A theory for cursive handwriting based on the minimization principle

 We propose a trajectory planning and control theory which provides explanations at the computation, algorithm, representation, and hardware levels for continuous movement such as connected cursive handwriting. The hardware is based on our previously proposed forward-inverse-relaxation neural network. Computationally, the optimization principle is the minimum torque-change criterion. At the representation level, hard constraints satisfied by a trajectory are represented as a set of via-points extracted from handwritten characters. Accordingly, we propose a via-point estimation algorithm that estimates via-points by repeating trajectory formation of a character and via-point extraction from the character. It is shown experimentally that for movements with a single via-point target, the via-point estimation algorithm can assign a point near the actual via-point target. Good quantitative agreement is found between human movement data and the trajectories generated by the proposed model. Received: 23 June 1994 / Accepted in revised form: 3 February 1995     

A Guide to Interpreting Soil Ingestion Studies. 2. Qualitative and Quantitative Evidence of Soil Ingestion

Abstract

Four major studies have attempted to qualitatively and quantitatively assess the extent of soil ingestion in children using the soil tracer methodology. The validity of the estimates of soil ingestion of each study was reevaluated in light of the inherent strengths and limitations of study design and/or execution as well as via a novel methodology to estimate the soil recovery variance of each tracer which then lead to the estimation of soil ingestion detection limits of each tracer for studies performing mass-balance analyses. Based on these analyses it is concluded that the Binder et al. (1986) and Van Wijnen et al. (1990) studies provide no convincing evidence to support qualitative and quantitative estimates of soil ingestion due to inherent limitations of their respective study designs. The Davis et al. (1990) and Calabrese et al. (1989) studies displayed convincing qualitative evidence of soil ingestion. However, the results indicate that the median soil ingestion estimates of Davis et al. were less reliable than those of Calabrese et al. The range of detection limits vary according to the tracer and the assumption of acceptable precision in recovery estimation. The minimum detection level of soil ingestion in children in the Calabrese et al. study with a variance in recovery of 100% ± 20% was 16 mg day^?1 based on Zr.

These findings are of particular regulatory significance since they provide: (1) a method of assessing the level of detection inherent in soil ingestion studies, (2) a reevaluation of the major soil ingestion studies in light of new methodology, and (3) guidance for future studies so that detection capacity can now be included in the presentation of study findings.     

Distributed parameter identification for a label-structured cell population dynamics model using CFSE histogram time-series data

In this work we address the problem of the robust identification of unknown parameters of a cell population dynamics model from experimental data on the kinetics of cells labelled with a fluorescence marker defining the division age of the cell. The model is formulated by a first order hyperbolic PDE for the distribution of cells with respect to the structure variable x (or z) being the intensity level (or the log₁₀-transformed intensity level) of the marker. The parameters of the model are the rate functions of cell division, death, label decay and the label dilution factor. We develop a computational approach to the identification of the model parameters with a particular focus on the cell birth rate α(z) as a function of the marker intensity, assuming the other model parameters are scalars to be estimated. To solve the inverse problem numerically, we parameterize α(z) and apply a maximum likelihood approach. The parametrization is based on cubic Hermite splines defined on a coarse mesh with either equally spaced a priori fixed nodes or nodes to be determined in the parameter estimation procedure. Ill-posedness of the inverse problem is indicated by multiple minima. To treat the ill-posed problem, we apply Tikhonov regularization with the regularization parameter determined by the discrepancy principle. We show that the solution of the regularized parameter estimation problem is consistent with the data set with an accuracy within the noise level in the measurements.      

