On Languages Accepted by P/T Systems Composed of joins

Recently, some studies linked the computational power of abstract computing systems based on multiset rewriting to models of Petri nets and the computation power of these nets to their topology. In turn, the computational power of these abstract computing devices can be understood by just looking at their topology, that is, information flow. Here we continue this line of research introducing J languages and proving that they can be accepted by place/transition systems whose underlying net is composed only of joins. Moreover, we investigate how J languages relate to other families of formal languages. In particular, we show that every J language can be accepted by a log n space-bounded non-deterministic Turing machine with a one-way read-only input. We also show that every J language has a semilinear Parikh map and that J languages and context-free languages (CFLs) are incomparable

Effective quantum gravity observables and locally covariant QFT

Perturbative algebraic quantum field theory (pAQFT) is a mathematically rigorous framework that allows to construct models of quantum field theories on a general class of Lorentzian manifolds. Recently this idea has been applied also to perturbative quantum gravity, treated as an effective theory. The difficulty was to find the right notion of observables that would in an appropriate sense be diffeomorphism invariant. In this article I will outline a general framework that allows to quantize theories with local symmetries (this includes infinitesimal diffeomorphism transformations) with the use of the BV (Batalin-Vilkovisky) formalism. This approach has been successfully applied to effective quantum gravity in a recent paper by R. Brunetti, K. Fredenhagen and myself. In the same paper we also proved perturbative background independence of the quantized theory, which is going to be discussed in the present work as well.Comment: 16 pages, based on a plenary talk given at the 14th Marcel Grossmann Meeting in Rome (July 2015

Towards Visual Feedback Loops for Robot-Controlled Additive Manufacturing

Robotic additive manufacturing methods have enabled the design and fabrication of novel forms and material systems that represent an important step forward for architectural fabrication. However, a common problem in additive manufacturing is to predict and incorporate the dynamic behavior of the material that is the result of the complex confluence of forces and material properties that occur during fabrication. While there have been some approaches towards verification systems, to date most robotic additive manufacturing processes lack verification to ensure deposition accuracy. Inaccuracies, or in some instances critical errors, can occur due to robot dynamics, material self-deflection, material coiling, or timing shifts in the case of multi-material prints. This paper addresses that gap by presenting an approach that uses vision-based sensing systems to assist robotic additive manufacturing processes. Using online image analysis techniques, occupancy maps can be created and updated during the fabrication process to document the actual position of the previously deposited material. This development is an intermediary step towards closed-loop robotic control systems that combine workspace sensing capabilities with decision-making algorithms to adjust toolpaths to correct for errors or inaccuracies if necessary. The occupancy grid map provides a complete representation of the print that can be analyzed to determine various key aspects, such as, print quality, extrusion diameter, adhesion between printed parts, and intersections within the meshes. This valuable quantitative information regarding system robustness can be used to influence the system’s future actions. This approach will help ensure consistent print quality and sound tectonics in robotic additive manufacturing processes, improving on current techniques and extending the possibilities of robotic fabrication in architecture

An Analytical and Numerical Study of Optimal Channel Networks

We analyze the Optimal Channel Network model for river networks using both analytical and numerical approaches. This is a lattice model in which a functional describing the dissipated energy is introduced and minimized in order to find the optimal configurations. The fractal character of river networks is reflected in the power law behaviour of various quantities characterising the morphology of the basin. In the context of a finite size scaling Ansatz, the exponents describing the power law behaviour are calculated exactly and show mean field behaviour, except for two limiting values of a parameter characterizing the dissipated energy, for which the system belongs to different universality classes. Two modified versions of the model, incorporating quenched disorder are considered: the first simulates heterogeneities in the local properties of the soil, the second considers the effects of a non-uniform rainfall. In the region of mean field behaviour, the model is shown to be robust to both kinds of perturbations. In the two limiting cases the random rainfall is still irrelevant, whereas the heterogeneity in the soil properties leads to new universality classes. Results of a numerical analysis of the model are reported that confirm and complement the theoretical analysis of the global minimum. The statistics of the local minima are found to more strongly resemble observational data on real rivers.Comment: 27 pages, ps-file, 11 Postscript figure

Cosmological perturbation theory and quantum gravity

It is shown how cosmological perturbation theory arises from a fully quantized perturbative theory of quantum gravity. Central for the derivation is a non-perturbative concept of gauge-invariant local observables by means of which perturbative invariant expressions of arbitrary order are generated. In particular, in the linearised theory, first order gauge-invariant observables familiar from cosmological perturbation theory are recovered. Explicit expressions of second order quantities are presented as well

Prognostic impact of systemic inflammatory diseases in elderly patients with congestive heart failure

Background and aims: Inflammation is part of the pathophysiology of congestive heart failure (CHF). However, little is known about the impact of the presence of systemic inflammatory disease (SID), defined as inflammatory syndrome with constitutional symptoms and involvement of at least two organs as co-morbidity on the clinical course and prognosis of patients with CHF. Methods and results: This is an analysis of all 622 patients included in TIME-CHF. After an 18 months follow-up, outcomes of patients with and without SID were compared. Primary endpoint was all-cause hospitalization free survival. Secondary endpoints were overall survival and CHF hospitalization free survival. At baseline, 38 patients had history of SID (6.1%). These patients had higher N-terminal pro brain natriuretic peptide and worse renal function than patients without SID. SID was a risk factor for adverse outcome [primary endpoint: hazard ratio (HR) = 1.73 (95% confidence interval: 1.18-2.55, P = 0.005); survival: HR = 2.60 (1.49-4.55, P = 0.001); CHF hospitalization free survival: HR = 2.3 (1.45-3.65, P < 0.001)]. In multivariate models, SID remained the strongest independent risk factor for survival and CHF hospitalization free survival. Conclusions: In elderly patients with CHF, SID is independently accompanied with adverse outcome. Given the increasing prevalence of SID in the elderly population, these findings are clinically important for both risk stratification and patient managemen

A hybrid framework for nonlinear dynamic simulations including full-field optical measurements and image decomposition algorithms

Innovative designs of transport vehicles need to be validated in order to demonstrate reliability and provide confidence. It is normal practice to study the mechanical response of the structural elements by comparing numerical results obtained from finite element simulation models with results obtained from experiment. In this frame, the use of wholefield optical techniques has been proven successful in the validation of deformation, strain, or vibration modes. The strength of full-field optical techniques is that the entire displacement field can be acquired. The objective of this article is to integrate full-field optical measurement methodologies with state-of-the-art computational simulation techniques for nonlinear transient dynamic events. In this frame, composite car bonnet frame structures of dimensions about 1.8 m 30.8 m are considered. They have been tested in low-velocity mass-drop impact loading with impact energies ranging from 20 to 200 J. In parallel, simulation models of the car bonnet frame have been developed using layered shell elements. The Zernike shape descriptor approach was used to decompose numerical and experimental data into moments for comparison purposes. A very good agreement between numerical and experimental results was observed. Therefore, integration of numerical analysis with full-field optical measurements along with sophisticated comparison techniques can increase design reliability