Partitioned Waveform Inversion Applied to Eurasia and Northern Africa

This report summarizes the data analysis achieved during Heather Bedle's eleven-week Technical Scholar internship at Lawrence Livermore National Labs during the early summer 2006. The work completed during this internship resulted in constraints on the crustal and upper mantle S-velocity structure in Northern Africa, the Mediterranean, the Middle East, and Europe, through the fitting of regional waveform data. This data extends current raypath coverage and will be included in a joint inversion along with data from surface wave group velocity measurements, S and P teleseismic arrival time data, and receiver function data to create an improved velocity model of the upper mantle in this region. The tectonic structure of the North African/Mediterranean/Europe/Middle Eastern study region is extremely heterogeneous. This region consists of, among others, stable cratons and platforms such as the West Africa Craton, and Baltica in Northern Europe; oceanic subduction zones throughout the Mediterranean Sea where the African and Eurasian plate collide; regions of continental collision as the Arabian Plate moves northward into the Turkish Plate; and rifting in the Red Sea, separating the Arabian and Nubian shields. With such diverse tectonic structures, many of the waveforms were difficult to fit. This is not unexpected as the waveforms are fit using an averaged structure. In many cases the raypaths encounter several tectonic features, complicating the waveform, and making it hard for the software to converge on a 1D average structure. Overall, the quality of the waveform data was average, with roughly 30% of the waveforms being discarded due to excessive noise that interfered with the frequency ranges of interest. An inversion for the 3D S-velocity structure of this region was also performed following the methodology of Partitioned Waveform Inversion (Nolet, 1990; Van der Lee and Nolet, 1997). The addition of the newly fit waveforms drastically extends the range of the model. The model now extends as far east in Africa to cover Chad and Niger, and reaches south to cover Zambia. The model is also stretched eastward to cover the eastern half of India, and northward to cover the southern portion of Scandinavia

Source and Propagation Characteristics of Explosive and Other Seismic Sources

Understanding of the source and propagation characteristics of seismic events of different types including earthquakes, explosions and mining-induced events is essential for successful discrimination of nuclear explosions. We are compiling a data set of mining related seismic events in east Eurasia. Natural earthquake data in the same region are also collected for comparison study between mining related events and earthquakes. The ground-truth data set will provide a unique and valuable resource for monitoring research. We will utilize the data set to investigate the source and propagation characteristics of seismic sources of different types including mine blasts, tremors, collapses and earthquakes. We will use various seismological techniques including spectral analysis, and waveform modeling to conduct the investigation. The research will improve our understanding of the S-wave excitation and propagation characteristics of chemical explosions and other source types

Enhancing Seismic Calibration Research Through Software Automation and Scientific Information Management

The National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research and Engineering (GNEM R&E) Program at LLNL has made significant progress enhancing the process of deriving seismic calibrations and performing scientific integration, analysis, and information management with software automation tools. Several achievements in schema design, data visualization, synthesis, and analysis were completed this year. Our tool efforts address the problematic issues of very large datasets and varied formats encountered during seismic calibration research. As data volumes have increased, scientific information management issues such as data quality assessment, ontology mapping, and metadata collection that are essential for production and validation of derived calibrations have negatively impacted researchers abilities to produce products. New information management and analysis tools have resulted in demonstrated gains in efficiency of producing scientific data products and improved accuracy of derived seismic calibrations. Significant software engineering and development efforts have produced an object-oriented framework that provides database centric coordination between scientific tools, users, and data. Nearly a half billion parameters, signals, measurements, and metadata entries are all stored in a relational database accessed by an extensive object-oriented multi-technology software framework that includes elements of stored procedures, real-time transactional database triggers and constraints, as well as coupled Java and C++ software libraries to handle the information interchange and validation requirements. Significant resources were applied to schema design to enable recording of processing flow and metadata. A core capability is the ability to rapidly select and present subsets of related signals and measurements to the researchers for analysis and distillation both visually (JAVA GUI client applications) and in batch mode (instantiation of multi-threaded applications on clusters of processors). Development of efficient data exploitation methods has become increasingly important throughout academic and government seismic research communities to address multi-disciplinary large scale initiatives. Effective frameworks must also simultaneously provide the researcher with robust measurement and analysis tools that can handle and extract groups of events effectively and isolate the researcher from the now onerous task of database management and metadata collection necessary for validation and error analysis. Sufficient information management robustness is required to avoid loss of metadata that would lead to incorrect calibration results in addition to increasing the data management burden. Our specific automation methodology and tools improve the researchers ability to assemble quality-controlled research products for delivery into the NNSA Knowledge Base (KB). The software and scientific automation tasks also provide the robust foundation upon which synergistic and efficient development of, GNEM R&E Program, seismic calibration research may be built

