A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

Applications of Fourier transform infrared spectroscopy

This article summarizes the basic principles of Fourier Transform Infrared Spectroscopy, with examples of methodologies and applications to different field sciences.

On the success of generalized food deception in orchids : the role of sympatric rewarding species and pollinators

Résumé : La production de nectar assure aux plantes entomophiles un important succès reproducteur. Malgré cela, de nombreuses espèces d'orchidées ne produisent pas de nectar. La majorité de ces orchidées dites trompeuses exploitent simplement l'instinct des pollinisateurs généralistes, qui les pousse à chercher du nectar dans les fleurs. Afin d'optimiser la récolte de nectar, les pollinisateurs apprennent à différencier les fleurs trompeuses des nectarifères, et à concentrer leurs visites sur ces dernières, au détriment des plantes trompeuses. Chez les orchidées non autogames, la reproduction est assurée uniquement par les pollinisateurs. L'apprentissage des pollinisateurs a donc un impact négatif sur la reproduction des orchidées trompeuses. Cependant, les caractéristiques d'une espèce trompeuse et des espèces nectarifères au sein d'une communauté végétale peuvent affecter l'apprentissage et le taux de visite des pollinisateurs aux plantes trompeuses. J'ai réalisé des expériences en milieu naturel et en milieu contrôlé, pour déterminer si les caractéristiques florales, spatiales et temporelles des communautés affectent le taux de visite et le succès reproducteur de plantes trompeuses. Une agrégation spatiale élevée des plantes trompeuses et des plantes nectarifères diminue le succès reproducteur des plantes trompeuses. De plus, les pollinisateurs visitent plus souvent l'espèce trompeuse Iorsque ses fleurs sont de couleur similaire à celles de l'espèce nectarifère. Cet effet bénéfique de la similarité pour la couleur des fleurs s'accentue si les deux espèces sont mélangées et proches spatialement, ou si l'espèce trompeuse fleurit après l'espèce nectarifère. Enfin, le comportement des pollinisateurs n'est pas tout de suite affecté lorsque les caractéristiques de la communauté changent. Les caractéristiques des communautés végétales affectent donc la reproduction des espèces trompeuses. Bien que L'absence de coûts associés à la production de nectar, l'exportation efficace de pollen et la production de graines de qualité dont bénéficient les orchidées trompeuses favorisent Ieur maintien, les caractéristiques de la communauté peuvent aussi y contribuer. Mon étude fournit donc une explication alternative et complémentaire au maintien des orchidées trompeuses. Je conclus par une discussion des implications possibles de ces résultats sur le maintien et l'évolution des orchidées trompeuses, en tenant compte de la dynamique des caractéristiques des communautés végétales naturelles. Abstract : Despite the importance of producing food to ensure a high reproductive success, many orchid species lack such rewards. The majority of deceptive orchids simply exploit the instinctive food-foraging behaviour of generalist pollinators. This strategy is termed generalized food deception. To optimize their foraging efficiency, pollinators can learn to discriminate deceptive from rewarding flowers and to focus their visits to the rewarding plants, to the disadvantage of the deceptive plants. Because the reproductive success of non-autogamous orchids entirely relies on pollinator visitation rate, pollinator learning decreases the reproductive success of deceptive orchids. However, the characteristics of deceptive and rewarding plants within a community may affect pollinator learning and visitation rate to a deceptive orchid. Therefore, the biological characteristics of natural plant communities may be crucial to the maintenance of generalized food deceptive orchids. My study focused on the floral, spatial and temporal characteristics of plant communities. I used both in and ex sitar experiments to investigate whether these characteristics influence pollinator visitation rates and the reproductive success of deceptive orchids. A high spatial aggregation of both deceptive and rewarding species decreased the reproductive success of the deceptive species. Also, being of similar flower colour to rewarding sympatric species increased pollinator visitation rates to a deceptive species. The beneficial effect of flower colour similarity was even more pronounced when both species were spatially closely mingled or when the deceptive species flowered after the rewarding species. Finally, pollinator behaviour was unaffected in the short term by a change in the characteristics of plant communities, indicating that pollinators need time to learn under new conditions. Thus, the characteristics of plant communities may crucially affect the reproductive success of deceptive orchids. Although the absence of costs associated with nectar production, the efficient pollen export and the high seed quality of deceptive orchids may favour their maintenance, the characteristics of plant communities may also contribute to it. Therefore, my study provides an alternative yet complementary explanation to the maintenance of generalized food deceptive orchids in natural populations. I discuss the possible implications for the maintenance and the evolution of generalized food deceptive orchids with regards to the floral and temporal dynamics of natural plant communities.

