Predetermined State Research Articles

Using Effective Empirical Sub-Networks to Move Equilibria of Gene Networks

Many biological processes are governed by the action of networks of genes, proteins, and other molecules. We ask how the equilibrium of such a gene network $\calN_0$ can be moved from an initial, perhaps undesirable, state ∃\calP_0$ to a pre-determined state $\calP_{aim}$ through external (pharmacological) intervention. The input for our analyses are the expression levels of genes in $\calP_0$ and $\calP_{aim}$, as well as those of sets of their genetic perturbations. We first find genes that are differentially expressed between the two groups, and partition them into clusters that are weakly coupled to each other. Since genes within cluster are strongly coupled, their expression levels change coherently between genetic perturbations. We asume that all genes within a cluster can be moved by appropriate changes in a few. We thus construct a subset $\calN_S$ that contains a small number of genes from each cluster. We next show how “effective” interactions between nodes of $\calN_S$ can be computed using expression levels of genes in $\calP_0$ and all its single knockout mutants. We argue that geometrical constraints imposed by the construction makes the solutions of $\calN_S$ close to those of $\calN_0$. This proximity of solutions allows us to compute how the equilibrium can be moved from $\calP_0$ to, or as close as possible to, $\calP_{aim}$.

Adapted polarization state contrast image

We propose a general method to maximize the polarimetric contrast between an object and its background using a predetermined illumination polarization state. After a first estimation of the polarimetric properties of the scene by classical Mueller imaging, we evaluate the incident polarized field that induces scattered polarization states by the object and background, as opposite as possible on the Poincar e sphere. With a detection method optimized for a 2-channel imaging system, Monte Carlo simulations of low flux coherent imaging are performed with various objects and backgrounds having different properties of retardance, dichroism and depolarization. With respect to classical Mueller imaging, possibly associated to the polar decomposition, our results show a noticeable increase in the Bhattacharyya distance used as our contrast parameter.

Spatio-temporal electrical stimuli shape behavior of an embodied cortical network in a goal-directed learning task

We developed an adaptive training algorithm, whereby an in vitro neocortical network learned to modulate its dynamics and achieve pre-determined activity states within tens of minutes through the application of patterned training stimuli using a multi-electrode array. A priori knowledge of functional connectivity was not necessary. Instead, effective training sequences were continuously discovered and refined based on real-time feedback of performance. The short-term neural dynamics in response to training became engraved in the network, requiring progressively fewer training stimuli to achieve successful behavior in a movement task. After 2 h of training, plasticity remained significantly greater than the baseline for 80 min (p-value <0.01). Interestingly, a given sequence of effective training stimuli did not induce significant plasticity (p-value = 0.82) or desired behavior, when replayed to the network and no longer contingent on feedback. Our results encourage an in vivo investigation of how targeted multi-site artificial stimulation of the brain, contingent on the activity of the body or even of the brain itself could treat neurological disorders by gradually shaping functional connectivity.Corrections were made to this article on 27 August 2008. Changes were made to affiliation 3, and to figure 2. The corrected electronic version is identical to the print version.

A precise curved motion planning for a differential driving mobile robot

A single curvature trajectory with a fixed rotation radius is proposed for an optimal trajectory plan for a differential driving mobile robot to capture a moving object. Generally, when the differential driving mobile robot moves along a path whose rotation radius is not constant, the tracking error of the mobile robot increases with the travel distance. Also, tracking errors increase greatly when the mobile robot follows a trajectory, with a small rotation radius. Based on these two observations, a single curvature trajectory, which has a constant and large rotation radius, is proposed as an optimal trajectory, in order to minimize the tracking error of the differential driving mobile robot. This paper first reviews the characteristics of a single curvature trajectory. Next, an algorithm to capture a moving object precisely is proposed using the single curvature trajectory. With the pre-determined initial states (i.e., position and orientation of the mobile robot and the final states), the mobile robot is made to capture a moving object. Through simulations and real experiments using a two DOF wheel-based mobile robot, the effectiveness of the proposed algorithm is verified.

