Spectral Analysis of GRBs Measured by RHESSI

The Ge spectrometer of the RHESSI satellite is sensitive to Gamma Ray Bursts (GRBs) from about 40 keV up to 17 MeV, thus ideally complementing the Swift/BAT instrument whose sensitivity decreases above 150 keV. We present preliminary results of spectral fits of RHESSI GRB data. After describing our method, the RHESSI results are discussed and compared with Swift and Konus.Comment: 4 pages, 4 figures, conference proceedings, 'Swift and GRBs: Unveiling the Relativistic Universe', San Servolo, Venice, 5-9 June 2006, to appear in Il Nouvo Ciment

Modeling Aerial Gamma-Ray Backgrounds using Non-negative Matrix Factorization

Airborne gamma-ray surveys are useful for many applications, ranging from geology and mining to public health and nuclear security. In all these contexts, the ability to decompose a measured spectrum into a linear combination of background source terms can provide useful insights into the data and lead to improvements over techniques that use spectral energy windows. Multiple methods for the linear decomposition of spectra exist but are subject to various drawbacks, such as allowing negative photon fluxes or requiring detailed Monte Carlo modeling. We propose using Non-negative Matrix Factorization (NMF) as a data-driven approach to spectral decomposition. Using aerial surveys that include flights over water, we demonstrate that the mathematical approach of NMF finds physically relevant structure in aerial gamma-ray background, namely that measured spectra can be expressed as the sum of nearby terrestrial emission, distant terrestrial emission, and radon and cosmic emission. These NMF background components are compared to the background components obtained using Noise-Adjusted Singular Value Decomposition (NASVD), which contain negative photon fluxes and thus do not represent emission spectra in as straightforward a way. Finally, we comment on potential areas of research that are enabled by NMF decompositions, such as new approaches to spectral anomaly detection and data fusion.Comment: 14 pages, 12 figures, accepted for publication in IEEE Transactions on Nuclear Scienc

Background and Anomaly Learning Methods for Static Gamma-ray Detectors

Static gamma-ray detector systems that are deployed outdoors for radiological monitoring purposes experience time- and spatially-varying natural backgrounds and encounters with man-made nuisance sources. In order to be sensitive to illicit sources, such systems must be able to distinguish those sources from benign variations due to, e.g., weather and human activity. In addition to fluctuations due to non-threats, each detector has its own response and energy resolution, so providing a large network of detectors with predetermined background and source templates can be an onerous task. Instead, we propose that static detectors use simple physics-informed algorithms to automatically learn the background and nuisance source signatures, which can them be used to bootstrap and feed into more complex algorithms. Specifically, we show that non-negative matrix factorization (NMF) can be used to distinguish static background from the effects of increased concentrations of radon progeny due to rainfall. We also show that a simple process of using multiple gross count rate filters can be used in real time to classify or ``triage'' spectra according to whether they belong to static, rain, or anomalous categories for processing with other algorithms. If a rain sensor is available, we propose a method to incorporate that signal as well. Two clustering methods for anomalous spectra are proposed, one using Kullback-Leibler divergence and the other using regularized NMF, with the goal of finding clusters of similar spectral anomalies that can be used to build anomaly templates. Finally we describe the issues involved in the implementation of some of these algorithms on deployed sensor nodes, including the need to monitor the background models for long-term drifting due to physical changes in the environment or changes in detector performance.Comment: 12 pages, 6 figures, accepted for publication in IEEE Transactions on Nuclear Scienc

