Photoinduced Gratings in Functionalized Azo-Carbazole Compounds in Picosecond Regime

We report results of diffraction grating inscription on thin films prepared from epoxy resin doped with azo-carbazole based dyes. Diffraction gratings were recorded at the wavelength 532 nm and monitored through intensity of first order of diffraction (632 nm). Atomic force microscope scans of the gratings show that a surface relief grating also appeared

An operational analysis of Lake Surface Water Temperature

Operational analyses of Lake Surface Water Temperature (LSWT) have many potential uses including improvement of numerical weather prediction (NWP) models on regional scales. In November 2011, LSWT was included in the Met Office Operational Sea Surface Temperature and Ice Analysis (OSTIA) product, for 248 lakes globally. The OSTIA analysis procedure, which has been optimised for oceans, has also been used for the lakes in this first version of the product. Infra-red satellite observations of lakes and in situ measurements are assimilated. The satellite observations are based on retrievals optimised for Sea Surface Temperature (SST) which, although they may introduce inaccuracies into the LSWT data, are currently the only near-real-time information available. The LSWT analysis has a global root mean square difference of 1.31 K and a mean difference of 0.65 K (including a cool skin effect of 0.2 K) compared to independent data from the ESA ARC-Lake project for a 3-month period (June to August 2009). It is demonstrated that the OSTIA LSWT is an improvement over the use of climatology to capture the day-to-day variation in global lake surface temperatures

A numerical investigation of wind speed effects on lake-effect storms

Observations of lake-effect storms that occur over the Great Lakes region during late autumn and winter indicate a high sensitivity to ambient wind speed and direction. In this paper, a two-dimensional version of the Penn State University/National Center for Atmospheric Research (PSU/NCAR) model is used to investigate the wind speed effects on lake-effect snowstorms that occur over the Great Lakes region.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42510/1/10546_2004_Article_BF00708966.pd

Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery

Peer reviewe

COMMENSURATE-INCOMMENSURATE PHASE TRANSITION IN (Co1-xMnx)2P

Neutron diffraction, a.c. initial magnetic susceptibility, magnetization, and heat capacity measurements allow a better understanding of the metamagnetic-like phase observed at low temperature in (Co1-xMnx)2P. The magnetic structures and phase transitions for x = 0.6 and 0.75 have been determined

Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record

PURPOSE: The purpose of this article was to develop and validate a natural language processing (NLP) algorithm to extract qualitative descriptors of microbial keratitis (MK) from electronic health records. METHODS: In this retrospective cohort study, patients with MK diagnoses from 2 academic centers were identified using electronic health records. An NLP algorithm was created to extract MK centrality, depth, and thinning. A random sample of patient with MK encounters were used to train the algorithm (400 encounters of 100 patients) and compared with expert chart review. The algorithm was evaluated in internal (n = 100) and external validation data sets (n = 59) in comparison with masked chart review. Outcomes were sensitivity and specificity of the NLP algorithm to extract qualitative MK features as compared with masked chart review performed by an ophthalmologist. RESULTS: Across data sets, gold-standard chart review found centrality was documented in 64.0% to 79.3% of charts, depth in 15.0% to 20.3%, and thinning in 25.4% to 31.3%. Compared with chart review, the NLP algorithm had a sensitivity of 80.3%, 50.0%, and 66.7% for identifying central MK, 85.4%, 66.7%, and 100% for deep MK, and 100.0%, 95.2%, and 100% for thin MK, in the training, internal, and external validation samples, respectively. Specificity was 41.1%, 38.6%, and 46.2% for centrality, 100%, 83.3%, and 71.4% for depth, and 93.3%, 100%, and was not applicable (n = 0) to the external data for thinning, in the samples, respectively. CONCLUSIONS: MK features are not documented consistently showing a lack of standardization in recording MK examination elements. NLP shows promise but will be limited if the available clinical data are missing from the chart

Converting to SITA-Standard from Full-Threshold Visual Field Testing in the Follow-up Phase of a Clinical Trial

