170,334 research outputs found

    Compact well-bounded operators

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    Every compact well-bounded operator has a representation as a linear combination of disjoint projections reminiscent of the representation of compact self-adjoint operators. In this note we show that the converse of this result holds, thus characterizing compact well-bounded operators. We also apply this result to study compact well-bounded operators on some special classes of Banach spaces such as hereditarily indecomposable spaces and certain spaces constructed by G. Pisier

    DS_10.1177_0363546518817749 – Supplemental material for Delayed ACL Reconstruction in Patients ≥40 Years of Age Is Associated With Increased Risk of Medial Meniscal Injury at 1 Year

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    Supplemental material, DS_10.1177_0363546518817749 for Delayed ACL Reconstruction in Patients ≥40 Years of Age Is Associated With Increased Risk of Medial Meniscal Injury at 1 Year by Jonathan A. Stone, Gabriel S. Perrone, Teron A. Nezwek, Qingping Cui, Steven C. Vlad, John C. Richmond and Matthew J. Salzler in The American Journal of Sports Medicine</p

    An object-oriented model of measurement systems

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    This paper presents a general object-oriented model for measurement systems. The limitations of the conventional function-oriented models are examined in the light of the generalized concept of measurement and its theoretical framework proposed previously by the authors. The proposed model identifies five classes of objects, i.e., measured object, measuring instrument, reference standard, human observer, and operating environment. Each is characterized by its own attributes and operations or functions at three levels, i.e., internal, operational, and environmental. The interactions between them are also modeled, including the coupling between the measured object and the measuring instrument, the human-instrument interface, the calibration, and the interference. It serves as both a modeling framework and a practical tool for description, analysis and design, and, in particular, for computer-aided analysis and design of a measuring system. It will find applications in instrumentation engineering and measurement research and education

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Strain and temperature sensors using multimode optical fiber Bragg gratings and correlation signal processing

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    Multimode fiber optic Bragg grating sensors for strain and temperature measurements using correlation signal processing methods have been developed. Two multimode Bragg grating sensors were fabricated in 62/125 m graded-index silica multimode fiber; the first sensor was produced by the holographic method and the second sensor by the phase mask technique. The sensors have signal reflectivity of approximately 35% at peak wavelengths of 835 nm and 859 nm, respectively. Strain testing of both sensors has been done from 0 to 1000 με and the temperature testing from 40 to 80°C. Strain and temperature sensitivity values are 0.55 pm/με and 6 pm/°C, respectively. The sensors are being applied in a power-by-light hydraulic valve monitoring system

    Mitomycin C in highly myopic eyes - Author reply

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    Ophthalmology. 2005 Feb;112(2):208-18; discussion 219. Mitomycin C modulation of corneal wound healing after photorefractive keratectomy in highly myopic eyes. Gambato C, Ghirlando A, Moretto E, Busato F, Midena E. SourceRefractive Surgery Service and Antimetabolite Therapy Research Unit, Department of Ophthalmology, University of Padova, Padova, Italy. Abstract PURPOSE: To evaluate the role of topical mitomycin C in corneal wound healing (CWH) after photorefractive keratectomy (PRK) in highly myopic eyes. DESIGN: Prospective, double-masked, randomized clinical trial. PARTICIPANTS: Seventy-two eyes of 36 patients affected by high (>7 diopters) myopia. METHODS: In each patient, one eye was randomly assigned to PRK with intraoperative topical 0.02% mitomycin C application, and the fellow eye was treated with a placebo. Postoperatively, mitomycin C-treated eyes received artificial tears (3 times daily, tapered in 3 months), whereas the fellow eye was treated with fluorometholone sodium 2% and artificial tears (3 times daily, tapered in 3 months). MAIN OUTCOME MEASURES: Uncorrected visual acuity (UCVA) and best-corrected visual acuity (BCVA), contrast sensitivity, manifest refraction, and biomicroscopy. Contrast sensitivity was determined using the Pelli-Robson chart. Corneal confocal microscopy documented CWH. RESULTS: Mean follow-up was 18 months (range, 12-36). No side effects or toxic effects were documented. At 12-month follow-up examination, UCVAs (logarithm of the minimum angle of resolution) were 0.4+/-0.48 and 0.5+/-0.53 (P = .03) in mitomycin C-treated eyes and corticosteroid-treated eyes, respectively. At 1 year, corneal haze developed in 20% of corticosteroid-treated eyes, versus 0% of mitomycin C-treated eyes. At 12, 24, and 36 months, corneal confocal microscopy showed activated keratocytes and extracellular matrix significantly more evident in untreated eyes (Ps = 0.004, 0.024, and 0.046, respectively). CONCLUSION: Topical intraoperative application of 0.02% mitomycin C can reduce haze formation in highly myopic eyes undergoing PRK. Comment in Ophthalmology. 2006 Feb;113(2):357; author reply 357-8

    Modelling and measurement accuracy enhancement of flue gas flow using neural networks

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    This paper discusses the modeling of the flue gas flow in industrial ducts and stacks using artificial neural networks (ANN's). Based upon the individual velocity and other operating conditions, an ANN model has been developed for the measurement of the volume flow rate. The model has been validated by the experiment using a case-study power plant. The results have shown that the model can largely compensate for the nonrepresentativeness of a sampling location and, as a result, the measurement accuracy of the flue gas flow can be significantly improved

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    A fibre optic sensor for the measurement of surface roughness and displacement using artificial neural networks

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    This paper presents a fiber optic sensor system, artificial neural networks (fast back-propagation) are employed for the data processing. The use of the neural networks makes it possible for the sensor to be used both for surface roughness and displacement measurement at the same time. The results indicate 100% correct surface classification for ten different surfaces (different materials, different manufacturing methods, and different surface roughnesses) and displacement errors less then ±5 μm. The actual accuracy was restricted by the calibration machine. A measuring range of ±0.8 mm for the displacement measurement was achieved
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