Detection of moving groups among early type stars

Our procedure to detect moving groups in the solar neighbourhood (Chen et al., 1997) in the four-dimensional space of the stellar velocity components and age has been improved. The method, which takes advantadge of non-parametric estimators of density distribution to avoid any a priori knowledge of the kinematic properties of these stellar groups, now includes the effect of observational errors on the process to select moving group stars, uses a better estimation of the density distribution of the total sample and field stars, and classifies moving group stars using all the available information. It is applied here to an accurately selected sample of early-type stars with known radial velocities and Strömgren photometry. Astrometric data are taken from the HIPPARCOS catalogue (ESA, 1997), which results in an important decrease in the observational errors with respect to ground-based data, and ensures the uniformity of the observed data. Both the improvement of our method and the use of precise astrometric data have allowed us not only to confirm the existence of classical moving groups, but also to detect finer structures that in several cases can be related to kinematic properties of nearby open clusters or associations.

PCR detection of the pKM.19/ScrfI RFLP (D7S23), a marker closely linked to the cystic fibrosis mutation

Source: Description: pKM-19 is a 1.0 kb EcoRI human genomic fragment inserted in pUC13, that detects a Scrfl (CC/NGG) RFLP (1, 2). We report here the primer sequences suitable for the detection of this RFLP by PCR...

Gated Geiger mode avalanche photodiode pixels with integrated readout electronics for low noise photon detection

Avalanche photodiodes operated in the Geiger mode offer a high intrinsic gain as well as an excellent timing accuracy. These qualities make the sensor specially suitable for those applications where detectors with high sensitivity and low timing uncertainty are required. Moreover, they are compatible with standard CMOS technologies, allowing sensor and front-end electronics integration within the pixel cell. However, the sensor suffers from high levels of intrinsic noise, which may lead to erroneous results and limit the range of detectable signals. They also increase the amount of data that has to be stored. In this work, we present a pixel based on a Geiger-mode avalanche photodiode operated in the gated mode to reduce the probability to detect noise counts interfering with photon arrival events. The readout circuit is based on a two grounds scheme to enable low reverse bias overvoltages and consequently lessen the dark count rate. Experimental characterization of the fabricated pixel with the HV-AMS 0.35µm standard technology is also presented in this article.

Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.