The inverse dynamics problem of neuromuscular control

The myoskeletal inverse dynamics problem and the myocybernetic control inverse problem were investigated with respect to their ill-posedness. The first problem consists of finding from observed experimental motion and reaction force data the resultant muscle moments that generated the observed motion, while the second aims at finding the corresponding neural controls. It is shown that both problems belong to the class of incorrectly posed (ill-posed) problems that, by definition, do not possess unique solutions. To illustrate this point, results of a forward dynamics simulation of a comprehensive neuromusculoskeletal model of the human body are presented. These results demonstrate that fairly chaotic neural control perturbations have very little influence on the resulting motion trajectory, at least in the present example. While a regularization procedure may be applied to solve successfully the myoskeletal inverse dynamics problem, the myocybernetic control inverse problem is unsolvable. The latter fact has the important implication that, based on the somatosensory inputs it receives, the pars intermedia in the cerebellum is not able to control individual motor unit stimulation rates and recruitment patterns but only whole muscles by means of a single compound signal. The latter signal is identified as the “common drive.” Presumably at the spinal level, special neural circuits are used to decompose the common drive signal into motor unit recruitment patterns and stimulation rates that are specific for a given mode of contraction and probably obey certain optimality principles. Received: 26 February 1999 / Accepted in revised form: 11 June 1999     

Formation and control of optimal trajectory in human multijoint arm movement

In this paper, we study trajectory planning and control in voluntary, human arm movements. When a hand is moved to a target, the central nervous system must select one specific trajectory among an infinite number of possible trajectories that lead to the target position. First, we discuss what criterion is adopted for trajectory determination. Several researchers measured the hand trajectories of skilled movements and found common invariant features. For example, when moving the hand between a pair of targets, subjects tended to generate roughly straight hand paths with bell-shaped speed profiles. On the basis of these observations and dynamic optimization theory, we propose a mathematical model which accounts for formation of hand trajectories. This model is formulated by defining an objective function, a measure of performance for any possible movement: square of the rate of change of torque integrated over the entire movement. That is, the objective function CT is defined as follows: (formula; see text) We overcome this difficult by developing an iterative scheme, with which the optimal trajectory and the associated motor command are simultaneously computed. To evaluate our model, human hand trajectories were experimentally measured under various behavioral situations. These results supported the idea that the human hand trajectory is planned and controlled in accordance with the minimum torque-change criterion.     

(Brady)Rhizobium-plant communications involved in infection and nodulation

Conclusion The interactions between(Brady)Rhizobium and legume plants involves many interesting problems. In the last ten years, there were remarkable experiments which have detected excreted flavonoid compounds at pmol levels from plant roots, which induce(Brady)Rhizobium nod gene expression (Long 1989, Nap and Bisseling 1990, Dénariéet al. 1992, Schlamanet al. 1992). The responses of rhizobial genes to the various kinds of chemical compound are different (Maxwellet al. 1989, Zaatet al. 1989, Davis and Johnston 1990, Hartwiget al. 1990, Hungriaet al. 1992). The resolution of pSym genes controlling those mechanisms makes way for the long-term goal of introducing nitrogen fixation ability into nonlegume plants. Recently, some experiments have shown thatRhizobium and other nitrogen fixing bacteria form nodule-like strutures on rice, barley or wheat (Al-Mallah 1989, Jinget al. 1990, Rolfe and Bender 1991). Some O₂ protection mechanism instead of leghemoglobin must be needed for nitrogen fixation byRhizobium or other N₂-fixing bacteria which have invaded in the nonlegume root tissue. The isolation of the plant mutants or preparation of transgenic plants capable of hyper-nodule formation having efficient nitrogen fixation ability may be major goals. For the attainment of these goals, transformation of a foreign genome (nif-ornod gene cassette) into the plant cell might be a good way to proceed (Barkeret al. 1990). It is also necessary to clarify the relationships between the level of relative endogenous plant hormones and the exchange of the differentiation of the root tissue to the nodule tissue. This phenomenon of redifferentiation of plant tissue by the results from(Brady)Rhizobium and legume communications will be an important approach likely to lead to solve the molecular basis of plant having “TOTIPOTENCY”.     

