Were Spanish migrants attracted by industrial agglomerations?: an analysis for the interwar years in the light of the new economic geography

In this paper we examine whether access to markets had a significant influence onmigration choices of Spanish internal migrants in the inter-war years. We perform astructural contrast of a New Economic Geography model that focus on the forwardlinkage that links workers location choice with the geography of industrial production,one of the centripetal forces that drive agglomeration in the NEG models. The resultshighlight the presence of this forward linkage in the Spanish economy of the inter-warperiod. That is, we prove the existence of a direct relation between workers¿ localizationdecisions and the market potential of the host regions. In addition, the direct estimationof the values associated with key parameters in the NEG model allows us to simulatethe migratory flows derived from different scenarios of the relative size of regions andthe distances between them. We show that in Spain the power of attraction of theagglomerations grew as they increased in size, but the high elasticity estimated for themigration costs reduced the intensity of the migratory flows. This could help to explainthe apparently low intensity of internal migrations in Spain until its upsurge during the1920s. This also explains the geography of migrations in Spain during this period,which hardly affected the regions furthest from the large industrial agglomerations (i.e.,regions such as Andalusia, Estremadura and Castile-La Mancha) but had an intenseeffect on the provinces nearest to the principal centres of industrial development.

Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models

Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

Calibration and application of the MN2D dynamics model to the avalanches of Las Leñas (Argentina)

During the winters of 1999 and 2000 large avalanches occurred in the ski resort of Las Leñas (Los Andes, Mendoza, Argentina). On 8 September 1999 an avalanche of new, dry snow ran over a path with a 1000 m vertical drop. On 30 June and on 1 July 2000 five avalanches of similar vertical drop, which start with new snow, entrained very wet snow during their descent, and evolved into dense snow avalanches. To use the MN2D dynamics model correctly, calibration of model parameters is necessary. Also, no previous works with the use of dynamics models exist in South America. The events used to calibrate the model occurred during the winters of 1999 and 2000 and are a good sample of the kind of avalanches which can occur in this area of the Andes range. By considering the slope morphology and topography, the snow and meteorological conditions and the results of the model simulations, it was estimated that these avalanches were not extreme events with a return period greater than one hundred years. This implies that, in natural conditions, bigger, extreme avalanches could happen. In this work, the MN2D dynamics model is calibrated with two different avalanches of the same magnitude: dry and wet. The importance of the topographic data in the simulation is evaluated. It is concluded that MN2D dynamics model can be used to simulate dry extreme avalanches in Argentinean Andes but not to simulate extreme wet avalanches, which are much more sensitive to the topography.

Production of nanometric particles in radio frequency glow discharges in mixtures of silane and methane

The formation of silicon particles in rf glow discharges has attracted attention due to their effect as a contaminant during film deposition or etching. However, silicon and silicon alloy powders produced by plasma¿enhanced chemical vapor deposition (PECVD) are promising new materials for sintering ceramics, for making nanoscale filters, or for supporting catalytic surfaces. Common characteristics of these powders are their high purity and the easy control of their stoichiometry through the composition of the precursor gas mixture. Plasma parameters also influence their structure. Nanometric powders of silicon¿carbon alloys exhibiting microstructural properties such as large hydrogen content and high surface/volume ratio have been produced in a PECVD reactor using mixtures of silane and methane at low pressure (-1 Torr) and low frequency square¿wave modulated rf power (13.56 MHz). The a¿Si1¿xCx:H powders were obtained from different precursor gas mixtures, from R=0.05 to R=9, where R=[SiH4]/([SiH4]+[CH4]). The structure of the a¿Si1¿xCx:H powder was analyzed by several techniques. The particles appeared agglomerated, with a wide size distribution between 5 and 100 nm. The silane/methane gas mixture determined the vibrational features of these powders in the infrared. Silicon-hydrogen groups were present for every gas composition, whereas carbon¿hydrogen and silicon¿carbon bonds appeared in methane¿rich mixtures (R-0.6). The thermal desorption of hydrogen revealed two main evolutions at about 375 and 660¿°C that were ascribed to hydrogen bonded to silicon and carbon, respectively. The estimated hydrogen atom concentration in the sample was about 50%.

Exchange rate predictability

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known thatexchange rate fluctuations are very difficult to predict using economic models, andthat a random walk forecasts exchange rates better than any economic model (theMeese and Rogoff puzzle). However, the recent literature has identified a series of fundamentals/methodologies that claim to have resolved the puzzle. This article providesa critical review of the recent literature on exchange rate forecasting and illustratesthe new methodologies and fundamentals that have been recently proposed in an up-to-date, thorough empirical analysis. Overall, our analysis of the literature and thedata suggests that the answer to the question: "Are exchange rates predictable?" is,"It depends" -on the choice of predictor, forecast horizon, sample period, model, andforecast evaluation method. Predictability is most apparent when one or more of thefollowing hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is therandom walk without drift.

