A second-order PHD filter with mean and variance in target number

The Probability Hypothesis Density (PHD) and Cardinalized PHD (CPHD) filters are popular solutions to the multi-target tracking problem due to their low complexity and ability to estimate the number and states of targets in cluttered environments. The PHD filter propagates the first-order moment (i.e. mean) of the number of targets while the CPHD propagates the cardinality distribution in the number of targets, albeit for a greater computational cost. Introducing the Panjer point process, this paper proposes a second-order PHD filter, propagating the second-order moment (i.e. variance) of the number of targets alongside its mean. The resulting algorithm is more versatile in the modelling choices than the PHD filter, and its computational cost is significantly lower compared to the CPHD filter. The paper compares the three filters in statistical simulations which demonstrate that the proposed filter reacts more quickly to changes in the number of targets, i.e., target births and target deaths, than the CPHD filter. In addition, a new statistic for multi-object filters is introduced in order to study the correlation between the estimated number of targets in different regions of the state space, and propose a quantitative analysis of the spooky effect for the three filters

Recommendation of RILEM TC 246-TDC : test methods to determine durability of concrete under combined environmental actions and mechanical load

The combination of environmental actions and mechanical load has obvious synergetic effects on the durability of concrete. But these effects have been widely neglected so far. For a realistic service life prediction the effect of an applied mechanical load on chloride penetration has been taken into consideration as a first and important step in RILEM TC 246-TDC since 2011. This recommendation focuses on the test method to determine the effect of applied compressive stress and tensile stress on chloride diffusion. It includes detailed experimental procedure to receive consistent results of chloride profile and the apparent chloride ion diffusion coefficient of concrete under compressive and tensile stress

Marker-Less Stage Drift Correction in Super-Resolution Microscopy Using the Single-Cluster PHD Filter

Fluorescence microscopy is a technique which allows the imaging of cellular and intracellular dynamics through the activation of fluorescent molecules attached to them. It is a very important technique because it can be used to analyze the behavior of intracellular processes in vivo in contrast to methods like electron microscopy. There are several challenges related to the extraction of meaningful information from images acquired from optical microscopes due to the low contrast between objects and background and the fact that point-like objects are observed as blurred spots due to the diffraction limit of the optical system. Another consideration is that for the study of intracellular dynamics, multiple particles must be tracked at the same time, which is a challenging task due to problems such as the presence of false positives and missed detections in the acquired data. Additionally, the objective of the microscope is not completely static with respect to the cover slip due to mechanical vibrations or thermal expansions which introduces bias in the measurements. In this paper, a Bayesian approach is used to simultaneously track the locations of objects with different motion behaviors and the stage drift using image data obtained from fluorescence microscopy experiments. Namely, detections are extracted from the acquired frames using image processing techniques, and then these detections are used to accurately estimate the particle positions and simultaneously correct the drift introduced by the motion of the sample stage. A single cluster Probability Hypothesis Density (PHD) filter with object classification is used for the estimation of the multiple target state assuming different motion behaviors. The detection and tracking methods are tested and their performance is evaluated on both simulated and real data

A symmetric polymer blend confined into a film with antisymmetric surfaces: interplay between wetting behavior and phase diagram

We study the phase behavior of a symmetric binary polymer blend which is confined into a thin film. The film surfaces interact with the monomers via short range potentials. We calculate the phase behavior within the self-consistent field theory of Gaussian chains. Over a wide range of parameters we find strong first order wetting transitions for the semi-infinite system, and the interplay between the wetting/prewetting behavior and the phase diagram in confined geometry is investigated. Antisymmetric boundaries, where one surface attracts the A component with the same strength than the opposite surface attracts the B component, are applied. The phase transition does not occur close to the bulk critical temperature but in the vicinity of the wetting transition. For very thin films or weak surface fields one finds a single critical point at $\phi_c=1/2$. For thicker films or stronger surface fields the phase diagram exhibits two critical points and two concomitant coexistence regions. Only below a triple point there is a single two phase coexistence region. When we increase the film thickness the two coexistence regions become the prewetting lines of the semi-infinite system, while the triple temperature converges towards the wetting transition temperature from above. The behavior close to the tricritical point, which separates phase diagrams with one and two critical points, is studied in the framework of a Ginzburg-Landau ansatz. Two-dimensional profiles of the interface between the laterally coexisting phases are calculated, and the interfacial and line tensions analyzed. The effect of fluctuations and corrections to the self-consistent field theory are discussed.Comment: Phys.Rev.E in prin

