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Modelling and analysis impact of El Nino and IOD to land and forest fire using polynomial and generalized logistic function: cases study in South Sumatra and Kalimantan, Indonesia

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MODELING EARTH SYSTEMS AND ENVIRONMENT 2022年第3期8卷 3341-3356页

作者： Nurdiati, Sri Sopaheluwakan, Ardhasena Julianto, Mochamad T. Septiawan, Pandu Rohimahastuti, Fadillah IPB Univ Dept Math Bogor 16680 Indonesia Agcy Meteorol Climatol & Geophys Ctr Appl Climate Serv Jakarta 10610 Indonesia

In the last 20 years, land and forest fires have become a phenomenon that occurs annually in South Sumatra and Kalimantan. More than 2.6 million ha of the area was burned only during very strong El Nino in 2015. Understanding the relation of fire indicators with various drivers such as dry spell, total precipitation, El Nino, and positive IOD is essential to prevent future fires. This study aims to propose a method that can be used to model and analyze the impact of El Nino and IOD on land and forest fires using polynomial and generalized logistic functions. Coefficients of the model are determined using the optimization method to maximize the correlation between climate and hotspot data. In analyzed regions, the model can represent the behavior of El Nino and IOD in influencing hotspot occurrence. In Kalimantan, the model is dominated by El Nino's impact with a coefficient value of 2.6, more than 3 x larger than the coefficient of IOD. South Sumatra's models show a balanced coefficient of ENSO (4.4) and IOD (3.25), while the highest impact occurred on the ENSO-IOD teleconnection coefficient with a value of 4.6. When used as a weight function, the model increases the correlation value of dry spell and hotspot at the center of the fire. Therefore, resulting in the more precise result of HCM analysis. A cross-validation test for weighted regression can increase the determination number (in %) of models with coefficient determination value more than 0.7 by around 28%-59% in Kalimantan and 0%-31% in South Sumatra. Moreover, the model can estimate hotspot data using monthly average data and ENSO/IOD index in the respective month. Using the copula-based joint distribution of estimate data and dry spell, we can estimate the conditional probability of 10% high extreme fire events close to the observed data conditional probability during El Nino in Kalimantan (less than 7% error average) and positive IOD in South Sumatra (around 26% error average).

关键词： Hotspot Drought ENSO IOD generalized logistic function Estimation

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Assessment of isoconversional methods and peak functions for the kinetic analysis of thermogravimetric data and its application to degradation processes of organic phase change materials

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JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2024年第23期149卷 13879-13899页

作者： Bayon, Rocio Garcia-Rojas, Redlich Rojas, Esther Rodriguez-Garcia, Margarita M. CIEMAT PSA Thermal Energy Storage Unit Ave Complutense 40 Madrid 28040 Spain

In this work, theoretical kinetic curves of both single- and multi-step reaction mechanisms were simulated by using different sets of kinetic parameters. Various isoconversional methods were applied for the kinetic analysis of these curves so that the corresponding activation energy vs. conversion degree curves were obtained and then compared with the energy values used in the simulations. For single-step reaction mechanisms Friedman method resulted to be the most accurate while for multi-step reaction mechanisms, Kissinger-Akahira-Sunose and Coats-Redfern methods led to the most accurate estimation of the activation energy. On the other hand, conversion rate curves of different single-step reaction mechanisms were fitted with two kinds of peak functions (normalized Fraser-Suzuki and generalized logistic) so that the relationships between the parameters of these functions and the kinetic parameters used in the simulations were obtained. These relationships were then used in the mathematical deconvolution analysis of conversion rate curves simulated for multi-step reaction mechanisms. In general, the curves resulting from deconvolution fitted quite well the simulated conversion rate curves and the analysis of the resulting single-step reaction curves with Kissinger method led the kinetic parameters close to the ones used in the simulations. Finally, a similar kinetic analysis was applied to experimental thermogravimetric measurements taken both under N2 and air for two phase change materials (PCMs) based on polyethylene glycol, PEG6000 and PEG12000. Activation energy values obtained with isoconversional methods for the measurements under N2, varied from 40 kJ mol-1 at low conversions up to 150 kJ mol-1 at high conversions, whereas for the measurements under air the energy values remained almost constant in the range of 50-75 kJ mol-1. The lower activation energies obtained for the measurements under air are clearly associated with the polymer combustion. The experime

