Double Deep-Q Learning-Based Output Tracking of Probabilistic Boolean Control Networks

In this article, a reinforcement learning (RL)-based scalable technique is presented to control the probabilistic Boolean control networks (PBCNs). In particular, a double deep- $Q$ network (DD $Q\text{N}$ ) approach is firstly proposed to address the output tracking problem of PBCNs, and optimal state feedback controllers are obtained such that the output of PBCNs tracks a constant as well as a time-varying reference signal. The presented method is model-free and offers scalability, thereby provides an efficient way to control large-scale PBCNs that are a natural choice to model gene regulatory networks (GRNs). Finally, three PBCN models of GRNs including a 16-gene and 28-gene networks are considered to verify the presented results

Deep phase modulation interferometry

We have developed a method to equip homodyne interferometers with the capability to operate with constant high sensitivity over many fringes for continuous real-time tracking. The method can be considered as an extension of the "J_1...J_4" methods, and its enhancement to deliver very sensitive angular measurements through Differential Wavefront Sensing is straightforward. Beam generation requires a sinusoidal phase modulation of several radians in one interferometer arm. On a stable optical bench, we have demonstrated a long-term sensitivity over thousands of seconds of 0.1 mrad/sqrt[Hz] that correspond to 20 pm/sqrt[Hz] in length, and 10 nrad/sqrt[Hz] in angle at millihertz frequencies

A Multi-Step Anomaly Detection Strategy Based on Robust Distances for the Steel Industry

Steel making industries exhibit extreme working conditions characterized by high temperature, pressure, and production speed as well as intense throughput. Due to high economic and energy investments of the overall production process, an intense and expensive preventive maintenance program is adopted to avoid breakdowns. Steel making process would greatly benefit from a predictive maintenance module able to detect incoming faults from data process analysis. However, due to intense preventive maintenance, available data recording process operations enclose only a few samples of fault events, avoiding the efficient application of classical data driven anomaly detection models. In an attempt to overcome the above mentioned limits, we report the outcome of an industrial research project on data-driven anomaly detection in a steel making production process. The study assesses a fault detection strategy for rotating machines in the hot rolling mill line: we developed an automatic two-step strategy, which combines two statistical methods over the available data set: more precisely, the combination of Re-weighted Minimum Covariance Determinant estimator and Hidden Markov Models helped identify working conditions in a drive reducer of a hot steel rolling mill line and automatically isolate signs of decreasing performance or upcoming failures. The proposed strategy has been validated on real data collected in a steel making plant placed in the South of Italy

Low loss coatings for the VIRGO large mirrors

présentée par L. PinardThe goal of the VIRGO program is to build a giant Michelson type interferometer (3 kilometer long arms) to detect gravitational waves. Large optical components (350 mm in diameter), having extremely low loss at 1064 nm, are needed. Today, the Ion beam Sputtering is the only deposition technique able to produce optical components with such performances. Consequently, a large ion beam sputtering deposition system was built to coat large optics up to 700 mm in diameter. The performances of this coater are described in term of layer uniformity on large scale and optical losses (absorption and scattering characterization). The VIRGO interferometer needs six main mirrors. The first set was ready in June 2002 and its installation is in progress on the VIRGO site (Italy). The optical performances of this first set are discussed. The requirements at 1064 nm are all satisfied. Indeed, the absorption level is close to 1 ppm (part per million), the scattering is lower than 5 ppm and the R.M.S. wavefront of these optics is lower than 8 nm on 150 mm in diameter. Finally, some solutions are proposed to further improve these performances, especially the absorption level (lower than 0.1 ppm) and the mechanical quality factor Q of the mirrors (thermal noise reduction)

Supplement: "Localization and broadband follow-up of the gravitational-wave transient GW150914" (2016, ApJL, 826, L13)

This Supplement provides supporting material for Abbott et al. (2016a). We briefly summarize past electromagnetic (EM) follow-up efforts as well as the organization and policy of the current EM follow-up program. We compare the four probability sky maps produced for the gravitational-wave transient GW150914, and provide additional details of the EM follow-up observations that were performed in the different bands

Localization and broadband follow-up of the gravitational-wave transient GW 150914

A gravitational-wave (GW) transient was identified in data recorded by the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) detectors on 2015 September 14. The event, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the GW data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network circulars, giving an overview of the participating facilities, the GW sky localization coverage, the timeline, and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic (EM) signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the EM data and results of the EM follow-up campaign are being disseminated in papers by the individual teams

A state observer for the Virgo inverted pendulum

International audienceWe report an application of Kalman filtering to the inverted pendulum (IP) of the Virgo gravitational wave interferometer. Using subspace method system identification techniques, we calculated a linear mechanical model of Virgo IP from experimental transfer functions. We then developed a Kalman filter, based on the obtained state space representation, that estimates from open loop time domain data, the state variables of the system. This allows the observation (and eventually control) of every resonance mode of the IP mechanical structure independently

MRI myocardium T2∗ measurement by a new PCA-based object recognition algorithm

MRI myocardium T∗2measurement is a very important task in MRI for the detection, for example, of myocardial iron overload. Generally, T∗2values are obtained by a T∗2multiecho MRI. In particular, signal intensities of selected ROIs on different TE images are evaluated and the signal -TE relation is used in order to estimate the T∗2. In order to correctly estimate the T∗2, it is important that the different selected ROIs correspond to the same anatomical pixels. In this paper, a new PCA-based recognition algorithm is presented in order to recognize and quantify the same anatomical pixels on different TE images of a multiecho sequence. The algorithm was implemented in Matlab. In order to test the algorithm and to obtain preliminary results, a group of 10 patients, referred to MRI with presumptive, clinical diagnosis of myocardial iron overload, was examined in order to test the algorithm. All patients showed no myocardial iron overload with a T∗2>20ms.To assess intra- and interobserver variability, two observers blindly analyzed the data by delimiting myocardial region. A good intra- and inter-observer reproducibility was obtained, in fact the mean difference between the two observer measurements was 0.8 ms and the 95% limits of agreement on the Bland-Altman plot were -4.8 to 6.5 ms

An MRI myocarditis index defined by a PCA-based object recognition algorithm

Magnetic Resonance Imaging (MRI) has shown promising results in diagnosing myocarditis that can be qualitatively observed as enhanced pixels on the cardiac muscles images. In this paper, a myocarditis index, defined as the ratio between enhanced pixels, representing an inflammation, and the total pixels of myocardial muscle, is presented. In order to recognize and quantify enhanced pixels, a PCA-based recognition algorithm is used. The algorithm, implemented in Matlab, was tested by examining a group of 10 patients, referred to MRI with presumptive, clinical diagnosis of myocarditis. To assess intra- and interobserver variability, two observers blindly analyzed data related to the 10 patients by delimiting myocardial region and selecting enhanced pixels. After 5 days the same observers redid the analysis. The obtained myocarditis indexes were compared to an ordinal variable (values in the 1 - 5 range) that represented the blind assessment of myocarditis seriousness given by two radiologists on the base of the patient case histories. Results show that there is a significant correlation (P < 0:001; r = 0:94) between myocarditis indexes and the radiologists' clinical judgments. Furthermore, a good intraobserver and interobserver reproducibility was obtained