Integrability of a linear center perturbed by a fifth degree homogeneous polynomial

In this work we study the integrability of two-dimensional autonomous system in the plane with linear part of center type and non-linear part given by homogeneous polynomials of fifth degree. We give a simple characterisation for the integrable cases in polar coordinates. Finally we formulate a conjecture about the independence of the two classes of parameters which appear on the system; if this conjecture is true the integrable cases found will be the only possible ones.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Variabilidad espacial del arroz como cultivo indicador de salinidad en regadíos del valle del Ebro a partir de series temporales en imágenes Landsat TM

El presente trabajo pretende la caracterización de la distribución espacial típica del cultivo de arroz en regadíos del valle del Ebro, donde la presencia del cultivo está ligada a la existencia de suelos salino-sódicos. Esta caracterización ha de permitir identificar las áreas donde es típica la presencia del cultivo año tras año y las áreas donde es frecuente su fluctuación debido tanto a condiciones variables de salinidad del suelo como a variabilidad en las condiciones de mercado. Para ello se ha recurrido al análisis de una serie temporal de mapas de cultivos (7 años) derivados de la clasificación supervisada de imágenes Landsat TM. La determinación de las áreas típicas y de fluctuación del cultivo de arroz se hace entonces a partir del análisis estadístico de clases, y mediante superposición espacial de coberturas en un entorno SIG-Raster.

Forecasting tourism demand using consumer expectations

Abstract Purpose- There is a lack of studies on tourism demand forecasting that use non-linear models. The aim of this paper is to introduce consumer expectations in time-series models in order to analyse their usefulness to forecast tourism demand. Design/methodology/approach- The paper focuses on forecasting tourism demand in Catalonia for the four main visitor markets (France, the UK, Germany and Italy) combining qualitative information with quantitative models: autoregressive (AR), autoregressive integrated moving average (ARIMA), self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. The forecasting performance of the different models is evaluated for different time horizons (one, two, three, six and 12 months). Findings- Although some differences are found between the results obtained for the different countries, when comparing the forecasting accuracy of the different techniques, ARIMA and Markov switching regime models outperform the rest of the models. In all cases, forecasts of arrivals show lower root mean square errors (RMSE) than forecasts of overnight stays. It is found that models with consumer expectations do not outperform benchmark models. These results are extensive to all time horizons analysed. Research limitations/implications- This study encourages the use of qualitative information and more advanced econometric techniques in order to improve tourism demand forecasting. Originality/value- This is the first study on tourism demand focusing specifically on Catalonia. To date, there have been no studies on tourism demand forecasting that use non-linear models such as self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. This paper fills this gap and analyses forecasting performance at a regional level. Keywords Tourism, Forecasting, Consumers, Spain, Demand management Paper type Research paper

Dynamic Criteria: a Longitudinal Analysis of Professional Basketball Players" Outcomes

This paper describes the fluctuations of temporal criteria dynamics in the context of professional sport. Specifically, we try to verify the underlying deterministic patterns in the outcomes of professional basketball players. We use a longitudinal approach based on the analysis of the outcomes of 94 basketball players over ten years, covering practically players" entire career development. Time series were analyzed with techniques derived from nonlinear dynamical systems theory. These techniques analyze the underlying patterns in outcomes without previous shape assumptions (linear or nonlinear). These techniques are capable of detecting an intermediate situation between randomness and determinism, called chaos. So they are very useful for the study of dynamic criteria in organizations. We have found most players (88.30%) have a deterministic pattern in their outcomes, and most cases are chaotic (81.92%). Players with chaotic patterns have higher outcomes than players with linear patterns. Moreover, players with power forward and center positions achieve better results than other players. The high number of chaotic patterns found suggests caution when appraising individual outcomes, when coaches try to find the appropriate combination of players to design a competitive team, and other personnel decisions. Management efforts must be made to assume this uncertainty.

Counter-propagating dual-trap optical tweezers based on linear momentum conservation

We present a dual-trap optical tweezers setup which directly measures forces using linear momentum conservation. The setup uses a counter-propagating geometry, which allows momentum measurement on each beam separately. The experimental advantages of this setup include low drift due to all-optical manipulation, and a robust calibration (independent of the features of the trapped object or buffer medium) due to the force measurement method. Although this design does not attain the high-resolution of some co-propagating setups, we show that it can be used to perform different single molecule measurements: fluctuation-based molecular stiffness characterization at different forces and hopping experiments on molecular hairpins. Remarkably, in our setup it is possible to manipulate very short tethers (such as molecular hairpins with short handles) down to the limit where beads are almost in contact. The setup is used to illustrate a novel method for measuring the stiffness of optical traps and tethers on the basis of equilibrium force fluctuations, i.e., without the need of measuring the force vs molecular extension curve. This method is of general interest for dual trap optical tweezers setups and can be extended to setups which do not directly measure forces.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

Hierarchical linear models in Psychiatry: A bibliometric study

Development of research methods requires a systematic review of their status. This study focuses on the use of Hierarchical Linear Modeling methods in psychiatric research. Evaluation includes 207 documents published until 2007, included and indexed in the ISI Web of Knowledge databases; analyses focuses on the 194 articles in the sample. Bibliometric methods are used to describe the publications patterns. Results indicate a growing interest in applying the models and an establishment of methods after 2000. Both Lotka"s and Bradford"s distributions are adjusted to the data.

