Evolution of the Cathode Spot Distribution in an Axial Magnetic Field Controlled Vacuum Arc at Long Contact Gap

The distribution of cathode spots in a CuCr25 vacuum arc controlled by an axial magnetic field and ignited on the lateral surface of the cathode is investigated for long gap distances, from the processing of high-speed video images. The processing method includes also estimating the current carried by a single spot and reconstructing the distribution of the current density at the cathode. Various distributions depending partly on the arc current are described

Assessment on experimental bacterial biofilms and in clinical practice of the efficacy of sampling solutions for microbiological testing of endoscopes

International audienceOpinions differ on the value of microbiological testing of endoscopes, which varies according to the technique used. We compared the efficacy on bacterial biofilms of sampling solutions used for the surveillance of the contamination of endoscope channels. To compare efficacy, we used an experimental model of a 48-h Pseudomonas biofilm grown on endoscope internal tubing. Sampling of this experimental biofilm was performed with a Tween 80-lecithin-based solution, saline, and sterile water. We also performed a randomized prospective study during routine clinical practice in our hospital sampling randomly with two different solutions the endoscopes after reprocessing. Biofilm recovery expressed as a logarithmic ratio of bacteria recovered on bacteria initially present in biofilm was significantly more effective with the Tween 80-lecithin-based solution than with saline solution (P = 0.002) and sterile water (P = 0.002). There was no significant difference between saline and sterile water. In the randomized clinical study, the rates of endoscopes that were contaminated with the Tween 80-lecithin-based sampling solution and the saline were 8/25 and 1/25, respectively (P = 0.02), and the mean numbers of bacteria recovered were 281 and 19 CFU/100 ml (P = 0.001), respectively. In conclusion, the efficiency and therefore the value of the monitoring of endoscope reprocessing by microbiological cultures is dependent on the sampling solutions used. A sampling solution with a tensioactive action is more efficient than saline in detecting biofilm contamination of endoscopes

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Validity Arguments for Diagnostic Assessment Using Automated Writing Evaluation

Two examples demonstrate an argument-based approach to validation of diagnostic assessment using automated writing evaluation (AWE). Criterion ®, was developed by Educational Testing Service to analyze students’ papers grammatically, providing sentence-level error feedback. An interpretive argument was developed for its use as part of the diagnostic assessment process in undergraduate university English for academic purposes (EAP) classes. The Intelligent Academic Discourse Evaluator (IADE) was developed for use in graduate EAP university classes, where the goal was to help students improve their discipline-specific writing. The validation for each was designed to support claims about the intended purposes of the assessments. We present the interpretive argument for each and show some of the data that have been gathered as backing for the respective validity arguments, which include the range of inferences that one would make in claiming validity of the interpretations, uses, and consequences of diagnostic AWE-based assessments

Differentiating muscle damage from myocardial injury by meaans of the serum creatinine kinase (CK) isoenzyme MB mass measurement/total CK activity ratio

We immunoenzymometrically measured creatine kinase (CK) isoenzyme MB in extracts of myocardium and in homogenates of five different skeletal muscles. CK-MB concentrations in the former averaged 80.9 micrograms/g wet tissue; in the skeletal muscles it varied widely, being (e.g.) 25-fold greater in diaphragm than in psoas. CK-MB in skeletal muscles ranged from 0.9 to 44 ng/U of total CK; the mean for myocardium was 202 ng/U. In sera from 10 trauma and 36 burn patients without myocardial involvement, maximum ratios for CK-MB mass/total CK activity averaged 7 (SEM 1) ng/U and 18 (SEM 6) ng/U, respectively. Except for an infant (220 ng/U), the highest ratio we found for serum after muscular damage was 38 ng/U. In contrast, the mean maximum ratio determined in 23 cases of acute myocardial infarction exceeded 200 ng/U. Among seven determinations performed 8 to 32 h after onset of symptoms, each infarct patient demonstrated at least one ratio greater than or equal to 110 ng/U. Ratios observed after infarct were unrelated to treatment received during the acute phase. We propose a CK-MB/total CK ratio of 80 ng/U as the cutoff value for differentiating myocardial necrosis from muscular injury

A meta-analysis of effectiveness studies on computer technology-supported language learning

With the aim of summarizing years of research comparing pedagogies for second/foreign language teaching supported with computer technology and pedagogy not-supported by computer technology, a meta-analysis was conducted of empirical research investigating language outcomes. Thirty-seven studies yielding 52 effect sizes were included, following a search of literature from 1970 to 2006 and screening of studies based on stated criteria. The differences in research designs required subdivision of studies, but overall results favored the technology-supported pedagogy, with a small, but positive and statistically significant effect size. Second/foreign language instruction supported by computer technology was found to be at least as effective as instruction without technology, and in studies using rigorous research designs the CALL groups outperformed the non-CALL groups. The analyses of instructional conditions, characteristics of participants, and conditions of the research design did not provide reliable results because of the small number of effect sizes representing each group. The meta-analysis results provide an empirically-based response to the questions of whether or not technology-supported pedagogies enhance language learning, and the process of conducting the meta-analysis pointed to areas in research methodology that would benefit from attention in future research

Inverse chemical modeling and radiocarbon dating of palaeogroundwaters: The Tertiairy Ledo-paniselian aquifer in Flanders, Belgium.

Groundwater samples from the Ledo-Paniselian aquifer have been interpreted for chemical reaction patterns

Transformation Consistency Regularization – A Semi-supervised Paradigm for Image-to-Image Translation

Scarcity of labeled data has motivated the development of semi-supervised learning methods, which learn from large portions of unlabeled data alongside a few labeled samples. Consistency Regularization between model's predictions under different input perturbations, particularly has shown to provide state-of-the art results in a semi-supervised framework. However, most of these method have been limited to classification and segmentation applications. We propose Transformation Consistency Regularization, which delves into a more challenging setting of image-to-image translation, which remains unexplored by semi-supervised algorithms. The method introduces a diverse set of geometric transformations and enforces the model's predictions for unlabeled data to be invariant to those transformations. We evaluate the efficacy of our algorithm on three different applications: image colorization, denoising and super-resolution. Our method is significantly data efficient, requiring only around 10 - 20% of labeled samples to achieve similar image reconstructions to its fully-supervised counterpart. Furthermore, we show the effectiveness of our method in video processing applications, where knowledge from a few frames can be leveraged to enhance the quality of the rest of the movie