An empirical re-evaluation of consumer disadvantage

Consumer disadvantage, concerned with inequality in the market place, is a topic that has attracted waves of interest for over 30 years. Despite recent, renewed interest among academics in marketing and related disciplines, it remains to be clearly conceptualized, debated or extensively empirically tested. This paper aims to address these issues, using findings from a qualitative study (focus groups) on grocery shopping which took place in a district centre in Southampton, UK. The findings demonstrate that consumer disadvantage should be thought of as a complex process, rather than as a pre-determined state based on membership of social disadvantage groups. The paper is the first to ask participants whether they perceive consumer disadvantage in relation to their own shopping experiences and reveals that disadvantaged consumers could be better off than traditionally thought. However, distortive psychological processes may be at work which mean positive accounts of shopping behaviour should not necessarily be taken at face value.

Mimicking Portfolios with Conditioning Information

AbstractMimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama (1996)) with conditional and unconditional mean-variance efficiency (Hansen and Richard (1987), Ferson and Siegel (2001)). Empirical examples illustrate the potential importance of time-varying mimicking portfolio weights and highlight challenges in their application.

The Challenge of Mastication: Preparing a Bolus Suitable for Deglutition

The main function of mastication is to transform a solid food into a bolus that can be swallowed safely. The bolus characteristics such as particles size or cohesiveness, are continuously sensed during mastication and they are important in initiating deglutition. This study examined the following question: What is the condition of the bolus just before swallowing? Ten subjects with normal dentition aged 37.5 +/- 3.7 years were asked to chew without swallowing six different foods (three nuts and three vegetables) while the number of cycles and the duration of the sequence were recorded. The particle size distribution shown by the expectorated food bolus just before swallowing was examined by image analysis. The results showed that, for a given food, the sizes of the bolus particles just before swallowing were comparable in all subjects. However, the number of cycles and duration of the sequence varied between subjects. Taken together these data strongly suggest that the granularity of the bolus before swallowing has to reach a predetermined state which is obtained by using an individual chewing strategy. This suggests that the bolus structure reflects a key factor for homeostasis and explains the large interindividual variability of the mastication physiologic parameters.

Extended invariance and its use in model predictive control

The use of time invariant linear state feedback control laws for the definition of terminal invariant regions can be conservative, thereby reducing the efficacy of predictive control in terms of size of stabilisable sets and closed-loop performance. This difficulty, which is particularly pronounced in the case of nonlinear and/or uncertain dynamics, can be remedied through the use of time-varying control laws and terminal invariant sets. In existing MPC schemes, however, these have to be computed online thereby rendering implementation impracticable for anything other than low-dimensional systems. Here, the definition of invariance is extended to apply over ν predicted control moves, thereby enabling the use of pre-determined (offline) time-varying state feedback gains. More importantly, this extension allows for the use of local uncertainty or linear difference inclusion sets, and thus affords significant improvements, e.g. in terms of the size of terminal regions.

