Operation of the DC Current Transformer intensity monitors at FNAL during Run II

Circulating beam intensity measurements at FNAL are provided by five DC current transformers (DCCT), one per machine. With the exception of the DCCT in the Recycler, all DCCT systems were designed and built at FNAL. This paper presents an overview of both DCCT systems, including the sensor, the electronics, and the front-end instrumentation software, as well as their performance during Run II

Smoothness-Increasing Accuracy-Conserving (SIAC) filtering and quasi interpolation: A unified view

Filtering plays a crucial role in postprocessing and analyzing data in scientific and engineering applications. Various application-specific filtering schemes have been proposed based on particular design criteria. In this paper, we focus on establishing the theoretical connection between quasi-interpolation and a class of kernels (based on B-splines) that are specifically designed for the postprocessing of the discontinuous Galerkin (DG) method called Smoothness-Increasing Accuracy-Conserving (SIAC) filtering. SIAC filtering, as the name suggests, aims to increase the smoothness of the DG approximation while conserving the inherent accuracy of the DG solution (superconvergence). Superconvergence properties of SIAC filtering has been studied in the literature. In this paper, we present the theoretical results that establish the connection between SIAC filtering to long-standing concepts in approximation theory such as quasi-interpolation and polynomial reproduction. This connection bridges the gap between the two related disciplines and provides a decisive advancement in designing new filters and mathematical analysis of their properties. In particular, we derive a closed formulation for convolution of SIAC kernels with polynomials. We also compare and contrast cardinal spline functions as an example of filters designed for image processing applications with SIAC filters of the same order, and study their properties

Justification of the coupled-mode approximation for a nonlinear elliptic problem with a periodic potential

Coupled-mode systems are used in physical literature to simplify the nonlinear Maxwell and Gross-Pitaevskii equations with a small periodic potential and to approximate localized solutions called gap solitons by analytical expressions involving hyperbolic functions. We justify the use of the one-dimensional stationary coupled-mode system for a relevant elliptic problem by employing the method of Lyapunov--Schmidt reductions in Fourier space. In particular, existence of periodic/anti-periodic and decaying solutions is proved and the error terms are controlled in suitable norms. The use of multi-dimensional stationary coupled-mode systems is justified for analysis of bifurcations of periodic/anti-periodic solutions in a small multi-dimensional periodic potential.Comment: 18 pages, no figure

Backward electroproduction of pi0 mesons on protons in the region of nucleon resonances at four momentum transfer squared Q**2 = 1.0 GeV**2

Exclusive electroproduction of pi0 mesons on protons in the backward hemisphere has been studied at Q**2 = 1.0 GeV**2 by detecting protons in the forward direction in coincidence with scattered electrons from the 4 GeV electron beam in Jefferson Lab's Hall A. The data span the range of the total (gamma* p) center-of-mass energy W from the pion production threshold to W = 2.0 GeV. The differential cross sections sigma_T+epsilon*sigma_L, sigma_TL, and sigma_TT were separated from the azimuthal distribution and are presented together with the MAID and SAID parametrizations.Comment: 17 pages, 11 figures, information can be found at http://hallaweb.jlab.org/experiment/E93-050/vcs.html updated content about SAID analysis updated MAID results following new reference nucl-th/0310041 updated figure

The Influence of a Firms\u27 Business Strategy on the Downside Risk of Earnings, Accruals and Cash Flow

This study examines whether a firm\u27s business strategy is an underlying determinant of downside risk in accounting earnings and its components. Based on organizational theory we predict that firms following an innovative prospector strategy exhibit lower profitability tendencies than firms following a cost-oriented defender strategy. Further, we anticipate that these strategies are asymmetrically positioned towards environmental uncertainty, with defenders focusing their efforts to efficiency, cost control, and minimizing exposure to downside risk, whereas prospectors direct their resources to flexibility, innovation, and maximizing the growth potential through aggressive expansion to new product markets. We find that prospectors are indeed less profitable than defenders. We also demonstrate that prospectors have greater total and downside earnings risk. Finally, we decompose earnings into accruals and cash flow and show that the higher exposure of prospectors to earnings downside risk is driven by the cash flow component rather than the accrual component. Collectively, our results suggest that considering how strategy interacts with financial reporting attributes is a useful way for evaluating a firms\u27 risk profile

Fractional dynamics pharmacokinetics–pharmacodynamic models

While an increasing number of fractional order integrals and differential equations applications have been reported in the physics, signal processing, engineering and bioengineering literatures, little attention has been paid to this class of models in the pharmacokinetics–pharmacodynamic (PKPD) literature. One of the reasons is computational: while the analytical solution of fractional differential equations is available in special cases, it this turns out that even the simplest PKPD models that can be constructed using fractional calculus do not allow an analytical solution. In this paper, we first introduce new families of PKPD models incorporating fractional order integrals and differential equations, and, second, exemplify and investigate their qualitative behavior. The families represent extensions of frequently used PK link and PD direct and indirect action models, using the tools of fractional calculus. In addition the PD models can be a function of a variable, the active drug, which can smoothly transition from concentration to exposure, to hyper-exposure, according to a fractional integral transformation. To investigate the behavior of the models we propose, we implement numerical algorithms for fractional integration and for the numerical solution of a system of fractional differential equations. For simplicity, in our investigation we concentrate on the pharmacodynamic side of the models, assuming standard (integer order) pharmacokinetics

Computer-aided assessment of diagnostic images for epidemiological research

<p>Abstract</p> <p>Background</p> <p>Diagnostic images are often assessed for clinical outcomes using subjective methods, which are limited by the skill of the reviewer. Computer-aided diagnosis (CAD) algorithms that assist reviewers in their decisions concerning outcomes have been developed to increase sensitivity and specificity in the clinical setting. However, these systems have not been well utilized in research settings to improve the measurement of clinical endpoints. Reductions in bias through their use could have important implications for etiologic research.</p> <p>Methods</p> <p>Using the example of cortical cataract detection, we developed an algorithm for assisting a reviewer in evaluating digital images for the presence and severity of lesions. Available image processing and statistical methods that were easily implementable were used as the basis for the CAD algorithm. The performance of the system was compared to the subjective assessment of five reviewers using 60 simulated images. Cortical cataract severity scores from 0 to 16 were assigned to the images by the reviewers and the CAD system, with each image assessed twice to obtain a measure of variability. Image characteristics that affected reviewer bias were also assessed by systematically varying the appearance of the simulated images.</p> <p>Results</p> <p>The algorithm yielded severity scores with smaller bias on images where cataract severity was mild to moderate (approximately ≤ 6/16^<it>ths</it>). On high severity images, the bias of the CAD system exceeded that of the reviewers. The variability of the CAD system was zero on repeated images but ranged from 0.48 to 1.22 for the reviewers. The direction and magnitude of the bias exhibited by the reviewers was a function of the number of cataract opacities, the shape and the contrast of the lesions in the simulated images.</p> <p>Conclusion</p> <p>CAD systems are feasible to implement with available software and can be valuable when medical images contain exposure or outcome information for etiologic research. Our results indicate that such systems have the potential to decrease bias and discriminate very small changes in disease severity. Simulated images are a tool that can be used to assess performance of a CAD system when a gold standard is not available.</p