Loss of Ergodicity in the Transition from Annealed to Quenched Disorder in a Finite Kinetic Ising Model

We consider a kinetic Ising model which represents a generic agent-based model for various types of socio-economic systems. We study the case of a finite (and not necessarily large) number of agents N as well as the asymptotic case when the number of agents tends to infinity. The main ingredient are individual decision thresholds which are either fixed over time (corresponding to quenched disorder in the Ising model, leading to nonlinear deterministic dynamics which are generically non-ergodic) or which may change randomly over time (corresponding to annealed disorder, leading to ergodic dynamics). We address the question how increasing the strength of annealed disorder relative to quenched disorder drives the system from non-ergodic behavior to ergodicity. Mathematically rigorous analysis provides an explicit and detailed picture for arbitrary realizations of the quenched initial thresholds, revealing an intriguing ""jumpy"" transition from non-ergodicity with many absorbing sets to ergodicity. For large N we find a critical strength of annealed randomness, above which the system becomes asymptotically ergodic. Our theoretical results suggests how to drive a system from an undesired socio-economic equilibrium (e. g. high level of corruption) to a desirable one (low level of corruption).

Macromolecular assembly of polycystin-2 intracytosolic C-terminal domain

Mutations in PKD2 are responsible for approximately 15% of the autosomal dominant polycystic kidney disease cases. This gene encodes polycystin-2, a calcium-permeable cation channel whose C-terminal intracytosolic tail (PC2t) plays an important role in its interaction with a number of different proteins. In the present study, we have comprehensively evaluated the macromolecular assembly of PC2t homooligomer using a series of biophysical and biochemical analyses. Our studies, based on a new delimitation of PC2t, have revealed that it is capable of assembling as a homotetramer independently of any other portion of the molecule. Our data support this tetrameric arrangement in the presence and absence of calcium. Molecular dynamics simulations performed with a modified all-atoms structure-based model supported the PC2t tetrameric assembly, as well as how different populations are disposed in solution. The simulations demonstrated, indeed, that the best-scored structures are the ones compatible with a fourfold oligomeric state. These findings clarify the structural properties of PC2t domain and strongly support a homotetramer assembly of PC2.

Systemic chemotherapy-induced microsatellite instability in the mononuclear cell fraction of women with breast cancer can be reproduced in vitro and abrogated by amifostine

Objectives Microsatellite instability (MSI) induction by alkylating agent-based chemotherapy (ACHT) may underlie both tumor resistance to chemotherapy and secondary leukaemias in cancer patients. We investigated if ACHT could induce MSI in tumor-derived plasma-circulating DNA (pfDNA) and in normal peripheral blood mononuclear (PBMN) cells. We also evaluated if amifostine could interfere with this process in an in-vitro model. Methods MSI was determined in pfDNA, PBMN cells and urine cell-free DNA (ufDNA) of 33 breast cancer patients before and after ACHT. MCF-7 cells and PBMN from normal donors were exposed in vitro to melphalan, with or without amifostine. Results We observed at least one MSI event in PBMN cells, pfDNA or ufDNA of 87, 80 and 80% of patients, respectively. In vitro, melphalan induced MSI in both MCF-7 and normal PBMN cells. In PBMN cells, ACHT-induced MSI occurred together with a significant decrease in the expression of the DNA mismatch repair gene hMSH2. Amifostine decreased hMSH2 expression and also prevented MSI induction only in normal PBMN cells. Conclusions ACHT induced MSI in PBMN cells and in tumour-derived pfDNA. Because of its protective effect against ACHT induction of MSI in normal PBMN cells in vitro, amifostine may be a potential agent for preventing secondary leukaemias in patients exposed to ACHT.

Aripiprazole, an atypical antipsychotic prevents the motor hyperactivity induced by psychotomimetics, and psyphostimulants in mice

Aripiprazole is an atypical antipsychotic that acts as a partial agonist at the dopamine D-2 receptor. It has been mainly investigated in dopamine-based models of schizophrenia, while its effects on glutamate-based paradigms have remained to be further characterized. Due to its unique mechanism of action, aripiprazole has also been considered as a replacement medication for psychostimulant abuse. Thus, in the present study we tested the hypothesis that aripiprazole would prevent the motor hyperactivity induced by psychostimulant and psychotomimetic drugs that act either by dopaminergic or glutamatergic mechanisms. Male Swiss mice received injections of aripiprazole (0.1-1 mg/kg) followed by drugs that enhance the dopamine-mediated neurotransmission, amphetamine (3 mg/kg) or cocaine (5 mg/kg), or by glutamate NMDA-receptor antagonists, ketamine (60 mg/kg) or MK-801 (0.4 mg/kg). Independent groups also received aripiprazole (0.1-1 mg/kg) or haloperidol (0.5 mg/kg) and were tested for catalepsy. All doses of aripiprazole were effective in preventing the motor stimulant effects of amphetamine and cocaine. Moreover, the higher dose also prevented the effects of ketamine and MK-801. The present study reports the effects of aripiprazole in dopaminergic and glutamatergic models predictive of antipsychotic activity, suggesting that both may be useful for screening novel partial agonists with antipsychotic activity. It also shows that aripiprazole may prevent the acute effects of psychostimulant drugs without significant motor impairment. C) 2007 Elsevier B.V. All rights reserved.