Conformational studies of human islet amyloid peptide using molecular dynamics and simulated annealing methods

Molecular dynamics simulations and simulated annealing in vacuum, model aqueous solution, and simulated membrane were used to analyze the conformational preferences of a segment spanning 20–29 residues of human islet amyloid polypeptide, [referred to as IAPP^H(20–29)]. Molecular dynamics simulations were conducted at 300 K on IAPP^H(20–29). The minimum energy conformers obtained in model aqueous solution and vacuum exhibited similar structures. Even in the absence of any constraints on peptide bonds, trans conformation was preferred consistently by all the peptide bonds. Analysis of the minimum energy conformers indicated that IAPP^H(20–29) showed a strong preference for turn structures in all the environments. These turn structures were stabilized by the formation of hydrogen bonds between the backbone amide and carbonyl groups. A good agreement was found between the results obtained from the molecular dynamics simulation and solid-state nmr experimental studies. © 1998 John Wiley & Sons, Inc. Biopoly 45: 9–20, 1998     

Evolutionary Stable Strategies and Trade-Offs in Generalized Beverton and Holt Growth Models

A generalized Beverton–Holt model is considered in which a parameterγcharacterizes the onset of density dependence. An evolutionary stable strategy analysis of this parameter, reported in Getz (1996), is developed further here, using invasion exponents and the strategy dynamics of Vincentet al.(1993). The parameterγis also allowed to be density dependent, and it is shown that the most successful strategies of this type are those for whichγis large for low densities and close to its minimum for high densities. A biological interpretation is given in the context of mobile females depositing their relatively sessile young on patches of resource, namely, females should overdisperse their young on resources when adult densities are high and underdisperse them when these densities are low. Finally the per capita growth rate parameter is also allowed to depend onγ. It is shown that this dependence provides a mechanism by which periodic or chaotic attractor dynamics could evolve towards equilibrium attractor dynamics.     

Dynamic optimization of the sit-to-stand movement

The purpose of this study was to clarify criteria that can predict trajectories during the sit-to-stand movement. In particular, the minimum jerk and minimum torque-change models were examined. Three patterns of sit-to-stand movement from a chair, i.e., upright, natural, and leaning forward, were measured in five young participants using a 3-D motion analysis device (200 Hz). The trajectory of the center of mass and its smoothness were examined, and the optimal trajectories predicted by both models were evaluated. Trajectories of the center of mass predicted by the minimum torque-change model, rather than the minimum jerk model, resembled the measured movements in all rising movement patterns. The upright pattern required greater extension torque of the knee and ankle joints at the instant of seat-off. The leaning-forward pattern required greater extension hip torque and higher movement cost than the natural and upright patterns. These results indicate that the natural sit-to-stand movement might be a result of dynamic optimization.     

End-point constraints in aiming movements: effects of approach angle and speed

 The present study focuses on two trajectory-formation models of point-to-point aiming movements, viz., the minimum-jerk and the minimum torque-change model. To date, few studies on minimum-jerk and minimum torque-change trajectories have incorporated self- or externally imposed end-point constraints, such as the direction and velocity with which a target area is approached. To investigate which model accounts best for the effects on movement trajectories of such – in many circumstances – realistic end-point constraints, we adjusted both the minimum-jerk and the minimum torque-change model so that they could generate trajectories of which the final part has a specific direction and speed. The adjusted models yield realistic trajectories with a high curvature near movement completion. Comparison of simulated and measured movement trajectories show that pointing movements that are constrained with respect to final movement direction and speed can be described in terms of minimization of joint-torque changes. Received: 7 July 1999 / Accepted in revised form: 8 January 2001     

A well-posed, embedded constraint representation of joint moments from kinesiological measurements

Joint moment estimation using the traditional inverse dynamics analysis presents two challenging problems, which limit its reliability. First, the quality of the computed moments depends directly on unreliable estimates of the segment accelerations obtained numerically by differentiating noisy marker measurements. Second, the representation of joint moments from combined video and force plate measurements belongs to a class of ill-posed problems, which does not possess a unique solution. This paper presents a well-posed representation derived from an embedded constraint equation. The proposed method, referred to as the embedded constraint representation (ECR), provides unique moment estimates, which satisfy all measurement constraints and boundary conditions and require fewer acceleration components than the traditional inverse dynamics method. Specifically, for an n-segment open chain planar system, the ECR requires n-3 acceleration components as compared to 3(n-1) components required by the traditional (from ground up) inverse dynamics analysis. Based on a simulated experiment using a simple three-segment model, the precision of the ECR is evaluated at different noise levels and compared to the traditional inverse dynamics technique. At the lowest noise levels, the inverse dynamics method is up to 50 percent more accurate while at the highest noise levels the ECR method is up to 100 percent more accurate. The ECR results over the entire range of noise levels reveals an average improvement on the order 20 percent in estimating the moments distal to the force plate and no significant improvement in estimating moments proximal to the force plate. The new method is particularly advantageous in a combined video, force plate, and accelerometery sensing strategy.     

