Inductive Proof Outlines for Monitors in Java

Abstract. The research concerning Java’s semantics and proof theory has mainly focussed on various aspects of sequential sub-languages. Java, however, integrates features of a class-based object-oriented language with the notion of multi-threading, where multiple threads can concurrently execute and exchange information via shared instance variables. Furthermore, each object can act as a monitor to assure mutual exclusion or to coordinate between threads. In this paper we present a sound and relatively complete assertional proof system for Java’s monitor concept, which generates verification conditions for a concurrent sublanguage JavaMT of Java. This work extends previous results by incorporating Java’s monitor methods

Observations of Coronal Mass Ejections with the Coronal Multichannel Polarimeter

The Coronal Multichannel Polarimeter (CoMP) measures not only the polarization of coronal emission, but also the full radiance profiles of coronal emission lines. For the first time, CoMP observations provide high-cadence image sequences of the coronal line intensity, Doppler shift and line width simultaneously in a large field of view. By studying the Doppler shift and line width we may explore more of the physical processes of CME initiation and propagation. Here we identify a list of CMEs observed by CoMP and present the first results of these observations. Our preliminary analysis shows that CMEs are usually associated with greatly increased Doppler shift and enhanced line width. These new observations provide not only valuable information to constrain CME models and probe various processes during the initial propagation of CMEs in the low corona, but also offer a possible cost-effective and low-risk means of space weather monitoring.Comment: 6 figures. Will appear in the special issue of Coronal Magnetism, Sol. Phy

Functional diversity of chemokines and chemokine receptors in response to viral infection of the central nervous system.

Encounters with neurotropic viruses result in varied outcomes ranging from encephalitis, paralytic poliomyelitis or other serious consequences to relatively benign infection. One of the principal factors that control the outcome of infection is the localized tissue response and subsequent immune response directed against the invading toxic agent. It is the role of the immune system to contain and control the spread of virus infection in the central nervous system (CNS), and paradoxically, this response may also be pathologic. Chemokines are potent proinflammatory molecules whose expression within virally infected tissues is often associated with protection and/or pathology which correlates with migration and accumulation of immune cells. Indeed, studies with a neurotropic murine coronavirus, mouse hepatitis virus (MHV), have provided important insight into the functional roles of chemokines and chemokine receptors in participating in various aspects of host defense as well as disease development within the CNS. This chapter will highlight recent discoveries that have provided insight into the diverse biologic roles of chemokines and their receptors in coordinating immune responses following viral infection of the CNS

Origins of the Ambient Solar Wind: Implications for Space Weather

The Sun's outer atmosphere is heated to temperatures of millions of degrees, and solar plasma flows out into interplanetary space at supersonic speeds. This paper reviews our current understanding of these interrelated problems: coronal heating and the acceleration of the ambient solar wind. We also discuss where the community stands in its ability to forecast how variations in the solar wind (i.e., fast and slow wind streams) impact the Earth. Although the last few decades have seen significant progress in observations and modeling, we still do not have a complete understanding of the relevant physical processes, nor do we have a quantitatively precise census of which coronal structures contribute to specific types of solar wind. Fast streams are known to be connected to the central regions of large coronal holes. Slow streams, however, appear to come from a wide range of sources, including streamers, pseudostreamers, coronal loops, active regions, and coronal hole boundaries. Complicating our understanding even more is the fact that processes such as turbulence, stream-stream interactions, and Coulomb collisions can make it difficult to unambiguously map a parcel measured at 1 AU back down to its coronal source. We also review recent progress -- in theoretical modeling, observational data analysis, and forecasting techniques that sit at the interface between data and theory -- that gives us hope that the above problems are indeed solvable.Comment: Accepted for publication in Space Science Reviews. Special issue connected with a 2016 ISSI workshop on "The Scientific Foundations of Space Weather." 44 pages, 9 figure

The variation of geomagnetic storm duration with intensity

Variability in the near-Earth solar wind conditions can adversely affect a number of ground- and space-based technologies. Such space-weather impacts on ground infrastructure are expected to increase primarily with geomagnetic storm intensity, but also storm duration, through time-integrated effects. Forecasting storm duration is also necessary for scheduling the resumption of safe operating of affected infrastructure. It is therefore important to understand the degree to which storm intensity and duration are correlated. The long-running, global geomagnetic disturbance index, aa , has recently been recalibrated to account for the geographic distribution of the component stations. We use this aaH index to analyse the relationship between geomagnetic storm intensity and storm duration over the past 150 years, further adding to our understanding of the climatology of geomagnetic activity. Defining storms using a peak-above-threshold approach, we find that more intense storms have longer durations, as expected, though the relationship is nonlinear. The distribution of durations for a given intensity is found to be approximately log-normal. On this basis, we provide a method to probabilistically predict storm duration given peak intensity, and test this against the aaH dataset. By considering the average profile of storms with a superposed-epoch analysis, we show that activity becomes less recurrent on the 27-day timescale with increasing intensity. This change in the dominant physical driver, and hence average profile, of geomagnetic activity with increasing threshold is likely the reason for the nonlinear behaviour of storm duration