Nuevas series anuales de población de América Latina desde el siglo XIX hasta el 2000

El estudio de la población en América Latina es un tema central en la historiografía de la región, sin embargo, las distintas estimaciones existentes muestran importantes discrepancias para los siglos XIX y XX. A partir del contraste de distintas bases de datos, la principal contribución del artículo consiste en ofrecer nuevas series de población homogéneas para el conjunto de países de América Latina, junto a una detallada explicación de la obtención de los datos, así como un análisis de las discrepancias que las distintas fuentes muestran. Los países que aborda este trabajo son Argentina, Brasil, Bolivia, Chile, Colombia, Costa Rica, Cuba, Guatemala, Ecuador, Haití, Honduras, México, Nicaragua, Panamá, Paraguay, Perú, República Dominicana, Uruguay y Venezuela; a lo que se agrega la suma de todos ellos para obtener la población latinoamericana. Estas nuevas series pueden resultar de gran utilidad para reinterpretar la historia económica de América Latina en el largo plazo. The analysis of population levels in Latin America plays an important role in the regional historiography. The estimated series appeared until now offers huge discrepancies, therefore, we believe essential to provide homogeneous series for the 19th and the 20th centuries. In our work we shed new light on this issue, from an exhaustive study of the existing Latin American historical sources for the region. Along with a detailed explanation of the data collection, we also provide an analysis of the discrepancies and the accuracy of sources. The study offers data from 21 countries in Latin America: Argentina, Brazil, Bolivia, Chile, Colombia, Costa Rica, Cuba, Guatemala, Ecuador, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Dominican Republic, Uruguay and Venezuela. This new evidence can be a crucial information to revisit Latin American Economic History in the long run.

Translations and Translators of English-language Literature in Catalan Literary Publications and Series between 1868 and 1910

Translations into Catalan of English and American authors during the final quarter of the nineteenth century are few and far between. Numerically, English-language literature most likely ranks fifth or sixth among all the translations of this period. We take inventory here of translations found in Catalan magazines from this time (the oldest dates from 1868) and in published series that came out at this time (if these continued until later, we trace them up to their final year). At the same time, the translators are examined, including reference, where available, as to whether the translations are direct or indirect. Finally, we consider some possible causes for the low English-language volume in Catalan translation during the period.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Exploring Non-linear Transformations for an Entropybased Voice Activity Detector

In this paper we explore the use of non-linear transformations in order to improve the performance of an entropy based voice activity detector (VAD). The idea of using a non-linear transformation comes from some previous work done in speech linear prediction (LPC) field based in source separation techniques, where the score function was added into the classical equations in order to take into account the real distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if signal is clean, estimated entropy is essentially the same; but if signal is noisy transformed frames (with score function) are able to give different entropy if the frame is voiced against unvoiced ones. Experimental results show that this fact permits to detect voice activity under high noise, where simple entropy method fails.

Patterns of primary growth increments in otoliths of Sparus aurata larvae in relation to water temperature and food consumption

Sparus aurata larvae reared under controlled water-temperature conditions during the first 24 days after hatching displayed a linear relationship between age (t) and standard length (SL): SL = 2.68 + 0.19 t (r2 = 0.91l). Increments were laid down in the sagittae with daily periodicity starting on day of hatching. Standard length (SL) and sagittae radius (OR) were correlated: SL(mm) = 2.65 + 0.012 OR(mm). The series of measurements of daily growth increment widths (DWI), food density and water temperature were analyzed by means of time series analysis. The DWI series were strongly autocorrelated, the growth on any one day was dependent upon growth on the previous day. Time series of water temperatures showed, as expected, a random pattern of variation, while food consumed daily was a function of food consumed the two previous days. The DWI series and the food density were correlated positively at lags 1 and 2. The results provided evidence of the importance of food intake upon the sagittae growth when temperature is optimal (20ºC). Sagittae growth was correlated with growth on the previous day, so this should be taken into account when fish growth is derived from sagittae growth rates.

On the computation of reducible invariant tori on a parallel computer

We present an algorithm for the computation of reducible invariant tori of discrete dynamical systems that is suitable for tori of dimensions larger than 1. It is based on a quadratically convergent scheme that approximates, at the same time, the Fourier series of the torus, its Floquet transformation, and its Floquet matrix. The Floquet matrix describes the linearization of the dynamics around the torus and, hence, its linear stability. The algorithm presents a high degree of parallelism, and the computational effort grows linearly with the number of Fourier modes needed to represent the solution. For these reasons it is a very good option to compute quasi-periodic solutions with several basic frequencies. The paper includes some examples (flows) to show the efficiency of the method in a parallel computer. In these flows we compute invariant tori of dimensions up to 5, by taking suitable sections.