Binary time series generated by chaotic logistic maps

This paper examines stochastic pairwise dependence structures in binary time series obtained from discretised versions of standard chaotic logistic maps. It is motivated by applications in communications modelling which make use of so-called chaotic binary sequences. The strength of non-linear stochastic dependence of the binary sequences is explored. In contrast to the original chaotic sequence, the binary version is non-chaotic with non-Markovian non-linear dependence, except in a special case. Marginal and joint probability distributions, and autocorrelation functions are elicited. Multivariate binary and more discretised time series from a single realisation of the logistic map are developed from the binary paradigm. Proposals for extension of the methodology to other cases of the general logistic map are developed. Finally, a brief illustration of the place of chaos-based binary processes in chaos communications is given.Binary sequence; chaos; chaos communications; dependence; discretisation; invariant distribution; logistic map; randomness

Synchronised laser chaos communication: statistical investigation of an experimental system

The paper is concerned with analyzing data from an experimental antipodal laser-based chaos shift-keying communication system. Binary messages are embedded in a chaotically behaving laser wave which is transmitted through a fiber-optic cable and are decoded at the receiver using a second laser synchronized with the emitter laser. Instrumentation in the experimental system makes it particularly interesting to be able to empirically analyze both optical noise and synchronization error as well as bit error rate. Both the noise and error are found to significantly depart in distribution from independent Gaussian. The conclusion from bit error rate results is that the antipodal laser chaos shift-keying system can offer a feasible approach to optical communication. The non-Gaussian optical noise and synchronous error results are a challenge to current theoretical modelling

Modelling Health State Utilities as a Transformation of Time to Death in Patients with Non-Small Cell Lung Cancer

Background: When utilities are analyzed by time to death (TTD), this has historically been implemented by ‘grouping’ observations as discrete time periods to create health state utilities. We extended the approach to use continuous functions, avoiding assumptions around groupings. The resulting models were used to test the concept with data from different regions and different country tariffs. Methods: Five-year follow-up in advanced non-small cell lung cancer (NSCLC) was used to fit six continuous TTD models using generalized estimating equations, which were compared with progression-based utilities and previously published TTD groupings. Sensitivity analyses were performed using only patients with a confirmed death, the last year of life only, and artificially censoring data at 24 months. The statistically best-fitting model was then applied to data subsets by region and different EQ-5D-3L country tariffs. Results: Continuous (natural) Log (TTD) and 1/TTD models outperformed other continuous models, grouped TTD, and progression-based models in statistical fit (mean absolute error and Quasi Information Criterion). This held through sensitivity and scenario analyses. The pattern of reduced utility as a patient approaches death was consistent across regions and EQ-5D tariffs using the preferred Log (TTD) model. Conclusions: The use of continuous models provides a statistically better fit than TTD groupings, without the need for strong assumptions about the health states experienced by patients. Where a TTD approach is merited for use in modelling, continuous functions should be considered, with the scope for further improvements in statistical fit by both widening the number of candidate models tested and the therapeutic areas investigated

individual participant data meta-analysis of randomised trials study protocol

Introduction Parenteral anticoagulants may improve outcomes in patients with cancer by reducing risk of venous thromboembolic disease and through a direct antitumour effect. Study-level systematic reviews indicate a reduction in venous thromboembolism and provide moderate confidence that a small survival benefit exists. It remains unclear if any patient subgroups experience potential benefits. Methods and analysis First, we will perform a comprehensive systematic search of MEDLINE, EMBASE and The Cochrane Library, hand search scientific conference abstracts and check clinical trials registries for randomised control trials of participants with solid cancers who are administered parenteral anticoagulants. We anticipate identifying at least 15 trials, exceeding 9000 participants. Second, we will perform an individual participant data meta-analysis to explore the magnitude of survival benefit and address whether subgroups of patients are more likely to benefit from parenteral anticoagulants. All analyses will follow the intention-to- treat principle. For our primary outcome, mortality, we will use multivariable hierarchical models with patient-level variables as fixed effects and a categorical trial variable as a random effect. We will adjust analysis for important prognostic characteristics. To investigate whether intervention effects vary by predefined subgroups of patients, we will test interaction terms in the statistical model. Furthermore, we will develop a risk-prediction model for venous thromboembolism, with a focus on control patients of randomised trials. Ethics and dissemination Aside from maintaining participant anonymity, there are no major ethical concerns. This will be the first individual participant data meta-analysis addressing heparin use among patients with cancer and will directly influence recommendations in clinical practice guidelines. Major cancer guideline development organisations will use eventual results to inform their guideline recommendations. Several knowledge users will disseminate results through presentations at clinical rounds as well as national and international conferences. We will prepare an evidence brief and facilitate dialogue to engage policymakers and stakeholders in acting on findings. Trial registration number PROSPERO CRD4201300352

Binding of Hyaluronan to the Native Lymphatic Vessel Endothelial Receptor LYVE-1 Is Critically Dependent on Receptor Clustering and Hyaluronan Organization

