Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression

In this paper, reanalysis fields from the ECMWF have been statistically downscaled to predict from large-scale atmospheric fields, surface moisture flux and daily precipitation at two observatories (Zaragoza and Tortosa, Ebro Valley, Spain) during the 1961-2001 period. Three types of downscaling models have been built: (i) analogues, (ii) analogues followed by random forests and (iii) analogues followed by multiple linear regression. The inputs consist of data (predictor fields) taken from the ERA-40 reanalysis. The predicted fields are precipitation and surface moisture flux as measured at the two observatories. With the aim to reduce the dimensionality of the problem, the ERA-40 fields have been decomposed using empirical orthogonal functions. Available daily data has been divided into two parts: a training period used to find a group of about 300 analogues to build the downscaling model (1961-1996) and a test period (19972001), where models' performance has been assessed using independent data. In the case of surface moisture flux, the models based on analogues followed by random forests do not clearly outperform those built on analogues plus multiple linear regression, while simple averages calculated from the nearest analogues found in the training period, yielded only slightly worse results. In the case of precipitation, the three types of model performed equally. These results suggest that most of the models' downscaling capabilities can be attributed to the analogues-calculation stage.

Factores determinantes de la integración de la variable medio ambiente en los planteamientos de la economía de la empresa y el marketing

[ES] Actualmente las empresas se enfrentan a un nuevo reto: la integración de los aspectos medioambientales en la gestión y toma de decisiones empresariales. Varios han sido los factores desencadenantes, que han inducido a la Economía de la Empresa y al Marketing a introducir la variable medio ambiente en sus planteamientos, en aras a conformar una base teórica sistematizada que permita abordar con éxito las necesidades medioambientales de la clientela y de la sociedad. En este trabajo se analizan los factores que han contribuido a incrementar la importancia de la variable medio ambiente en la empresa, así como las causas que, en su día, motivaron su exclusión.

El compromiso como variable mediadora para la predicción de las futuras intenciones de consumo en los servicios. Una aproximación empírica a los consumidores de artes escénicas en España

[ES] El presente trabajo de investigación trata de arrojar luz sobre las relaciones entre las variables Satisfacción, Compromiso, Confianza y Futuras Intenciones de compra. Con este fin, se propone un Modelo de Gestión de las Relaciones con Clientes de Servicios en el que se observa que la variable más importante en la consecución de resultados positivos en lo que respecta a intenciones de asistencia futura de los consumidores es el Compromiso.

Ancient DNA from Hunter-Gatherer and Farmer Groups from Northern Spain Supports a Random Dispersion Model for the Neolithic Expansion into Europe

10 p.

Factores explicativos de la intención de emprender en la mujer. Aspectos diferenciales en la población universitaria según la variable género

El objetivo del presente trabajo de investigación es arrojar luz sobre los factores que explican la menor intencionalidad en la población femenina para involucrarse en procesos de creación de empresas. Para ello, se ha desarrollado un modelo de ecuaciones estructurales que identifica un conjunto de variables que permiten explicar la intención de emprender en la población potencialmente emprendedora. La validación del modelo se ha realizado mediante una encuesta realizada a 1222 estudiantes de 12 titulaciones diferentes de la Universidad de Málaga. La aplicación del modelo a las poblaciones masculina y femenina ha permitido apreciar diferencias significativas en los patrones de comportamiento en función del género, identificando un proceso más complejo y necesitado de apoyo externo en la población femenina con respecto a la masculina.

Robust speed control for a variable speed wind turbine

Modern wind turbines are designed in order to work in variable speed opera-tions. To perform this task, these turbines are provided with adjustable speed generators, like the double feed induction generator (DFIG). One of the main advantages of adjustable speed generators is improving the system efficiency compared with _xed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However, this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. The proposed design also uses the vector oriented control theory in order to simplify the DFIG dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and pa-rameter uncertainties using the Lyapunov stability theory. Finally, the simulated results show on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, which usually appear in real systems.

Adaptive variable structure control law for a variable speed wind turbine

Presentado en el 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11

Sliding mode control law for a variable speedwind turbine

Modern wind turbines are designed in order to work in variable speed operations. To perform this task, wind turbines are provided with adjustable speed generators, like the double feed induction generator. One of the main advantage of adjustable speed generators is improving the system efficiency compared to fixed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. An integral sliding surface is used, because the integral term avoids the use of the acceleration signal, which reduces the high frequency components in the sliding variable. The proposed design also uses the vector oriented control theory in order to simplify the generator dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and parameter uncertainties by using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, that usually appear in real systems.

Sliding mode control strategy for variable speed wind turbines

EFTA 2009

Variable structure control for maximum wind power extraction

EuroPES 2009

Nonperturbative dynamical decoupling with random control

Parametric fluctuations or stochastic signals are introduced into the rectangular pulse sequence to investigate the feasibility of random dynamical decoupling. In a large parameter region, we find that the out-of-order control pulses work as well as the regular pulses for dynamical decoupling and dissipation suppression. Calculations and analysis are enabled by and based on a nonperturbative dynamical decoupling approach allowed by an exact quantum-state-diffusion equation. When the average frequency and duration of the pulse sequence take proper values, the random control sequence is robust, fault-tolerant, and insensitive to pulse strength deviations and interpulse temporal separation in the quasi-periodic sequence. This relaxes the operational requirements placed on quantum control devices to a great deal.