关键词： Kinetic analysis Isoconversional methods Fraser-Suzuki function generalized logistic function Fitting Mathematical deconvolution analysis TG measurements PCM

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BIFURCATION CURVES OF A DIRICHLET PROBLEM WITH GEOMETRICALLY CONCAVE NONLINEARITY AND AN APPLICATION TO THE generalized logistic GROWTH MODEL

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PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY 2021年第3期149卷 1117-1126页

作者： Hung, Kuo-Chih Natl Chin Yi Univ Technol Fundamental Gen Educ Ctr Taichung 411 Taiwan

We study the bifurcation curves for a Dirichlet problem with geometrically concave nonlinearity. We give an application to the generalized logistic growth model {u ''(x)+ lambda f(u) = 0, - 1 < x < 1, u(-1) = u(1) = 0, f(u) = u(alpha) [1- (u/K)(beta)](gamma) , alpha, beta,gamma > 0. There are totally six qualitatively bifurcation curves of order relations for (alpha, beta, gamma).

关键词： Exact multiplicity positive solution bifurcation curve geometrically concave nonlinearity generalized logistic function

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Mathematical Simulation of the Sliding Friction of Silicon Carbide in an Aqueous Medium

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RUSSIAN METALLURGY 2021年第4期2021卷 507-511页

作者： Breki, A. D. Chulkin, S. G. Gvozdev, A. E. Kolmakov, A. G. Peter Great St Petersburg Polytech Univ St Petersburg 195251 Russia St Petersburg State Marine Tech Univ St Petersburg 190121 Russia Tula State Pedag Univ Tula 300026 Russia Russian Acad Sci Baikov Inst Met & Mat Sci Moscow 119334 Russia

The sliding friction of silicon carbide bodies in an aqueous medium is studied using the models that take into account sigmoid changes in the friction force. The dependence of the friction force on the sliding velocit... 详细信息

关键词： sliding friction silicon carbide mathematical model friction force friction power friction momentum generalized logistic function

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COVID-19: data-driven dynamics, statistical and distributed delay models, and observations

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NONLINEAR DYNAMICS 2020年第3期101卷 1527-1543页

作者： Liu, Xianbo Zheng, Xie Balachandran, Balakumar Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China Univ Maryland Dept Mech Engn College Pk MD 20742 USA

COVID-19 was declared as a pandemic by the World Health Organization on March 11, 2020. Here, the dynamics of this epidemic is studied by using a generalized logistic function model and extended compartmental models with and without delays. For a chosen population, it is shown as to how forecasting may be done on the spreading of the infection by using a generalized logistic function model, which can be interpreted as a basic compartmental model. In an extended compartmental model, which is a modified form of the SEIQR model, the population is divided into susceptible, exposed, infectious, quarantined, and removed (recovered or dead) compartments, and a set of delay integral equations is used to describe the system dynamics. Time-varying infection rates are allowed in the model to capture the responses to control measures taken, and distributed delay distributions are used to capture variability in individual responses to an infection. The constructed extended compartmental model is a nonlinear dynamical system with distributed delays and time-varying parameters. The critical role of data is elucidated, and it is discussed as to how the compartmental model can be used to capture responses to various measures including quarantining. Data for different parts of the world are considered, and comparisons are also made in terms of the reproductive number. The obtained results can be useful for furthering the understanding of disease dynamics as well as for planning purposes.