Dominance orders in animal societies: The self-organization hypothesis revisited

In previous papers (Theraulaz et al., 1995; Bonabeau et al., 1996) we suggested, following Hogeweg and Hesper (1983, 1985), that the formation of dominance orders in animal societies could result from a self-organizing process involving a double reinforcement mechanism: winners reinforce their probability of winning and losers reinforce their probability of losing. This assumption, and subsequent models relying on it, were based on empirical data on primitively eusocial wasps (Polistes dominulus). By reanalysing some of the experimental data that was previously thought to be irrelevant, we show that it is impossible to distinguish this assumption from a competing assumption based on preexisting differences among individuals. We propose experiments to help discriminate between the two assumptions and their corresponding models—the self-organization model and the correlational model. We urge other researchers to be cautious when interpreting their dominance data with the ’self-organization mindset’; in particular, ‘winner and loser effects’, which are often considered to give support to the self-organization assumption, are equally consistent with the correlational assumption.     

Coordination dynamics of trajectory formation

 The present study aims to understand the neurally based coordination dynamics (multistability, loss of stability, transitions, etc.) of trajectory formation in a simple task. Six subjects produced two spatial patterns of coordination in the xy plane by alternating the abduction-adduction and flexion-extension motions of their right index finger. Each pattern was characterized by a unique temporal ratio between the x and y directions of motion: (1) a figure zero, a 1:1 temporal pattern; and (2) a figure eight, a 2:1 temporal pattern. The patterns were produced rhythmically and movement frequency was scaled across ten frequency plateaus, with ten cycles of motion per step. As movement frequency increased, switching from a figure eight to a figure zero was observed at critical cycling frequencies. The switch from pattern (2) to pattern (1) was identified in the spatial trajectory and power spectra of x(t) and y(t). En route to the transition, enhancement of fluctuations was observed in the Fourier amplitudes of x(t) and y(t), specifically at f ₀ (the metronome frequency) and 2f ₀ (the first harmonic of f ₀). Interestingly, there was no difference in the spatial variability of the two patterns. Overall, the data demonstrate that spatial patterns of coordination can be characterized in terms of the temporal relationship between the spatial components of the trajectory itself. We discuss the experimental findings in relation to other end-point planning and multijoint control strategies, as well as the much more general problem of temporal synchronization in many interlimb and intralimb coordination tasks. Received: 24 February 1995/Accepted in revised form: 8 August 1995     

A full body musculoskeletal model based on flexible multibody simulation approach utilised in bone strain analysis during human locomotion

Load-induced strains applied to bone can stimulate its development and adaptation. In order to quantify the incident strains within the skeleton, in vivo implementation of strain gauges on the surfaces of bone is typically used. However, in vivo strain measurements require invasive methodology that is challenging and limited to certain regions of superficial bones only such as the anterior surface of the tibia. Based on our previous study [Al Nazer et al. (2008) J Biomech. 41:1036–1043], an alternative numerical approach to analyse in vivo strains based on the flexible multibody simulation approach was proposed. The purpose of this study was to extend the idea of using the flexible multibody approach in the analysis of bone strains during physical activity through integrating the magnetic resonance imaging (MRI) technique within the framework. In order to investigate the reliability and validity of the proposed approach, a three-dimensional full body musculoskeletal model with a flexible tibia was used as a demonstration example. The model was used in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model was developed using the actual geometry of human tibia, which was obtained from three-dimensional reconstruction of MRI. Motion capture data obtained from walking at constant velocity were used to drive the model during the inverse dynamics simulation in order to teach the muscles to reproduce the motion in the forward dynamics simulation. Based on the agreement between the literature-based in vivo strain measurements and the simulated strain results, it can be concluded that the flexible multibody approach enables reasonable predictions of bone strain in response to dynamic loading. The information obtained from the present approach can be useful in clinical applications including devising exercises to prevent bone fragility or to accelerate fracture healing.     

