Food habits of Steller sea lions (Eumetopias jubatus) off Oregon and northern California, 1986–2007

We described the diet of the eastern stock of Steller sea lions (Eumetopias jubatus) from 1416 scat samples collected from five sites in Oregon and northern California from 1986 through 2007. A total of 47 prey types from 30 families were identified. The most common prey was Pacific hake (Merluccius productus), followed by salmonids (Oncorhynchus spp.), skates (Rajidae), Pacific lamprey (Lampetra tridentata), herrings (Clupeidae), rockfish (Sebastes spp.), and northern anchovy (Engraulis mordax). Steller sea lion diet composition varied seasonally, annually, and spatially. Hake and salmonids were the most commonly identified prey in scats collected during the summer (breeding season), whereas hake and skate were most common in the nonbreeding season. Continued research on Steller sea lion diet and foraging behavior in the southern extent of their range is necessary to address issues such as climate change, interaction with competing California sea lions, and predation impacts on valuable or sensitive fish stocks

Alexandria: Extensible Framework for Rapid Exploration of Social Media

The Alexandria system under development at IBM Research provides an extensible framework and platform for supporting a variety of big-data analytics and visualizations. The system is currently focused on enabling rapid exploration of text-based social media data. The system provides tools to help with constructing "domain models" (i.e., families of keywords and extractors to enable focus on tweets and other social media documents relevant to a project), to rapidly extract and segment the relevant social media and its authors, to apply further analytics (such as finding trends and anomalous terms), and visualizing the results. The system architecture is centered around a variety of REST-based service APIs to enable flexible orchestration of the system capabilities; these are especially useful to support knowledge-worker driven iterative exploration of social phenomena. The architecture also enables rapid integration of Alexandria capabilities with other social media analytics system, as has been demonstrated through an integration with IBM Research's SystemG. This paper describes a prototypical usage scenario for Alexandria, along with the architecture and key underlying analytics.Comment: 8 page

Measurement of Dynamic Properties of Clay Using the Downhole Freestanding Shear Device

The Downhole Freestanding Shear Device is a new, in situ tool for measuring the dynamic properties of cohesive soil deposits. It has been designed and developed to perform cyclic torsional shear tests on freestanding specimens beneath the bottom of a cased borehole, with the goal of measuring local strains on soil which has not been significantly disturbed by the drilling, sampling, or unloading/reloading processes associated with conventional laboratory testing. The research team has completed the device, and is now in the process of validating its performance, first in a laboratory setting. The current paper presents results from the initial tests on soil, illustrating that this new device is capable of measuring shear modulus and damping over a wide range of shear strains, from 10-3 % to nearly 1%

Liquefaction of Soils in the 1989 Loma Prieta Earthquake

The Loma Prieta Earthquake of October 17, 1989 was the most costly single natural disaster in U.S. history, resulting in losses of $7 to$9 billion, and claiming 63 lives. These damages were concentrated mainly at a number of distinct sites comprising a relatively small fraction of the affected region, as local site conditions and related geotechnical factors exerted a major influence on damage patterns and loss of life in this catastrophic event. This paper discusses one of these geotechnical factors, the widespread occurrence of soil liquefaction during the earthquake, as well as the associated damages and the resulting lessons learned. Additional significant geotechnical factors which exerted a strong influence on damage patterns during this event, including site-dependent dynamic response and seismically-induced slope instability, are discussed in companion papers in these proceedings

Dark matter line emission constraints from NuSTAR observations of the Bullet Cluster

Line emission from dark matter is well motivated for some candidates e.g. sterile neutrinos. We present the first search for dark matter line emission in the 3-80keV range in a pointed observation of the Bullet Cluster with NuSTAR. We do not detect any significant line emission and instead we derive upper limits (95% CL) on the flux, and interpret these constraints in the context of sterile neutrinos and more generic dark matter candidates. NuSTAR does not have the sensitivity to constrain the recently claimed line detection at 3.5keV, but improves on the constraints for energies of 10-25keV.Comment: 7 pages, 5 figures, submitted to Ap

Effects on Freshwater Organisms of Magnetic Fields Associated with Hydrokinetic Turbines

Underwater cables will be used to transmit electricity between turbines in an array (interturbine cables), between the array and a submerged step-up transformer (if part of the design), and from the transformer or array to shore. All types of electrical transmitting cables (as well as the generator itself) will emit EMF into the surrounding water. The electric current will induce magnetic fields in the immediate vicinity, which may affect the behavior or viability of animals. Because direct electrical field emissions can be prevented by shielding and armoring, we focused our studies on the magnetic fields that are unavoidably induced by electric current moving through a generator or transmission cable. These initial experiments were carried out to evaluate whether a static magnetic field, such as would be produced by a direct current (DC) transmitting cable, would affect the behavior of common freshwater fish and invertebrates

