2,399 research outputs found
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
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Current research practices on pro-environmental behavior: A survey of environmental psychologists
No abstrac
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
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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 , 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 and , 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
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