Novel Evidence hat Attributing Affectively Salient Signal to Random Noise Is Associated with Psychosis

We wished to replicate evidence that an experimental paradigm of speech illusions is associated with psychotic experiences. Fifty-four patients with a first episode of psychosis (FEP) and 150 healthy subjects were examined in an experimental paradigm assessing the presence of speech illusion in neutral white noise. Socio-demographic, cognitive function and family history data were collected. The Positive and Negative Syndrome Scale (PANSS) was administered in the patient group and the Structured Interview for Schizotypy-Revised (SIS-R), and the Community Assessment of Psychic Experiences (CAPE) in the control group. Patients had a much higher rate of speech illusions (33.3% versus 8.7%, ORadjusted: 5.1, 95% CI: 2.3-11.5), which was only partly explained by differences in IQ (ORadjusted: 3.4, 95% CI: 1.4-8.3). Differences were particularly marked for signals in random noise that were perceived as affectively salient (ORadjusted: 9.7, 95% CI: 1.8-53.9). Speech illusion tended to be associated with positive symptoms in patients (ORadjusted: 3.3, 95% CI: 0.9-11.6), particularly affectively salient illusions (ORadjusted: 8.3, 95% CI: 0.7-100.3). In controls, speech illusions were not associated with positive schizotypy (ORadjusted: 1.1, 95% CI: 0.3-3.4) or self-reported psychotic experiences (ORadjusted: 1.4, 95% CI: 0.4-4.6). Experimental paradigms indexing the tendency to detect affectively salient signals in noise may be used to identify liability to psychosis.

Efficacy of a cognitive and behavioural psychotherapy applied by primary care psychologists in patients with mixed anxiety-depressive disorder: a research protocol

Background: In contrast with the recommendations of clinical practice guidelines, the most common treatment for anxiety and depressive disorders in primary care is pharmacological. The aim of this study is to assess the efficacy of a cognitive-behavioural psychological intervention, delivered by primary care psychologists in patients with mixed anxiety-depressive disorder compared to usual care. Methods/Design: This is an open-label, multicentre, randomized, and controlled study with two parallel groups. A random sample of 246 patients will be recruited with mild-to-moderate mixed anxiety-depressive disorder, from the target population on the lists of 41 primary care doctors. Patients will be randomly assigned to the intervention group, who will receive standardised cognitive-behavioural therapy delivered by psychologists together with usual care, or to a control group, who will receive usual care alone. The cognitive-behavioural therapy intervention is composed of eight individual 60-minute face-to face sessions conducted in eight consecutive weeks. A follow-up session will be conducted over the telephone, for reinforcement or referral as appropriate, 6 months after the intervention, as required. The primary outcome variable will be the change in scores on the Short Form-36 General Health Survey. We will also measure the change in the frequency and intensity of anxiety symptoms (State-Trait Anxiety Inventory) and depression (Beck Depression Inventory) at baseline, and 3, 6 and 12 months later. Additionally, we will collect information on the use of drugs and health care services. Discussion: The aim of this study is to assess the efficacy of a primary care-based cognitive-behavioural psychological intervention in patients with mixed anxiety-depressive disorder. The international scientific evidence has demonstrated the need for psychologists in primary care. However, given the differences between health policies and health services, it is important to test the effect of these psychological interventions in our geographical setting.

Can environmental constraints determine random patterns of plant species co-occurrence?

Plant community ecologists use the null model approach to infer assembly processes from observed patterns of species co-occurrence. In about a third of published studies, the null hypothesis of random assembly cannot be rejected. When this occurs, plant ecologists interpret that the observed random pattern is not environmentally constrained - but probably generated by stochastic processes. The null model approach (using the C-score and the discrepancy index) was used to test for random assembly under two simulation algorithms. Logistic regression, distance-based redundancy analysis, and constrained ordination were used to test for environmental determinism (species segregation along environmental gradients or turnover and species aggregation). This article introduces an environmentally determined community of alpine hydrophytes that presents itself as randomly assembled. The pathway through which the random pattern arises in this community is suggested to be as follows: Two simultaneous environmental processes, one leading to species aggregation and the other leading to species segregation, concurrently generate the observed pattern, which results to be neither aggregated nor segregated - but random. A simulation study supports this suggestion. Although apparently simple, the null model approach seems to assume that a single ecological factor prevails or that if several factors decisively influence the community, then they all exert their influence in the same direction, generating either aggregation or segregation. As these assumptions are unlikely to hold in most cases and assembly processes cannot be inferred from random patterns, we would like to propose plant ecologists to investigate specifically the ecological processes responsible for observed random patterns, instead of trying to infer processes from patterns

Crank-Nicholson method for rate equations in powder random lasers

3rd International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE 2014)