4,345 research outputs found

    A specialized inventory problem in banks: optimizing retail sweeps

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    Deposits held at Federal Reserve Banks are an essential input to the business activity of most depository institutions in the United States. Managing these deposits is an important and complex inventory problem, for two reasons. First, Federal Reserve regulations require that depository institutions hold certain amounts of such deposits at the Federal Reserve Banks to satisfy statutory reserve requirements against customers* transaction accounts (demand deposits and other checkable deposits). Second, some inventory of such deposits is essential for banks to operate one of their core lines of business: furnishing payment services to households and firms. including wire transfers, ACH payments, and check clearing settlement. Because the Federal Reserve does not pay interest on such deposits used to satisfy statutory reserve requirements, banks seek to minimize their inventory of such deposits. In 1994, the banking industry introduced a new inventory management tool for such deposits, the retail deposit sweep program, which avoids the statutory requirement by reclassifying transaction deposits as savings deposits. In this analysis, we examine two algorithms for operating such sweeps programs within the limits of Federal Reserve regulations.Banks and banking ; Retail trade

    Aerial photography collected with a multirotor drone reveals impact of Eurasian beaver reintroduction on ecosystem structure

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    doi: 10.1139/juvs-2015-0005Copyright © 2015 Canadian Science PublishingBeavers are often described as ecological engineers with an ability to modify the structure and flow of fluvial systems and create complex wetland environments with dams, ponds and canals. Consequently, beaver activity has implications for a wide range of environmental ecosystem services including biodiversity, flood risk mitigation, water quality and sustainable drinking water provision. With the current debate surrounding the reintroduction of beavers into the United Kingdom, it is critical to be able to monitor the impact of beavers upon the environment. This study presents the first proof of concept results showing how a lightweight hexacopter fitted with a simple digital camera can be used to derive orthophoto and digital surface model (DSM) data products at a site where beavers have recently been reintroduced. Early results indicate that analysis of the fine-scale (0.01 m) orthophoto and DSM can be used to identify impacts on the ecosystem structure including the extent of dams and associated ponds, and changes in vegetation structure due to beaver tree felling activity. Unmanned aerial vehicle data acquisition offers an effective toolkit for regular repeat monitoring at fine spatial resolution which is a critical attribute for monitoring rapidly-changing and difficult to access beaver-impacted ecosystems

    Mrgprd Enhances Excitability in Specific Populations of Cutaneous Murine Polymodal Nociceptors

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    The Mas-related G protein-coupled receptor D (Mrgprd) is selectively expressed in nonpeptidergic nociceptors that innervate the outer layers of mammalian skin. The function of Mrgprd in nociceptive neurons and the physiologically relevant somatosensory stimuli that activate Mrgprd^-expressing (Mrgprd^+) neurons are currently unknown. To address these issues, we studied three Mrgprd knock-in mouse lines using an ex vivo somatosensory preparation to examine the role of the Mrgprd receptor and Mrgprd+ afferents in cutaneous somatosensation. In mouse hairy skin, Mrgprd, as marked by expression of green fluorescent protein reporters, was expressed predominantly in the population of nonpeptidergic, TRPV1-negative, C-polymodal nociceptors. In mice lacking Mrgprd, this population of nociceptors exhibited decreased sensitivity to cold, heat, and mechanical stimuli. Additionally, in vitro patch-clamp studies were performed on cultured dorsal root ganglion neurons from Mrgprd^(–/–) and Mrgprd^(+/–) mice. These studies revealed a higher rheobase in neurons from Mrgprd^(–/–) mice than from Mrgprd^(+/–) mice. Furthermore, the application of the Mrgprd ligand β-alanine significantly reduced the rheobase and increased the firing rate in neurons from Mrgprd^(+/–) mice but was without effect in neurons from Mrgprd^(–/–) mice. Our results demonstrate that Mrgprd influences the excitability of polymodal nonpeptidergic nociceptors to mechanical and thermal stimuli

    Cognitive architectures as Lakatosian research programmes: two case studies

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    Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility

    Comparing Observed Stellar Kinematics and Surface Densities in a Low-latitude Bulge Field to Galactic Population Synthesis Models

