Mass transfer and gas-liquid interface properties of single CO2 bubbles rising in tap water

To improve the mass transfer efficiency in many industrial applications better understanding of the mass transfer rate is required. High speed images of single CO2 bubbles rising in tap water were analysed to investigate the relationship between the mass transfer and properties of single bubbles. Transition to a lower mass transfer rate was shown to correspond with the transition from a mobile to an immobile bubble surface. This was indicated by the change in bubble rise velocity, bubble rise path and bubble shape. The presence of surfactants in untreated tap water appear to effect the transition point, particularly for bubbles with a smaller initial diameter and lower rise velocity

Venus Interior Structure Mission (VISM): Establishing a Seismic Network on Venus

Magellan radar data show the surface of Venus to contain a wide range of geologic features (large volcanoes, extensive rift valleys, etc.). Although networks of interconnecting zones of deformation are identified, a system of spreading ridges and subduction zones like those that dominate the tectonic style of the Earth do not appear to be present. In addition, the absence of a mantle low-viscosity zone suggests a strong link between mantle dynamics and the surface. As a natural follow-on to the Magellan mission, establishing a network of seismometers on Venus will provide detailed quantitative information on the large scale interior structure of the planet. When analyzed in conjunction with image, gravity, and topography information, these data will aid in constraining mechanisms that drive surface deformation

A functional analysis of two transdiagnostic, emotion-focused interventions on nonsuicidal self-injury

OBJECTIVE: Nonsuicidal self-injury (NSSI) is prevalent and associated with clinically significant consequences. Developing time-efficient and cost-effective interventions for NSSI has proven difficult given that the critical components for NSSI treatment remain largely unknown. The aim of this study was to examine the specific effects of mindful emotion awareness training and cognitive reappraisal, 2 transdiagnostic treatment strategies that purportedly address the functional processes thought to maintain self-injurious behavior, on NSSI urges and acts. METHOD: Using a counterbalanced, combined series (multiple baseline and data-driven phase change) aggregated single-case experimental design, the unique and combined impact of these 2 4-week interventions was evaluated among 10 diagnostically heterogeneous self-injuring adults. Ecological momentary assessment was used to provide daily ratings of NSSI urges and acts during all study phases. RESULTS: Eight of 10 participants demonstrated clinically meaningful reductions in NSSI; 6 participants responded to 1 intervention alone, whereas 2 participants responded after the addition of the alternative intervention. Group analyses indicated statistically significant overall effects of study phase on NSSI, with fewer NSSI urges and acts occurring after the interventions were introduced. The interventions were also associated with moderate to large reductions in self-reported levels of anxiety and depression, and large improvements in mindful emotion awareness and cognitive reappraisal skills. CONCLUSIONS: Findings suggest that brief mindful emotion awareness and cognitive reappraisal interventions can lead to reductions in NSSI urges and acts. Transdiagnostic, emotion-focused therapeutic strategies delivered in time-limited formats may serve as practical yet powerful treatment approaches, especially for lower-risk self-injuring individuals.Dr. Barlow receives royalties from Oxford University Press, Guilford Publications Inc., Cengage Learning, and Pearson Publishing. Grant monies for various projects come from the National Institute of Mental Health (F31MH100761), the National Institute of Alcohol and Alcohol Abuse, and Colciencias (Government of Columbia Initiative for Science, Technology, and Health Innovation). Consulting and honoraria during the past several years have come from the Agency for Healthcare Research and Quality, the Foundation for Informed Medical Decision Making, the Department of Defense, the Renfrew Center, the Chinese University of Hong Kong, Universidad Catolica de Santa Maria (Arequipa, Peru), New Zealand Psychological Association, Hebrew University of Jerusalem, Mayo Clinic, and various American Universities. (F31MH100761 - National Institute of Mental Health; National Institute of Alcohol and Alcohol Abuse; Colciencias (Government of Columbia Initiative for Science, Technology, and Health Innovation))Accepted manuscrip

Effects of Intravenous Ketamine on Explicit and Implicit Measures of Suicidality in Treatment-Resistant Depression

Background Intravenous ketamine has shown rapid antidepressant effects in early trials, making it a potentially attractive candidate for depressed patients at imminent risk of suicide. The Implicit Association Test (IAT), a performance-based measure of association between concepts, may have utility in suicide assessment. Methods Twenty-six patients with treatment-resistant depression were assessed using the suicidality item of the Montgomery-Asberg Depression Rating Scale (MADRS-SI) 2 hours before and 24 hours following a single subanesthetic dose of intravenous ketamine. Ten patients also completed IATs assessing implicit suicidal associations at comparable time points. In a second study, nine patients received thrice-weekly ketamine infusions over a 12-day period. Results Twenty-four hours after a single infusion, MADRS-SI scores were reduced on average by 2.08 points on a 0 to 6 scale (p < .001; d = 1.37), and 81% of patients received a rating of 0 or 1 postinfusion. Implicit suicidal associations were also reduced following ketamine (p = .003; d = 1.36), with reductions correlated across implicit and explicit measures. MADRS-SI reductions were sustained for 12 days by repeated-dose ketamine (p < .001; d = 2.42). Conclusions These preliminary findings support the premise that ketamine has rapid beneficial effects on suicidal cognition and warrants further study.Psycholog