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

The martensitic transformation in ceramics - its role in transformation toughening

This paper reviews the current knowledge and understanding of martensitic transformations in ceramics - the tetragonal to monoclinic transformation in zirconia in particular. This martensitic transformation is the key to transformation toughening in zirconia ceramics. A very considerable body of experimental data on the characteristics of this transformation is now available. In addition, theoretical predictions can be made using the phenomenological theory of martensitic transformations. As the paper will illustrate, the phenomenological theory is capable of explaining all the reported microstructural and crystallographic features of the transformation in zirconia and in some other ceramic systems. Hence the theory, supported by experiment, can be used with considerable confidence to provide the quantitative data that is essential for developing a credible, comprehensive understanding of the transformation toughening process. A critical feature in transformation toughening is the shape strain that accompanies the transformation. This shape strain, or nucleation strain, determines whether or not the stress-induced martensitic transformation can occur at the tip of a potentially dangerous crack. If transformation does take place, then it is the net transformation strain left behind in the transformed region that provides toughening by hindering crack growth. The fracture mechanics based models for transformation toughening, therefore, depend on having a full understanding of the characteristics of the martensitic transformation and, in particular, on being able to specify both these strains. A review of the development of the models for transformation toughening shows that their refinement and improvement over the last couple of decades has been largely a result of the inclusion of more of the characteristics of the stress-induced martensitic transformation. The paper advances an improved model for the stress-induced martensitic transformation and the strains resulting from the transformation. This model, which separates the nucleation strain from the subsequent net transformation strain, is shown to be superior to any of the constitutive models currently available. (C) 2002 Elsevier Science Ltd. All rights reserved.

Modelagem da dispersão de odores em ambientes urbanos

O presente trabalho investigou o problema da modelagem da dispersão de compostos odorantes em presença de obstáculos (cúbicos e com forma complexa) sob condição de estabilidade atmosférica neutra. Foi empregada modelagem numérica baseada nas equações de transporte (CFD1) bem como em modelos algébricos baseados na pluma Gausseana (AERMOD2, CALPUFF3 e FPM4). Para a validação dos resultados dos modelos e a avaliação do seu desempenho foram empregados dados de experimentos em túnel de vento e em campo. A fim de incluir os efeitos da turbulência atmosférica na dispersão, dois diferentes modelos de sub-malha associados à Simulação das Grandes Escalas (LES5) foram investigados (Smagorinsky dinâmico e WALE6) e, para a inclusão dos efeitos de obstáculos na dispersão nos modelos Gausseanos, foi empregado o modelo PRIME7. O uso do PRIME também foi proposto para o FPM como uma inovação. De forma geral, os resultados indicam que o uso de CFD/LES é uma ferramenta útil para a investigação da dispersão e o impacto de compostos odorantes em presença de obstáculos e também para desenvolvimento dos modelos Gausseanos. Os resultados também indicam que o modelo FPM proposto, com a inclusão dos efeitos do obstáculo baseado no PRIME também é uma ferramenta muito útil em modelagem da dispersão de odores devido à sua simplicidade e fácil configuração quando comparado a modelos mais complexos como CFD e mesmo os modelos regulatórios AERMOD e CALPUFF. A grande vantagem do FPM é a possibilidade de estimar-se o fator de intermitência e a relação pico-média (P/M), parâmetros úteis para a avaliação do impacto de odores. Os resultados obtidos no presente trabalho indicam que a determinação dos parâmetros de dispersão para os segmentos de pluma, bem como os parâmetros de tempo longo nas proximidades da fonte e do obstáculo no modelo FPM pode ser melhorada e simulações CFD podem ser usadas como uma ferramenta de desenvolvimento para este propósito. Palavras chave: controle de odor, dispersão, fluidodinâmica computacional, modelagem matemática, modelagem gaussiana de pluma flutuante, simulação de grandes vórtices (LES).

(Virtual) Agents for running electricity markets

This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.

On the solubility of three disperse anthraquinone dyes in supercritical carbon dioxide: new experimental data and correlation

Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.

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.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Virtual power producers simulation - negotiating renewable distributed generation in competitive electricity markets

Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.