Special issue on quantum control

Controlling the dynamics or measurement of quantum systems via the manipulation of external parameters is a most important phenomenon that lies at the heart of several fields including atomic and optical physics, molecular chemistry and quantum information. As quantum technologies have matured, a host of practical applications of quantum control have been realized in quantum optics, cavity QED, atomic spin ensembles, ion trapping, and Bose--Einstein condensation. As a result, quantum control theory is a rapidly growing research field. The aim of this special issue is to give an idea of the present status of research in quantum control, and to stimulate further activity. The papers chosen cover a great variety of ideas in this field. To aid the reader, we have divided the papers into four broad sections: quantum filtering and feedback control; open-loop control; quantum information applications; optical and related applications. Of course there are many papers that cross the boundaries between the categories we have identified, so we encourage readers to peruse the whole issue. While some may quibble with our classification scheme, we think it will be useful, especially to those who are new to the area. In each section the papers are ordered by date of submission. The first section is on quantum filtering and feedback control. Quantum filtering means determining estimates for some (or all) observables of the system from classical measurement results obtained gradually over time from the output of the quantum system. The conditioned quantum state is one way to generate such estimates. This filtering of the measurement results is useful for feedback control (also known as closed-loop control), because those estimates can be used as the basis for varying the external control parameters. This section begins with a review article (the one exception to the ordering of papers by submission date). The second section is on open-loop control in the broad sense. This is concerned with how to drive a quantum system from an initial given state to a pre-determined target state. This includes the question of controllability: whether a controller can drive a quantum system to a desired state, for which the main tools are group theory and graph theory. Quantum optimal control is concerned with finding the best control fields (according to some cost function) to achieve the desired target for a controllable system. Coherent control is a particularly powerful method for guiding the state of a quantum system (typically a molecule) towards the target by applying semiclassical potentials and exploiting quantum interference effects. Another technique is learning control (which can be considered a kind of closed-loop control) in which the experiment is run many times, and each time the output from the sample is used to modify the control fields for the next (independently prepared) sample. The third and fourth sections are devoted more to applications. The third section comprises applications of ideas and techniques from quantum control (primarily coherent control) to quantum information. These include new schemes for and novel analyses of quantum logic operations, quantum error correction, quantum communication, and quantum algorithms. Finally, the fourth section contains papers on optical or atom-optical (i.e. matter wave) implementations of quantum control ideas, and related applications such as tomography. In closing, we take the opportunity to express our gratitude to the authors of the papers and to the reviewers, for their respective efforts in preparing and ensuring the high quality of the work and its presentation.

On the Relevance of Monetary Aggregates in Monetary Policy Models

This paper develops a business cycle model with a financial intermediation sector. Financial wealth is defined as a predetermined state variable. Both, the additional sector of financial intermediaries and predetermination of financial wealth, affect the demand for real financial wealth. If real financial wealth also enters the monetary policy rule, the conditions for stability and uniqueness of the macroeconomic equilibrium path change fundamentally compared to standard New Keynesian business cycle models. Here, real financial wealth is interpreted as a real broad monetary aggregate. Furthermore, different interest rate rules and their consequences for stability and uniqueness of the macroeconomic equilibrium path are considered. Two monetary policy rules are found to be feasible - i.e. if these monetary policy rules are applied there exists a stable and unique macroeconomic equilibrium path. Simulations of the model showed that the monetary policy rule considering inflation and broad money as indicators is optimal.

Genes, neurons and codes: remarks on biological communication.

I examine critically the application of information-theoretic ideas to biological communication during embryonic development and in the functioning central nervous system (CNS). I show that intercellular communication relies mostly on simple signals whose role is to effect a selection among predetermined cellular states. Hence, a crucial role is played by cellular memory, which stabilizes such states. Memory in cells is partly located in the nuclear DNA; no less important however is (phenotypic) memory lying in the cell's organelles and compartments. Because of combinatorial effects in gene expression patterns, cell memory is an enormously powerful mechanism, which also underlies plasticity, and thus constitutes the factor unifying genetic determination, plasticity and learning. Communication in the CNS is analyzed in some detail: here, cellular memory is embodied in anatomy (i.e., cell shape) and neurochemistry. These are the major, relatively "static" factors affecting the routing of neural impulses in the adult CNS. In addition, however, faster channeling is also required: action potentials must be directed to their targets along a few of exponentially many paths, and this dynamic routing is crucial for proper operation. I suggest that collective oscillatory modes may play a role in solving this addressing problem, in the same way that the clock signal gates the operation of man-made computers.

Mimicking Portfolios with Conditioning Information

Mimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama, 1996) with conditional and unconditional mean variance efficiency (Hansen and Richard (1987), Ferson and Siegel, 2001).