Observations of the Prompt Gamma-Ray Emission of GRB 070125

The long, bright gamma-ray burst GRB 070125 was localized by the Interplanetary Network. We present light curves of the prompt gamma-ray emission as observed by Konus-WIND, RHESSI, Suzaku-WAM, and \textit{Swift}-BAT. We detail the results of joint spectral fits with Konus and RHESSI data. The burst shows moderate hard-to-soft evolution in its multi-peaked emission over a period of about one minute. The total burst fluence as observed by Konus is $1.79 \times 10^{-4}$ erg/cm$^2$ (20 keV--10 MeV). Using the spectroscopic redshift $z=1.548$, we find that the burst is consistent with the ``Amati'' $E_{peak,i}-E_{iso}$ correlation. Assuming a jet opening angle derived from broadband modeling of the burst afterglow, GRB 070125 is a significant outlier to the ``Ghirlanda'' $E_{peak,i}-E_\gamma$ correlation. Its collimation-corrected energy release $E_\gamma = 2.5 \times 10^{52}$ ergs is the largest yet observed.Comment: 25 pages, 6 figures; accepted for publication in ApJ. Improved spectral fits and energetics estimate

The state of the art in non-pharmacological interventions for developmental stuttering. Part 1: a systematic review of effectiveness

Background The growing range of available treatment options for people who stutter presents a challenge for clinicians, service managers and commissioners, who need to have access to the best available treatment evidence to guide them in providing the most appropriate interventions. While a number of reviews of interventions for specific populations or a specific type of intervention have been carried out, a broad-based systematic review across all forms of intervention for adults and children was needed to provide evidence to underpin future guidelines, inform the implementation of effective treatments and identify future research priorities. Aims To identify and synthesize the published research evidence on the clinical effectiveness of the broad range of non-pharmacological interventions for the management of developmental stuttering. Methods & Procedures A systematic review of the literature reporting interventions for developmental stuttering was carried out between August 2013 and April 2014. Searches were not limited by language or location, but were restricted by date to studies published from 1990 onwards. Methods for the identification of relevant studies included electronic database searching, reference list checking, citation searching and hand searching of key journals. Appraisal of study quality was performed using a tool based on established criteria for considering risk of bias. Due to heterogeneity in intervention content and outcomes, a narrative synthesis was completed. Main Contribution The review included all available types of intervention and found that most may be of benefit to at least some people who stutter. There was evidence, however, of considerable individual variation in response to these interventions. The review indicated that effects could be maintained following all types of interventions (although this was weakest with regard to feedback and technology interventions). Conclusions This review highlights a need for greater consensus with regard to the key outcomes used to evaluate stuttering interventions, and also a need for enhanced understanding of the process whereby interventions effect change. Further analysis of the variation in effectiveness for different individuals or groups is needed in order to identify who may benefit most from which intervention

Should digestion assays be used to estimate persistence of potential allergens in tests for safety of novel food proteins?

Food allergies affect an estimated 3 to 4% of adults and up to 8% of children in developed western countries. Results from in vitro simulated gastric digestion studies with purified proteins are routinely used to assess the allergenic potential of novel food proteins. The digestion of purified proteins in simulated gastric fluid typically progresses in an exponential fashion allowing persistence to be quantified using pseudo-first-order rate constants or half lives. However, the persistence of purified proteins in simulated gastric fluid is a poor predictor of the allergenic status of food proteins, potentially due to food matrix effects that can be significant in vivo. The evaluation of the persistence of novel proteins in whole, prepared food exposed to simulated gastric fluid may provide a more correlative result, but such assays should be thoroughly validated to demonstrate a predictive capacity before they are accepted to predict the allergenic potential of novel food proteins

Brain classification reveals the right cerebellum as the best biomarker of dyslexia

