Semiparametric sieve-type generalized least squares inference

This article considers the problem of statistical inference in linear regression models with dependent errors. A sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the generating mechanism of the errors. The asymptotic properties of the sieve-type GLS estimator are established under general conditions, including mixingale-type conditions as well as conditions which allow for long-range dependence in the stochastic regressors and/or the errors. A Monte Carlo study examines the finite-sample properties of the method for testing regression hypotheses

Convergence Conditions for Random Quantum Circuits

Efficient methods for generating pseudo-randomly distributed unitary operators are needed for the practical application of Haar distributed random operators in quantum communication and noise estimation protocols. We develop a theoretical framework for analyzing pseudo-random ensembles generated through a random circuit composition. We prove that the measure over random circuits converges exponentially (with increasing circuit length) to the uniform (Haar) measure on the unitary group and describe how the rate of convergence may be calculated for specific applications.Comment: 4 pages (revtex), comments welcome. v2: reference added, title changed; v3: published version, minor changes, references update

An efficient algorithm for learning with semi-bandit feedback

We consider the problem of online combinatorial optimization under semi-bandit feedback. The goal of the learner is to sequentially select its actions from a combinatorial decision set so as to minimize its cumulative loss. We propose a learning algorithm for this problem based on combining the Follow-the-Perturbed-Leader (FPL) prediction method with a novel loss estimation procedure called Geometric Resampling (GR). Contrary to previous solutions, the resulting algorithm can be efficiently implemented for any decision set where efficient offline combinatorial optimization is possible at all. Assuming that the elements of the decision set can be described with d-dimensional binary vectors with at most m non-zero entries, we show that the expected regret of our algorithm after T rounds is O(m sqrt(dT log d)). As a side result, we also improve the best known regret bounds for FPL in the full information setting to O(m^(3/2) sqrt(T log d)), gaining a factor of sqrt(d/m) over previous bounds for this algorithm.Comment: submitted to ALT 201

Polynomial Cointegration among Stationary Processes with Long Memory

n this paper we consider polynomial cointegrating relationships among stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zeroComment: 25 pages, 7 figures. Submitted in August 200

Evolutionary fine-tuning of conformational ensembles in FimH during host-pathogen interactions

Positive selection in the two-domain type 1 pilus adhesin FimH enhances Escherichia coli fitness in urinary tract infection (UTI). We report a comprehensive atomic-level view of FimH in two-state conformational ensembles in solution, composed of one low-affinity tense (T) and multiple high-affinity relaxed (R) conformations. Positively selected residues allosterically modulate the equilibrium between these two conformational states, each of which engages mannose through distinct binding orientations. A FimH variant that only adopts the R state is severely attenuated early in a mouse model of uncomplicated UTI but is proficient at colonizing catheterized bladders in vivo or bladder transitional-like epithelial cells in vitro. Thus, the bladder habitat has barrier(s) to R state–mediated colonization possibly conferred by the terminally differentiated bladder epithelium and/or decoy receptors in urine. Together, our studies reveal the conformational landscape in solution, binding mechanisms, and adhesive strength of an allosteric two-domain adhesin that evolved “moderate” affinity to optimize persistence in the bladder during UTI

Untangling the Conceptual Isssues Raised in Reydon and Scholz’s Critique of Organizational Ecology and Darwinian Populations

Reydon and Scholz raise doubts about the Darwinian status of organizational ecology by arguing that Darwinian principles are not applicable to organizational populations. Although their critique of organizational ecology’s typological essentialism is correct, they go on to reject the Darwinian status of organizational populations. This paper claims that the distinction between replicators and interactors, raised in modern philosophy of biology but not discussed by Reydon and Scholz, points the way forward for organizational ecologists. It is possible to conceptualise evolving Darwinian populations providing the inheritance mechanism is appropriately specified. By this approach, adaptation and selection are no longer dichotomised, and the evolutionary significance of knowledge transmission is highlightedPeer reviewe

Single-molecule super-resolution imaging of chromosomes and in situ haplotype visualization using Oligopaint FISH probes

Fluorescence in situ hybridization (FISH) is a powerful single-cell technique for studying nuclear structure and organization. Here we report two advances in FISH-based imaging. We first describe the in situ visualization of single-copy regions of the genome using two single-molecule super-resolution methodologies. We then introduce a robust and reliable system that harnesses single-nucleotide polymorphisms (SNPs) to visually distinguish the maternal and paternal homologous chromosomes in mammalian and insect systems. Both of these new technologies are enabled by renewable, bioinformatically designed, oligonucleotide-based Oligopaint probes, which we augment with a strategy that uses secondary oligonucleotides (oligos) to produce and enhance fluorescent signals. These advances should substantially expand the capability to query parent-of-origin-specific chromosome positioning and gene expression on a cell-by-cell basis

Building Trust, Experiential Learning, and the Importance of Sovereignty: Capacity Building in Pre-Engineering Education - a Tribal College Perspective

At tribal colleges and mainstream universities, program success is often identified solely with matriculation and graduation rates. However, particularly for new STEM programs, capacity building is another key measure of success. In this paper, three of the co-authors, who are faculty members at a tribally-controlled college and participants in a multi-year collaborative pre-engineering education initiative between a tribal college and two mainstream universities, provide their perspectives on capacity building in summer camp activities within the alliance. The three each wrote essays reflecting on capacity building, guided by pre-determined questions written by the fourth author. Through qualitative analysis, we present common themes, divergent opinions, and quotations extracted from the essays from their unique perspective as faculty at a tribally-controlled college. We emphasize impacts among the partnering schools, faculty, students, and communities where the summer camp activities took place. Three common themes dominated the essays including the importance of (1) building trust within the reservation community, (2) recognizing the effectiveness of experiential and project-based service-learning approaches, and (3) encouraging tribally-controlled colleges to take a lead role in determining research and educational foci