Intrinsic Ferromagnetic Impurity Phases in SmFeAsO1−x F x Detected by μSR

We report μSR measurements on SmFeAsO_1−x F _x which helped us to identify the signature of diluted ferromagnetic inclusions, ubiquitous in the iron pnictides. These impurities are characterized by a Curie temperature close to room temperature and they seem responsible for a non negligible magnetic relaxation of the implanted muons, which should not be confused with intrinsic pnictide properties.      

A contribution to the interpretation of polymer viscoelasticity in DMTA testing

Some ideas relevant to the prevailing viscoelasticity interpretations of dynamic mechanical thermal analysis (DMTA) experiments are presented. The main aspect is the inclusion of kinetic energy and inertia as variables, seeing the relaxing mass constantly increasing during strain, assigning inertial variation and not viscosity to energy dissipation. The equations developed make it possible to obtain the values of important viscoelastic properties, under in any experimental condition, with the data taken from previous experiments.     

AlGaN/GaN MISHEMT with hBN as gate dielectric

Metal/Insulator/Semiconductor AlGaN/GaN High Electron Mobility Transistors (MISHEMTs) on sapphire substrate were fabricated with hexagonal Boron Nitride (hBN) thin film as gate dielectric. The hBN thin film, deposited by MW-PECVD, is an insulator permitting to obtain a low leakage current gate, an interface state density as low as 5 × 1011 cm^? 2 eV^? 1 for hBN/AlGaN interface and low roughness surface less than 0.4 nm. HBN thin film is deposited to have optical c-axis oriented weakly tilted to the perpendicular at the AlGaN barrier surface and to increase the lateral electrical resistivity. DC measurement on MISHEMT exhibits promising performance for microwave power devices associated to a good gate charge control in enhancement mode.     

Fast algorithms for nonparametric population modeling of large data sets

Population models are widely applied in biomedical data analysis since they characterize both the average and individual responses of a population of subjects. In the absence of a reliable mechanistic model, one can resort to the Bayesian nonparametric approach that models the individual curves as Gaussian processes. This paper develops an efficient computational scheme for estimating the average and individual curves from large data sets collected in standardized experiments, i.e. with a fixed sampling schedule. It is shown that the overall scheme exhibits a “client-server” architecture. The server is in charge of handling and processing the collective data base of past experiments. The clients ask the server for the information needed to reconstruct the individual curve in a single new experiment. This architecture allows the clients to take advantage of the overall data set without violating possible privacy and confidentiality constraints and with negligible computational effort.     

Synthetic single crystal diamond dosimeters for Intensity Modulated Radiation Therapy applications

A synthetic single crystal diamond Schottky diode, in a p-type/intrinsic/metal structure, deposited by Chemical Vapour Deposition (CVD) and operating in photovoltaic regime, with no external bias voltage applied, was tested as a dosimeter for Intensity Modulated Radiation Therapy (IMRT) applications. The device response was compared with dose measurements from two commercial ionization chambers and a 2D diode array in an IMRT prostate cancer treatment plan. The obtained results indicate that CVD synthetic single crystal diamond-based dosimeters can successfully be used for highly conformed radiotherapy and IMRT dosimetry, due to their small size and high sensitivity per unit volume.     

Advanced Adaptive Sonar for Mapping Applications

An advanced adaptive sonar module is described, capable of being configured to different circumstances and distances according to reflectors found in the environment. Thanks to the sensory distribution, it is possible to identify three basic types of reflector (planes, edges and corners). Furthermore, a heuristic map of the environment is built. The proposed methods have been computationally optimized, and implemented in a real-time system based on a Field-Programmable Gate Array (FPGA) and a Digital Signal Processor (DSP). Results have been obtained in the detection, classification and mapping of obstacles; and finally testing has been carried out on a commercial vehicle.     

Cluster-grouping: from subgroup discovery to clustering

We introduce the problem of cluster-grouping and show that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and classification. The algorithm CG for solving cluster-grouping problems is then introduced, and it is incorporated as a component in several existing and novel algorithms for tackling subgroup discovery, clustering and classification. The resulting systems are empirically compared to state-of-the-art systems such as CN2, CBA, Ripper, Autoclass and CobWeb. The results indicate that the CG algorithm can be useful as a generic local pattern mining component in a wide variety of data mining and machine learning algorithms.     

Spray formation of middle distillates for autothermal reforming

The reforming of diesel and diesel-like fuels plays a central role in the development of fuel cell systems for on-board power supplies. The vaporization of the fuel via a spray formation and the subsequent mixture with water vapor and air determine the quality of the reforming process, as is shown in this paper. By using a high quality nozzle residual hydrocarbons were below 25 ppmV during the reforming of standard diesel. Through the use of a fuel injector in pulsed operation, the load range was able to be increased from 1:1.67 to 1:6. Spray pattern analyses were conducted using a high-speed camera. The formation of the spray pattern lasted 1.5–2 ms. The testing of a fast-closing magnetic valve manufactured by GSR Ventiltechnik was carried out on the autothermal reformer (ATR) type AH2. It exist not any direct influence of the pulsed operation on hydrogen production.     

SRAM dynamic stability estimation using MPFP and its applications

In this paper, an accurate approach for estimating the dynamic stability of static random access memory (SRAM) is proposed. The conventional methods of SRAM stability estimation suffer from two major drawbacks: (1) using static failure criteria, such as SNM, which does not capture the transient and dynamic behavior of SRAM operation, and (2) using quasi-Monte-Carlo simulation, which approximates the failure distribution, resulting in large errors at the tails where the desired failure probabilities exist. These drawbacks are eliminated by employing accurate simulation-based dynamic failure criteria along with a new distribution-independent, Most-probable-failure-point search technique for accurate probability calculation. Compared to previously published techniques, the proposed dynamic stability technique offers orders of magnitude improvement in accuracy. Furthermore, the proposed dynamic stability technique enables the correct evaluation of stability in real operation conditions and for different dynamic circuit techniques, such as dynamic write back, where the conventional methods are not applicable.