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PubMed1975

[A kinetic model of experimental leukosis. Regularities in the development of reticulosarcomatosis in mice].

The kinetics of development of a new transplantable reticulosarcomatosis was studied in CC57Br mice.. Tumour development was estimated from changes in the weight of metaplastic organs by means of kinetic curves constructed on the basis of changes of all parameters characterized by exponential and power functions. The kinetic model of reticulosarcomatosis is recommended for use in quantitative research in experimental oncology.

Animals↗
PubMed1988

Kinematic networks. A distributed model for representing and regularizing motor redundancy.

Motor control in primates relates to a system which is highly redundant from the mechanical point of view--redundancy coming from an imbalance between the set of independently controllable variables and the set of system variables. The consequence is the manifestation of a broad class of ill-posed problems, problems for which it is difficult to identify unique solutions. For example (i) the problem of determining the coordinated patterns of rotation of the arm joints for a planned trajectory of the hand; (ii) the problem of determining the distribution of muscle forces for a desired set of joint torques. Ill-posed problems, in general, require regularization methods which allow to spell acceptable, if not unique, solutions. In the case of the motor system, we propose that the basic regularization mechanism is provided by the potential fields generated by the elastic properties of muscles, according to an organizational principle that we call "Passive Motion Paradigm". The physiological basis of this hypothesis is reviewed and a "Kinematic Network" (K-net) model is proposed that expresses the kinematic transformations and the causal relations implied by elasticity. Moreover, it is shown how K-nets can be obtained from a kinematic "Body Model", in the context of a specific task. Two particularly significant results are: (i) the uniform treatment of closed as well as open kinematic chains, and (ii) the development of a new method for the automatic generation of kinematic equations with arbitrary topology. Moreover, the model is akin to the concept of "motor equivalence" in the sense that it provides families of motor equivalent trajectories parametrized by tunable motor impedances.

Biomechanical Phenomena↗
PubMed1998

Influence of skull anisotropy for the forward and inverse problem in EEG: simulation studies using FEM on realistic head models.

For the sake of realism in the description of conduction from primary neural currents to scalp potentials, we investigated the influence of skull anisotropy on the forward and inverse problems in brain functional imaging with EEG. At present, all methods available for cortical imaging assume a spherical geometry, or when using realistic head shapes do not consider the anisotropy of head tissues. However, to our knowledge, no study relates the implication of this simplifying hypothesis on the spatial resolution of EEG for source imaging. In this paper, a method using finite elements in a realistic head geometry is implemented and validated. The influence of erroneous conductivity values for the head tissues is presented, and results show that the conductivities of the brain and the skull in the radial orientation are the most critical ones. In the inverse problem, this influence has been evaluated with simulations using a distributed source model with a comparison of two regularization techniques, with the isotropic model working on data sets produced by a nonisotropic model. Regularization with minimum norm priors produces source images with spurious activity, meaning that the errors in the head model totally annihilate any localization ability. But nonlinear regularization allows the accurate recovery of simultaneous spots of activity, while the restoration of very close active regions is profoundly disabled by errors in the head model. We conclude that for robust cortical source imaging with EEG, a realistic head model taking anisotropy of tissues into account should be used.

Anisotropy↗
PubMed2002

A model based upon pseudo regular spacing of cells combined with the randomisation of the nuclei can explain the significant changes in high-frequency ultrasound signals during apoptosis.

Recent ultrasound (US) experiments on packed myeloid leukaemia cells have shown that, at frequencies from 32 to 40 MHz, significant increases of signal amplitude were observed during apoptosis. This paper is an attempt to explain these signal increases based upon a simulation of the backscattered signals from the cells nuclei. The simulation is an expansion of work in which a condensed sample of cells, with fairly regular sizes, could be considered as an imperfect crystal. Thus, destructive interference could occur and this would be observed as a large reduced value of backscattered signals compared with the values obtained from a similar, but random, scattering source. This current paper explores the possibility that simple changes in the nuclei, such as their observed condensation or the small loss of nuclei scatterers from cells, could cause a significant increase in the observed backscattered signals. This model indicates that the greater backscattered signals can be explained by further randomisation of the average positions of the scattering sources in each cell. When these "microechoes" are added together, so that the destructive interference is reduced, a large increase in the signal is predicted. The simplified model strongly suggests that much of observed large increases of the backscattered signals could be simply explained by the randomisation of the position of the condensed nuclei during apoptosis, and the destruction of the nuclei could produce further signal amplitude changes due to disruption of the cloud of backscattered waves.

