Eigenlogic: a Quantum View for Multiple-Valued and Fuzzy Systems

We propose a matrix model for two- and many-valued logic using families of observables in Hilbert space, the eigenvalues give the truth values of logical propositions where the atomic input proposition cases are represented by the respective eigenvectors. For binary logic using the truth values {0,1} logical observables are pairwise commuting projectors. For the truth values {+1,-1} the operator system is formally equivalent to that of a composite spin 1/2 system, the logical observables being isometries belonging to the Pauli group. Also in this approach fuzzy logic arises naturally when considering non-eigenvectors. The fuzzy membership function is obtained by the quantum mean value of the logical projector observable and turns out to be a probability measure in agreement with recent quantum cognition models. The analogy of many-valued logic with quantum angular momentum is then established. Logical observables for three-value logic are formulated as functions of the Lz observable of the orbital angular momentum l=1. The representative 3-valued 2-argument logical observables for the Min and Max connectives are explicitly obtained.Comment: 11 pages, 2 table

A sensor fusion layer to cope with reduced visibility in SLAM

Mapping and navigating with mobile robots in scenarios with reduced visibility, e.g. due to smoke, dust, or fog, is still a big challenge nowadays. In spite of the tremendous advance on Simultaneous Localization and Mapping (SLAM) techniques for the past decade, most of current algorithms fail in those environments because they usually rely on optical sensors providing dense range data, e.g. laser range finders, stereo vision, LIDARs, RGB-D, etc., whose measurement process is highly disturbed by particles of smoke, dust, or steam. This article addresses the problem of performing SLAM under reduced visibility conditions by proposing a sensor fusion layer which takes advantage from complementary characteristics between a laser range finder (LRF) and an array of sonars. This sensor fusion layer is ultimately used with a state-of-the-art SLAM technique to be resilient in scenarios where visibility cannot be assumed at all times. Special attention is given to mapping using commercial off-the-shelf (COTS) sensors, namely arrays of sonars which, being usually available in robotic platforms, raise technical issues that were investigated in the course of this work. Two sensor fusion methods, a heuristic method and a fuzzy logic-based method, are presented and discussed, corresponding to different stages of the research work conducted. The experimental validation of both methods with two different mobile robot platforms in smoky indoor scenarios showed that they provide a robust solution, using only COTS sensors, for adequately coping with reduced visibility in the SLAM process, thus decreasing significantly its impact in the mapping and localization results obtained

A sensor fusion layer to cope with reduced visibility in SLAM

Mapping and navigating with mobile robots in scenarios with reduced visibility, e.g. due to smoke, dust, or fog, is still a big challenge nowadays. In spite of the tremendous advance on Simultaneous Localization and Mapping (SLAM) techniques for the past decade, most of current algorithms fail in those environments because they usually rely on optical sensors providing dense range data, e.g. laser range finders, stereo vision, LIDARs, RGB-D, etc., whose measurement process is highly disturbed by particles of smoke, dust, or steam. This article addresses the problem of performing SLAM under reduced visibility conditions by proposing a sensor fusion layer which takes advantage from complementary characteristics between a laser range finder (LRF) and an array of sonars. This sensor fusion layer is ultimately used with a state-of-the-art SLAM technique to be resilient in scenarios where visibility cannot be assumed at all times. Special attention is given to mapping using commercial off-the-shelf (COTS) sensors, namely arrays of sonars which, being usually available in robotic platforms, raise technical issues that were investigated in the course of this work. Two sensor fusion methods, a heuristic method and a fuzzy logic-based method, are presented and discussed, corresponding to different stages of the research work conducted. The experimental validation of both methods with two different mobile robot platforms in smoky indoor scenarios showed that they provide a robust solution, using only COTS sensors, for adequately coping with reduced visibility in the SLAM process, thus decreasing significantly its impact in the mapping and localization results obtained

