcome of RD-Covid-19 Model Outcome for RUSSIA -- 8 Conclusions -- References -- Mediterranean Diet-A Healthy Dietary Pattern and Lifestyle for Strong Immunity -- 1 Introduction -- 2 Mediterranean Lifestyle -- 3 Benefits of Mediterranean Diet -- 4 Mediterranean Diet for a Healthy Gut -- 5 Conclusion -- References -- Rate-Induced Tipping Phenomena in Compartment Models of Epidemics -- 1 Introduction -- 1.1 Outline -- 2 Preliminaries -- 2.1 Compartment Models with Time-Dependent Parameters -- 2.2 Autonomous SIR Model -- 2.3 Autonomous SIRS Model -- 3 Linear Compartment Models -- 3.1 Artifacts of Rate-Induced Tipping -- 4 Nonlinear Compartment Models -- 4.1 Local Normal Form for a Bifurcation of Codimension Two -- 4.2 Idealized Models -- 5 Irreducible Rate-Induced Tipping in Non-autonomous Models -- 5.1 Artifacts of Rate-Induced Tipping -- 6 Conclusion -- References -- Analysis of Impact of Covid-19 Pandemic on Financial Markets -- 1 Introduction -- 2 Market Behaviour During Initial and Intermediate Pandemic Phases -- 2.1 Covid-19 Market Crash (2020/02/19-2020/03/19) -- 2.2 Market Recovery After Covid-19 Crash (2020/03/20 - 2020/03/26) -- 2.3 Pandemic Growth After 2020/03/18 -- 3 Framework for Modelling Pandemic Impact -- 3.1 Susceptible, Infected, Recovered and Death (SIRD) Model with Time-"]
[{"$nulls":4},"Dependent Parameters and Social Distancing -- 3.2 Calibration Algorithm -- 3.3 Phenomenological Pandemic Model (PPM) -- 3.4 The Process N(t) in an Intermediate Phase -- 3.5 Approximation to PPM -- 3.6 Calibration of PPM -- 3.7 Mapping Epidemic Variables to Financial Risk Factors -- 4 Simulation of Stress Scenarios -- 4.1 Simulation of Risk Drivers Under the SIRD Model -- 4.2 PPM Simulation."]
[{"$nulls":4},"5 Conclusion."]
[null,"2.","Record Nr.",null,"UNINA9910151633203321"]
[null,null,"Autore",null,"Fitzgerald John D"]
[null,null,"Titolo",null,"The Great Brain Does It Again"]
[null,null,"Pubbl/distr/stampa",null,"East Rutherford : , : Penguin Young Readers Group, , 2017"]
[{"$nulls":4},"©2017"]
[null,null,"ISBN",null,"0-425-29003-4"]
[null,null,"Descrizione fisica",null,"1 online resource (85 pages)"]
[null,null,"Collana",null,"The Great Brain ; ; v.7"]
[null,null,"Disciplina",null,"823/.9/1"]
[null,null,"Soggetti",null,"Humorous stories"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","In turn-of-the-century Mormon Utah, Tom's great brain comes up with eight more schemes, most of them concerned with earning money."]