Apoptosis↗
PubMed2001

The K-function for nearly regular point processes.

We propose modeling a nearly regular point pattern by a generalized Neyman-Scott process in which the offspring are Gaussian perturbations from a regular mean configuration. The mean configuration of interest is an equilateral grid, but our results can be used for any stationary regular grid. The case of uniformly distributed points is first studied as a benchmark. By considering the square of the interpoint distances, we can evaluate the first two moments of the K-function. These results can be used for parameter estimation, and simulations are used to both verify the theory and to assess the accuracy of the estimators. The methodology is applied to an investigation of regularity in plumes observed from swimming microorganisms.

Animals↗
PubMed2001

Regularization in a neural model of motion perception.

Neurons in sensory systems encode and transmit information about attributes of the environment. Much of the information transmitted by spiking neurons appears to be encoded in the rate at which they fire. This rate necessarily has a positive value. In this paper, the implication of this constraint for models of motion detection is examined. The detection of image motion is represented mathematically as a quadratic programming problem in which variables used to represent image speed are restricted to positive values. This novel representation requires that additional constraints are introduced to stabilize motion computations because quadratic programming problems require a surplus of unknowns to code for image speed. Two further constraints are introduced into the model to take into account possible cases of image degeneracy. They are based upon (i) an a priori preference for small image speeds, and (ii) the assumption that image motion parallel to contours of constant intensity for a one-dimensional signal is zero. The latter assumption is shown to account for perceived biases in speed reported for type I plaid patterns [Castet, E. & Morgan, M. (1996). Apparent speed of type-I symmetrical plaids. Vision Research 36, 223-32]. The model suggests that the visual system uses separate constraints to stabilize motion computations. One set of constraints arises from the nature of the motion detection process itself, while another two constraints take into account possible cases of degeneracy where image contrast is low or near zero and where the image function is one-dimensional and the aperture problem prevails.

Computer Simulation↗
PubMed1981

Role of non-planar peptide unit in regular polypeptide helices. New model for poly-beta-benzyl-L-Aspartate.

The effect of non-planarity of the peptide unit on helical structures stabilized by intrachain hydrogen bonds is discussed. While the present calculations generally agree with those already reported in the literature for right-handed helical structures, it is found that the most stable left-handed structure is a novel helix, called the delta-helix. Its helical parameters are close to these reported for poly-beta-benzyl-L -aspartate. Conformational energy calculations show that poly-beta-benzyl-L -aspartate with the delta-helical structure is considerably more stable than the structure it is generally believed to take up (the omega-helix) by about 15 kcal/mol-residue.

Chemical Phenomena↗
PubMed2006

Spontaneous speech events in two speech databases of human-computer and human-human dialogs in Spanish.

Previous works in English have revealed that disfluencies follow regular patterns and that incorporating them into the language model of a speech recognizer leads to lower perplexities and sometimes to a better performance. Although work on disfluency modeling has been applied outside the English community (e.g., in Japanese), as far as we know there is no specific work dealing with disfluencies in Spanish. In this paper, we follow a data driven approach in exploring the potential benefit of modeling disfluencies in a speech recognizer in Spanish. Two databases of human-computer and human-human dialogs are considered, which allow the absolute and relative frequencies of disfluencies in the two situations to be compared. The rate of disfluencies in human-human dialogs is found to be very close to that found for similar databases in English. Due to setup factors, the rate of disfluencies found in human-computer dialogs was remarkably higher than that reported for similar databases in English. In any case, from the point of view of speech recognition, the high frequencies of disfluencies and the distinct features of the acoustic events related to them support the need for explicit acoustic models. The regularities observed in the distribution of filled pauses and speech repairs reveal that including them in the language model of the speech recognizer may be also helpful. The extent to which the number of events depends on utterance length and on the speaker is also explored. Statistics are shown that follow previous studies for English, and a sizeable space is devoted to comparing our results with them. Finally, various possible cues for the automatic detection of speech repairs--a key issue from the point of view of speech understanding--are explored: silent pauses, filled pauses, lengthenings, cut off words and discourse markers. As previously observed for English, none of them was found to be reliable by itself. More information, especially at the acoustic-prosodic level, is no doubt needed to reliably detect speech repairs.