Statistical Gaussian Model of Image Regions in Stochastic Watershed Segmentation

International audienceStochastic watershed is an image segmentation technique based on mathematical morphology which produces a probability density function of image contours. Estimated probabilities depend mainly on local distances between pixels. This paper introduces a variant of stochastic watershed where the probabilities of contours are computed from a Gaussian model of image regions. In this framework, the basic ingredient is the distance between pairs of regions, hence a distance between normal distributions. Hence several alternatives of statistical distances for normal distributions are compared, namely Bhattacharyya distance, Hellinger metric distance and Wasserstein metric distance

Droplet actuation induced by coalescence: experimental evidences and phenomenological modeling

This paper considers the interaction between two droplets placed on a substrate in immediate vicinity. We show here that when the two droplets are of different fluids and especially when one of the droplet is highly volatile, a wealth of fascinating phenomena can be observed. In particular, the interaction may result in the actuation of the droplet system, i.e. its displacement over a finite length. In order to control this displacement, we consider droplets confined on a hydrophilic stripe created by plasma-treating a PDMS substrate. This controlled actuation opens up unexplored opportunities in the field of microfluidics. In order to explain the observed actuation phenomenon, we propose a simple phenomenological model based on Newton's second law and a simple balance between the driving force arising from surface energy gradients and the viscous resistive force. This simple model is able to reproduce qualitatively and quantitatively the observed droplet dynamics

Creating a FACETS digital toolkit to promote quality of life of people with multiple sclerosis through Participatory Design

In this paper, we report on the first stages of creating a stand-alone digital toolkit focusing on the homework elements of FACETS (Fatigue: Applying Cognitive behavioural and Energy effectiveness Techniques to lifeStyle). FACETS is an evidence-based face-to-face fatigue management group programme for people with multiple sclerosis. This paper details the participatory design process from requirements elicitation to initial prototyping and how offline activities linked to each session have been mapped in the digitised solution (mobile app)

Effects of Intravenous Ketamine on Explicit and Implicit Measures of Suicidality in Treatment-Resistant Depression

Background Intravenous ketamine has shown rapid antidepressant effects in early trials, making it a potentially attractive candidate for depressed patients at imminent risk of suicide. The Implicit Association Test (IAT), a performance-based measure of association between concepts, may have utility in suicide assessment. Methods Twenty-six patients with treatment-resistant depression were assessed using the suicidality item of the Montgomery-Asberg Depression Rating Scale (MADRS-SI) 2 hours before and 24 hours following a single subanesthetic dose of intravenous ketamine. Ten patients also completed IATs assessing implicit suicidal associations at comparable time points. In a second study, nine patients received thrice-weekly ketamine infusions over a 12-day period. Results Twenty-four hours after a single infusion, MADRS-SI scores were reduced on average by 2.08 points on a 0 to 6 scale (p < .001; d = 1.37), and 81% of patients received a rating of 0 or 1 postinfusion. Implicit suicidal associations were also reduced following ketamine (p = .003; d = 1.36), with reductions correlated across implicit and explicit measures. MADRS-SI reductions were sustained for 12 days by repeated-dose ketamine (p < .001; d = 2.42). Conclusions These preliminary findings support the premise that ketamine has rapid beneficial effects on suicidal cognition and warrants further study.Psycholog

The Bregman chord divergence

Distances are fundamental primitives whose choice significantly impacts the performances of algorithms in machine learning and signal processing. However selecting the most appropriate distance for a given task is an endeavor. Instead of testing one by one the entries of an ever-expanding dictionary of {\em ad hoc} distances, one rather prefers to consider parametric classes of distances that are exhaustively characterized by axioms derived from first principles. Bregman divergences are such a class. However fine-tuning a Bregman divergence is delicate since it requires to smoothly adjust a functional generator. In this work, we propose an extension of Bregman divergences called the Bregman chord divergences. This new class of distances does not require gradient calculations, uses two scalar parameters that can be easily tailored in applications, and generalizes asymptotically Bregman divergences.Comment: 10 page

Bregman Voronoi Diagrams: Properties, Algorithms and Applications

The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define many variants of Voronoi diagrams depending on the class of objects, the distance functions and the embedding space. In this paper, we investigate a framework for defining and building Voronoi diagrams for a broad class of distance functions called Bregman divergences. Bregman divergences include not only the traditional (squared) Euclidean distance but also various divergence measures based on entropic functions. Accordingly, Bregman Voronoi diagrams allow to define information-theoretic Voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. We define several types of Bregman diagrams, establish correspondences between those diagrams (using the Legendre transformation), and show how to compute them efficiently. We also introduce extensions of these diagrams, e.g. k-order and k-bag Bregman Voronoi diagrams, and introduce Bregman triangulations of a set of points and their connexion with Bregman Voronoi diagrams. We show that these triangulations capture many of the properties of the celebrated Delaunay triangulation. Finally, we give some applications of Bregman Voronoi diagrams which are of interest in the context of computational geometry and machine learning.Comment: Extend the proceedings abstract of SODA 2007 (46 pages, 15 figures