Modeling and Analyzing Adaptive User-Centric Systems in Real-Time Maude

Pervasive user-centric applications are systems which are meant to sense the presence, mood, and intentions of users in order to optimize user comfort and performance. Building such applications requires not only state-of-the art techniques from artificial intelligence but also sound software engineering methods for facilitating modular design, runtime adaptation and verification of critical system requirements. In this paper we focus on high-level design and analysis, and use the algebraic rewriting language Real-Time Maude for specifying applications in a real-time setting. We propose a generic component-based approach for modeling pervasive user-centric systems and we show how to analyze and prove crucial properties of the system architecture through model checking and simulation. For proving time-dependent properties we use Metric Temporal Logic (MTL) and present analysis algorithms for model checking two subclasses of MTL formulas: time-bounded response and time-bounded safety MTL formulas. The underlying idea is to extend the Real-Time Maude model with suitable clocks, to transform the MTL formulas into LTL formulas over the extended specification, and then to use the LTL model checker of Maude. It is shown that these analyses are sound and complete for maximal time sampling. The approach is illustrated by a simple adaptive advertising scenario in which an adaptive advertisement display can react to actions of the users in front of the display.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Weighted Modal Transition Systems

Specification theories as a tool in model-driven development processes of component-based software systems have recently attracted a considerable attention. Current specification theories are however qualitative in nature, and therefore fragile in the sense that the inevitable approximation of systems by models, combined with the fundamental unpredictability of hardware platforms, makes it difficult to transfer conclusions about the behavior, based on models, to the actual system. Hence this approach is arguably unsuited for modern software systems. We propose here the first specification theory which allows to capture quantitative aspects during the refinement and implementation process, thus leveraging the problems of the qualitative setting. Our proposed quantitative specification framework uses weighted modal transition systems as a formal model of specifications. These are labeled transition systems with the additional feature that they can model optional behavior which may or may not be implemented by the system. Satisfaction and refinement is lifted from the well-known qualitative to our quantitative setting, by introducing a notion of distances between weighted modal transition systems. We show that quantitative versions of parallel composition as well as quotient (the dual to parallel composition) inherit the properties from the Boolean setting.Comment: Submitted to Formal Methods in System Desig

Interface Theories for (A)synchronously Communicating Modal I/O-Transition Systems

Interface specifications play an important role in component-based software development. An interface theory is a formal framework supporting composition, refinement and compatibility of interface specifications. We present different interface theories which use modal I/O-transition systems as their underlying domain for interface specifications: synchronous interface theories, which employ a synchronous communication schema, as well as a novel interface theory for asynchronous communication where components communicate via FIFO-buffers.Comment: In Proceedings FIT 2010, arXiv:1101.426

A Geometric Variational Approach to Bayesian Inference

We propose a novel Riemannian geometric framework for variational inference in Bayesian models based on the nonparametric Fisher-Rao metric on the manifold of probability density functions. Under the square-root density representation, the manifold can be identified with the positive orthant of the unit hypersphere in L2, and the Fisher-Rao metric reduces to the standard L2 metric. Exploiting such a Riemannian structure, we formulate the task of approximating the posterior distribution as a variational problem on the hypersphere based on the alpha-divergence. This provides a tighter lower bound on the marginal distribution when compared to, and a corresponding upper bound unavailable with, approaches based on the Kullback-Leibler divergence. We propose a novel gradient-based algorithm for the variational problem based on Frechet derivative operators motivated by the geometry of the Hilbert sphere, and examine its properties. Through simulations and real-data applications, we demonstrate the utility of the proposed geometric framework and algorithm on several Bayesian models

Candida albicans β-Glucan Differentiates Human Monocytes Into a Specific Subset of Macrophages