Communication↗
PubMed2005

Signal regularity and the mindlessness model of vigilance.

Robertson, Manly, Andrade, Baddeley, and Yiend (1997) have proposed that detection failures in vigilance tasks result from a 'mindless' withdrawal of attentional effort from the monitoring assignment. To explore that view, they modified the traditional vigilance task, in which observers make button-press responses to signify the detection of rarely occurring critical signals, to one in which button-press responses acknowledge frequently occurring non-signal events and response withholding signifies signal detection. This modification is designed to promote a mindless withdrawal of attentional effort from the task through routinization. The present study challenges the validity of the mindlessness model by showing that with both types of task, observers utilize subtle patterns in the temporal structure of critical signal appearances to develop expectations about the time course of those appearances that affect performance efficiency. Such expectations enhance performance on the traditional vigilance task, but degrade performance on the modified task.

Adolescent↗
PubMed1991

Cellular immunology in regular dialysis: a biological model for biocompatibility evaluation.

Cellular immunity represents an interesting biological model for biocompatibility evaluation of artificial materials owing to its sensitivity to contact with the external environment and its capability of modulating response reactions to foreign agents. Advanced methodologies such as flow cytometry and the immunoenzyme techniques in particular have given new insights into lymphocyte structure and functions, enabling analysis of the in vivo modification of these cells. By means of these sophisticated techniques we investigated lymphocyte activation and proliferation during one single haemodialysis session. Findings clearly show that increases in HLA antigen density (class I and II), DNA synthesis, and interleukin-2 receptor serum concentration (Il-2R) take place during the dialysis procedure, and reach their maximum during the first hour of extracorporeal circulation. The relationship between dialysis procedure and cellular immunity appears noticeable and is of potential value in the evaluation and quantification of the biocompatibility of different dialysis membranes.

Adult↗
PubMed2004

Stability of negative ionization fronts: Regularization by electric screening?

We recently have proposed that a reduced interfacial model for streamer propagation is able to explain spontaneous branching. Such models require regularization. In the present paper we investigate how transversal Fourier modes of a planar ionization front are regularized by the electric screening length. For a fixed value of the electric field ahead of the front we calculate the dispersion relation numerically. These results guide the derivation of analytical asymptotes for arbitrary fields: for small wave-vector k, the growth rate s(k) grows linearly with k, for large k, it saturates at some positive plateau value. We give a physical interpretation of these results.

Journal Article↗
PubMed1996

Use of lactation curves for analysis of milk production data.

Nonlinear equations were compared with categorical analysis to account for DIM effects on milk production. Five different models for lactation curves were evaluated. Derived from a multiphasic lactation curve, the selected lactation curve appeared to result in random residuals and performed more consistently than the multiphasic curve. Residuals from the fitting of lactation curves were then used for split-plot analysis (continuous model) to estimate treatment effects. Statistical performance of this model was compared with split-plot analysis based on a discrete model with regularly spaced intervals to account for DIM effects (discrete model). The fitting of lactation curves accounted for herd, lactation number, and interaction effects of herd and lactation number and accounted for 34.1 and 44.3% of variance among cows for primiparous and multiparous cows, respectively. The continuous model detected interactions of genetic and management factors with treatment of multiparous cows that were not detected by the discrete model. No statistically significant differences were detected between the two modeling approaches. The continuous model appeared to violate fewer assumptions regarding data distribution than did the discrete model, which reduced the risk of introducing bias during the estimation of treatment effects. The continuous model seemed to be more sensitive to subtle interactions of treatment and other factors.

Animals↗
PubMed2006

Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprines.

Acetylcholinesterase inhibition was modeled for a set of huprines using ensembles of Bayesian-regularized Genetic Neural Networks. In the Bayesian-regularized Genetic Neural Network approach the Bayesian regularization avoids overfitted regressions and the genetic algorithm allows exploring a wide pool of three-dimensional descriptors. The predictive capacity of our selected model was evaluated by averaging multiple validation sets generated as members of neural network ensembles. When 60 members are assembled, the neural network ensemble provides a reliable measure of training and test set R(2)-values of 0.945 and 0.850 respectively. In other respects, the ability of the nonlinear selected genetic algorithm space for differentiate the data were evidenced when total data set was well distributed in a Kohonen self-organizing map. The analysis of the self-organizing map zones allows establishing the main structural features differentiated by our vectorial space.

Acetylcholinesterase↗