PURPOSE. To evaluate the impact of converting from Humphrey 24-2 full-threshold (FT) visual field (VF) testing to SITA-Standard (SS) VF testing during the follow-up phase of a clinical trial. METHODS. VF data were obtained from 243 patients in the Collaborative Initial Glaucoma Treatment Study (CIGTS) who had follow-up visits in 2004. FT and SS VF tests were performed in random order on the same day. RESULTS. The average duration of the SS test (6.3 minutes) was shorter (P Ͻ 0.0001, paired t-test) than the FT test (11.8 minutes). The mean deviation did not differ between SS and FT testing. A small difference was found in the pattern SD (PSD) (P ϭ 0.02). The mean CIGTS score from the FT test (4.5) was significantly lower (P Ͻ 0.0001) than the mean CIGTS score from the SS test (6.0). Although the two tests yielded identical Glaucoma Hemifield Test (GHT) results in 179 patients (76%), 16 patients had a normal GHT result on FT testing and an SS test result that was outside normal limits. Six patients had the reverse finding. The most significant factor associated with an increased (positive) difference between the CIGTS VF score generated from SS and FT testing was conducting the FT test first (P Ͻ 0.0001). CONCLUSIONS. Although SS and FT testing yielded very similar mean deviation results, the CIGTS VF score and GHT differed between SS and FT tests. Changing the approach used to measuring a study's primary VF outcome should be accompanied by a critical evaluation of the change's impact. (Invest Ophthalmol Vis Sci. 2005;46:2755-2759) DOI:10.1167/iovs.05-0006 I n the course of conducting long-term clinical trials, key methods used to assess outcomes may become obsolete, be difficult to maintain, or be updated over time. In the Collaborative Initial Glaucoma Treatment Study (CIGTS), 1 visual field (VF) change over time is the primary outcome. Its measurement at the study onset (in the fall of 1993) was made with the Humphrey 24-2 full-threshold (FT) test (Carl Zeiss Meditec, Dublin, CA) 2 and that testing approach was uniformly used at the study's 14 clinical centers through December 2003. At that time, study investigators approved converting to VF testing by the Swedish Interactive Threshold Algorithm (SITA) Standard test. 3 This decision was based on evidence that the SITA strategy produces results similar to those of the FT test, 4 is sensitive and specific for detecting glaucomatous VF defects, 5-7 and reduced testing time substantially. 4 -10 To evaluate the impact of this conversion for the study's primary outcome, a protocol was instituted in the CIGTS to determine whether the SITA-Standard results yielded similar or different scores from those produced by the FT test. METHODS A total of 245 CIGTS patients attended study follow-up visits between January 2004 and January 2005, the time frame in which the VF conversion protocol was under way. A center-specific randomization schedule was used to determine the order of VF testing of the patient's study eye. The FT test and the SITA-Standard test were then obtained in the specified order. Recovery time was allowed between testing, with the amount dependent on the patient's assessment of readiness. The CIGTS protocol required reliable tests, based on scoring of fixation losses (criterion of Ͻ33%), false-positive and -negative errors (criterion of Ͻ33%), and the short-term fluctuation (SF) value (criterion, Յ4.0 dB). Because the SITA-Standard test does not produce an SF value, its reliability was based on the first three parameters. In two patients, pupil dilation was induced between the two VF tests, as indicated by the intertest pupil diameter being 4 mm disparate. These two patients' data are not included in this report, yielding n ϭ 243 with comparable VF test results. Both VF test results were scored according to the CIGTS VF scoring algorithm, 1,11 which assigns weights to points on the VF test's total deviation probability plot according to the extent of departure from normal values, as expressed by point-specific probabilities, which are empirically derived percentiles from the distributions of values at each of the 52 points from age-specific sets of normal subjects collected by the manufacturer. 2 The proprietary distributions are built into the VF test software and are not available for inspection. The probability at each of the 52 points is reported as no defect or P Յ 0.05, Յ 0.02, Յ 0.01, or Յ 0.005, meaning that the measured value at that point was at or below the respective percentile of the age-specific empiric distribution at that position in the field for normal subjects. A point is called defective if its probability is 0.05 or less and it has at least two neighboring points with probabilities of 0.05 or less in the same vertical hemifield (superior or inferior). A weight is assigned depending on the minimum depth of the defect at the given point and the two most defective neighboring points. A minimum defect of 0.05, 0.02, 0.01, or 0.005 is given a weight of 1, 2, 3, or 4, respectively. A point without two neighboring points all depressed to at least P Յ 0.05 is given a weight of 0. For example, a point at P Յ 0.01 with only two neighboring points of defect, both at P Յ 0.05, would receive a weight of 1. The weights for all 52 points in the field are summed, resulting in a value between 0 and 208 (52 ϫ 4). The sum is then scaled to a range of 0 to 20 (by dividing by 10.4), resulting in a score that is a nearly continuous measure of VF loss. Other Humphrey VF test parameters that are common to both testing procedures-test duration, pupil From the Departments of 1 Ophthalmology and Visual Sciences