A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

A study of the errors of the averaged models in the restricted three-body problem in a short time scale

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multiple-time higher-order perturbation analysis of the regularized long-wavelength equation

By considering the long-wavelength limit of the regularized long wave (RLW) equation, we study its multiple-time higher-order evolution equations. As a first result, the equations of the Korteweg-de Vries hierarchy are shown to play a crucial role in providing a secularity-free perturbation theory in the specific case of a solitary-wave solution. Then, as a consequence, we show that the related perturbative series can be summed and gives exactly the solitary-wave solution of the RLW equation. Finally, some comments and considerations are made on the N-soliton solution, as well as on the limitations of applicability of the multiple-scale method in obtaining uniform perturbative series.

Astronomical time scale for Paleocene and early Eocene sediments

The astronomical-tuned time scale is rapidly extended into the Paleogene but, due to the existence of an Eocene gap, different tuning options had to be presented for the Paleocene. These options differ both in number and tuning of ~405-kyr eccentricity related cycles and are only partially consistent with recalculated 40Ar/39Ar constraints for the Cretaceous/Paleogene (K/Pg) and Paleocene/Eocene (P/E) boundaries. In this paper, we evaluate the cyclostratigraphic interpretation of records from ODP Leg 198 and 208 sites, and the Zumaia section to solve the problem of the different tuning options. We found that the interval between the K/Pg boundary and the early Late Paleocene biotic event (ELPE) comprises 17 instead of 16 * ~405-kyr eccentricity related cycles as previously proposed, while the entire Paleocene contains 25 * ~405-kyr cycles. Starting from 40Ar/39Ar age constraints for the K/Pg boundary, a new tuning to 405-kyr eccentricity is presented for the Paleocene and earliest Eocene, which results in ages of ~66.0 and ~ 56.0 Ma for the K/Pg and P/E boundaries, respectively. This tuning introduces considerable differences in age for a number of nannofossil events at ODP Sites 1209 and 1262 in the interval between 61 and 63 Ma, but eliminates large and abrupt changes in the seafloor spreading rate. The tuning seems further consistent with recalculated 40Ar/39Ar ages for ash layer -17 of early Eocene age. However, despite this apparent consistency with existing radio-isotopic constraints, an alternative 405-kyr younger or, less likely, older tuning cannot be excluded at this stage.

Time-frequency and time-scale analysis of Barkhausen noise signals

Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Time-frequency and time-scale characterisation of the beat-by-beat high-resolution electrocardiogram

Proceedings of the Sixth Portuguese Conference on Bioemedical Engineering faro, Portugal

Turnover and accumulation of genetic diversity across large time-scale cycles of isolation and connection of populations.

Major climatic and geological events but also population history (secondary contacts) have generated cycles of population isolation and connection of long and short periods. Recent empirical and theoretical studies suggest that fast evolutionary processes might be triggered by such events, as commonly illustrated in ecology by the adaptive radiation of cichlid fishes (isolation and reconnection of lakes and watersheds) and in epidemiology by the fast adaptation of the influenza virus (isolation and reconnection in hosts). We test whether cyclic population isolation and connection provide the raw material (standing genetic variation) for species evolution and diversification. Our analytical results demonstrate that population isolation and connection can provide, to populations, a high excess of genetic diversity compared with what is expected at equilibrium. This excess is either cyclic (high allele turnover) or cumulates with time depending on the duration of the isolation and the connection periods and the mutation rate. We show that diversification rates of animal clades are associated with specific periods of climatic cycles in the Quaternary. We finally discuss the importance of our results for macroevolutionary patterns and for the inference of population history from genomic data.

Time-scale and other invariants of integrative mechanical behavior in living cells.

