Readout Concepts for DEPFET Pixel Arrays

Field effect transistors embedded into a depleted silicon bulk (DEPFETs) can be used as the first amplifying element for the detection of small signal charges deposited in the bulk by ionizing particles, X-ray photons or visible light. Very good noise performance at room temperature due to the low capacitance of the collecting electrode has been demonstrated. Regular two dimensional arrangements of DEPFETs can be read out by turning on individual rows and reading currents or voltages in the columns. Such arrangements allow the fast, low power readout of larger arrays with the possibility of random access to selected pixels. In this paper, different readout concepts are discussed as they are required for arrays with incomplete or complete clear and for readout at the source or the drain. Examples of VLSI chips for the steering of the gate and clear rows and for reading out the columns are presented.Comment: 8 pages, 9 figures, submitted to Nucl. Instr. and Methods as proceedings of the 9th European Symposium on Semiconductor Detectors, Elmau, June 23-27, 200

An analysis of production procedures in the stage play Harriet

It is the purpose of this thesis to present the research, planning, and actual production procedures of the play entitled Harriet, as written by Florence Ryerson and Colin Clements. This is the production which was originally done by Gilbert Miller at Henry Miller\u27s Theatre in 1943 with Miss Helen Hayes in the title role

Narrow beam dosimetry for high-energy hadrons and electrons

Organ doses and effective dose were calculated with the latest version of the Monte Carlo transport code FLUKA in the case of an anthropomorphic mathematical model exposed to monoenergetic narrow beams of protons, pions and electrons in the energy range 10°— 400 GeV. The target organs considered were right eye, thyroid, thymus, lung and breast. Simple scaling laws to the calculated values are given. The present data and formula should prove useful for dosimetric estimations in case of accidental exposures to high-energy beams

Expert System for Bomb Factory Detection by Networks of Advance Sensors

Abstract: (1) Background: Police forces and security administrations are nowadays considering Improvised explosives (IEs) as a major threat. The chemical substances used to prepare IEs are called precursors, and their presence could allow police forces to locate a bomb factory where the on-going manufacturing of IEs is carried out. (2) Methods: An expert system was developed and tested in handling signals from a network of sensors, allowing an early warning. The expert system allows the detection of one precursor based on the signal provided by a single sensor, the detection of one precursor based on the signal provided by more than one sensor, and the production of a global alarm level based on data fusion from all the sensors of the network. (3) Results: The expert system was tested in the Italian Air Force base of Pratica di Mare (Italy) and in the Swedish Defence Research Agency (FOI) in Grindsjön (Sweden). (4) Conclusion: The performance of the expert system was successfully evaluated under relevant environmental conditions. The approach used in the development of the expert system allows maximum flexibility in terms of integration of the response provided by any sensor, allowing to easily include in the network all possible new sensors

Analysis of housing risk factors for the welfare of lean and heavy pigs in a sample of european fattening farms

SIMPLE SUMMARY: Animal welfare is a major challenge that most European pig producers have been facing in recent decades to comply with EU legislation and to meet the increasing societal and market demand for pork produced in a sustainable way. Pig welfare is ruled in terms of minimum requirements for housing and management, but stakeholders have considered that both farm-level and animal-based indicators are fundamental to monitor animal welfare. Some of the welfare issues still affecting fattening pigs are the lack of space, bedding and manipulable material, and the continued practice of routine tail docking of pigs. Tail docking is applied routinely across most European countries to reduce the occurrence of severe tail biting lesions, despite its ban in the EU. An observational study on 51 pig farms in seven EU countries, aimed at investigating housing risk factors for the welfare of finishing pigs, showed that body weight and presence of bedded solid floored resting area (BED) identify three clusters of farms. The outcomes of this study confirmed that BED and larger availability of space per pig, above the minimum requirement of EU legislation, can limit the occurrence of lesions in pigs with undocked tails. ABSTRACT: Pig welfare is affected by housing conditions, the minimum requirements of which are set up by EU legislation. Animal and non-animal-based measures are useful indicators to investigate housing risk factors for pig welfare. An observational study on 51 pig farms in seven EU countries, aimed at investigating housing risk factors for the welfare of finishing pigs, showed body weight and presence of bedded solid floored resting area (BED) identifying three clusters of farms. Farms with BED were featured by no or limited tail docking, larger availability of manipulable materials and lower number of pigs per farm and per annual work unit. In these farms, less skin and ear lesions were found, compared with lean pigs of farms without BED, which were characterized by lower pig space allowance, mortality rate and medication cost. In farms without BED, heavy pigs were featured by more space per pig, more pigs per drinker and higher mortality rate and medication cost per pig, compared to lean pigs. No statistical difference in tail lesions was found between the three farm clusters, although tail docking was performed in all farms without BED and not performed on most farms with BED

Practical comparison of sparse methods for classification of Arabica and Robusta coffee species using near infrared hyperspectral imaging

In the present work sparse-based methods are applied to the analysis of hyperspectral images with the aim at studying their capability of being adequate methods for variable selection in a classification framework. The key aspect of sparse methods is the possibility of performing variable selection by forcing the model coefficients related to irrelevant variables to zero. In particular, two different sparse classification approaches, i.e. sPCA+kNN and sPLS-DA, were compared with the corresponding classical methods (PCA + kNN and PLS-DA) to classify Arabica and Robusta coffee species. Green coffee samples were analyzed using near infrared hyperspectral imaging and the average spectra from each hyperspectral image were used to build training and test sets; furthermore a test image was used to evaluate the performances of the considered methods at pixel-level. In our case, sparse methods led to similar results as classical methods, with the advantage of obtaining more interpretable and parsimonious models. An important result to highlight is that variable selection performed with two different sparse classification approaches converged to the selection of same spectral regions, which implies the chemical relevance of those regions in the discrimination of Arabica and Robusta coffee species

Colourgrams GUI: A graphical user-friendly interface for the analysis of large datasets of RGB images

Colourgrams GUI is a graphical user-friendly interface developed in order to facilitate the analysis of large datasets of RGB images through the colourgrams approach. Briefly, the colourgrams approach consists in converting a dataset of RGB images into a matrix of one-dimensional signals, the colourgrams, each one codifying the colour content of the corresponding original image. This matrix of signals can be in turn analysed by means of common multivariate statistical methods, such as Principal Component Analysis (PCA) for exploratory analysis of the image dataset, or Partial Least Squares (PLS) regression for the quantification of colour-related properties of interest. Colourgrams GUI allows to easily convert the dataset of RGB images into the colourgrams matrix, to interactively visualize the signals coloured according to qualitative and/or quantitative properties of the corresponding samples and to visualize the colour features corresponding to selected colourgram regions into the image domain. In addition, the software also allows to analyse the colourgrams matrix by means of PCA and PLS