Mightyl: A compositional translation from mitl to timed automata

Metric Interval Temporal Logic (MITL) was first proposed in the early 1990s as a specification formalism for real-time systems. Apart from its appealing intuitive syntax, there are also theoretical evidences that make MITL a prime real-time counterpart of Linear Temporal Logic (LTL). Unfortunately, the tool support for MITL verification is still lacking to this day. In this paper, we propose a new construction from MITL to timed automata via very-weak one-clock alternating timed automata. Our construction subsumes the well-known construction from LTL to Büchi automata by Gastin and Oddoux and yet has the additional benefits of being compositional and integrating easily with existing tools. We implement the construction in our new tool MightyL and report on experiments using Uppaal and LTSmin as back-ends

Type Ia Supernovae as Stellar Endpoints and Cosmological Tools

Empirically, Type Ia supernovae are the most useful, precise, and mature tools for determining astronomical distances. Acting as calibrated candles they revealed the presence of dark energy and are being used to measure its properties. However, the nature of the SN Ia explosion, and the progenitors involved, have remained elusive, even after seven decades of research. But now new large surveys are bringing about a paradigm shift --- we can finally compare samples of hundreds of supernovae to isolate critical variables. As a result of this, and advances in modeling, breakthroughs in understanding all aspects of SNe Ia are finally starting to happen.Comment: Invited review for Nature Communications. Final published version. Shortened, update

Autonomic neuropathy predisposes to rosiglitazone-induced vascular leakage in insulin-treated patients with type 2 diabetes: a randomised, controlled trial on thiazolidinedione-induced vascular leakage

Contains fulltext : 88447.pdf (publisher's version ) (Closed access)AIMS/HYPOTHESIS: The mechanism of fluid-related complications caused by thiazolidinedione derivatives is unclear. One potential mechanism is thiazolidinedione-induced arterial vasodilatation, which results in vascular leakage and a fall in blood pressure, normally counterbalanced by sympathetic activation and subsequent renal fluid retention. We hypothesised that thiazolidinedione-induced vascular leakage will be particularly prominent in patients with autonomic neuropathy. METHODS: We conducted a randomised, double-blind, placebo-controlled, parallel study in 40 patients with type 2 diabetes on insulin treatment recruited from a university medical centre. The randomisation was performed by a central office using a randomisation schedule. Both treatment groups, placebo (n = 21) and rosiglitazone (n = 19), were stratified for sex and level of autonomic neuropathy as assessed by Ewing score (or=2.5). We investigated the effects of 16 weeks of treatment with rosiglitazone 4 mg twice daily on vascular leakage (transcapillary escape rate of albumin, TERalb), body weight, extracellular volume and plasma volume. RESULTS: Thirty-nine patients were included in the analysis. In patients with high Ewing scores (n = 16), rosiglitazone increased TERalb significantly (DeltaTERalb: rosiglitazone +2.43 +/- 0.45%/h, placebo -0.11 +/- 0.15%/h, p = 0.002), while rosiglitazone had no effect in the patients with low Ewing scores (n = 23). Rosiglitazone-induced increases in TERalb and Ewing score at baseline were correlated (r = 0.65, p = 0.02). There was no correlation between Ewing score and rosiglitazone-induced changes in fluid variables. One subject was withdrawn from the study because of atrial fibrillation. CONCLUSIONS/INTERPRETATION: Rosiglitazone may increase vascular leakage in insulin-treated patients with type 2 diabetes with autonomic neuropathy. Autonomic neuropathy did not exaggerate rosiglitazone-induced fluid retention. Therefore, autonomic neuropathy should be considered as a risk factor for thiazolidinedione-induced oedema, not for thiazolidinedione-induced fluid retention. TRIAL REGISTRATION: ClinicalTrials.gov NCT00422955. FUNDING: GlaxoSmithKline.1 september 201

The Evolution of Compact Binary Star Systems

We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.Comment: 105 pages, 18 figure

Image perception and interpretation of abnormalities; can we believe our eyes? Can we do something about it?

The radiologist’s visual impression of images is transmitted, via non-visual means (the report), to the clinician. There are several complex steps from the perception of the images by the radiologist to the understanding of the impression by the clinician. With a process as complex as this, it is no wonder that errors in perception, cognition, interpretation, transmission and understanding are very common. This paper reviews the processes of perception and error generation and possible strategies for minimising them

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

The Effect of Interpersonal Psychotherapy and other Psychodynamic Therapies versus ‘Treatment as Usual’ in Patients with Major Depressive Disorder

Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Interpersonal psychotherapy and other psychodynamic therapies may be effective interventions for major depressive disorder, but the effects have only had limited assessment in systematic reviews.Cochrane systematic review methodology with meta-analysis and trial sequential analysis of randomized trials comparing the effect of psychodynamic therapies versus ‘treatment as usual’ for major depressive disorder. To be included the participants had to be older than 17 years with a primary diagnosis of major depressive disorder. Altogether, we included six trials randomizing a total of 648 participants. Five trials assessed ‘interpersonal psychotherapy’ and only one trial assessed ‘psychodynamic psychotherapy’. All six trials had high risk of bias. Meta-analysis on all six trials showed that the psychodynamic interventions significantly reduced depressive symptoms on the 17-item Hamilton Rating Scale for Depression (mean difference −3.12 (95% confidence interval −4.39 to −1.86;P<0.00001), no heterogeneity) compared with ‘treatment as usual’. Trial sequential analysis confirmed this result.We did not find convincing evidence supporting or refuting the effect of interpersonal psychotherapy or psychodynamic therapy compared with ‘treatment as usual’ for patients with major depressive disorder. The potential beneficial effect seems small and effects on major outcomes are unknown. Randomized trials with low risk of systematic errors and low risk of random errors are needed