Background Developmental dyslexia is a specific cognitive disorder in reading acquisition that has genetic and neurological origins. Despite histological evidence for brain differences in dyslexia, we recently demonstrated that in large cohort of subjects, no differences between control and dyslexic readers can be found at the macroscopic level (MRI voxel), because of large variances in brain local volumes. In the present study, we aimed at finding brain areas that most discriminate dyslexic from control normal readers despite the large variance across subjects. After segmenting brain grey matter, normalizing brain size and shape and modulating the voxels' content, normal readers' brains were used to build a 'typical' brain via bootstrapped confidence intervals. Each dyslexic reader's brain was then classified independently at each voxel as being within or outside the normal range. We used this simple strategy to build a brain map showing regional percentages of differences between groups. The significance of this map was then assessed using a randomization technique. Results The right cerebellar declive and the right lentiform nucleus were the two areas that significantly differed the most between groups with 100% of the dyslexic subjects (N = 38) falling outside of the control group (N = 39) 95% confidence interval boundaries. The clinical relevance of this result was assessed by inquiring cognitive brain-based differences among dyslexic brain subgroups in comparison to normal readers' performances. The strongest difference between dyslexic subgroups was observed between subjects with lower cerebellar declive (LCD) grey matter volumes than controls and subjects with higher cerebellar declive (HCD) grey matter volumes than controls. Dyslexic subjects with LCD volumes performed worse than subjects with HCD volumes in phonologically and lexicon related tasks. Furthermore, cerebellar and lentiform grey matter volumes interacted in dyslexic subjects, so that lower and higher lentiform grey matter volumes compared to controls differently modulated the phonological and lexical performances. Best performances (observed in controls) corresponded to an optimal value of grey matter and they dropped for higher or lower volumes. Conclusion These results provide evidence for the existence of various subtypes of dyslexia characterized by different brain phenotypes. In addition, behavioural analyses suggest that these brain phenotypes relate to different deficits of automatization of language-based processes such as grapheme/phoneme correspondence and/or rapid access to lexicon entries. article available here: http://www.biomedcentral.com/1471-2202/10/6

Resting-State Brain Activity in Adult Males Who Stutter

Although developmental stuttering has been extensively studied with structural and task-based functional magnetic resonance imaging (fMRI), few studies have focused on resting-state brain activity in this disorder. We investigated resting-state brain activity of stuttering subjects by analyzing the amplitude of low-frequency fluctuation (ALFF), region of interest (ROI)-based functional connectivity (FC) and independent component analysis (ICA)-based FC. Forty-four adult males with developmental stuttering and 46 age-matched fluent male controls were scanned using resting-state fMRI. ALFF, ROI-based FCs and ICA-based FCs were compared between male stuttering subjects and fluent controls in a voxel-wise manner. Compared with fluent controls, stuttering subjects showed increased ALFF in left brain areas related to speech motor and auditory functions and bilateral prefrontal cortices related to cognitive control. However, stuttering subjects showed decreased ALFF in the left posterior language reception area and bilateral non-speech motor areas. ROI-based FC analysis revealed decreased FC between the posterior language area involved in the perception and decoding of sensory information and anterior brain area involved in the initiation of speech motor function, as well as increased FC within anterior or posterior speech- and language-associated areas and between the prefrontal areas and default-mode network (DMN) in stuttering subjects. ICA showed that stuttering subjects had decreased FC in the DMN and increased FC in the sensorimotor network. Our findings support the concept that stuttering subjects have deficits in multiple functional systems (motor, language, auditory and DMN) and in the connections between them

Metabolic Profiling of an Echinostoma caproni Infection in the Mouse for Biomarker Discovery

Consumption of raw fish and other freshwater products can lead to unpleasant worm infections. Indeed, such worm infections are of growing public health and veterinary concern, but they are often neglected, partially explained by the difficulty of accurate diagnosis. In the present study we infected 12 mice with an intestinal worm (i.e., Echinostoma caproni) and collected blood, stool, and urine samples 7 times between 1 and 33 days after the infection. At the same time points, blood, stool, and urine were also sampled from 12 uninfected mice. These biofluid samples were examined with a spectrometer and data were analyzed with a multivariate approach. We observed important differences between the infected and the uninfected control animals. For example, we found an increased level of branched chain amino acids in the stool of infected mice and subsequent depletion in blood plasma. Additionally, we observed changes related to a disturbed intestinal bacterial composition, particularly in urine and stool. The combination of results from the three types of biofluids gave the most comprehensive characterization of an E. caproni infection in the mouse. Urine would be the biofluid of choice for diagnosis of an infection because the ease of sample collection and the high number and extent of changed metabolites