β-Glucan derived from cell walls of Candida albicans is a potent immune modulator. It has been shown to induce trained immunity in monocytes via epigenetic and metabolic reprogramming and to protect from lethal sepsis if applied prior to infection. Since β-glucan-trained monocytes have not been classified within the system of mononuclear phagocytes we analyzed these cells metabolically, phenotypically and functionally with a focus on monocyte-to-macrophage differentiation and compared them with naïve monocytes and other types of monocyte-derived cells such as classically (M1) or alternatively (M2) activated macrophages and monocyte-derived dendritic cells (moDCs). We show that β-glucan inhibits spontaneous apoptosis of monocytes independent from autocrine or paracrine M-CSF release and stimulates monocyte differentiation into macrophages. β-Glucan-differentiated macrophages exhibit increased cell size and granularity and enhanced metabolic activity when compared to naïve monocytes. Although β-glucan-primed cells expressed markers of alternative activation and secreted higher levels of IL-10 after lipopolysaccharide (LPS), their capability to release pro-inflammatory cytokines and to kill bacteria was unaffected. Our data demonstrate that β-glucan priming induces a population of immune competent long-lived monocyte-derived macrophages that may be involved in immunoregulatory processes

Use of the GlideScope®-Ranger for pre-hospital intubations by anaesthesia trained emergency physicians – an observational study

Background: Pre-hospital endotracheal intubation is more difficult than in the operating room (OR). Therefore, enhanced airway management devices such as video laryngoscopes may be helpful to improve the success rate of pre-hospital intubation. We describe the use of the Glidescope®-Ranger (GS-R) as an alternative airway tool used at the discretion of the emergency physician (EP) in charge. Methods: During a 3.5 year period, the GS-R was available to be used either as the primary or backup tool for pre-hospital intubation by anaesthesia trained EP with limited expertise using angulated videolaryngoscopes. Results: During this period 672 patients needed pre-hospital intubation of which the GS-R was used in 56 cases. The overall GS-R success rate was 66 % (range of 34–100 % among EP). The reasons for difficulties or failure included inexperience of the EP with the GS-R, impaired view due to secretion, vomitus, blood or the inability to see the screen in very bright environment due to sunlight. Conclusion: Special expertise and substantial training is needed to successfully accomplish tracheal intubation with the GS-R in the pre-hospital setting. Providers inexperienced with DL as well as video-assisted intubation should not expect to be able to perform tracheal intubation easily just because a videolaryngoscope is available. Additionally, indirect laryngoscopy might be difficult or even impossible to achieve in the pre-hospital setting due to impeding circumstances such as blood, secretions or bright sun-light. Therefore, videolaryngoscopes, here the GS-R, should not be considered as the “Holy Grail” of endotracheal intubation, neither for the experts nor for inexperienced providers. Electronic supplementary material The online version of this article (doi:10.1186/s12873-016-0069-2) contains supplementary material, which is available to authorized users

Flavour Physics in the Soft Wall Model

We extend the description of flavour that exists in the Randall-Sundrum (RS) model to the soft wall (SW) model in which the IR brane is removed and the Higgs is free to propagate in the bulk. It is demonstrated that, like the RS model, one can generate the hierarchy of fermion masses by localising the fermions at different locations throughout the space. However, there are two significant differences. Firstly the possible fermion masses scale down, from the electroweak scale, less steeply than in the RS model and secondly there now exists a minimum fermion mass for fermions sitting towards the UV brane. With a quadratic Higgs VEV, this minimum mass is about fifteen orders of magnitude lower than the electroweak scale. We derive the gauge propagator and despite the KK masses scaling as $m_n^2\sim n$, it is demonstrated that the coefficients of four fermion operators are not divergent at tree level. FCNC's amongst kaons and leptons are considered and compared to calculations in the RS model, with a brane localised Higgs and equivalent levels of tuning. It is found that since the gauge fermion couplings are slightly more universal and the SM fermions typically sit slightly further towards the UV brane, the contributions to observables such as $\epsilon_K$ and $\Delta m_K$, from the exchange of KK gauge fields, are significantly reduced.Comment: 33 pages, 15 figures, 5 tables; v2: references added; v3: modifications to figures 4,5 and 6. version to appear in JHE

