Intermittently-visual tracking experiments reveal the roles of error-correction and predictive mechanisms in the human visual-motor control system

Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

Applying robust control theory to solve problems in bio-medical sciences: study of an apoptotic model

Biological models of an apoptotic process are studied using models describing a system of differential equations derived from reaction kinetics information. The mathematical model is re-formulated in a state-space robust control theory framework where parametric and dynamic uncertainty can be modelled to account for variations naturally occurring in biological processes. We propose to handle the nonlinearities using neural networks.

Towards cost-sensitive adaptation: when is it worth updating your predictive model?

Our digital universe is rapidly expanding,more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possible and as frequently as possible. In this study we consider potential model update as an investment decision, which, as in the financial markets, should be taken only if a certain return on investment is expected. We introduce and motivate a new research problem for data streams ? cost-sensitive adaptation. We propose a reference framework for analyzing adaptation strategies in terms of costs and benefits. Our framework allows to characterize and decompose the costs of model updates, and to asses and interpret the gains in performance due to model adaptation for a given learning algorithm on a given prediction task. Our proof-of-concept experiment demonstrates how the framework can aid in analyzing and managing adaptation decisions in the chemical industry.

Decadal predictability of the Atlantic meridional overturning circulation and climate in the IPSL-CM5A-LR model

This study explores the decadal potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) as represented in the IPSL-CM5A-LR model, along with the predictability of associated oceanic and atmospheric fields. Using a 1000-year control run, we analyze the prognostic potential predictability (PPP) of the AMOC through ensembles of simulations with perturbed initial conditions. Based on a measure of the ensemble spread, the modelled AMOC has an average predictive skill of 8 years, with some degree of dependence on the AMOC initial state. Diagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the PPP. Both approaches clearly bring out the same regions exhibiting the highest predictive skill. Generally, surface temperature has the highest skill up to 2 decades in the far North Atlantic ocean. There are also weak signals over a few oceanic areas in the tropics and subtropics. Predictability over land is restricted to the coastal areas bordering oceanic predictable regions. Potential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the Nordic Seas. Regions of weak signals show some dependence on AMOC initial state. All the identified regions are closely linked to decadal AMOC fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. Evidence for dependence on AMOC initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates.

Use of a predictive model for food insecurity estimates in Brazil

In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

Exercise improves cardiovascular control in a model of dislipidemia and menopause

The present study investigated the effects of exercise training on arterial pressure, baroreflex sensitivity, cardiovascular autonomic control and metabolic parameters on female LDL-receptor knockout ovariectomized mice. Mice were divided into two groups: sedentary and trained. Trained group was submitted to an exercise training protocol. Blood cholesterol was measured. Arterial pressure (AP) signals were directly recorded in conscious mice. Baroreflex sensitivity was evaluated by tachycardic and bradycardic responses to AP changes. Cardiovascular autonomic modulation was measured in frequency (FFT) and time domains. Maximal exercise capacity was increased in trained as compared to sedentary group. Blood cholesterol was diminished in trained mice (191 +/- 8 mg/dL) when compared to sedentary mice (250 +/- 9 mg/dL, p<0.05). Mean AP and HR were reduced in trained group (101 +/- 3 mmHg and 535 +/- 14 bpm, p<0.05) when compared with sedentary group (125 +/- 3 mmHg and 600 +/- 12 bpm). Exercise training induced improvement in bradycardic reflex response in trained animals (-4.24 +/- 0.62 bpm/mmHg) in relation to sedentary animals (-1.49 +/- 0.15 bpm/mmHg, p<0.01); tachycardic reflex responses were similar between studied groups. Exercise training increased the variance (34 +/- 8 vs. 6.6 +/- 1.5 ms(2) in sedentary, p<0.005) and the high-frequency band (HF) of the pulse interval (IP) (53 +/- 7% vs. 26 +/- 6% in sedentary, p<0.01). It is tempting to speculate that results of this experimental study might represent a rationale for this non-pharmacological intervention in the management of cardiovascular risk factors in dyslipidemic post-menopause women. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Bifurcation analysis of a model for biological control

In this paper we study the Lyapunov stability and Hopf bifurcation in a biological system which models the biological control of parasites of orange plantations. (c) 2007 Elsevier Ltd. All rights reserved.

