Generic solutions for some integrable lattice equations

We derive the expressions for $\psi$-functions and generic solutions of lattice principal chiral equations, lattice KP hierarchy and hierarchy including lattice N-wave type equations. $\tau$-function of $n$ free fermions plays fundamental role in this context. Miwa's coordinates in our case appear as the lattice parameters.Comment: The text of the talk at NEEDS-93 conference, Gallipoli, Italy, September-93, LaTeX, 8 pages. Several typos and minor errors are correcte

Confinement effects in a guided-wave interferometer with millimeter-scale arm separation

Guided-wave atom interferometers measure interference effects using atoms held in a confining potential. In one common implementation, the confinement is primarily two-dimensional, and the atoms move along the nearly free dimension under the influence of an off-resonant standing wave laser beam. In this configuration, residual confinement along the nominally free axis can introduce a phase gradient to the atoms that limits the arm separation of the interferometer. We experimentally investigate this effect in detail, and show that it can be alleviated by having the atoms undergo a more symmetric motion in the guide. This can be achieved by either using additional laser pulses or by allowing the atoms to freely oscillate in the potential. Using these techniques, we demonstrate interferometer measurement times up to 72 ms and arm separations up to 0.42 mm with a well controlled phase, or times of 0.91 s and separations of 1.7 mm with an uncontrolled phase.Comment: 14 pages, 6 figure

Module networks revisited: computational assessment and prioritization of model predictions

The solution of high-dimensional inference and prediction problems in computational biology is almost always a compromise between mathematical theory and practical constraints such as limited computational resources. As time progresses, computational power increases but well-established inference methods often remain locked in their initial suboptimal solution. We revisit the approach of Segal et al. (2003) to infer regulatory modules and their condition-specific regulators from gene expression data. In contrast to their direct optimization-based solution we use a more representative centroid-like solution extracted from an ensemble of possible statistical models to explain the data. The ensemble method automatically selects a subset of most informative genes and builds a quantitatively better model for them. Genes which cluster together in the majority of models produce functionally more coherent modules. Regulators which are consistently assigned to a module are more often supported by literature, but a single model always contains many regulator assignments not supported by the ensemble. Reliably detecting condition-specific or combinatorial regulation is particularly hard in a single optimum but can be achieved using ensemble averaging.Comment: 8 pages REVTeX, 6 figure

Commuting Flows and Conservation Laws for Noncommutative Lax Hierarchies

We discuss commuting flows and conservation laws for Lax hierarchies on noncommutative spaces in the framework of the Sato theory. On commutative spaces, the Sato theory has revealed essential aspects of the integrability for wide class of soliton equations which are derived from the Lax hierarchies in terms of pseudo-differential operators. Noncommutative extension of the Sato theory has been already studied by the author and Kouichi Toda, and the existence of various noncommutative Lax hierarchies are guaranteed. In the present paper, we present conservation laws for the noncommutative Lax hierarchies with both space-space and space-time noncommutativities and prove the existence of infinite number of conserved densities. We also give the explicit representations of them in terms of Lax operators. Our results include noncommutative versions of KP, KdV, Boussinesq, coupled KdV, Sawada-Kotera, modified KdV equations and so on.Comment: 22 pages, LaTeX, v2: typos corrected, references added, version to appear in JM

Geometric structures on loop and path spaces

Is is known that the loop space associated to a Riemannian manifold admits a quasi-symplectic structure. This article shows that this structure is not likely to recover the underlying Riemannian metric by proving a result that is a strong indication of the "almost" independence of the quasi-symplectic structure with respect to the metric. Finally conditions to have contact structures on these spaces are studied.Comment: Final version. To appear in Proceedings of Math. Sci. Indian Academy of Science

The effect of a finite roll rate on the miss-distance of a bank-to-turn missile

AbstractWe consider a three-dimensional pursuit-evasion situation where a highly maneuverable evader, which we model as a “pedestrian” á la Isaacs, is engaged by a faster-pursuer. The pursuer has limited maneuverability, that is, the pursuer has a minimal turning radius, and in order to change the spatial direction of his velocity vector, he must first re-align his thrust vector in a similar manner to a bank-to-turn missile. The state space of the ensuing differential game is three-dimensional and its complexity is intermediate between Isaac's [1] classical “Homicidal Chauffeur” and “Two Car” differential games. This new DG is solved as a game of kind, and a capture criterion for a faster but less maneuverable pursuer is analytically established in terms of the game parameters

Counting statistics of collective photon transmissions

We theoretically study cooperative effects in the steady-state transmission of photons through a medium of $N$ radiators. Using methods from quantum transport, we find a cross-over in scaling from $N$ to $N^2$ in the current and even higher powers of $N$ in the higher cumulants of the photon counting statistics as a function of the tunable source occupation. The effect should be observable for atoms confined within a nano-cell with a pumped optical cavity as photon source.Comment: extended results, 9 pages, 2 figures, to appear in Annals of Physic

Interventions using behavioural insights to influence children's diet-related outcomes: a systematic review

The global prevalence of children with overweight and obesity continues to rise. Obesity in childhood has dire long-term consequences on health, social and economic outcomes. Promising interventions using behavioural insights to address obesity in childhood have emerged. This systematic review examines the effectiveness and health equity implications of interventions using behavioural insights to improve children's diet-related outcomes. The search strategy included searches on six electronic databases, reference lists of previous systematic reviews and backward searching of all included studies. One-hundred and eight papers describing 137 interventions were included. Interventions using behavioural insights were effective at modifying children's diet-related outcomes in 74% of all included interventions. The most promising approaches involved using incentives, changing defaults and modifying the physical environment. Information provision alone was the least effective approach. Health equity implications were rarely analysed or discussed. There was limited evidence of the sustainability of interventions-both in relation to their overall effectiveness and cost-effectiveness. The limited evidence on health equity, long-term effectiveness and the cost-effectiveness of these interventions limit what can be inferred for policymakers. This review synthesises the use of behavioural insights to improve children's diet-related outcomes, which can be used to inform future interventions

Motif Discovery through Predictive Modeling of Gene Regulation

We present MEDUSA, an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting. At each iteration of the algorithm, MEDUSA builds a motif model whose presence in the promoter region of a gene, coupled with activity of a regulator in an experiment, is predictive of differential expression. In this way, we learn motifs that are functional and predictive of regulatory response rather than motifs that are simply overrepresented in promoter sequences. Moreover, MEDUSA produces a model of the transcriptional control logic that can predict the expression of any gene in the organism, given the sequence of the promoter region of the target gene and the expression state of a set of known or putative transcription factors and signaling molecules. Each motif model is either a $k$-length sequence, a dimer, or a PSSM that is built by agglomerative probabilistic clustering of sequences with similar boosting loss. By applying MEDUSA to a set of environmental stress response expression data in yeast, we learn motifs whose ability to predict differential expression of target genes outperforms motifs from the TRANSFAC dataset and from a previously published candidate set of PSSMs. We also show that MEDUSA retrieves many experimentally confirmed binding sites associated with environmental stress response from the literature.Comment: RECOMB 200