An application of structural equation modeling of test dispositional optimism as mediator or moderator in quality of life in patients with chronic disease

The aim of the present study was to test a hypothetical model to examine if dispositional optimism exerts a moderating or a mediating effect between personality traits and quality of life, in Portuguese patients with chronic diseases. A sample of 540 patients was recruited from central hospitals in various districts of Portugal. All patients completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, and quality of life. Structural equation modeling (SEM) was used to analyze the moderating and mediating effects. Results suggest that dispositional optimism exerts a mediator rather than a moderator role between personality traits and quality of life, suggesting that “the expectation that good things will happen” contributes to a better general well-being and better mental functioning.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Stochastic effects in a seasonally forced epidemic model

The interplay of seasonality, the system's nonlinearities and intrinsic stochasticity, is studied for a seasonally forced susceptible-exposed-infective-recovered stochastic model. The model is explored in the parameter region that corresponds to childhood infectious diseases such as measles. The power spectrum of the stochastic fluctuations around the attractors of the deterministic system that describes the model in the thermodynamic limit is computed analytically and validated by stochastic simulations for large system sizes. Size effects are studied through additional simulations. Other effects such as switching between coexisting attractors induced by stochasticity often mentioned in the literature as playing an important role in the dynamics of childhood infectious diseases are also investigated. The main conclusion is that stochastic amplification, rather than these effects, is the key ingredient to understand the observed incidence patterns.

Modeling, control and simulation of full-power converter wind turbines equipped with permanent magnet synchronous generator

In this paper, two wind turbines equipped with a permanent magnet synchronous generator (PMSG) and respectively with a two-level or a multilevel converter are simulated in order to access the malfunction transient performance. Three different drive train mass models, respectively, one, two and three mass models, are considered in order to model the bending flexibility of the blades. Moreover, a fractional-order control strategy is studied comparatively to a classical integer-order control strategy. Computer simulations are carried out, and conclusions about the total harmonic distortion (THD) of the electric current injected into the electric grid are in favor of the fractional-order control strategy.

Power converter topologies for wind energy conversion systems: Integrated modeling, control strategy and performance simulation

This paper presents new integrated model for variable-speed wind energy conversion systems, considering a more accurate dynamic of the wind turbine, rotor, generator, power converter and filter. Pulse width modulation by space vector modulation associated with sliding mode is used for controlling the power converters. Also, power factor control is introduced at the output of the power converters. Comprehensive performance simulation studies are carried out with matrix, two-level and multilevel power converter topologies in order to adequately assert the system performance. Conclusions are duly drawn.

Análise do desempenho da tecnologia 4G LTE

O objectivo deste trabalho passa pelo desenvolvimento de uma ferramenta de simulação dinâmica de recursos rádio em LTE no sentido descendente, com recurso à Framework OMNeT++. A ferramenta desenvolvida permite realizar o planeamento das estações base, simulação e análise de resultados. São descritos os principais aspectos da tecnologia de acesso rádio, designadamente a arquitectura da rede, a codificação, definição dos recursos rádio, os ritmos de transmissão suportados ao nível de canal e o mecanismo de controlo de admissão. Foi definido o cenário de utilização de recursos rádio que inclui a definição de modelos de tráfego e de serviços orientados a pacotes e circuitos. Foi ainda considerado um cenário de referência para a verificação e validação do modelo de simulação. A simulação efectua-se ao nível de sistema, suportada por um modelo dinâmico, estocástico e orientado por eventos discretos de modo a contemplar os diferentes mecanismos característicos da tecnologia OFDMA. Os resultados obtidos permitem a análise de desempenho dos serviços, estações base e sistema ao nível do throughput médio da rede, throughput médio por eNodeB e throughput médio por móvel para além de permitir analisar o contributo de outros parâmetros designadamente, largura de banda, raio de cobertura, perfil dos serviços, esquema de modulação, entre outros. Dos resultados obtidos foi possível verificar que, considerando um cenário com estações base com raio de cobertura de 100 m obteve-se um throughput ao nível do utilizador final igual a 4.69494 Mbps, ou seja, 7 vezes superior quando comparado a estações base com raios de cobertura de 200m.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Mathematical modeling of pressurized system behaviour with entrapped air

The presence of entrapped air in pressurized hydraulic systems is considered a critical condition for the infrastructure security, due to the transient pressure enhancement related with its dynamic behaviour, similar to non-linear spring action. A mathematical model for the assessment of hydraulic transients resulting from rapid pressurizations, under referred condition is presented. Water movement was modeled through the elastic column theory considering a moving liquid boundary and the entrapped air pocket as lumped gas mass, where the acoustic effects are negligible. The method of characteristics was used to obtain the numerical solution of the liquid flow. The resulting model is applied to an experimental set-up having entrapped air in the top of a vertical pipe section and the numerical results are analyzed.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: Astudy case of the 1755 Lisbon tsunami in Algarve, Portugal (vol 182, pg 187, 2010)

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

QSAR modeling of antitubercular activity of diverse organic compounds

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.

Modeling Allee Effect from Beta(p, 2) Densities

In this work we develop and investigate generalized populational growth models, adjusted from Beta(p, 2) densities, with Allee effect. The use of a positive parameter leads the presented generalization, which yields some more flexible models with variable extinction rates. An Allee limit is incorporated so that the models under study have strong Allee effect.

Monte Carlo modeling and simulations of the High Definition (HD120) micro MLC and validation against measurements for a 6 MV beam

Purpose: The most recent Varian® micro multileaf collimator(MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRCMonte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian® Trilogy® (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. The HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of 18.7 g cm− 3 and an overall leakage of about 1.1 ± 0.03%. The discrepancies between the film measured and simulated closed and blocked fields are below 2% and 8%, respectively. Other measurements were performed for alternated leaf patterns and the agreement is satisfactory (to within 4%). The dynamic mode for this MLC was implemented and the discrepancies between film measurements and simulations are within 4%. Conclusions: The Varian® Trilogy® (2300 C/D) linear accelerator including the HD120 MLC was successfully modeled and simulated using the Monte CarloBEAMNRC code by developing an independent CM, the HDMLC CM, either in static and dynamic modes.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

Modeling for control design of a multi-reach water canal

This article addresses the problem of obtaining reduced complexity models of multi-reach water delivery canals that are suitable for robust and linear parameter varying (LPV) control design. In the first stage, by applying a method known from the literature, a finite dimensional rational transfer function of a priori defined order is obtained for each canal reach by linearizing the Saint-Venant equations. Then, by using block diagrams algebra, these different models are combined with linearized gate models in order to obtain the overall canal model. In what concerns the control design objectives, this approach has the advantages of providing a model with prescribed order and to quantify the high frequency uncertainty due to model approximation. A case study with a 3-reach canal is presented, and the resulting model is compared with experimental data. © 2014 IEEE.