Time-energy correlations in solar flare occurrence

The existence of time-energy correlations in flare occurrence is still an open and much debated problem. This study addresses the question whether statistically significant correlations are present between energies of successive flares as well as energies and waiting times. We analyze the GOES catalog with a statistical approach based on the comparison of the real catalog with a reshuffled one where energies are decorrelated. This analysis reduces the effect of background activity and is able to reveal the role of obscuration. We show the existence of non-trivial correlations between waiting times and energies, as well as between energies of subsequent flares. More precisely, we find that flares close in time tend to have the second event with large energy. Moreover, after large flares the flaring rate significantly increases, together with the probability of other large flares. Results suggest that correlations between energies and waiting times are a physical property and not an effect of obscuration. These findings could give important information on the mechanisms for energy storage and release in the solar corona

Chemical considerations in the interpretation of toxicity of metals in soil

Extended abstract.Enzo Lombi, Mike J. McLaughlin and Rebecca E. Hamo

New perspectives in the pathophysiology and treatment of affective disorders: the role of melatonin and serotonin

Более 40 лет в области исследований патогенеза депрессии и разработки адекватных препаратов для эффективной терапии этого расстройства доминировала моноаминовая гипотеза, предполагающая в основе депрессии дисбаланс функции серотонина, норадреналина и, возможно, дофамина. Хотя эти моноаминовые нейротрансмиттеры, роль которых обсуждается в данной публикации, несомненно, участвуют в патогенезе депрессии, их дефицит — лишь часть истории, так как для полного объяснения механизмов депрессии необходимо также учитывать другие нарушения вне рамок дисбаланса моноаминов. Существует явная потребность в более эффективных препаратах с улучшенной переносимостью и более быстрым действием. Разработка новых антидепрессантов на основании механизмов, не связанных с моноаминовой гипотезой, представляется более перспективной. Сегодня повышенное внимание уделяется связи аффективных расстройств, включая и депрессию, с аномальными изменениями в циркадианных ритмах. В этой публикации рассматривается роль мелатонина и его рецепторов при депрессии, а также данные по недавно разработанному антидепрессанту с подтвержденной клинической эффективностью — Вальдоксану. Этот препарат, обладающий свойствами агониста мелатонина и антагониста 5-НТ2С-рецепторов, является предвестником нового концептуального подхода к терапии депрессии

934-28 Sensitivity and Specificity of Angiographic Markers for Thrombus: A Prospective Comparison with Angioscopy

The limitations of angiography for the detection of intracoronary thrombus are well recognized. Between November 1991 and July 1994, we performed 402 angioscopy procedures in 225 vessels in 202 patients, with the Image-Cath (Baxter).We performed a prospective study in 190 of these patients, who had an interpretable angioscopy performed just before PTCA to determine the sensitivity and specificity of predetermined angiographic criteria that are considered to be indicative of the presence of intracoronary thrombus. Angiographically verified thrombus was used as the gold standard for comparison. Lesions were classified on angiography (2 orthogonal views) by independent observers. The presence of an intraluminal filling defect, of overhanging edges, of haziness, or of ulceration were noted. The characteristic ulceration was not mutually exclusive of the other 3 characteristics.Of 15 filling defects on angiography 14 (93%) had thrombus on angiography; in the 23 lesions with overhanging edges 19 (83%) had thrombus on angioscopy; in the 27 ulcerated lesions 21 (78%) had angioscopic thrombus; in the 6 lesions that were hazy on angiography 5 had angioscopic thrombus.AngioscopyThrombus+Thrombus-AngiographyThrombus+4512Thrombus-4093In our model, using 5 prespecified angiographic characteristics, angiography had high specificity (89%) but relatively low sensitivity (53%) for the detection of thrombus compared to angioscopy

Investigation of grain orientations of melt-textured HTSC with addition of uranium oxide, Y2O3 and Y2BaCuO5

Local grain orientations were studied in melt-textured YBCO samples processed with various amounts of depleted uranuim oxide (DU) and Y 2O3 by means of electron backscatter diffraction (EBSD) analysis. The addition of DU leads to the formation of Ucontaining nanoparticles (Y2Ba4CuUOx) with sizes of around 200 nm, embedded in the superconducting Y-123 matrix. The orientation of the Y 2BaCuO5 (Y-211) particles, which are also present in the YBCO bulk microstructure, is generally random as is the case in other melttextured Y-123 samples. The presence of Y-211 particles, however, also affects the orientation of the Y-123 matrix in these samples

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

BACKGROUND: Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. METHODS: A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. RESULTS: We apply our approach to five malaria interventions under development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements. CONCLUSIONS: Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. This study highlights the role of mathematical models to support intervention development. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions

Virtual Reality and Programming by Demonstration: Teaching a Robot to Grasp a Dynamic Object by the Generalization of Human Demonstrations

Humans possess the ability to perform complex manipulations without the need to consciously perceive detailed motion plans. When a large number of trials and tests are required for techniques such as learning by imitation and programming by demonstration, the virtual reality approach provides an effective method. Indeed, virtual environments can be built economically and quickly, and can be automatically reinitialized. In the fields of robotics and virtual reality, this has now become commonplace. Rather than imitating human actions, our focus is to develop an intuitive and interactive method based on user demonstrations to create humanlike, autonomous behavior for a virtual character or robot. Initially, a virtual character is built via real-time virtual simulation in which the user demonstrates the task by controlling the virtual agent. The necessary data (position, speed, etc.) to accomplish the task are acquired in a Cartesian space during the demonstration session. These data are then generalized off-line by using a neural network with a back-propagation algorithm. The objective is to model a function that represents the studied task, and by so doing, to adapt the agent to deal with new cases. In this study, the virtual agent is a 6-DOF arm manipulator, Kuka Kr6, and the task is to grasp a ball thrown into its workspace. Our approach is to find a minimum number of necessary demonstrations while maintaining adequate task efficiency. Moreover, the relationship between the number of dimensions of the estimated function and the number of human trials is studied, depending on the evolution of the learning system

Evidence of triggered star formation in G327.3-0.6. Dust-continuum mapping of an infrared dark cloud with P-ArT\'eMiS

Aims. Expanding HII regions and propagating shocks are common in the environment of young high-mass star-forming complexes. They can compress a pre-existing molecular cloud and trigger the formation of dense cores. We investigate whether these phenomena can explain the formation of high-mass protostars within an infrared dark cloud located at the position of G327.3-0.6 in the Galactic plane, in between two large infrared bubbles and two HII regions. Methods: The region of G327.3-0.6 was imaged at 450 ? m with the CEA P-ArT\'eMiS bolometer array on the Atacama Pathfinder EXperiment telescope in Chile. APEX/LABOCA and APEX-2A, and Spitzer/IRAC and MIPS archives data were used in this study. Results: Ten massive cores were detected in the P-ArT\'eMiS image, embedded within the infrared dark cloud seen in absorption at both 8 and 24 ?m. Their luminosities and masses indicate that they form high-mass stars. The kinematical study of the region suggests that the infrared bubbles expand toward the infrared dark cloud. Conclusions: Under the influence of expanding bubbles, star formation occurs in the infrared dark areas at the border of HII regions and infrared bubbles.Comment: 4 page