Study on the response of IFMIF fission chambers to mixed neutron-gamma fields: PH-2 experimental tests

The engineering design of fissionchambers as on-line radiation detectors for IFMIF is being performed in the framework of the IFMIF-EVEDA works. In this paper the results of the experiments performed in the BR2 reactor during the phase-2 of the foreseen validation activities are addressed. Two detectors have been tested in a mixedneutron-gamma field with high neutron fluence and gamma absorbed dose rates, comparable with the expected values in the HFTM in IFMIF. Since the neutron spectra in all BR2 channels are dominated by the thermal neutron component, the detectors have been surrounded by a cylindrical gadolinium screen to cut the thermal neutron component, in order to get a more representative test for IFMIF conditions. The integrated gamma absorbed dose was about 4 × 1010 Gy and the fast neutron fluence (E > 0.1 MeV) 4 × 1020 n/cm2. The fissionchambers were calibrated in three BR2 channels with different neutron-to-gamma ratio, and the long-term evolution of the signals was studied and compared with theoretical calculations

A Comparison of different Uncertainty Activation Cross-Section Data Libraries and collapsed values for different neutron spectra: ADS, FISSION and FUSION

PART I:Cross-section uncertainties under differentneutron spectra. PART II: Processing uncertainty libraries

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations

Complexity analysis of spontaneous brain activity: effects of depression and antidepressant treatment

Magnetoencephalography (MEG) allows the real-time recording of neural activity and oscillatory activity in distributed neural networks. We applied a non-linear complexity analysis to resting-state neural activity as measured using whole-head MEG. Recordings were obtained from 20 unmedicated patients with major depressive disorder and 19 matched healthy controls. Subsequently, after 6 months of pharmacological treatment with the antidepressant mirtazapine 30 mg/day, patients received a second MEG scan. A measure of the complexity of neural signals, the Lempel–Ziv Complexity (LZC), was derived from the MEG time series. We found that depressed patients showed higher pre-treatment complexity values compared with controls, and that complexity values decreased after 6 months of effective pharmacological treatment, although this effect was statistically significant only in younger patients. The main treatment effect was to recover the tendency observed in controls of a positive correlation between age and complexity values. Importantly, the reduction of complexity with treatment correlated with the degree of clinical symptom remission. We suggest that LZC, a formal measure of neural activity complexity, is sensitive to the dynamic physiological changes observed in depression and may potentially offer an objective marker of depression and its remission after treatment.

Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

GRS Results for the Burnup Pin-cell Benchmark Propagation of Cross-Section, Fission Yields and Decay Data Uncertainties

GRS Results for the Burnup Pin-cell Benchmark Propagation of Cross-Section, Fission Yields and Decay Data Uncertainties

Generation of Fission Yield covariance data and application to Fission Pulse Decay Heat calculations

Generation of Fission Yield covariance data and application to Fission Pulse Decay Heat calculations

Application of a Bayesian/Generalised Least-Squares method to generate correlations between independent neutron fission yield data

Fission product yields are fundamental parameters for several nuclear engineering calculations and in particular for burn-up/activation problems. The impact of their uncertainties was widely studied in the past and valuations were released, although still incomplete. Recently, the nuclear community expressed the need for full fission yield covariance matrices to produce inventory calculation results that take into account the complete uncertainty data. In this work, we studied and applied a Bayesian/generalised least-squares method for covariance generation, and compared the generated uncertainties to the original data stored in the JEFF-3.1.2 library. Then, we focused on the effect of fission yield covariance information on fission pulse decay heat results for thermal fission of 235U. Calculations were carried out using different codes (ACAB and ALEPH-2) after introducing the new covariance values. Results were compared with those obtained with the uncertainty data currently provided by the library. The uncertainty quantification was performed with the Monte Carlo sampling technique. Indeed, correlations between fission yields strongly affect the statistics of decay heat. Introduction Nowadays, any engineering calculation performed in the nuclear field should be accompanied by an uncertainty analysis. In such an analysis, different sources of uncertainties are taken into account. Works such as those performed under the UAM project (Ivanov, et al., 2013) treat nuclear data as a source of uncertainty, in particular cross-section data for which uncertainties given in the form of covariance matrices are already provided in the major nuclear data libraries. Meanwhile, fission yield uncertainties were often neglected or treated shallowly, because their effects were considered of second order compared to cross-sections (Garcia-Herranz, et al., 2010). However, the Working Party on International Nuclear Data Evaluation Co-operation (WPEC)

Testing JEFF-3.1.1 and ENDF/B-VII.1 Decay and Fission Yield Nuclear Data Libraries with Fission Pulse Neutron Emission and Decay Heat Experiments

The aim of this work is to test the present status of Evaluated Nuclear Decay and Fission Yield Data Libraries to predict decay heat and delayed neutron emission rate, average neutron energy and neutron delayed spectra after a neutron fission pulse. Calculations are performed with JEFF-3.1.1 and ENDF/B-VII.1, and these are compared with experimental values. An uncertainty propagation assessment of the current nuclear data uncertainties is performed.

Propagation of Neutron Cross Section, Fission Yield, and Decay Data Uncertainties in Depletion Calculations

Propagation of nuclear data uncertainties in reactor calculations is interesting for design purposes and libraries evaluation. Previous versions of the GRS XSUSA library propagated only neutron cross section uncertainties. We have extended XSUSA uncertainty assessment capabilities by including propagation of fission yields and decay data uncertainties due to the their relevance in depletion simulations. We apply this extended methodology to the UAM6 PWR Pin-Cell Burnup Benchmark, which involves uncertainty propagation through burnup.