Concordance indices with left-truncated and right-censored data

In the context of time-to-event analysis, a primary objective is to model the risk of experiencing a particular event in relation to a set of observed predictors. The Concordance Index (C-Index) is a statistic frequently used in practice to assess how well such models discriminate between various risk levels in a population. However, the properties of conventional C-Index estimators when applied to left-truncated time-to-event data have not been well studied, despite the fact that left-truncation is commonly encountered in observational studies. We show that the limiting values of the conventional C-Index estimators depend on the underlying distribution of truncation times, which is similar to the situation with right-censoring as discussed in Uno et al. (2011) [On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Statistics in Medicine 30(10), 1105–1117]. We develop a new C-Index estimator based on inverse probability weighting (IPW) that corrects for this limitation, and we generalize this estimator to settings with left-truncated and right-censored data. The proposed IPW estimators are highly robust to the underlying truncation distribution and often outperform the conventional methods in terms of bias, mean squared error, and coverage probability. We apply these estimators to evaluate a predictive survival model for mortality among patients with end-stage renal disease.     

An optimal control problem for ovine brucellosis with culling

A mathematical model is used to study the dynamics of ovine brucellosis when transmitted directly from infected individual, through contact with a contaminated environment or vertically through mother to child. The model developed by Aïnseba et al. [A model for ovine brucellosis incorporating direct and indirect transmission, J. Biol. Dyn. 4 (2010), pp. 2–11. Available at http://www.math.u-bordeaux1.fr/～pmagal100p/papers/BBM-JBD09.pdf. Accessed 3 July 2012] was modified to include culling and then used to determine important parameters in the spread of human brucellosis using sensitivity analysis. An optimal control analysis was performed on the model to determine the best way to control such as a disease in the population. Three time-dependent controls to prevent exposure, cull the infected and reduce environmental transmission were used to set up to minimize infection at a minimum cost.     

161 Discovery of potent KdsA inhibitors of Leptospira interrogans through homology modeling,docking, and molecular dynamics simulations

Leptospira interrogans is the foremost cause of human leptospirosis. Discovery of novel lead molecules for common drug targets of more than 250 Leptospira serovars is of significant research interest. Lipopolysaccharide (LPS) layer prevent entry of hydrophobic agents into the cell and protect structural integrity of the bacterium. KDO-8-phosphate synthase (KdsA) catalyzes the first step of KDO biosynthesis that leads to formation of inner core of LPS. KdsA was identified as a potential drug target against Leptospira interrogans through subtractive genomic approach, metabolic pathway analysis, and comparative analysis (Amineni et al., 2010). The present study rationalizes a systematic implementation of homology modeling, docking, and molecular dynamics simulations to discover potent KdsA inhibitors (Pradhan et al., 2013; Umamaheswari et al., 2010). A reliable tertiary structure of KdsA in complex with substrate PEP was constructed based on co-crystal structure of Aquifex aeolicus KdsA synthase with PEP using Modeller9v10. Geometry-based analog search for PEP was performed from LigandInfo database to generate an in house library of 352 ligands. The ligand data-set was docked into KdsA active site through three-stage docking technique (HTVS, SP, and XP) using Glidev5.7. Thirteen lead molecules were found to have better binding affinity compared to PEP (XP Gscore?=??7.38?kcal/mol; Figure 1). The best lead molecule (KdsA- lead1 docking complex) showed XP Gscore of ?10.26?kcal/mol and the binding interactions (Figure 2) were correlated favorably with PEP–KdsA interactions (Figure 1). Molecular dynamics simulations of KdsA– lead1 docking complex for 10?ns had revealed that the complex (Figure 3) remained stable in closer to physiological environmental condition. The predicted pharmacological properties of lead1 were well within the range of a drug molecule with good ADME profile, hence, would be intriguing towards development of potent inhibitor molecule against KdsA of Leptospira.     

A recurrent neural model for proto-object based contour integration and figure-ground segregation

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects (“proto-objects”) based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594–6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492–1499 2007; Chen et al. Neuron, 82(3), 682–694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.