Deletion of PEA-15 in mice is associated with specific impairments of spatial learning abilities

<p>Abstract</p> <p>Background</p> <p>PEA-15 is a phosphoprotein that binds and regulates ERK MAP kinase and RSK2 and is highly expressed throughout the brain. PEA-15 alters c-Fos and CREB-mediated transcription as a result of these interactions. To determine if PEA-15 contributes to the function of the nervous system we tested mice lacking PEA-15 in a series of experiments designed to measure learning, sensory/motor function, and stress reactivity.</p> <p>Results</p> <p>We report that PEA-15 null mice exhibited impaired learning in three distinct spatial tasks, while they exhibited normal fear conditioning, passive avoidance, egocentric navigation, and odor discrimination. PEA-15 null mice also had deficient forepaw strength and in limited instances, heightened stress reactivity and/or anxiety. However, these non-cognitive variables did not appear to account for the observed spatial learning impairments. The null mice maintained normal weight, pain sensitivity, and coordination when compared to wild type controls.</p> <p>Conclusion</p> <p>We found that PEA-15 null mice have spatial learning disabilities that are similar to those of mice where ERK or RSK2 function is impaired. We suggest PEA-15 may be an essential regulator of ERK-dependent spatial learning.</p

SPE 1 Data Quicklook report

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Regional Seismic Discrimination Optimization With and Without Nuclear Test Data: Western U.S. Examples

The western U.S. has abundant natural seismicity, historic nuclear explosion data, and widespread mine blasts, making it a good testing ground to study the performance of regional source-type discrimination techniques. We have assembled and measured a large set of these events to systematically explore how to best optimize discrimination performance. Nuclear explosions can be discriminated from a background of earthquakes using regional phase (Pn, Pg, Sn, Lg) amplitude measures such as high frequency P/S ratios. The discrimination performance is improved if the amplitudes can be corrected for source size and path length effects. We show good results are achieved using earthquakes alone to calibrate for these effects with the MDAC technique (Walter and Taylor, 2001). We show significant further improvement is then possible by combining multiple MDAC amplitude ratios using an optimized weighting technique such as Linear Discriminant Analysis (LDA). However this requires data or models for both earthquakes and explosions. In many areas of the world regional distance nuclear explosion data is lacking, but mine blast data is available. Mine explosions are often designed to fracture and/or move rock, giving them different frequency and amplitude behavior than contained chemical shots, which seismically look like nuclear tests. Here we explore discrimination performance differences between explosion types, the possible disparity in the optimization parameters that would be chosen if only chemical explosions were available and the corresponding effect of that disparity on nuclear explosion discrimination. There are a variety of additional techniques in the literature also having the potential to improve regional high frequency P/S discrimination. We explore two of these here: three-component averaging and maximum phase amplitude measures. Typical discrimination studies use only the vertical component measures and for some historic regional nuclear records these are all that are available. However S-waves are often better recorded on the horizontal components and some studies have shown that using a three-component average or a vertical-P/horizontal-S or other three-component measure can improve discrimination over using the vertical alone (e.g. Kim et al. 1997; Bowers et al 2001). Here we compare the performance of vertical and three-component measures on the western U. S. test set. A complication in regional discrimination is the variation in P and S-wave propagation with region. The dominantly observed regional high frequency S-wave can vary with path between Sn and Lg in a spatially complex way. Since the relative lack of high frequency S-waves is the signature of an explosion, failing to account for this could lead to misidentifying an earthquake as an explosion. The regional P phases Pn and Pg vary similarly with path and also with distance, with Pg sometimes being a strong phase at near regional distances but not far regional. One way to try and handle these issues is to correct for all four regional phases but choose the phase with the maximum amplitude. A variation on this strategy is to always use Pn but choose the maximum S phase (e.g. Bottone et al. 2002). Here we compare the discrimination performance of several different (max P)/(max S) measures to vertical, three-component and multivariate measures. Our preliminary results show that multivariate measures perform much better than single ratios, though transportability of the LDA weights between regions is an issue. Also in our preliminary results, we do not find large discrimination performance improvements with three-component averages and maximum phase amplitude measures compared to using the vertical component alone