Towards a complete propagation of nuclear data uncertainties Fission yields and decay data

Propagation of nuclear data uncertainties to calculated values is interesting for design purposes and libraries evaluation. XSUSA, developed at GRS, propagates cross section uncertainties to nuclear calculations. In depletion simulations, fission yields and decay data are also involved and suppose a possible source of uncertainty that must be taken into account. We have developed tools to generate varied fission yields and decay libraries and to propagate uncertainties trough depletion in order to complete the XSUSA uncertainty assessment capabilities. A simple test to probe the methodology is defined and discussed.

Characterization of spontaneous combustuion tendency of dried sewage sludge

The general purpose of this study was the determination of the safety conditions to avoid the presence of explosive atmospheres in the wastewater industry. Eight Spanish plants located in Madrid, Barcelona and Málaga were considered and several sludge samples were taken in different seasons. The base for the assessment of the spontaneous ignition behaviour of dust accumulations is the experimental determination of the self-ignition temperature under isothermal conditions. Self-ignition temperatures at four volumes were obtained for one sample of sewage sludge, allowing their extrapolation to large storage facilities. A simple test method, based also on an isothermal study of samples, is the UN classification of substances liable to spontaneous combustion. Two different samples were so tested, obtaining unlike results if transported in packages of different volumes. By means of thermogravimetric techniques it is possible to analyse the thermal susceptibility of dried sewage sludge. Apparent activation energy can be obtained from the rate of weight loss. It is also applied to the study of self-ignition susceptibility by modifying test conditions when oxygen stream is introduced. As a consequence of this oxidant contribution, sample behaviour can be very different during testing and a step drop or sudden loss of weight is observed at a characteristic temperature for every substance, associated to a rapid combustion. Plotting both the activation energy and the characteristic temperature, a map of self-ignition risk was obtained for 10 samples, showing different risk levels for samples taken in different locations and at different seasons. A prediction of the self-ignition risk level can be also determined.

Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment

The neurophysiological changes associated with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) include an increase in low frequency activity, as measured with electroencephalography or magnetoencephalography (MEG). A relevant property of spectral measures is the alpha peak, which corresponds to the dominant alpha rhythm. Here we studied the spatial distribution of MEG resting state alpha peak frequency and amplitude values in a sample of 27 MCI patients and 24 age-matched healthy controls. Power spectra were reconstructed in source space with linearly constrained minimum variance beamformer. Then, 88 Regions of Interest (ROIs) were defined and an alpha peak per ROI and subject was identified. Statistical analyses were performed at every ROI, accounting for age, sex and educational level. Peak frequency was significantly decreased (p < 0.05) in MCIs in many posterior ROIs. The average peak frequency over all ROIs was 9.68 ± 0.71 Hz for controls and 9.05 ± 0.90 Hz for MCIs and the average normalized amplitude was (2.57 ± 0.59)·10−2 for controls and (2.70 ± 0.49)·10−2 for MCIs. Age and gender were also found to play a role in the alpha peak, since its frequency was higher in females than in males in posterior ROIs and correlated negatively with age in frontal ROIs. Furthermore, we examined the dependence of peak parameters with hippocampal volume, which is a commonly used marker of early structural AD-related damage. Peak frequency was positively correlated with hippocampal volume in many posterior ROIs. Overall, these findings indicate a pathological alpha slowing in MCI.

A study on the lateralization of the effect of musical imagery on spontaneous otoacoustic emissions

It has been suggested that different pathways through the brain are followed depending on the type of information that is being processed. Although it is now known that there is a continuous exchange of information through both hemispheres, language is considered to be processed by the left hemisphere, where Broca?s and Wernicke?s areas are located. On the other hand, music is thought to be processed mainly by the right hemisphere. According to Sininger Y.S. & Cone- Wesson, B. (2004), there is a similar but contralateral specialization of the human ears; due to the fact that auditory pathways cross-over at the brainstem. A previous study showed an effect of musical imagery on spontaneous otoacoustic emissions (SOAEs) (Perez-Acosta and Ramos-Amezquita, 2006), providing evidence of an efferent influence from the auditory cortex on the basilar membrane. Based on these results, the present work is a comparative study between left and right ears of a population of eight musicians that presented SOAEs. A familiar musical tune was chosen, and the subjects were trained in the task of evoking it after having heard it. Samples of ear-canal signals were obtained and processed in order to extract frequency and amplitude data on the SOAEs. This procedure was carried out before, during and after the musical image creation task. Results were then analyzed to compare the difference between SOAE responses of left and right ears. A clear asymmetrical SOAEs response to musical imagery tasks between left and right ears was obtained. Significant changes of SOAE amplitude related to musical imagery tasks were only observed on the right ear of the subjects. These results may suggest a predominant left hemisphere activity related to a melodic image creation task.

An ontology-driven communication architecture for spontaneous interoperability in Home Automation systems

Current solutions to the interoperability problem in Home Automation systems are based on a priori agreements where protocols are standardized and later integrated through specific gateways. In this regards, spontaneous interoperability, or the ability to integrate new devices into the system with minimum planning in advance, is still considered a major challenge that requires new models of connectivity. In this paper we present an ontology-driven communication architecture whose main contribution is that it facilitates spontaneous interoperability at system model level by means of semantic integration. The architecture has been validated through a prototype and the main challenges for achieving complete spontaneous interoperability are also evaluated.