{\rtf1\ansi\ansicpg1250\deff0\deflang1038\deflangfe1038\deftab708{\fonttbl{\f0\froman\fprq2\fcharset238{\*\fname Times New Roman;}Times New Roman CE;}} \viewkind4\uc1\pard\f0\fs24 Automated analysis of off-line measured gamma-spectra using \scaps UniSampo\scaps0 gamma-ray spectrum analysis software including criterias for alarming systems \par }

2005 ◽  
Vol 264 (1) ◽  
pp. 239-241
Author(s):  
M. T. Nikkinen
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Christian S. Guay ◽  
Mariam Khebir ◽  
T. Shiva Shahiri ◽  
Ariana Szilagyi ◽  
Erin Elizabeth Cole ◽  
...  

Abstract Background Real-time automated analysis of videos of the microvasculature is an essential step in the development of research protocols and clinical algorithms that incorporate point-of-care microvascular analysis. In response to the call for validation studies of available automated analysis software by the European Society of Intensive Care Medicine, and building on a previous validation study in sheep, we report the first human validation study of AVA 4. Methods Two retrospective perioperative datasets of human microcirculation videos (P1 and P2) and one prospective healthy volunteer dataset (V1) were used in this validation study. Video quality was assessed using the modified Microcirculation Image Quality Selection (MIQS) score. Videos were initially analyzed with (1) AVA software 3.2 by two experienced investigators using the gold standard semi-automated method, followed by an analysis with (2) AVA automated software 4.1. Microvascular variables measured were perfused vessel density (PVD), total vessel density (TVD), and proportion of perfused vessels (PPV). Bland–Altman analysis and intraclass correlation coefficients (ICC) were used to measure agreement between the two methods. Each method’s ability to discriminate between microcirculatory states before and after induction of general anesthesia was assessed using paired t-tests. Results Fifty-two videos from P1, 128 videos from P2 and 26 videos from V1 met inclusion criteria for analysis. Correlational analysis and Bland–Altman analysis revealed poor agreement and no correlation between AVA 4.1 and AVA 3.2. Following the induction of general anesthesia, TVD and PVD measured using AVA 3.2 increased significantly for P1 (p < 0.05) and P2 (p < 0.05). However, these changes could not be replicated with the data generated by AVA 4.1. Conclusions AVA 4.1 is not a suitable tool for research or clinical purposes at this time. Future validation studies of automated microvascular flow analysis software should aim to measure the new software’s agreement with the gold standard, its ability to discriminate between clinical states and the quality thresholds at which its performance becomes unacceptable.


Author(s):  
Xu HongKun ◽  
Fang Fang ◽  
Ni Shijun ◽  
He Jianfeng ◽  
You Lei

Gamma-ray spectrum analysis was essential for radioactive environmental monitoring, and it had been widely used in many areas of nuclear engineering. However, for the low-energy region of gamma-ray spectrum, weak peaks were contained in the fast-decreasing background, so it was difficult to extract characteristic information from original spectra. In order to get a better analytic result based on wavelet methods in frequency domain, we had processed the gamma-ray spectrometer data of Chang’E-1 and well extracted some useful information of spectral characteristic peaks. Then, we preliminarily mapped the distribution of net peak counts for potassium on lunar surface, which indirectly reflected the distribution of elemental abundance. At last, we compared our analytic result with that of Apollo and Lunar Prospector and found some consistencies and differences.


2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S79-S79
Author(s):  
Noelle Warfford ◽  
Gregory J Meyer ◽  
Emily T O’Gorman ◽  
Joshua J Eblin ◽  
Joni L Mihura

Abstract Background Research is increasingly pointing toward the need for a dimensional, rather than categorical, conceptualization of psychopathology. This is particularly true within the literature on psychosis and related disorders. Taking a dimensional approach to conceptualizing psychosis requires deconstructing its components in assessment. The Rorschach Performance Assessment System (R-PAS) contains meta-analytically supported scales with international norms that are used to categorically rate signs of disordered thinking and perceptions in individuals’ responses to the Rorschach inkblots. Recently, a new dimensionalized set of scales called the Scales of Problematic Communication and Thinking (SPCT) have been developed for R-PAS with three main components: Disturbed and Confusing Communication, Illogical Verbal Justification, and Incongruous Perceptual Combinations. Research also suggests that linguistic measures of speech cohesion can be used to successfully predict conversion to psychosis in clinical high-risk patients and may be more related to stable neurocognitive deficits than clinical measures of disorganized speech. Coh-Metrix, an automated speech analysis software, provides over 100 specific measures of linguistic cohesion, such as connectivity, syntax simplicity, and referential cohesion. The purpose of this presentation is twofold: (a) to report recent findings showing the SPCT provides incremental validity over the traditional R-PAS measure of disordered thinking in predicting clinician ratings of disorganized thinking on the PANSS and (b) to determine if Coh-Metrix measures of linguistic cohesion provide incremental validity to SPCT ratings in predicting these PANSS ratings. Methods R-PAS protocols from a maximum-security inpatient forensic hospital (N = 91) aged 19 to 80 years (M=40) and predominantly male (89%) were coded for thinking and perceptual disturbances using the R-PAS traditional measure of disordered thinking and the 6-point dimensional SPCT measure. The patients’ primary clinician provided PANSS ratings. Protocols will be coded for speech cohesion using 15 indices from the automated speech analysis software Coh-Metrix, which were chosen based on a literature review. Results Interrater reliability was excellent for the SPCT ratings (ICC = 0.97) and good for the PANSS clinician ratings (ICC = 0.71). In a previous study, SPCT ratings showed significant associations with the clinician ratings of disorganized thinking on the PANSS (r = 0.42, p &lt; 0.01, N = 90); hierarchical regression analyses demonstrated incremental validity over the traditional R-PAS measure of disordered thinking (ΔR = 0.28, p &lt; 0.01). Using hierarchical regression analyses, the Coh-Metrix indices of cohesion are predicted to provide incremental validity to the SPCT ratings. Discussion The SPCT shows promise as a reliable and valid dimensionalized measure for assessing the continuum of clear thinking to psychosis-level disturbances. The measures of linguistic cohesion provided by Coh-Metrix have the potential to offer clinicians a quick, efficient, and objective method for assessing disorganized thinking. The R-PAS international norms are currently being coded for SPCT and, if Coh-Metrix measures provide incremental validity, will be coded for these measures as well. Using these measures in combination with SPCT ratings can provide clinicians with a clearer understanding of this significant component of psychosis.


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