Statistical modeling of bowing control applied to violin sound synthesis

Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

Post-Nonlinear Mixtures and Beyond

Although sources in general nonlinear mixturm arc not separable iising only statistical independence, a special and realistic case of nonlinear mixtnres, the post nonlinear (PNL) mixture is separable choosing a suited separating system. Then, a natural approach is based on the estimation of tho separating Bystem parameters by minimizing an indcpendence criterion, like estimated mwce mutual information. This class of methods requires higher (than 2) order statistics, and cannot separate Gaarsian sources. However, use of [weak) prior, like source temporal correlation or nonstationarity, leads to other source separation Jgw rithms, which are able to separate Gaussian sourra, and can even, for a few of them, works with second-order statistics. Recently, modeling time correlated s011rces by Markov models, we propose vcry efficient algorithms hmed on minimization of the conditional mutual information. Currently, using the prior of temporally correlated sources, we investigate the fesihility of inverting PNL mixtures with non-bijectiw non-liacarities, like quadratic functions. In this paper, we review the main ICA and BSS results for riunlinear mixtures, present PNL models and algorithms, and finish with advanced resutts using temporally correlated snu~sm

Constraints on effective field theory parameters for the Lambda N -> NN transition

The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

Constraints on effective field theory parameters for the Lambda N -> NN transition

The relation between the low-energy constants appearing in the effective field theory description of the Lambda N -> NN transition potential and the parameters of the one-meson-exchange model previously developed is obtained. We extract the relative importance of the different exchange mechanisms included in the meson picture by means of a comparison to the corresponding operational structures appearing in the effective approach. The ability of this procedure to obtain the weak baryon-baryon-meson couplings for a possible scalar exchange is also discussed.

High pressure induced changes in beef muscle proteome: correlation with quality parameters

The relationship between pressure induced changes on individual proteins and selected quality parameters in bovine longissimus thoracis et lumborum (LTL) muscle was studied. Pressures ranging from 200 to 600 MPa at 20 °C were used. High pressure processing (HPP) at pressures above 200 MPa induced strong modifications of protein solubility, meat colour and water holding capacity (WHC). The protein profiles of non-treated and pressure treated meat were observed using two dimensional electrophoresis. Proteins showing significant differences in abundance among treatments were identified by mass spectrometry. Pressure levels above 200 MPa strongly modified bovine LTL proteome with main effects being insolubilisation of sarcoplasmic proteins and solubilisation of myofibrillar proteins. Sarcoplasmic proteins were more susceptible to HPP effects than myofibrillar. Individual protein changes were significantly correlated with protein solubility, L*, b* and WHC, providing further insights into the mechanistic processes underlying HPP influence on quality and providing the basis for the future development of protein markers to assess the quality of processed meats.

An epidemiological study of dental agenesis in a primary health area in Spain: estimated prevalence and associated factors

Objectives: To evaluate the prevalence of dental agenesis and its possible association with other developmental dental anomalies and systemic entities. Setting and Sample Population: Descriptive transversal study, for which 1518 clinical records, of patients visited by the Odontological Service of the Primary Health Centre of Cassà de la Selva (Girona-Spain) between December 2002 and February 2006 were reviewed. The data were recorded in relation to the oral and dental anomalies and the associated systemic entities, between the ones referred as concomitant in literature. Results: Values of 9.48% (7.25% excluding the third molars) for dental agenesis and 0.39% for oligodontia were obtained. The presence of dental agenesis concomitant with some other forms of oral and dental anomalies was observed. Attention must be drawn to the fact that a greater number of concomitant systemic entities were observed in those patients that presented a severe phenotypical pattern of dental agenesis. Conclusions: The results of the present study do not differ from the ones reported in studies of similar characteristics among Occidental and Spanish populations. The relationship observed between certain systemic entities and developmental dental anomalies suggest a possible common genetic etiology

On the connectivity of the escaping set for complex exponential Misiurewicz parameters

Let $ E_{\lambda}(z)=\lambda {\rm exp}(z), \lambda\in \mathbb{C}$, be the complex exponential family. For all functions in the family there is a unique asymptotic value at 0 (and no critical values). For a fixed $ \lambda$, the set of points in $ \mathbb{C}$ with orbit tending to infinity is called the escaping set. We prove that the escaping set of $ E_{\lambda}$ with $ \lambda$ Misiurewicz (that is, a parameter for which the orbit of the singular value is strictly preperiodic) is a connected set.

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

The effect of scale in daily precipitation hazard assessment

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm) and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute