Qualitative design and implementation of human-robot spatial interactions

Despite the large number of navigation algorithms available for mobile robots, in many social contexts they often exhibit inopportune motion behaviours in proximity of people, often with very "unnatural" movements due to the execution of segmented trajectories or the sudden activation of safety mechanisms (e.g., for obstacle avoidance). We argue that the reason of the problem is not only the difficulty of modelling human behaviours and generating opportune robot control policies, but also the way human-robot spatial interactions are represented and implemented. In this paper we propose a new methodology based on a qualitative representation of spatial interactions, which is both flexible and compact, adopting the well-defined and coherent formalization of Qualitative Trajectory Calculus (QTC). We show the potential of a QTC-based approach to abstract and design complex robot behaviours, where the desired robot's behaviour is represented together with its actual performance in one coherent approach, focusing on spatial interactions rather than pure navigation problems

Photon Structure and Quantum Fluctuation

Photon structure derives from quantum fluctuation in quantum field theory to fermion and anti-fermion, and has been an experimentally established feature of electrodynamics since the discovery of the positron. In hadronic physics, the observation of factorisable photon structure is similarly a fundamental test of the quantum field theory Quantum Chromodynamics (QCD). An overview of measurements of hadronic photon structure in e+e- and ep interactions is presented, and comparison made with theoretical expectation, drawing on the essential features of photon fluctuation into quark and anti-quark in QCD.Comment: 29 pages, 15 figures, to appear in Philosophical Transactions of the Royal Society of London (Series A: Mathematical, Physical and Engineering Sciences

Risk-aware motion planning for automated vehicle among human-driven cars

We consider the maneuver planning problem for automated vehicles when they share the road with human-driven cars and interact with each other using a finite set of maneuvers. Each maneuver is calculated considering input constraints, actuator disturbances and sensor noise, so that we can use a maneuver automaton to perform higher-level planning that is robust against lower-level effects. In order to model the behavior of human-driven cars in response to the intent of the automated vehicle, we use control improvisation to build a probabilistic model. To accommodate for potential mismatches between the learned human model and human driving behaviors, we use a conditional value-at-risk objective function to obtain the optimal policy for the automated vehicle. We demonstrate through simulations that our motion planning framework consisting of an interactive human driving model and risk-aware motion planning strategy makes it possible to adapt to different traffic conditions and confidence levels

Leading particle effect, inelasticity and the connection between average multiplicities in {\bf e+e−e^+e^-} and {\bf pppp} processes

The Regge-Mueller formalism is used to describe the inclusive spectrum of the proton in $p p$ collisions. From such a description the energy dependences of both average inelasticity and leading proton multiplicity are calculated. These quantities are then used to establish the connection between the average charged particle multiplicities measured in {\bf $e^+e^-$} and {\bf $pp/{\bar p}p$} processes. The description obtained for the leading proton cross section implies that Feynman scaling is strongly violated only at the extreme values of $x_F$, that is at the central region ($x_F \approx 0$) and at the diffraction region ($x_F \approx 1$), while it is approximately observed in the intermediate region of the spectrum.Comment: 20 pages, 10 figures, to be published in Physical Review

A New 5 Flavour NLO Analysis and Parametrizations of Parton Distributions of the Real Photon

New, radiatively generated, NLO quark (u,d,s,c,b) and gluon densities in a real, unpolarized photon are presented. We perform three global fits, based on the NLO DGLAP evolution equations for Q^2>1 GeV^2, to all the available structure function F_2^gamma(x,Q^2) data. As in our previous LO analysis we utilize two theoretical approaches. Two models, denoted as FFNS_{CJK}1 & 2 NLO, adopt the so-called Fixed Flavour-Number Scheme for calculation of the heavy-quark contributions to F_2^gamma(x,Q^2), the CJK NLO model applies the ACOT(chi) scheme. We examine the results of our fits by a comparison with the LEP data for the Q^2 dependence of the F_2^gamma, averaged over various x-regions, and the F_2,c^gamma. Grid parametrizations of the parton densities for all fits are provided.Comment: 49 pages, 27 postscript figures; FORTRAN programs available at http://www.fuw.edu.pl/~pjank/param.htm

Irreversible time-dependent rheological behavior of cement slurries : constitutive model and experiments

Over the last few decades, much focus has been given to investigating the reversible rheological behavior of thixotropic materials, but the description of the rheology of materials undergoing an irreversible process is still challenging. In this work, the time-dependent rheological behavior of a cement slurry is investigated. Different rheometric experiments are performed to evaluate the structure breakdown under shear, cement gelation, and curing process. A recently proposed thixotropic elasto-viscoplastic model [de Souza Mendes, Soft Matter 7, 2471-2483 (2011)] is modified to account for irreversible effects, which can be either of a chemical or physical nature, making the current model capable of describing reversible and irreversible processes with a single structure parameter. The parameters of the model are estimated from constant shear rate tests and from the flow curve of the fresh cement slurry. The model predictions are compared to step-down and step-up in stress experiments, and the results show that the model successfully describes experimental data obtained. Interesting phenomena are observed and discussed, including (i) thixotropic behavior during the dormant period, (ii) shear banding, (iii) irreversible changes in cement slurry rheology after the hydration reactions accelerate, and (iv) the existence of a characteristic time for the transition from a thixotropic-yield-stress material to a solid during curing. The predictive capability of the new model includes bifurcation, shear banding, stress overshoots, effects of chemical reactions, and irreversible shear degradation. It is argued that the ideas employed in the present work can be used to incorporate irreversible effects into other thixotropic models, giving rise to the possibility of describing the transient rheological behavior of complex materials in an unprecedented fashion. (c) 2019 The Society of Rheology

Inducing safer oblique trees without costs

Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming

Inhibitor binding mode and allosteric regulation of Na+-glucose symporters.

Sodium-dependent glucose transporters (SGLTs) exploit sodium gradients to transport sugars across the plasma membrane. Due to their role in renal sugar reabsorption, SGLTs are targets for the treatment of type 2 diabetes. Current therapeutics are phlorizin derivatives that contain a sugar moiety bound to an aromatic aglycon tail. Here, we develop structural models of human SGLT1/2 in complex with inhibitors by combining computational and functional studies. Inhibitors bind with the sugar moiety in the sugar pocket and the aglycon tail in the extracellular vestibule. The binding poses corroborate mutagenesis studies and suggest a partial closure of the outer gate upon binding. The models also reveal a putative Na+ binding site in hSGLT1 whose disruption reduces the transport stoichiometry to the value observed in hSGLT2 and increases inhibition by aglycon tails. Our work demonstrates that subtype selectivity arises from Na+-regulated outer gate closure and a variable region in extracellular loop EL5