Exact score distribution computation for ontological similarity searches

<p>Abstract</p> <p>Background</p> <p>Semantic similarity searches in ontologies are an important component of many bioinformatic algorithms, e.g., finding functionally related proteins with the Gene Ontology or phenotypically similar diseases with the Human Phenotype Ontology (HPO). We have recently shown that the performance of semantic similarity searches can be improved by ranking results according to the probability of obtaining a given score at random rather than by the scores themselves. However, to date, there are no algorithms for computing the exact distribution of semantic similarity scores, which is necessary for computing the exact <it>P</it>-value of a given score.</p> <p>Results</p> <p>In this paper we consider the exact computation of score distributions for similarity searches in ontologies, and introduce a simple null hypothesis which can be used to compute a <it>P</it>-value for the statistical significance of similarity scores. We concentrate on measures based on Resnik's definition of ontological similarity. A new algorithm is proposed that collapses subgraphs of the ontology graph and thereby allows fast score distribution computation. The new algorithm is several orders of magnitude faster than the naive approach, as we demonstrate by computing score distributions for similarity searches in the HPO. It is shown that exact <it>P</it>-value calculation improves clinical diagnosis using the HPO compared to approaches based on sampling.</p> <p>Conclusions</p> <p>The new algorithm enables for the first time exact <it>P</it>-value calculation via exact score distribution computation for ontology similarity searches. The approach is applicable to any ontology for which the annotation-propagation rule holds and can improve any bioinformatic method that makes only use of the raw similarity scores. The algorithm was implemented in Java, supports any ontology in OBO format, and is available for non-commercial and academic usage under: <url>https://compbio.charite.de/svn/hpo/trunk/src/tools/significance/</url></p

History of Galaxy Interactions and their Impact on Star Formation over the Last 7 Gyr from GEMS

We perform a comprehensive estimate of the frequency of galaxy mergers and their impact on star formation over z~0.24--0.80 (lookback time T_b~3--7 Gyr) using 3698 (M*>=1e9 Msun) galaxies with GEMS HST, COMBO-17, and Spitzer data. Our results are: (1) Among 790 high mass (M*>=2.5e10 Msun) galaxies, the visually-based merger fraction over z~0.24--0.80, ranges from 9%+-5% to 8%+-2%. Lower limits on the major and minor merger fractions over this interval range from 1.1% to 3.5%, and 3.6% to 7.5%, respectively. This is the first approximate empirical estimate of the frequency of minor mergers at z<1. For a visibility timescale of ~0.5 Gyr, it follows that over T_b~3--7 Gyr, ~68% of high mass systems have undergone a merger of mass ratio >1/10, with ~16%, 45%, and 7% of these corresponding respectively to major, minor, and ambiguous `major or minor' mergers. The mean merger rate is a few x 1e-4 Gyr-1 Mpc-3. (2) We compare the empirical merger fraction and rate for high mass galaxies to a suite of Lambda CDM-based models: halo occupation distribution models, semi-analytic models, and hydrodynamic SPH simulations. We find qualitative agreement between observations and models such that the (major+minor) merger fraction or rate from different models bracket the observations, and show a factor of five dispersion. Near-future improvements can now start to rule out certain merger scenarios. (3) Among ~3698 M*>=1e9 Msun galaxies, we find that the mean SFR of visibly merging systems is only modestly enhanced compared to non-interacting galaxies over z~0.24--0.80. Visibly merging systems only account for less than 30% of the cosmic SFR density over T_b~3--7 Gyr. This suggests that the behavior of the cosmic SFR density over the last 7 Gyr is predominantly shaped by non-interacting galaxies.Comment: Accepted for Publication in the Astrophysical Journal. 17 pages of text, 21 figures, 3 tables. Uses emulateapj5.st