An economic model of gun control

Guns stolen from law-abiding households provide the principal source of guns for criminals. The lethality of crime instruments increases with the availability of guns, so the gun market is subject to externalities that generate excessive ownership and inadequate spending on protective measures to deter gun theft. One motive for gun ownership is self defense, and the gun market is subject to coordination failure: the more guns purchased lawfully, the more will be stolen by criminals, so the greater the incentive for lawful . consumers to purchase guns for self defense. As a result, there may be multiple equilibria in the gun market and more than one equilibrium crime rate. We show that a simple refundable deposit for guns will internalize the externalities in the gun market and may cause large downward jumps in gun ownership, the lethality of crime instruments, and the social costs of crime.

Double sampling (x)over-bar control chart for a first-order autoregressive moving average process model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predictive formulation of the Nambu-Jona-Lasinio model

A novel strategy to handle divergences typical of perturbative calculations is implemented for the Nambu-Jona-Lasinio model and its phenomenological consequences investigated. The central idea of the method is to avoid the critical step involved in the regularization process, namely, the explicit evaluation of divergent integrals. This goal is achieved by assuming a regularization distribution in an implicit way and making use, in intermediary steps, only of very general properties of such regularization. The finite parts are separated from the divergent ones and integrated free from effects of the regularization. The divergent parts are organized in terms of standard objects, which are independent of the ( arbitrary) momenta running in internal lines of loop graphs. Through the analysis of symmetry relations, a set of properties for the divergent objects are identified, which we denominate consistency relations, reducing the number of divergent objects to only a few. The calculational strategy eliminates unphysical dependencies of the arbitrary choices for the routing of internal momenta, leading to ambiguity-free, and symmetry-preserving physical amplitudes. We show that the imposition of scale properties for the basic divergent objects leads to a critical condition for the constituent quark mass such that the remaining arbitrariness is removed. The model becomes predictive in the sense that its phenomenological consequences do not depend on possible choices made in intermediary steps. Numerical results are obtained for physical quantities at the one-loop level for the pion and sigma masses and pion-quark and sigma-quark coupling constants.

On non-linear dynamics and control designs applied to the ideal and non-ideal variants of the Fitzhugh-Nagumo (FN) mathematical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On non-linear dynamics and an optimal control synthesis of the action potential of membranes (ideal and non-ideal cases) of the Hodgkin-Huxley (HH) mathematical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Establishing the risk of neonatal mortality using a fuzzy predictive model

O objetivo do artigo foi avaliar o uso da lógica fuzzy para estimar possibilidade de óbito neonatal. Desenvolveu-se um modelo computacional com base na teoria dos conjuntos fuzzy, tendo como variáveis peso ao nascer, idade gestacional, escore de Apgar e relato de natimorto. Empregou-se o método de inferência de Mamdani, e a variável de saída foi o risco de morte neonatal. Criaram-se 24 regras de acordo com as variáveis de entrada, e a validação do modelo utilizou um banco de dados real de uma cidade brasileira. A acurácia foi estimada pela curva ROC; os riscos foram comparados pelo teste t de Student. O programa MATLAB 6.5 foi usado para construir o modelo. Os riscos médios foram menores para os que sobreviveram (p < 0,001). A acurácia do modelo foi 0,90. A maior acurácia foi com possibilidade de risco igual ou menor que 25% (sensibilidade = 0,70, especificidade = 0,98, valor preditivo negativo = 0,99 e valor preditivo positivo = 0,22). O modelo mostrou acurácia e valor preditivo negativo bons, podendo ser utilizado em hospitais gerais.

Assessment of aquatic plants in the reservoirs of AES-Tiete and development of an integrated control model for the most important species

The general objective of this work was to develop a monitoring and management model for aquatic plants that could be used in reservoir cascades in Brazil, using the reservoirs of AES-Tiete as a study case. The investigations were carried out at the reservoirs of Barra-Bonita, Bariri, Ibitinga, Promissao, and Nova-Avanhandava, located in the Tiete River Basin; Agua Vermelha, located in the Grande River Basin; Caconde, Limoeiro, and Euclides da Cunha, which are part of the Pardo River Basin; and the Mogi-Guacu reservoir, which belongs to the Mogi-Guacu River basin. The main products of this work were: development of techniques using satellite-generated images for monitoring and planning aquatic plant control; planning and construction of a boat to move floating plant masses and an airboat equipped with a DGPS navigation and application flow control system. Results allowed to conclude that the occurrence of all types of aquatic plants is directly associated with sedimentation process and, consequently, with nutrient and light availability. Reservoirs placed at the beginning of cascades are more subject to sedimentation and occurrence of marginal, floating and emerged plants, and are the priority when it comes to controlling these plants, since they provide a supply of weeds for the other reservoirs. Reservoirs placed downstream show smaller amounts of water-suspended solids, with greater transmission of light and occurrence of submerged plants.