Transient Annealing in Sekiconductor Devices Following Pulsed Neutron Irradiation

Transient annealing following pulsed neutron exposure has been investigated in silicon transistors and solar cells as a function of both irradiation temperature and injection level. In addition, experiments incorporating both X and gamma ray irradiation have demonstrated that transient annealing is a bulk, not a surface, effect. The observed annealing following neutron irradiation is considerably slower at low temperatures than at room temperature. At 213°K thg density of annealable defects remaining at 10-10 seconds after exposure is approximately three times that observed at this same time for a 300°K irradiation. The injection studies show that at any temperatures from 76°K to 300°K the presence of minority carrier injection considerably speeds the transient annealing processes. A model is presented which explains many of the features observed in transient annealing. Various kinetic processes are discussed in the derivation of this model, including diffusion-limited and generation-limited processes, and the results of the model are compared with experimental data.     

Calibration of dosemeters used in mammography with different X ray qualities: EUROMET project no. 526

The effect of different X ray radiation qualities on the calibration of mammographic dosemeters was investigated within the framework of a EUROMET (European Collaboration in Measurement Standards) project. The calibration coefficients for two ionization chambers and two semiconductor detectors were established in 13 dosimetry calibration laboratories for radiation qualities used in mammography. They were compared with coefficients for other radiation qualities, including those defined in ISO 4037-1, with first half value layers in the mammographic range. The results indicate that the choice of the radiation quality is not crucial for instruments with a small energy dependence of the response. However, the radiation quality has to be chosen carefully if instruments with a marked dependence of their response to the radiation energy are calibrated.     

Using matrix peaks to map topography: increased mass resolution and enhanced sensitivity in chemical imaging

It is well known in secondary ion mass spectrometry (SIMS) that sample topography leads to decreased mass resolution. Specifically, the ion's time of flight is dependent on where it was generated. Here, using matrix-enhanced SIMS, it is demonstrated that, in addition to increasing the yield of intact pseudomolecular ions, the matrix allows the user to semiquantitatively record the topography of a sample. Through mapping the topography-related mass shifts of the matrix (which leads to decreased mass resolution), the analogous mass shifts of higher mass ions can be deconvoluted and higher resolution and greater sensitivity obtained. Furthermore, the semiquantitative topographical map obtained can be compared with any chemical images obtained, allowing the user to quickly ascertain whether local intensity maximums are due to topological features or represent genuine features of interest.     

Clearing the mind: A working memory model of distraction from negative mood.

The present research examined whether and how loading working memory can attenuate negative mood. In three experiments, participants were exposed to neutral, weakly negative, or strongly negative pictures followed by a task and a mood scale. Working memory demands were varied by manipulating task presence (Study 1), complexity (Study 2), and predictability (Study 3). Participants in all three experiments reported less negative moods in negative trials with high compared to low working memory demand. Working memory demands did not affect mood in the neutral trials. When working memory demands were high, participants no longer reported more negative moods in response to strongly negative pictures than to weakly negative pictures. These findings suggest that loading working memory prevents mood-congruent processing, and thereby promotes distraction from negative moods. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Verification of cardiac tissue electrophysiology simulators using an N-version benchmark

Ongoing developments in cardiac modelling have resulted, in particular, in the development of advanced and increasingly complex computational frameworks for simulating cardiac tissue electrophysiology. The goal of these simulations is often to represent the detailed physiology and pathologies of the heart using codes that exploit the computational potential of high-performance computing architectures. These developments have rapidly progressed the simulation capacity of cardiac virtual physiological human style models; however, they have also made it increasingly challenging to verify that a given code provides a faithful representation of the purported governing equations and corresponding solution techniques. This study provides the first cardiac tissue electrophysiology simulation benchmark to allow these codes to be verified. The benchmark was successfully evaluated on 11 simulation platforms to generate a consensus gold-standard converged solution. The benchmark definition in combination with the gold-standard solution can now be used to verify new simulation codes and numerical methods in the future.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper

In this study several pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment are evaluated. GeoCBI (Geo Composite Burn Index) field data of burn severity were correlated with remotely sensed measures, based on the NBR (Normalized Burn Ratio), the NDMI (Normalized Difference Moisture Index) and the NDVI (Normalized Difference Vegetation Index). In addition, the strength of the correlation was evaluated for specific fuel types and the influence of the regression model type is pointed out. The NBR was the best remotely sensed index for assessing burn severity, followed by the NDMI and the NDVI. For this case study of the 2007 Peloponnese fires, results show that the GeoCBI–dNBR (differenced NBR) approach yields a moderate–high R ²?=?0.65. Absolute indices outperformed their relative equivalents, which accounted for pre-fire vegetation state. The GeoCBI–dNBR relationship was stronger for forested ecotypes than for shrub lands. The relationship between the field data and the dNBR and dNDMI (differenced NDMI) was nonlinear, while the GeoCBI–dNDVI (differenced NDVI) relationship appeared linear.