BLUE, BLUP and the Kalman filter: some new results

In this contribution, we extend ‘Kalman-filter’ theory by introducing a new BLUE–BLUP recursion of the partitioned measurement and dynamic models. Instead of working with known state-vector means, we relax the model and assume these means to be unknown. The recursive BLUP is derived from first principles, in which a prominent role is played by the model’s misclosures. As a consequence of the mean state-vector relaxing assumption, the recursion does away with the usual need of having to specify the initial state-vector variance matrix. Next to the recursive BLUP, we introduce, for the same model, the recursive BLUE. This extension is another consequence of assuming the state-vector means unknown. In the standard Kalman filter set-up with known state-vector means, such difference between estimation and prediction does not occur. It is shown how the two intertwined recursions can be combined into one general BLUE–BLUP recursion, the outputs of which produce for every epoch, in parallel, the BLUP for the random state-vector and the BLUE for the mean of the state-vector

Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling

BACKGROUND: Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching (FRAP) is becoming more important. METHODS AND RESULTS: The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching (FRAP) protocol, and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells, to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy, one can also uniquely estimate the individual values of the binding rate coefficients if the molecular diffusion coefficient is known. One can also simultaneously estimate the dissociation rate parameter and molecular diffusion coefficient given the pseudo-association rate parameter is known. However, the protocol provides insufficient information for unique simultaneous estimation of three parameters (diffusion coefficient and binding rate parameters) owing to the high intercorrelation between the molecular diffusion coefficient and pseudo-association rate parameter. Attempts to estimate macromolecule mass transport and binding rate parameters simultaneously from FRAP data result in misleading conclusions regarding concentrations of free macromolecule and bound complex inside the cell, average binding time per vacant site, average time for diffusion of macromolecules from one site to the next, and slow or rapid mobility of biomolecules in cells. CONCLUSION: To obtain unique values for molecular diffusion coefficient and binding rate parameters from FRAP data, we propose conducting two FRAP experiments on the same class of macromolecule and cell. One experiment should be used to measure the molecular diffusion coefficient independently of binding in an effective diffusion regime and the other should be conducted in a reaction dominant or reaction-diffusion regime to quantify binding rate parameters. The method described in this paper is likely to be widely used to estimate in-vivo biomolecule mass transport and binding rate parameters

Optomechanical Crystals

Structured, periodic optical materials can be used to form photonic crystals capable of dispersing, routing, and trapping light. A similar phenomena in periodic elastic structures can be used to manipulate mechanical vibrations. Here we present the design and experimental realization of strongly coupled optical and mechanical modes in a planar, periodic nanostructure on a silicon chip. 200-Terahertz photons are co-localized with mechanical modes of Gigahertz frequency and 100-femtogram mass. The effective coupling length, which describes the strength of the photon-phonon interaction, is as small as 2.9 microns, which, together with minute oscillator mass, allows all-optical actuation and transduction of nanomechanical motion with near quantum-limited sensitivity. Optomechanical crystals have many potential applications, from RF-over-optical communication to the study of quantum effects in mesoscopic mechanical systems.Comment: 16 pages, 7 figure

Association of HbA1c Values with Mortality and Cardiovascular Events in Diabetic Dialysis Patients. The INVOR Study and Review of the Literature

BACKGROUND: Improved glycemic control reduces complications in patients with diabetes mellitus (DM). However, it is discussed controversially whether patients with diabetes mellitus and end-stage renal disease benefit from strict glycemic control. METHODS: We followed 78 patients with DM initiating dialysis treatment of the region of Vorarlberg in a prospective cohort study applying a time-dependent Cox regression analysis using all measured laboratory values for up to more than seven years. This resulted in 880 HbA(1c) measurements (with one measurement every 3.16 patient months on average) during the entire observation period. Non-linear P-splines were used to allow flexible modeling of the association with mortality and cardiovascular disease (CVD) events. RESULTS: We observed a decreased mortality risk with increasing HbA(1c) values (HR = 0.72 per 1% increase, p = 0.024). Adjustment for age and sex and additional adjustment for other CVD risk factors only slightly attenuated the association (HR = 0.71, p = 0.044). A non-linear P-spline showed that the association did not follow a fully linear pattern with a highly significant non-linear component (p = 0.001) with an increased risk of all-cause mortality for HbA(1c) values up to 6-7%. Causes of death were associated with HbA(1c) values. The risk for CVD events, however, increased with increasing HbA(1c) values (HR = 1.24 per 1% increase, p = 0.048) but vanished after extended adjustments. CONCLUSIONS: This study considered the entire information collected on HbA(1c) over a period of more than seven years. Besides the methodological advantages our data indicate a significant inverse association between HbA(1c) levels and all-cause mortality. However, for CVD events no significant association could be found

