Casimir Effect confronts Cosmological Constant

It has been speculated that the zero-point energy of the vacuum, regularized due to the existence of a suitable ultraviolet cut-off scale, could be the source of the non-vanishing cosmological constant that is driving the present acceleration of the universe. We show that the presence of such a cut-off can significantly alter the results for the Casimir force between parallel conducting plates and even lead to repulsive Casimir force when the plate separation is smaller than the cut-off scale length. Using the current experimental data we rule out the possibility that the observed cosmological constant arises from the zero-point energy which is made finite by a suitable cut-off. Any such cut-off which is consistent with the observed Casimir effect will lead to an energy density which is about 10^{12} times larger than the observed one, if gravity couples to these modes. The implications are discussed.Comment: revtex4; four pages; 5 fig

Particle creation, classicality and related issues in quantum field theory: II. Examples from field theory

We adopt the general formalism, which was developed in Paper I (arXiv:0708.1233) to analyze the evolution of a quantized time-dependent oscillator, to address several questions in the context of quantum field theory in time dependent external backgrounds. In particular, we study the question of emergence of classicality in terms of the phase space evolution and its relation to particle production, and clarify some conceptual issues. We consider a quantized scalar field evolving in a constant electric field and in FRW spacetimes which illustrate the two extreme cases of late time adiabatic and highly non-adiabatic evolution. Using the time-dependent generalizations of various quantities like particle number density, effective Lagrangian etc. introduced in Paper I, we contrast the evolution in these two limits bringing out key differences between the Schwinger effect and evolution in the de Sitter background. Further, our examples suggest that the notion of classicality is multifaceted and any one single criterion may not have universal applicability. For example, the peaking of the phase space Wigner distribution on the classical trajectory \emph{alone} does not imply transition to classical behavior. An analysis of the behavior of the \emph{classicality parameter}, which was introduced in Paper I, leads to the conclusion that strong particle production is necessary for the quantum state to become highly correlated in phase space at late times.Comment: RevTeX 4; 27 pages; 18 figures; second of a series of two papers, the first being arXiv:0708.1233 [gr-qc]; high resolution figures available from the authors on reques

Particle creation, classicality and related issues in quantum field theory: I. Formalism and toy models

The quantum theory of a harmonic oscillator with a time dependent frequency arises in several important physical problems, especially in the study of quantum field theory in an external background. While the mathematics of this system is straightforward, several conceptual issues arise in such a study. We present a general formalism to address some of the conceptual issues like the emergence of classicality, definition of particle content, back reaction etc. In particular, we parametrize the wave function in terms of a complex number (which we call excitation parameter) and express all physically relevant quantities in terms it. Many of the notions -- like those of particle number density, effective Lagrangian etc., which are usually defined using asymptotic in-out states -- are generalized as time-dependent concepts and we show that these generalized definitions lead to useful and reasonable results. Having developed the general formalism we apply it to several examples. Exact analytic expressions are found for a particular toy model and approximate analytic solutions are obtained in the extreme cases of adiabatic and highly non-adiabatic evolution. We then work out the exact results numerically for a variety of models and compare them with the analytic results and approximations. The formalism is useful in addressing the question of emergence of classicality of the quantum state, its relation to particle production and to clarify several conceptual issues related to this. In Paper II (arXiv:0708.1237), which is a sequel to this, the formalism will be applied to analyze the corresponding issues in the context of quantum field theory in background cosmological models and electric fields.Comment: RevTeX 4; 32 pages; 28 figures; first of a series of two papers, the second being arXiv:0708.1237 [gr-qc]; high resolution figures available from the authors on reques

Learning with a network of competing synapses

Competition between synapses arises in some forms of correlation-based plasticity. Here we propose a game theory-inspired model of synaptic interactions whose dynamics is driven by competition between synapses in their weak and strong states, which are characterized by different timescales. The learning of inputs and memory are meaningfully definable in an effective description of networked synaptic populations. We study, numerically and analytically, the dynamic responses of the effective system to various signal types, particularly with reference to an existing empirical motor adaptation model. The dependence of the system-level behavior on the synaptic parameters, and the signal strength, is brought out in a clear manner, thus illuminating issues such as those of optimal performance, and the functional role of multiple timescales.Comment: 16 pages, 9 figures; published in PLoS ON

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis

Abstract Background A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. Results We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how “distant” they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Conclusions Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and diversity of the template dataset, but, given the rapid accumulation of solved protein complex structures, its scope and utility are expected to keep steadily improving

A Critical Analysis of the Differences Among Design Methods for Low-Speed Axial Fans

Complete list of domain-domain interactions from iPfam. Column headers: 1) Pfam ID of domain 1; 2) Pfam ID of domain 2; 3) PDB chain ID of domain 1; 4) PDB chain ID of domain 2; 5) Uniprot accession of PDB chain 1; 6) Uniprot accession of PDB chain 2. (TXT 6425 kb

Additional file 1: Figure S1. of Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis

Histograms summarizing the occurrences of Pfam-A functional domains in the human (blue) and MTB (red) proteomes. Nearly 30% of the proteins in both species have been assigned more than one domain. Figure S2. Pair-wise comparisons between MTB proteins and their putative orthologs listed in the Integr8 (upper figure), eggNOG (lower left) and KEGG Orthology/KO (lower right) databases. Note the relatively smaller number of orthologs assigned by Integr8. Figure S3. Using the interolog approach to extend the limited set of DDI templates provided by PDB. Evolutionarily conserved PPIs (involving orthologs) are assumed to share a common underlying pattern of domain-domain interactions. This allows interacting domains to be inferred for PPIs for which structure information is not directly available (here, A’-B’). Figure S4. Diversity in terms of length and sequence composition across the polypeptide sequences assigned to the Ulp1 protease family C-terminal catalytic domain (PF02902). The scatter plot follows from all-vs-all pairwise sequence alignment using the Smith-Waterman method. Pairs coming from the same proteome (blue) or from different proteomes (cyan) have been assigned different colors. Figure S5. Statistical over-representation of interacting Pfam domain pairs (from iPfam/3DID) in a PPI network for co-localized, coexpressed cytosolic proteins in E. coli. Several domain pairs do not show significant association with the PPI set. The darker horizontal line represents the p-value < 0.05 threshold. (PDF 1100 kb

From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach

<div><p>High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that <i>subset</i> of regulators whose <i>aggregated target set</i> best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory <i>subnetworks</i>, rather than just the target sets of <i>individual</i> regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on <i>E</i>. <i>coli</i> microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for <i>M</i>. <i>tuberculosis</i>, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.</p></div