A Generalized Model Study of Scour Around Bridge Piers and Abutments, HR-24, 1953

Four classes of variables are apparent in the problem of scour around bridge piers and abutments--geometry of piers and abutments, stream-flow characteristics, sediment characteristics, and geometry of site. The laboratory investigation, from its inception, has been divided into four phases based on these classes. In each phase the variables in three of the classes are held constant and those in the pertinent class are varied. To date, the first three phases have been studied. Typical scour bole patterns related to the geometry of the pier or abutment have been found. For equilibrium conditions of scour with uniform sand, the velocity of flow and the sand size do not appear to have any measurable effects on the depth of scour. This result is especially encouraging in the search for correlation between model and prototype since it would indicate that, primarily, only the depth of flow might be involved in the scale effect. The technique of model testing has been simplified, therefore, because rate of sediment transportation does not need to be scaled. Prior to the establishment of equilibrium conditions, however, depths of scour in excess of those for equilibrium conditions have been found. A concept of active scour as an imbalance between sediment transport capacity and rate of sediment supply has been used to explain the laboratory observations.

On the bicanonical map of irregular varieties

From the point of view of uniform bounds for the birationality of pluricanonical maps, irregular varieties of general type and maximal Albanese dimension behave similarly to curves. In fact Chen-Hacon showed that, at least when their holomorphic Euler characteristic is positive, the tricanonical map of such varieties is always birational. In this paper we study the bicanonical map. We consider the natural subclass of varieties of maximal Albanese dimension formed by primitive varieties of Albanese general type. We prove that the only such varieties with non-birational bicanonical map are the natural higher-dimensional generalization to this context of curves of genus $2$: varieties birationally equivalent to the theta-divisor of an indecomposable principally polarized abelian variety. The proof is based on the (generalized) Fourier-Mukai transform.

Wave-height hazard analysis in Eastern Coast of Spain : Bayesian approach using generalized Pareto distribution

Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Generalized synchronization in directionally coupled systems with identical individual dynamics

A simple chaotic flow is presented, which when driven by an identical copy of itself, for certain initial conditions, is able to display generalized synchronization instead of identical synchronization. Being that the drive and the response are observed in exactly the same coordinate system, generalized synchronization is demonstrated by means of the auxiliary system approach and by the conditional Lyapunov spectrum. This is interpreted in terms of changes in the structure of the system stationary points, caused by the coupling, which modify its global behavior.

SAR Interferometric phase noise reduction using wavelet transform

The problem of synthetic aperture radar interferometric phase noise reduction is addressed. A new technique based on discrete wavelet transforms is presented. This technique guarantees high resolution phase estimation without using phase image segmentation. Areas containing only noise are hardly processed. Tests with synthetic and real interferograms are reported.

On the inverse windowed Fourier transform

The inversion problem concerning the windowed Fourier transform is considered. It is shown that, out of the infinite solutions that the problem admits, the windowed Fourier transform is the "optimal" solution according to a maximum-entropy selection criterion.

The continuous wavelet transform as a maximum entropy solution of the corresponding inverse problem

The continuous wavelet transform is obtained as a maximumentropy solution of the corresponding inverse problem. It is well knownthat although a signal can be reconstructed from its wavelet transform,the expansion is not unique due to the redundancy of continuous wavelets.Hence, the inverse problem has no unique solution. If we want to recognizeone solution as "optimal", then an appropriate decision criterion hasto be adopted. We show here that the continuous wavelet transform is an"optimal" solution in a maximum entropy sense.

On wideband deconvolution using wavelet transform

A discussion on the expression proposed in [1]–[3]for deconvolving the wideband density function is presented. Weprove here that such an expression reduces to be proportionalto the wideband correlation receiver output, or continuous wavelettransform of the received signal with respect to the transmittedone. Moreover, we show that the same result has been implicitlyassumed in [1], when the deconvolution equation is derived. Westress the fact that the analyzed approach is just the orthogonalprojection of the density function onto the image of the wavelettransform with respect to the transmitted signal. Consequently,the approach can be considered a good representation of thedensity function only under the prior knowledge that the densityfunction belongs to such a subspace. The choice of the transmittedsignal is thus crucial to this approach.