An anticipative feedback solution for the infinite-horizon, linear-quadratic, dynamic, Stackelberg game

This paper derives and illustrates a new suboptimal-consistent feedback solution for an infinite-horizon, linear-quadratic, dynamic, Stackelberg game. This solution lies in the same solution space as the infinite-horizon, dynamic-programming, feedback solution but puts the leader in a preferred equilibrium position. The idea comes from Kydland (J. Econ. Theory 15 (1977)) who suggested deriving a consistent feedback solution for an infinite-horizon, linear-quadratic, dynamic, Stackelberg game by varying the coefficients in the player's linear constant-coefficient decision rules. Here feedback is understood in the sense of setting a current control vector as a function of a predetermined state vector. The proposed solution is derived for discrete- and continuous-time games and is called the anticipative feedback solution. The solution is illustrated with a numerical example of a duopoly model.

STUDIES ON INJECTEDFEELBACK AND DYNAMIC CONTROLS OF CHAOTIC SYSTEMS

A method of injected-feelback control of chaotic systems in Chai's circuits is put forward. By the method,the chaotic systems can be controlled in predetermined equilibrium states and the vibrational cyclical trajectories. With the change of control parameters,typical variation of physical state is studied to extend the applications of chau's circuits chaotic systems in Chai's circuits.

Exponentially fading memory learning in forward-looking economic models

In this paper we analyze forward-looking economic models under bounded rationality. We consider a learning mechanism characterized by exponentially fading memory with a learning step not vanishing in the limit. The dynamics of the model under bounded rationality can be parametrized with respect to the memory of the learning mechanism. We show that memory plays a stabilizing role in a local sense: it induces local convergence towards a stationary rational expectations equilibrium and in some cases it does not allow for nonperfect foresight attractors obtained through local bifurcations. We discuss this learning mechanism in pure exchange overlapping generations models. We also analyze models with predetermined state variables, in this setting the effect of memory on the learning dynamics is controversial.

Interactive ERP recording increases the amplitude of the endogenous P300 peak in schizophrenia

The P300 is a long-latency cognitive event-related potential (ERP) elicited by the presentation of relevant target stimuli. Unfortunately, the standard ERP recording technique takes no account of the background EEG during stimulus presentation. However, a recently developed technique (interactive recording) controls for variability in the EEG by applying stimuli only when the background EEG is in a predetermined state. The use of the interactive technique has led to significant changes in the P300 amplitude in control studies. Since P300 amplitude data are commonly used in schizophrenia research, and have previously been associated with cognitive deficits in schizophrenia, we studied the effects of interactive recording in a schizophrenia population. The same ERP paradigm was implemented twice for each subject, using both standard ERP and the interactive recording techniques. There was a significant increase in the amplitude of the P300 peak with interactive recording, although no significant change in latency. The results indicate that the effect of background EEG may need to be taken into account when conducting general ERP-based studies in schizophrenia. The results also indicate that the method may be used to investigate the effects of EEG variation on ERP values and, by implication, on cognitive processes. In particular, the recognition of EEG states that lead to a higher amplitude ERP value may aid in the further development of EEG investigations of schizophrenia. A similar development is indicated between cognitive research in schizophrenia and the sub-second brain-states in which cognitive function may be reflected.

The molecular basis of multiple vector insertion by gene targeting in mammalian cells.

Gene targeting using sequence insertion vectors generally results in integration of one copy of the targeting vector generating a tandem duplication of the cognate chromosomal region of homology. However, occasionally the target locus is found to contain >1 copy of the integrated vector. The mechanism by which the latter recombinants arise is not known. In the present study, we investigated the molecular basis by which multiple vectors become integrated at the chromosomal immunoglobulin mu locus in a murine hybridoma. To accomplish this, specially designed insertion vectors were constructed that included six diagnostic restriction enzyme markers in the Cmu region of homology to the target chromosomal mu locus. This enabled contributions by the vector-borne and chromosomal Cmu sequences at the recombinant locus to be ascertained. Targeted recombinants were isolated and analyzed to determine the number of vector copies integrated at the chromosomal immunoglobulin mu locus. Targeted recombinants identified as bearing >1 copy of the integrated vector resulted from a Cmu triplication formed by two vector copies in tandem. Examination of the fate of the Cmu region markers suggested that this class of recombinant was generated predominantly, if not exclusively, by two targeted vector integration events, each involving insertion of a single copy of the vector. Both vector insertion events into the chromosomal mu locus were consistent with the double-strand-break repair mechanism of homologous recombination. We interpret our results, taken together, to mean that a proportion of recipient cells is in a predetermined state that is amenable to targeted but not random vector integration.