Observation of Static Pictures of Dynamic Actions Enhances the Activity of Movement-Related Brain Areas

Physiological studies of perfectly still observers have shown interesting correlations between increasing effortfulness of observed actions and increases in heart and respiration rates. Not much is known about the cortical response induced by observing effortful actions. The aim of this study was to investigate the time course and neural correlates of perception of implied motion, by presenting 260 pictures of human actions differing in degrees of dynamism and muscular exertion. ERPs were recorded from 128 sites in young male and female adults engaged in a secondary perceptual task.Our results indicate that even when the stimulus shows no explicit motion, observation of static photographs of human actions with implied motion produces a clear increase in cortical activation, manifest in a long-lasting positivity (LP) between 350–600 ms that is much greater to dynamic than less dynamic actions, especially in men. A swLORETA linear inverse solution computed on the dynamic-minus-static difference wave in the time window 380–430 ms showed that a series of regions was activated, including the right V5/MT, left EBA, left STS (BA38), left premotor (BA6) and motor (BA4) areas, cingulate and IF cortex.Overall, the data suggest that corresponding mirror neurons respond more strongly to implied dynamic than to less dynamic actions. The sex difference might be partially cultural and reflect a preference of young adult males for highly dynamic actions depicting intense muscular activity, or a sporty context

Three classical Cepheid variable stars in the nuclear bulge of the Milky Way

The nuclear bulge is a region with a radius of about 200 parsecs around the centre of the Milky Way. It contains stars with ages ranging from a few million years to over a billion years, yet its star-formation history and the triggering process for star formation remain to be resolved. Recently, episodic star formation, powered by changes in the gas content, has been suggested. Classical Cepheid variable stars have pulsation periods that decrease with increasing age, so it is possible to probe the star-formation history on the basis of the distribution of their periods. Here we report the presence of three classical Cepheids in the nuclear bulge with pulsation periods of approximately 20 days, within 40 parsecs (projected distance) of the central black hole. No Cepheids with longer or shorter periods were found. We infer that there was a period about 25 million years ago, and possibly lasting until recently, in which star formation increased relative to the period of 30-70 million years ago.Comment: 19 pages, 5 figures, 1 table (including main paper and supplemantary information

Occlusion of LTP-Like Plasticity in Human Primary Motor Cortex by Action Observation

Passive observation of motor actions induces cortical activity in the primary motor cortex (M1) of the onlooker, which could potentially contribute to motor learning. While recent studies report modulation of motor performance following action observation, the neurophysiological mechanism supporting these behavioral changes remains to be specifically defined. Here, we assessed whether the observation of a repetitive thumb movement – similarly to active motor practice – would inhibit subsequent long-term potentiation-like (LTP) plasticity induced by paired-associative stimulation (PAS). Before undergoing PAS, participants were asked to either 1) perform abductions of the right thumb as fast as possible; 2) passively observe someone else perform thumb abductions; or 3) passively observe a moving dot mimicking thumb movements. Motor evoked potentials (MEP) were used to assess cortical excitability before and after motor practice (or observation) and at two time points following PAS. Results show that, similarly to participants in the motor practice group, individuals observing repeated motor actions showed marked inhibition of PAS-induced LTP, while the “moving dot” group displayed the expected increase in MEP amplitude, despite differences in baseline excitability. Interestingly, LTP occlusion in the action-observation group was present even if no increase in cortical excitability or movement speed was observed following observation. These results suggest that mere observation of repeated hand actions is sufficient to induce LTP, despite the absence of motor learning