关键词： Dynamics and control of epidemics generalized logistic function System identification SEIQR model Delay integral equations

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Integration of multiple response signals into the probability of detection modelling in eddy current NDE of flaws

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NDT & E INTERNATIONAL 2021年 118卷 102401-102401页

作者： Baskaran, Prashanth Pasadas, D. J. Ramos, H. G. Ribeiro, A. L. Univ Lisbon Inst Super Tecn Inst Telecomunicacoes Lisbon Portugal

A new method of modelling the probability of detection (PoD) of a flaw parameter (flaw length) for the case of multiple correlated flaw response signals is proposed in this work. The PoD modelling is assisted by boundary element method in order to compute the required flaw features, the maximum change in the impedance of a coil, at two different frequencies. Experiments were performed using a LCR meter to verify the predictions of the boundary element model. The modelling was performed on a finite thickness aluminum-1050 plate with a narrow opening surface flaw. The features were computed for various flaw lengths and fit with a bi-variate Gaussian distribution, thus evading the problem of heteroscedasticity. On knowing the signal thresholds, the PoD of a flaw length can be computed from the Gaussian density. The obtained discrete PoD is then regressed by a generalized logistic function (GLF) in order to attain a continuous function for the PoD of the flaw length. The parameters of the GLF are estimated via non-linear least squares minimization by Levenberg-Marquardt algorithm.

关键词： Eddy current NDT Probability of detection (PoD) Boundary element model (BEM) generalized logistic function Levenberg-Marquardt algorithm

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Inversion Charge Density of MOS transistor with generalized logistic functions

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SCIENCE OF SINTERING 2018年第2期50卷 225-235页

作者： Kevkic, Tijana Stojanovic, Vladica Petrovic, Vera Randelovic, Dragan Univ Pristina Kosovska Mitrovica Fac Sci & Math Lole Ribara 29 Kosovska Mitrovica 38220 Serbia Sch Elect Engn & Comp Sci Appl Studies Vojvode Stepe 283 Belgrade 11000 Serbia Acad Criminalist & Police Studies Cara Dusana 196 Belgrade 11000 Serbia

In this paper, the expression for the charge density in inversion layer at the surface of semiconductor has been improved. The improvement is related to the replacement of an empirical smoothing factor by new one which has generalized logistic (GL) functional form. The introduction of the GL function of the second type in the original interpolating expression leads to continual and smooth transition of the inversion charge density (ICD) between different regions of metal-oxide-semiconductor (MOS) operation. Moreover, in this way any empirical determinations are avoided. The simulated values of the ICD match closely with the numerical results of implicit charge sheet model for a wide range of dopant concentration and oxide thickness. In addition, the proposed GL fitting procedure has been also extended in the case where quantum mechanical effects play important role in inversion mode of scaled MOS devices.

关键词： Inversion charge density MOS modeling generalized logistic function Quantum mechanical effects

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Robust parametric modeling of Alzheimer's disease progression

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NEUROIMAGE 2021年 225卷 117460-117460页

作者： Ghazi, Mostafa Mehdipour Nielsen, Mads Pai, Akshay Modat, Marc Cardoso, M. Jorge Ourselin, Sebastien Sorensen, Lauge Biomediq AS Copenhagen Denmark Cerebriu AS Copenhagen Denmark Univ Copenhagen Dept Comp Sci Copenhagen Denmark UCL Dept Med Phys & Biomed Engn London England Kings Coll London Sch Biomed Engn & Imaging Sci London England

Quantitative characterization of disease progression using longitudinal data can provide long-term predictions for the pathological stages of individuals. This work studies the robust modeling of Alzheimer's disease progression using parametric methods. The proposed method linearly maps the individual's age to a disease progression score (DPS) and jointly fits constrained generalized logistic functions to the longitudinal dynamics of biomarkers as functions of the DPS using M-estimation. Robustness of the estimates is quantified using bootstrapping via Monte Carlo resampling, and the estimated inflection points of the fitted functions are used to temporally order the modeled biomarkers in the disease course. Kernel density estimation is applied to the obtained DPSs for clinical status classification using a Bayesian classifier. Different M-estimators and logistic functions, including a novel type proposed in this study, called modified Stannard, are evaluated on the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for robust modeling of volumetric magnetic resonance imaging (MRI) and positron emission tomography (PET) biomarkers, cerebrospinal fluid (CSF) measurements, as well as cognitive tests. The results show that the modified Stannard function fitted using the logistic loss achieves the best modeling performance with an average normalized mean absolute error (NMAE) of 0.991 across all biomarkers and bootstraps. Applied to the ADNI test set, this model achieves a multiclass area under the ROC curve (AUC) of 0.934 in clinical status classification. The obtained results for the proposed model outperform almost all state-of-the-art results in predicting biomarker values and classifying clinical status. Finally, the experiments show that the proposed model, trained using abundant ADNI data, generalizes well to data from the National Alzheimer's Coordinating Center (NACC) with an average NMAE of 1.182 and a multiclass AUC of 0.929.

