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The rate estimation of nuclear reactions induced in high intensity laser-target interaction (≥1016 W/cm2), is strongly depending on the neutron detection efficiency and ion charge discrimination, according to particles involved in exit open-channels. Ion discrimination is basically performed by means of analysis of pits observed on track detector, which is critically dependent on calibration and/or fast TOF devices based on SiC and diamond detectors. Last setup is used to determine the ion energy and to obtain a rough estimation of yields. However, for each TOF interval, the dependence of yield from the energy deposited in the detector sensitive region, introduces a distortion in the ion spectra. Moreover, if two ion species are present in the same spectrum, the discrimination of their contribution is not attainable. In this paper a new method is described which allows to discriminate the contribution of two ion species in the wide energy range of nuclear reactions induced in laser-target interactions. The method is based on charge response of two TOF-SiC detectors, of suitable thicknesses, placed in adjacent positions. In presence of two ion species, the response of the detectors, associated with different energy losses, can determine the ion specific contribution to each TOF interval.

This paper is concerned with the automatic analysis of data coming from the multidetector array CHIMERA, used in nuclear physics at intermediate energies. Each of Chimera's detection cells is a telescope made of a [DELTA]E silicon detector and a CsI(Tl) crystal, thick enough to stop all the charged light particles. The signals produced in the CsI(Tl) scintillators can be subdivided into two components--Fast and Slow. These data are collected in the form of bi-dimensional matrices (Fast-Slow matrices), particularly important for light particle identification. The proposed approach consists in applying image processing techniques. In particular, Grossberg's pre-attentive neural networks are used as a first step in order to isolate the regions of physical interest in the matrices and to roughly identify the directions depicted by the most intense lines; a successive step of filtering based on Markov random fields is then performed. Index Terms--Clustering methods, image processing, nuclear measurements, visualization.

We have built and tested a computational unit for on-line processing of special algorithms to be embedded in the central processing unit VERSAmodule Eurocard (CPU VME)-crate of the CHIMERA data acquisition system. The computational unit consists of a number of VME digital signal processor (DSP)-based commercial boards delivering 720 MFlops/board. Index Terms--Data acquisition (DAQ), digital signal processor (DSP), on-line computation.

The CHIMERA 4[pi] detector trigger system is described. The trigger decisions are based on a combination of geometrical multiplicity of detected particles and other logic signals. The trigger can manage the buffer memory of the used analog to digital converters. This allows performance of parallel data conversion and readout and substantial improvement of the acquisition system dead-time performances. The trigger module generates all the necessary gate signals for the converters and the control signals necessary to synchronize the readout. It also allows the remote control of the whole system. Index Terms--4[pi] detector, data acquisition, dead time, parallel readout, trigger system.

In nuclear physics at intermediate energies, the use of multidetector arrays consisting of thousands of detectors is customary. This paper presents a novel approach to the automatic classification of data collected by the 4[Pi] detector CHIMERA, constituted by 1192 telescopes of a thin silicon transparent detector coupled to a thick CsI(TI) scintillator. The method is based on spatial density data processing and produces frequency distributions of the most significant physical parameters. These one-dimensional spectra can be more easily analyzed than the standard two-dimensional scatter plots. With respect to manual or semiautomatic procedures, presently used for data analysis, our method offers the advantages of drastic time reduction and unbiased criteria for cluster identification. The proposed method can be successfully used in both off-line data analysis and multidetector stability control. Index Terms--Clustering methods, image processing, nuclear measurements, visualization.

Presents a novel approach to the automatic classification of data collection by the CHIMERA detector. Importance of data classification to nuclear physics measurement; Details on the semiautomatic system; Conclusion.

Hospital-acquired legionellosis is a major problem. In Italy this issue is still underestimated because the reported figures are lower than the actual cases. This is probably due to a lack of diagnosis and monitoring. In Sicily, no cases of hospital-acquired legionellosis were reported in the last few years. In the year 2001, a reference laboratory was set up to help health authorities monitor and prevent hospital-acquired legionellosis. The authors report the data concerning a measure of environmental monitoring and water treatment carried out in a hospital where no legionellosis was ever detected before.