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    We present an analysis of Galactic bulge stars from Hubble Space Telescope Wide Field Camera 3 observations of the Stanek window (l, b = [0.25,-2.15]) from two epochs approximately two years apart. This data set is adjacent to the provisional Wide-field Infrared Survey Telescope (WFIRST) microlensing field. Proper motions are measured for approximately 115,000 stars down to 28th mag in V band and 25th mag in I band, with accuracies of 0.5 mas yr-1 (20 km s-1) at I ≈ 21. A cut on the longitudinal proper motion μ l allows us to separate disk and bulge populations and produce bulge-only star counts that are corrected for photometric completeness and efficiency of the proper-motion cut. The kinematic dispersions and surface density in the field are compared to the nearby SWEEPS sight line, finding a marginally larger-than-expected gradient in stellar density. The observed bulge star counts and kinematics are further compared to the Besançon, Galaxia, and GalMod Galactic population synthesis models. We find that most of the models underpredict low-mass bulge stars by ∼33% below the main-sequence turnoff, and upwards of ∼70% at redder J and H wavebands. While considering inaccuracies in the Galactic models, we give implications for the exoplanet yield from the WFIRST microlensing mission

    Vertical Resolution of a Seismic Survey in Stratigraphic Sequences less than 100 m Deep in Southeastern Kansas

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    A 400-m long, 12-fold high-resolution common depth point (CDP) reflection seismic profile was acquired across shallow converging Pennsylvanian strata in the Independence area of southeastern Kansas. One of the principal objectives was to determine practical vertical resolution limits in an excellent shallow seismic-data area with borehole control. The dominant frequency of the CDP stacked data is in excess of 150 Hz based on peak-to-peak measurements. Interference phenomena observed on stacked seismic data incorporated with models derived from log and drill-hole information suggest a practical vertical resolution limit of about 7 m, or one-third of the dominant wavelength. The data suggest conventional rules of thumb describing resolution potential are not accurate when reflectors on shallow, narrow bandwidth data converge rapidly across horizontal distances less than the Fresnel Zone

    Mean Field Theory of the Localization Transition

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    A mean field theory of the localization transition for bosonic systems is developed. Localization is shown to be sensitive to the distribution of the random site energies. It occurs in the presence of a triangular distribution, but not a uniform one. The inverse participation ratio, the single site Green's function, the superfluid order parameter and the corresponding susceptibility are calculated, and the appropriate exponents determined. All of these quantities indicate the presence of a new phase, which can be identified as the {\it Bose-glass}.Comment: 4 pages, Revtex, 2 figures appende

    Cancer incidence and stage at diagnosis among people with recent-onset psychotic disorders: A retrospective cohort study using health administrative data from Ontario, Canada.

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    OBJECTIVE: Prior evidence on the relative risk of cancer among people with psychotic disorders is equivocal. The objective of this study was to compare incidence and stage at diagnosis of cancer for people with psychotic disorders relative to the general population. METHOD: We constructed a retrospective cohort of people with a first diagnosis of non-affective psychotic disorder and a comparison group from the general population using linked health administrative databases in Ontario, Canada. The cohort was followed for incident diagnoses of cancer over a 25-year period. We used Poisson and logistic regression models to compare cancer incidence and stage at diagnosis between people with psychotic disorders and the comparison group, adjusting for confounding factors. RESULTS: People with psychotic disorders had an 8.6% higher incidence (IRR = 1.09, 95%CI = 1.05,1.12) of cancer overall relative to the comparison group, with effect modification by sex and substantial variation across cancer sites. People with psychotic disorders also had 23% greater odds (OR = 1.23, 95%CI = 1.13,1.34) of being diagnosed with more advanced stage cancer relative to the comparison group. CONCLUSIONS: We found evidence of elevated cancer incidence in people with non-affective psychotic disorders relative to the general population. The higher odds of more advanced stage cancer diagnoses in people with psychotic disorders represents an opportunity to improve patient participation in recommended cancer screening, as well as timely access to services for cancer diagnosis and treatment. Future research should examine confounding effects of lifestyle factors and antipsychotic medications on the risk of developing cancer among people with psychotic disorders

    Evaluating concentration estimation errors in ELISA microarray experiments

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    BACKGROUND: Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors. RESULTS: We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. CONCLUSIONS: This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses. Applying propagation of error to a variety of ELISA microarray concentration estimation models is straightforward. Displaying the results in the three-panel layout succinctly summarizes both the standard and sample data while providing an informative critique of applicability of the fitted model, the uncertainty in concentration estimates, and the quality of both the experiment and the ELISA microarray process
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