In dealing with systems as complex as the cytoskeleton, we need organizing principles or, short of that, an empirical framework into which these systems fit. We report here unexpected invariants of cytoskeletal behavior that comprise such an empirical framework. We measured elastic and frictional moduli of a variety of cell types over a wide range of time scales and using a variety of biological interventions. In all instances elastic stresses dominated at frequencies below 300 Hz, increased only weakly with frequency, and followed a power law; no characteristic time scale was evident. Frictional stresses paralleled the elastic behavior at frequencies below 10 Hz but approached a Newtonian viscous behavior at higher frequencies. Surprisingly, all data could be collapsed onto master curves, the existence of which implies that elastic and frictional stresses share a common underlying mechanism. Taken together, these findings define an unanticipated integrative framework for studying protein interactions within the complex microenvironment of the cell body, and appear to set limits on what can be predicted about integrated mechanical behavior of the matrix based solely on cytoskeletal constituents considered in isolation. Moreover, these observations are consistent with the hypothesis that the cytoskeleton of the living cell behaves as a soft glassy material, wherein cytoskeletal proteins modulate cell mechanical properties mainly by changing an effective temperature of the cytoskeletal matrix. If so, then the effective temperature becomes an easily quantified determinant of the ability of the cytoskeleton to deform, flow, and reorganize.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

SDF 1-alpha (CXCL12) triggers glutamate exocytosis from astrocytes on a millisecond time scale: Imaging analysis at the single-vesicle level with TIRF microscopy

Chemokines are small chemotactic molecules widely expressed throughout the central nervous system. A number of papers, during the past few years, have suggested that they have physiological functions in addition to their roles in neuroinflammatory diseases. In this context, the best evidence concerns the CXC-chemokine stromal cell-derived factor (SDF-1alpha or CXCL12) and its receptor CXCR4, whose signalling cascade is also implicated in the glutamate release process from astrocytes. Recently, astrocytic synaptic like microvesicles (SLMVs) that express vesicular glutamate transporters (VGLUTs) and are able to release glutamate by Ca(2+)-dependent regulated exocytosis, have been described both in tissue and in cultured astrocytes. Here, in order to elucidate whether SDF-1alpha/CXCR4 system can participate to the brain fast communication systems, we investigated whether the activation of CXCR4 receptor triggers glutamate exocytosis in astrocytes. By using total internal reflection (TIRF) microscopy and the membrane-fluorescent styryl dye FM4-64, we adapted an imaging methodology recently developed to measure exocytosis and recycling in synaptic terminals, and monitored the CXCR4-mediated exocytosis of SLMVs in astrocytes. We analyzed the co-localization of VGLUT with the FM dye at single-vesicle level, and observed the kinetics of the FM dye release during single fusion events. We found that the activation of CXCR4 receptors triggered a burst of exocytosis on a millisecond time scale that involved the release of Ca(2+) from internal stores. These results support the idea that astrocytes can respond to external stimuli and communicate with the neighboring cells via fast release of glutamate.

Recent oppositely directed trends in solar climate forcings and the global mean surface air temperature. II. Different reconstructions of the total solar irradiance variation and dependence on response time scale

We have previously placed the solar contribution to recent global warming in context using observations and without recourse to climate models. It was shown that all solar forcings of climate have declined since 1987. The present paper extends that analysis to include the effects of the various time constants with which the Earth’s climate system might react to solar forcing. The solar input waveform over the past 100 years is defined using observed and inferred galactic cosmic ray fluxes, valid for either a direct effect of cosmic rays on climate or an effect via their known correlation with total solar irradiance (TSI), or for a combination of the two. The implications, and the relative merits, of the various TSI composite data series are discussed and independent tests reveal that the PMOD composite used in our previous paper is the most realistic. Use of the ACRIM composite, which shows a rise in TSI over recent decades, is shown to be inconsistent with most published evidence for solar influences on pre-industrial climate. The conclusions of our previous paper, that solar forcing has declined over the past 20 years while surface air temperatures have continued to rise, are shown to apply for the full range of potential time constants for the climate response to the variations in the solar forcings.