Sodium (Na) ultra-short echo time imaging in the human brain using a 3D-Cones trajectory

Object: Sodium magnetic resonance imaging (Na-MRI) of the brain has shown changes in Na signal as a hallmark of various neurological diseases such as stroke, Alzheimer's disease, Multiple Sclerosis and Huntington's disease. To improve scan times and image quality, we have implemented the 3D-Cones (CN) sequence for in vivo Na brain MRI. Materials and methods: Using signal-to-noise (SNR) as a measurement of sequence performance, CN is compared against more established 3D-radial k-space sampling schemes featuring cylindrical stack-of-stars (SOS) and 3D-spokes kooshball (KB) trajectories, on five healthy volunteers in a clinical setting. Resolution was evaluated by simulating the point-spread-functions (PSFs) and experimental measures on a phantom. Results: All sequences were shown to have a similar SNR arbitrary units (AU) of 6-6.5 in brain white matter, 7-9 in gray matter and 17-18 AU in cerebrospinal fluid. SNR between white and gray matter were significantly different for KB and CN (p = 0.046 and <0.001 respectively), but not for SOS (p = 0.1). Group mean standard deviations were significantly smaller for CN (p = 0.016). Theoretical full-width at half-maximum linewidth of the PSF for CN is broadened by only 0.1, compared to 0.3 and 0.8 pixels for SOS and KB respectively. Actual image resolution is estimated as 8, 9 and 6.3 mm for SOS, KB and CN respectively. Conclusion: The CN sequence provides stronger tissue contrast than both SOS and KB, with more reproducible SNR measurements compared to KB. For CN, a higher true resolution in the same amount of time with no significant trade-off in SNR is achieved. CN is therefore more suitable for Na-MRI in the brain. © 2013 The Author(s)

Sodium ((23)Na) ultra-short echo time imaging in the human brain using a 3D-Cones trajectory

Object: Sodium magnetic resonance imaging ((23)Na-MRI) of the brain has shown changes in (23)Na signal as a hallmark of various neurological diseases such as stroke, Alzheimer's disease, Multiple Sclerosis and Huntington's disease. To improve scan times and image quality, we have implemented the 3D-Cones (CN) sequence for in vivo (23)Na brain MRI. Materials and Methods: Using signal-to-noise (SNR) as a measurement of sequence performance, CN is compared against more established 3D-radial k-space sampling schemes featuring cylindrical stack-of-stars (SOS) and 3D-spokes kooshball (KB) trajectories, on five healthy volunteers in a clinical setting. Resolution was evaluated by simulating the point-spread-functions (PSFs) and experimental measures on a phantom. Results: All sequences were shown to have a similar SNR arbitrary units (AU) of 6–6.5 in brain white matter, 7–9 in gray matter and 17–18 AU in cerebrospinal fluid. SNR between white and gray matter were significantly different for KB and CN (p = 0.046 and\0.001 respectively), but not for SOS (p = 0.1). Group mean standard deviations were significantly smaller for CN (p = 0.016). Theoretical full-width at half-maximum linewidth of the PSF for CN is broadened by only 0.1, compared to 0.3 and 0.8 pixels for SOS and KB respectively. Actual image resolution is estimated as 8, 9 and 6.3 mm for SOS, KB and CN respectively. Conclusion: The CN sequence provides stronger tissue contrast than both SOS and KB, with more reproducible SNR measurements compared to KB. For CN, a higher true resolution in the same amount of time with no significant trade-off in SNR is achieved. CN is therefore more suitable for 23Na-MRI in the brain

Robust Bayes-Like Estimation: Rho-Bayes estimation

We consider the problem of estimating the joint distribution $P$ of $n$ independent random variables within the Bayes paradigm from a non-asymptotic point of view. Assuming that $P$ admits some density $s$ with respect to a given reference measure, we consider a density model $\overline S$ for $s$ that we endow with a prior distribution $\pi$ (with support $\overline S$) and we build a robust alternative to the classical Bayes posterior distribution which possesses similar concentration properties around $s$ whenever it belongs to the model $\overline S$. Furthermore, in density estimation, the Hellinger distance between the classical and the robust posterior distributions tends to 0, as the number of observations tends to infinity, under suitable assumptions on the model and the prior, provided that the model $\overline S$ contains the true density $s$. However, unlike what happens with the classical Bayes posterior distribution, we show that the concentration properties of this new posterior distribution are still preserved in the case of a misspecification of the model, that is when $s$ does not belong to $\overline S$ but is close enough to it with respect to the Hellinger distance.Comment: 68 page