3D Real-Time Echocardiography Combined with Mini Pressure Wire Generate Reliable Pressure-Volume Loops in Small Hearts

BACKGROUND: Pressure-volume loops (PVL) provide vital information regarding ventricular performance and pathophysiology in cardiac disease. Unfortunately, acquisition of PVL by conductance technology is not feasible in neonates and small children due to the available human catheter size and resulting invasiveness. The aim of the study was to validate the accuracy of PVL in small hearts using volume data obtained by real-time three-dimensional echocardiography (3DE) and simultaneously acquired pressure data. METHODS: In 17 piglets (weight range: 3.6–8.0 kg) left ventricular PVL were generated by 3DE and simultaneous recordings of ventricular pressure using a mini pressure wire (PVL3D). PVL3D were compared to conductance catheter measurements (PVLCond) under various hemodynamic conditions (baseline, alpha-adrenergic stimulation with phenylephrine, beta-adrenoreceptor-blockage using esmolol). In order to validate the accuracy of 3D volumetric data, cardiac magnetic resonance imaging (CMR) was performed in another 8 piglets. RESULTS: Correlation between CMR- and 3DE-derived volumes was good (enddiastolic volume: mean bias -0.03ml ±1.34ml). Computation of PVL3D in small hearts was feasible and comparable to results obtained by conductance technology. Bland-Altman analysis showed a low bias between PVL3D and PVLCond. Systolic and diastolic parameters were closely associated (Intraclass-Correlation Coefficient for: systolic myocardial elastance 0.95, arterial elastance 0.93, diastolic relaxation constant tau 0.90, indexed end-diastolic volume 0.98). Hemodynamic changes under different conditions were well detected by both methods (ICC 0.82 to 0.98). Inter- and intra-observer coefficients of variation were below 5% for all parameters. CONCLUSIONS: PVL3D generated from 3DE combined with mini pressure wire represent a novel, feasible and reliable method to assess different hemodynamic conditions of cardiac function in hearts comparable to neonate and infant size. This methodology may be integrated into clinical practice and cardiac catheterization programs and has the capability to contribute to clinical decision making even in small hearts

Nonstrict hierarchical reinforcement learning for interactive systems and robots

Conversational systems and robots that use reinforcement learning for policy optimization in large domains often face the problem of limited scalability. This problem has been addressed either by using function approximation techniques that estimate the approximate true value function of a policy or by using a hierarchical decomposition of a learning task into subtasks. We present a novel approach for dialogue policy optimization that combines the benefits of both hierarchical control and function approximation and that allows flexible transitions between dialogue subtasks to give human users more control over the dialogue. To this end, each reinforcement learning agent in the hierarchy is extended with a subtask transition function and a dynamic state space to allow flexible switching between subdialogues. In addition, the subtask policies are represented with linear function approximation in order to generalize the decision making to situations unseen in training. Our proposed approach is evaluated in an interactive conversational robot that learns to play quiz games. Experimental results, using simulation and real users, provide evidence that our proposed approach can lead to more flexible (natural) interactions than strict hierarchical control and that it is preferred by human users

Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems

This work was supported by the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) at Bielefeld University, funded by the German Research Foundation (DFG), and the DFG-funded DUEL project (grant SCHL 845/5-1)

Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset prostate cancer

Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in 11 tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of > 10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA