Symbolic Reachability Analysis of B through ProB and LTSmin

We present a symbolic reachability analysis approach for B that can provide a significant speedup over traditional explicit state model checking. The symbolic analysis is implemented by linking ProB to LTSmin, a high-performance language independent model checker. The link is achieved via LTSmin's PINS interface, allowing ProB to benefit from LTSmin's analysis algorithms, while only writing a few hundred lines of glue-code, along with a bridge between ProB and C using ZeroMQ. ProB supports model checking of several formal specification languages such as B, Event-B, Z and TLA. Our experiments are based on a wide variety of B-Method and Event-B models to demonstrate the efficiency of the new link. Among the tested categories are state space generation and deadlock detection; but action detection and invariant checking are also feasible in principle. In many cases we observe speedups of several orders of magnitude. We also compare the results with other approaches for improving model checking, such as partial order reduction or symmetry reduction. We thus provide a new scalable, symbolic analysis algorithm for the B-Method and Event-B, along with a platform to integrate other model checking improvements via LTSmin in the future

A 5 item version of the Compliance Questionnaire for Rheumatology (CQR5) successfully identifies low adherence to DMARDs

© 2013 Hughes et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedTaking DMARDs as prescribed is an essential part of self-management for patients with Rheumatoid Arthritis. To date, the Compliance Questionnaire for Rheumatology (CQR) is the only self-report adherence measure created specifically for and validated in rheumatic diseases. However, the factor structure of the CQR has not been reported and it can be considered lengthy at 19 items. The aim of this study was to test the factor structure of the CQR and reduce the number of items whilst retaining robust explanation of non-adherence to DMARDs. Such a reduction would increase the clinical utility of the scale, to identify patients with sub-optimal adherence to DMARDs in the clinic as well as for research purposes.Peer reviewe

The Photosynthetic Function of Manganese and Chloride

Author Institution: Charles F. Kettering Foundation, Yellow Springs, Ohi

On the Linearization of the First and Second Painleve' Equations

We found Fuchs--Garnier pairs in 3X3 matrices for the first and second Painleve' equations which are linear in the spectral parameter. As an application of our pairs for the second Painleve' equation we use the generalized Laplace transform to derive an invertible integral transformation relating two its Fuchs--Garnier pairs in 2X2 matrices with different singularity structures, namely, the pair due to Jimbo and Miwa and the one found by Harnad, Tracy, and Widom. Together with the certain other transformations it allows us to relate all known 2X2 matrix Fuchs--Garnier pairs for the second Painleve' equation with the original Garnier pair.Comment: 17 pages, 2 figure

Development of new metrics to assess and quantify climatic drivers of extreme event driven Arctic browning

Rapid climate change in Arctic regions is resulting in more frequent extreme climatic events. These can cause large-scale vegetation damage, and are therefore among key drivers of declines in biomass and productivity (or “browning”) observed across Arctic regions in recent years. Extreme events which cause browning are driven by multiple interacting climatic variables, and are defined by their ecological impact – most commonly plant mortality. Quantifying the climatic causes of these multivariate, ecologically defined events is challenging, and so existing work has typically determined the climatic causes of browning events on a case-by-case basis in a descriptive, unsystematic manner. While this has allowed development of important qualitative understanding of the mechanisms underlying extreme event driven browning, it cannot definitively link browning to specific climatic variables, or predict how changes in these variables will influence browning severity. It is therefore not yet possible to determine how extreme events will influence ecosystem responses to climate change across Arctic regions. To address this, novel, process-based climate metrics that can be used to quantify the conditions and interactions that drive the ecological responses defining common extreme events were developed using publicly available snow depth and air temperature data (two of the main climate variables implicated in browning). These process-based metrics explained up to 63% of variation in plot-level Normalised Difference Vegetation Index (NDVI) at sites within areas affected by extreme events across boreal and sub-Arctic Norway. This demonstrates potential to use simple metrics to assess the contribution of extreme events to changes in Arctic biomass and productivity at regional scales. In addition, scaling up these metrics across the Norwegian Arctic region resulted in significant correlations with remotely-sensed NDVI, and provided much-needed insights into how climatic variables interact to determine the severity of browning across Arctic regions

Arctic browning: Impacts of extreme climatic events on heathland ecosystem CO2 fluxes.

Extreme climatic events are among the drivers of recent declines in plant biomass and productivity observed across Arctic ecosystems, known as "Arctic browning." These events can cause landscape-scale vegetation damage and so are likely to have major impacts on ecosystem CO2 balance. However, there is little understanding of the impacts on CO2 fluxes, especially across the growing season. Furthermore, while widespread shoot mortality is commonly observed with browning events, recent observations show that shoot stress responses are also common, and manifest as high levels of persistent anthocyanin pigmentation. Whether or how this response impacts ecosystem CO2 fluxes is not known. To address these research needs, a growing season assessment of browning impacts following frost drought and extreme winter warming (both extreme climatic events) on the key ecosystem CO2 fluxes Net Ecosystem Exchange (NEE), Gross Primary Productivity (GPP), ecosystem respiration (Reco ) and soil respiration (Rsoil ) was carried out in widespread sub-Arctic dwarf shrub heathland, incorporating both mortality and stress responses. Browning (mortality and stress responses combined) caused considerable site-level reductions in GPP and NEE (of up to 44%), with greatest impacts occurring at early and late season. Furthermore, impacts on CO2 fluxes associated with stress often equalled or exceeded those resulting from vegetation mortality. This demonstrates that extreme events can have major impacts on ecosystem CO2 balance, considerably reducing the carbon sink capacity of the ecosystem, even where vegetation is not killed. Structural Equation Modelling and additional measurements, including decomposition rates and leaf respiration, provided further insight into mechanisms underlying impacts of mortality and stress on CO2 fluxes. The scale of reductions in ecosystem CO2 uptake highlights the need for a process-based understanding of Arctic browning in order to predict how vegetation and CO2 balance will respond to continuing climate change