Piptaderol From Piptadenia africana

A new glyceryl derivative (Glyceryl-1-hexacosanoate) and a flavone derivative (methyletherapigenin) were isolated from the stem bark extract of Piptadenia africana, a western Cameroonian plant species. Common terpenes like sitosterol, β-amyrin and eicosane were also isolated. These compounds were identified using physical and spectroscopic methods including mp, IR, 1H and 13C-NMR, DEPT, COSY, HMQC, HMBC, EI MS, HREI MS as well as some chemical transformations. The antibacterial activity of the extract, the fractions and the pure compounds is also discussed. Keywords: Piptadenia africana, Leguminoseae, Glyceryl-1-hexacosanoate, Methyletherapigenin, Chemotaxonomy, Antibacterial activity.African Journal of Traditional and Complementary Medicine Vol. 4 (3) 2007: pp. 294-29

Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

7 pages, 4 figures Acknowledgement We are grateful to M. Riedl and G. Ansmann for fruitful discussions and critical comments on earlier versions of the manuscript. This work was supported by the Volkswagen Foundation (Grant Nos. 88461, 88462, 88463, 85390, 85391 and 85392).Peer reviewedPreprin

Incapacités liées à la douleur au bas du dos chez les travailleuses / travailleurs au Québec

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal

Recurrences of strange attractors

The transitions from or to strange nonchaotic attractors are investigated by recurrence plot-based methods. The techniques used here take into account the recurrence times and the fact that trajectories on strange nonchaotic attractors (SNAs) synchronize. The performance of these techniques is shown for the Heagy-Hammel transition to SNAs and for the fractalization transition to SNAs for which other usual nonlinear analysis tools are not successful

Recurrence-Based Synchronization Analysis of Weakly Coupled Bursting Neurons under External ELF Fields

We investigate the response characteristics of a two-dimensional neuron model exposed to an externally applied extremely low frequency (ELF) sinusoidal electric field and the synchronization of neurons weakly coupled with gap junction. We find, by numerical simulations, that neurons can exhibit different spiking patterns, which are well observed in the structure of the recurrence plot (RP). We further study the synchronization between weakly coupled neurons in chaotic regimes under the influence of a weak ELF electric field. In general, detecting the phases of chaotic spiky signals is not easy by using standard methods. Recurrence analysis provides a reliable tool for defining phases even for noncoherent regimes or spiky signals. Recurrence-based synchronization analysis reveals that, even in the range of weak coupling, phase synchronization of the coupled neurons occurs and, by adding an ELF electric field, this synchronization increases depending on the amplitude of the externally applied ELF electric field. We further suggest a novel measure for RP-based phase synchronization analysis, which better takes into account the probabilities of recurrences.Peer Reviewe

Kolmogorov-Sinai entropy from recurrence times

Observing how long a dynamical system takes to return to some state is one of the most simple ways to model and quantify its dynamics from data series. This work proposes two formulas to estimate the KS entropy and a lower bound of it, a sort of Shannon's entropy per unit of time, from the recurrence times of chaotic systems. One formula provides the KS entropy and is more theoretically oriented since one has to measure also the low probable very long returns. The other provides a lower bound for the KS entropy and is more experimentally oriented since one has to measure only the high probable short returns. These formulas are a consequence of the fact that the series of returns do contain the same information of the trajectory that generated it. That suggests that recurrence times might be valuable when making models of complex systems

Complex Network Approach for Recurrence Analysis of Time Series

We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix calculated from time series with the adjacency matrix of a complex network, and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potentials of these complex network measures for detecting dynamical transitions. Finally we apply the proposed approach to a marine palaeo-climate record and identify subtle changes of the climate regime.Comment: 23 pages, 7 figure

The chemistry and biological activity of the Hyacinthaceae

Covering: 1914 to 2012The Hyacinthaceae (sensu APGII), with approximately 900 species in about 70 genera, can be divided into three main subfamilies, the Hyacinthoideae, the Urgineoideae and the Ornithogaloideae, with a small fourth subfamily the Oziroëoideae, restricted to South America. The plants included in this family have long been used in traditional medicine for a wide range of medicinal applications. This, together with some significant toxicity to livestock has led to the chemical composition of many of the species being investigated. The compounds found are, for the most part, subfamily-restricted, with homoisoflavanones and spirocyclic nortriterpenoids characterising the Hyacinthoideae, bufadienolides characterising the Urgineoideae, and cardenolides and steroidal glycosides characterising the Ornithogaloideae. The phytochemical profiles of 38 genera of the Hyacinthaceae will be discussed as well as any biological activity associated with both crude extracts and compounds isolated. The Hyacinthaceae of southern Africa were last reviewed in 2000 (T. S. Pohl, N. R. Crouch and D. A. Mulholland, Curr. Org. Chem., 2000, 4, 1287-1324; ); the current contribution considers the family at a global level