Time-Sharing Policies for Controlled Markov Chains

We propose a class of nonstationary policies called policy time sharing (PTS), which possesses several desirable properties for problems where the criteria are of the average-cost type; an optimal policy exists within this class, the computation of optimal policies is straightforward, and the implementation of this policy is easy. While in the finite state case stationary policies are also known to share these properties, the new policies are much more flexible, in the sense that they can be applied to solve adaptive problems, and they suggest new ways to incorporate the particular structure of the problem at-hand into the derivation of optimal policies. In addition, they provide insight into the pathwise-structure of controlled Markov chains. To use PTS policies one alternates between the use of several stationary deterministic policies, switching when reaching some predetermined state. In some (countable state) cases optimal solutions of the PTS type are available and easy to compute, whereas optimal stationary policies are not available. Examples that illustrate the last point and the usefulness of the new approach are discussed, involving constrained optimization problems with countable state space or compact action space.

Free energy calculations on calcium and magnesium complexes: Protein and phospholipid model systems

AbstractFree energy calculations have been performed on a variety of calcium (Ca(II)) and magnesium (Mg(II)) complexes as model systems for protein‐metal, phospholipid‐metal, and protein‐metal‐phospholipid interactions. The major goal of this work was to advance our understanding of Ca(II) ion selectivity in the blood coagulation proteins. The limitations of present force field methods as applied to divalent metal ion‐containing systems is discussed. The effects of different water models, varying nonbond cutoff values, and counterions are evaluated. Additionally, the effects of complete charge transformation between predetermined quantum mechanical states is evaluated in which all of the charges of the metal complexes as well as the van der Waals radii of the metals are perturbed. Protein models include formate, malonate, ethylene‐diaminetetraacetate, and 1,1,4,4 ‐butanetetracarboxylic acid. Phospholipid mimics included methylphosphatidylserine, methylphosphatidylcholine, dimethyl phosphate, and trans‐cyclohexane‐1,3‐diphosphate. The present set of calculations tends to overestimate Mg(II) binding in the various test systems for which experimental results exist, an effect which may in part be due to the lack of explicit polarization/charge transfer terms for all molecules, including water, in the force field. However, these calculations support the notion that coagulation protein selectivity towards Ca(II) is likely due to a greater ease of desolvation of Ca(II) over Mg(II).

The dose dependence of glucocorticoid-inducible gene expression results from changes in the number of transcriptionally active templates.

Glucocorticoid hormones induce the transcription of genes having glucocorticoid response elements in a dose dependent manner. To determine whether this dose dependence represents a response of individual templates or of the mass of templates, we introduced a bacterial beta-galactosidase gene linked to the glucocorticoid-inducible enhancer/promoter of the mouse mammary tumor virus (MTV) into Ltk- cells and obtained stable transformants containing a single or a few templates per cell. Visual inspection and flow cytometry analysis by enzyme histochemistry assay for beta-galactosidase revealed that individual cells showed very heterogeneous beta-galactosidase activity after 48 h induction with dexamethasone. When the glucocorticoid concentration was increased, an increasing cell population producing beta-galactosidase was observed. These phenomena were probably not due to heterogeneity of template copy number or to a predetermined cellular state among individual cells, since cells forming a single small colony gave similar results. This was also supported by data showing that recloned cells retained both their responsiveness to the glucocorticoid hormone and their digestion pattern in Southern blotting analyses. These results indicate that the dose dependent increase of glucocorticoid-inducible gene expression is caused by an increase in the number of transcriptionally active templates.