A Dopaminergic Gene Cluster in the Prefrontal Cortex Predicts Performance Indicative of General Intelligence in Genetically Heterogeneous Mice

Background: Genetically heterogeneous mice express a trait that is qualitatively and psychometrically analogous to general intelligence in humans, and as in humans, this trait co-varies with the processing efficacy of working memory (including its dependence on selective attention). Dopamine signaling in the prefrontal cortex (PFC) has been established to play a critical role in animals ’ performance in both working memory and selective attention tasks. Owing to this role of the PFC in the regulation of working memory, here we compared PFC gene expression profiles of 60 genetically diverse CD-1 mice that exhibited a wide range of general learning abilities (i.e., aggregate performance across five diverse learning tasks). Methodology/Principal Findings: Animals ’ general cognitive abilities were first determined based on their aggregate performance across a battery of five diverse learning tasks. With a procedure designed to minimize false positive identifications, analysis of gene expression microarrays (comprised of &lt;25,000 genes) identified a small number (,20) of genes that were differentially expressed across animals that exhibited fast and slow aggregate learning abilities. Of these genes, one functional cluster was identified, and this cluster (Darpp-32, Drd1a, and Rgs9) is an established modulator of dopamine signaling. Subsequent quantitative PCR found that expression of these dopaminegic genes plus one vascular gene (Nudt6) were significantly correlated with individual animal’s general cognitive performance. Conclusions/Significance: These results indicate that D1-mediated dopamine signaling in the PFC, possibly through it

Obstructed defaecation syndrome: European consensus guidelines on the surgical management.

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The repeatability of cognitive performance:A meta-analysis

This is the author accepted manuscript. The final version is available from The Royal Society via the DOI in this record.Behavioural and cognitive processes play important roles in mediating an individual's interactions with its environment. Yet, while there is a vast literature on repeatable individual differences in behaviour, relatively little is known about the repeatability of cognitive performance. To further our understanding of the evolution of cognition, we gathered 44 studies on individual performance of 25 species across six animal classes and used meta-analysis to assess whether cognitive performance is repeatable. We compared repeatability (R) in performance (1) on the same task presented at different times (temporal repeatability), and (2) on different tasks that measured the same putative cognitive ability (contextual repeatability). We also addressed whether R estimates were influenced by seven extrinsic factors (moderators): type of cognitive performance measurement, type of cognitive task, delay between tests, origin of the subjects, experimental context, taxonomic class and publication status. We found support for both temporal and contextual repeatability of cognitive performance, with mean R estimates ranging between 0.15 and 0.28. Repeatability estimates were mostly influenced by the type of cognitive performance measures and publication status. Our findings highlight the widespread occurrence of consistent inter-individual variation in cognition across a range of taxa which, like behaviour, may be associated with fitness outcomes.PKYC is supported by Japan Society for the Promotion of Science (PE1801); JOvH was funded by an ERC consolidator grant (616474). MC and this research was supported by a grant from the Human Frontier Science Program to ASC and JM-F (RGP0006/2015)

Advances in the role of sacral nerve neuromodulation in lower urinary tract symptoms

Sacral neuromodulation has been developed to treat chronic lower urinary tract symptoms, resistant to classical conservative therapy. The suspected mechanisms of action include afferent stimulation of the central nervous system and modulation of activity at the level of the brain. Typical neuromodulation is indicated both in overactivity and in underactivity of the lower urinary tract. In the majority of patients, a unilateral electrode in a sacral foramen and connected to a pulse generator is sufficient to achieve significant clinical results also on long term. In recent years, other urological indications have been explored