Extreme-ultraviolet emission lines of S X in solar flare and active region spectra

R-matrix calculations of electron impact excitation rates in N- like S x are used to derive theoretical emission-line intensity ratios involving 2s(2)2p(3)-2s2p(4) transitions in the 189-265 Angstrom wavelength range. A comparison of these with observational data for solar flares and active regions, obtained with the Naval Research Laboratory's S082A spectrograph on board Skylab and the Solar EUV Rocket Telescope and Spectrograph, reveals that many of the S x lines in the spectra are badly blended with emission features from other species. However, the intensity ratios I(228.70 Angstrom)/I(264.24 Angstrom) and I(228.70 Angstrom)/I(259.49 Angstrom) are found to provide useful electron density diagnostics for flares, although the latter cannot be employed for active regions, because of blending of the 259.49 Angstrom line with an unidentified transition in these solar features.

A comparison of theoretical MgVI emission line strengths with active-region observations from serts

R-matrix calculations of electron impact excitation rates in N-like Mg vi are used to derive theoretical electron-density-sensitive emission line ratios involving 2s(2)2p(3)-2s2p(4) transitions in the 269-403 Angstrom wavelength range. A comparison of these with observations of a solar active region, obtained during the 1989 flight of the Solar EUV Rocket Telescope and Spectrograph (SERTS), reveals good agreement between theory and observation for the 2s(2)2p(3) S-4-2s2p(4) P-4 transitions at 399.28, 400.67, and 403.30 Angstrom, and the 2s(2)2p(3) P-2-2s2p(4) D-2 lines at 387.77 and 387.97 Angstrom. However, intensities for the other lines attributed to Mg vi in this spectrum by various authors do not match the present theoretical predictions. We argue that these discrepancies are not due to errors in the adopted atomic data, as previously suggested, but rather to observational uncertainties or mis-identifications. Some of the features previously identified as Mg vi lines in the SERTS spectrum, such as 291.36 and 293.15 Angstrom, are judged to be noise, while others (including 349.16 Angstrom) appear to be blended.

S XI emission lines in active region spectra obtained with the Solar EUV Rocket Telescope and Spectrograph (SERTS)

Theoretical electron density sensitive emission line ratios involving a total of eleven 2s(2)2p(2)-2s2p(3) transitions in S XI between 187 and 292 Angstrom are presented. A comparison of these with solar active region observations obtained during rocket flights by the Solar EUV Rocket Telescope and Spectrograph (SERTS) reveals generally good agreement between theory and experiment. However, the 186.87 Angstrom line is masked by fairly strong Fe XII emission at the same wavelength, while 239.83 Angstrom is blended with an unknown feature, and 285.58 Angstrom is blended with possibly N IV 285.56 Angstrom. In addition, the 191.23 Angstrom line appears to be more seriously blended with an Fe XIII feature than previously believed. The presence of several new S XI lines is confirmed in the SERTS spectra, at wavelengths of 188.66, 247.14 and 291.59 Angstrom, in excellent agreement with laboratory measurements. In particular, the detection of the 2s(2)2p(2) P- 3(1) -2s2p(3) P-3(0,1) transitions at 242.91 Angstrom is the first time (to our knowledge) that this feature has been identified in the solar spectrum. The potential usefulness of the S XI line ratios as electron density diagnostics for the solar transition region and corona is briefly discussed.

Identification in the Ca II K spectral region of sharp-lined B- type stars

Previous Call K observations of the B-type star HD 83206 have revealed putative high-velocity interstellar clouds (HVCs) at Local Standard of Rest (LSR) velocities of -80 and -110 km s(- 1). Similar results were also found for the sightline towards HD135485. In this article, we show that these absorption lines are in fact due tr, stellar SII features. As the Call K absorption line in B-type stars is often used to assess the presence and distance of HVCs. we also present a very high quality spectrum of HD 83206 in the Ca II K region (similar to+/-4 Angstrom or +/-300 km s(-1)), so that in the future confusion between stellar lines and HVC features may be avoided.

High-frequency oscillations in a solar active region coronal loop

The Solar Eclipse Corona Imaging System (SECIS) was used to record high-cadence observations of the solar corona during the total solar eclipse of 1999 August 11. During the 2 min 23.5 s of totality, 6364 images were recorded simultaneously in each of the two channels: a white light channel, and the Fe xiv (5303 Angstrom) 'green line' channel (T similar to2 MK). Here we report initial results from the SECIS experiment, including the discovery of a 6-s intensity oscillation in an active region coronal loop.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.

An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.