关键词： Alzheimer's disease Disease progression modeling M-estimation generalized logistic function Kernel density estimation Bayesian classifier Magnetic resonance imaging Positron emission tomography Cerebrospinal fluid

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IN VITRO POPULATION GROWTH OF HUMAN GLIOBLASTOMAS: REAL PATIENTS AND CURVE FITTING

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Hematology, Transfusion and Cell Therapy 2025年 47卷 103807-103807页

作者： Diego Samuel Rodrigues Letícia Fernanda Alves João Frederico da Costa Azevedo Meyer Moníze Valéria Ramos da Silva Natália Barreto Catarina Raposo Faculdade de Tecnologia Universidade Estadual de Campinas (UNICAMP) Limeira SP Brazil PhD Program in Applied Mathematics Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil Instituto de Matemática Estatística e Computação Científica Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil Faculdade de Ciências Farmacêuticas Universidade Estadual de Campinas (UNICAMP) Campinas SP Brazil

Introduction/Justification For more than a century, a variety of ordinary differential equation growth models have been used to describe and predict the proliferation of human malignancies. Indeed, in the field of mathematical oncology, the growth of cell populations over time is typically represented by sigmoidal functions, such as logistic or Gompertz curves and their generalizations. These models are particularly focused on understanding and predicting the proliferation of cancer cells, including those from human glioblastomas, which can be very aggressive brain tumors with a survival rate of less than two years. Objectives This research examines in vitro cell cultures of five lines of human glioblastoma using curve fitting and numerical parameter estimation of real datasets to separately describe the growth profile of all these cell populations lineages over time. Materials and Methods Cell culture experiments were performed in the Advanced Therapeutics Laboratory at FCF-UNICAMP. These included a well-established human glioblastoma cell line (NG97) and four other glioblastoma cell lines derived from clinical patients designated N07, C03, L09 and J01. Twelve repeated time series of experiments were collected for each cell line. Cell counting was performed daily on days 1 to 6. The drda R package was used for curve fitting of the measured data aiming to determine the intrinsic growth rate and other parameters for each of the five cell lines. The 5-parameter generalized logistic curve was used, and all the resulting models were analyzed under statistical criteria such as the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Results Curve fitting analysis revealed significant diversity in the population growth of different cell lines. The drda R package proved to be highly effective in capturing these different behaviors and the unique sigmoidal shapes associated with them. Notably, the population growth of NG97 cells showed the least

关键词： generalized logistic function Glioblastomas Mathematical Oncology

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Towards a novel backdating strategy for creating built-up land time series data using contemporary spatial constraints

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REMOTE SENSING OF ENVIRONMENT 2020年第0期238卷 111197-000页

作者： Uhl, Johannes H. Leyk, Stefan Univ Colorado Dept Geog Boulder CO 80309 USA

For retrospective land cover change analysis extending back in time earlier than approximately the year 2000, multispectral remote sensing data such as the Landsat archive are often the only available and systematically archived data source. However, the spatial resolution of such observations often impedes the change analysis of geographic phenomena that may occur at sub-pixel level, such as changes in built-up land. In such cases, the integration of these data products with increasingly available contemporary high resolution settlement data employed as spatial constraints can potentially mitigate this drawback. Little research has been done regarding the quantitative potential of such integrative approaches, often due to the lack of multi-temporal reference data about changes in built-up area at sufficient spatio-temporal granularity and extent. In this contribution, we present and evaluate a time-series based approach for built-up area change analysis using Landsat time series data, spatially constrained by contemporary building footprint data. We evaluate the potential of our approach using a highly accurate multi-temporal reference database of built-up areas created through integrating publicly available building footprint and cadastral data in selected regions of the United States of America.

关键词： Retrospective human settlement modelling Urban change analysis Landsat Google earth engine Time series classification generalized logistic function Support vector machine Time series clustering Data integration

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