The lymphatic endothelial receptor LYVE-1 has been implicated in both uptake of hyaluronan (HA) from tissue matrix and in facilitating transit of leukocytes and tumor cells through lymphatic vessels based largely on in vitro studies with recombinant receptor in transfected fibroblasts. Curiously, however, LYVE-1 in lymphatic endothelium displays little if any binding to HA in vitro, and this has led to the conclusion that the native receptor is functionally silenced, a feature that is difficult to reconcile with its proposed in vivo functions. Nonetheless, as we reported recently, LYVE-1 can function as a receptor for HA-encapsulated Group A streptococci and mediate lymphatic dissemination in mice. Here we resolve these paradoxical findings and show that the capacity of LYVE-1 to bind HA is strictly dependent on avidity, demanding appropriate receptor self-association and/or HA multimerization. In particular, we demonstrate the prerequisite of a critical LYVE-1 threshold density and show that HA binding may be elicited in lymphatic endothelium by surface clustering with divalent LYVE-1 mAbs. In addition, we show that cross-linking of biotinylated HA in streptavidin multimers or supramolecular complexes with the inflammation-induced protein TSG-6 enables binding even in the absence of LYVE-1 cross-linking. Finally, we show that endogenous HA on the surface of macrophages can engage LYVE-1, facilitating their adhesion and transit across lymphatic endothelium. These results reveal LYVE-1 as a low affinity receptor tuned to discriminate between different HA configurations through avidity and establish a new mechanistic basis for the functions ascribed to LYVE-1 in matrix HA binding and leukocyte trafficking in vivo

Higher order residual analysis for nonlinear time series with autoregressive correlation structures

The paper considers nonlinear time series whose second order autocorrelations satisfy autoregressive Yule-Walker equations. The usual linear residuals are then uncorrelated, but not independent, as would be the case for linear autoregressive processes. Two such types of nonlinear model are treated in some detail: random coefficient autoregression and multiplicative autoregression. The proposed analysis involves crosscorrelation of the usual linear residuals and their squares. This function is obtained for the two types of model considered, and allows differentiation between models with the same autocorrelation structure in the same class. For the random coefficient models it is shown that one side of the crosscorrelation function is zero, giving a useful signature of thes processes. The non-zero features of the other side of the crosscorrelations are informative of the higher order dependency structure. In applications this residual analysis requires only standard statistical calculations, and extends rather than replaces the usual second order analysis. Keywords: Nonlinear time series; Autoregressive; Linear residuals; Random coefficient autoregression; Multiplicative autoregression; Residual analysisNaval Postgraduate School, Monterey, CA.http://archive.org/details/higherorderresid30lewiN

The dynamics and statistics of bivariate chaotic maps in communications modeling

Statistical and dynamical properties of bivariate (two-dimensional) maps are less understood than their univariate counterparts. This paper gives a synthesis of extended results with exemplifications by bivariate logistic maps, the bivariate Arnold cat map and a bivariate Chebyshev map. The use of synchronization from bivariate maps in communication modeling is exemplified by an embryonic chaos shift keying system

Chaos communication synchronization: Combatting noise by distribution transformation

Research in electronic communications has developed chaos-based modelling to enable messages to be carried by chaotic broad-band spreading sequences. When such systems are used it is necessary to simultaneously know the spreading sequence at both the transmitting and receiving stations. This is possible using the idea of synchronization with bivariate maps, providing there is no noise present in the system. When noise is present in the transmission channel, recovery of the spreading sequence may be degraded or impossible. Once noise is added to the spreading sequence, the result may no longer lie within the boundary of the chaotic map. A usual and obvious method of dealing with this problem is to cap iterations lying outside the bounds at their extremes, but the procedure amplifies loss of synchronization. With a minimum of technical details and a computational focus, this paper first develops relevant dynamical and communication theory in the bivariate map context, and then presents a better way of improving synchronization by distribution transformation. The transmission sequence is transformed, using knowledge of the invariant distribution of the spreading sequence, and before noise corrupts the signal in the transmission channel. An ‘inverse’ transformation can then be applied at the receiver station so that the noise has a reduced impact on the recovery of the spreading sequence and hence its synchronization. Statistical simulations illustrating the effectiveness of the approach are presented

Chaos communication performance analysis: Taking advantage of statistical theory

This paper seeks to outline and illustrate the statistical basis of performance modelling of chaos-based communication systems. It is argued that likelihood decoding of message bits and theoretical derivation of decoder error probability leads to exact results and enhanced engineering insights. Moreover, the exact results, replacing earlier Gaussian approximations, suggest ways to optimally design such systems. The main emphasis will be on coherent chaos shift-keying communication, both in its single- and multiple- user versions

Volatile ARMA modelling of GARCH squares

This paper points out that the ARMA models followed by GARCH squares are volatile and gives explicit and general forms of their dependent and volatile innovations. The volatility function of the ARMA innovations is shown to be the square of the corresponding GARCH volatility function. The prediction of GARCH squares is facilitated by the ARMA structure and predictive intervals are considered. Further, the developments suggest families of volatile ARMA processes