Microbial Load Monitor

The Microbial Load Monitor (MLM) is an automated and computerized system for detection and identification of microorganisms. Additionally, the system is designed to enumerate and provide antimicrobic susceptibility profiles for medically significant bacteria. The system is designed to accomplish these tasks in a time of 13 hours or less versus the traditional time of 24 hours for negatives and 72 hours or more for positives usually required for standard microbiological analysis. The MLM concept differs from other methods of microbial detection in that the system is designed to accept raw untreated clinical samples and to selectively identify each group or species that may be present in a polymicrobic sample

Diagnostics of Coronal Magnetic Fields Through the Hanle Effect in UV and IR Lines

The plasma thermodynamics in the solar upper atmosphere, particularly in the corona, are dominated by the magnetic field, which controls the flow and dissipation of energy. The relative lack of knowledge of the coronal vector magnetic field is a major handicap for progress in coronal physics. This makes the development of measurement methods of coronal magnetic fields a high priority in solar physics. The Hanle effect in the UV and IR spectral lines is a largely unexplored diagnostic. We use magnetohydrodynamic (MHD) simulations to study the magnitude of the signal to be expected for typical coronal magnetic fields for selected spectral lines in the UV and IR wavelength ranges, namely the H I Ly-$\alpha$ and the He I 10830 {\AA} lines. We show that the selected lines are useful for reliable diagnosis of coronal magnetic fields. The results show that the combination of polarization measurements of spectral lines with different sensitivities to the Hanle effect may be most appropriate for deducing coronal magnetic properties from future observations.Comment: 15 pages, 5 figures, Frontiers in Astronomy and Space Sciences, 201

Three-body structure of the nnΛnn\Lambda system with ΛN−ΣN\Lambda N-\Sigma N coupling

The structure of the three-body $nn\Lambda$ system, which has been observed recently by the HypHI collaboration, is investigated taking $\Lambda N-\Sigma N$ coupling explicitly into account. The $YN$ and $NN$ interactions employed in this work reproduce the binding energies of $^3_{\Lambda}$H, $^4_{\Lambda}$H and $^4_{\Lambda}$He. We do not find any $^3_{\Lambda}n$ bound state, which contradicts the interpretation of the data reported by the HypHI collaboration.Comment: To be publsihed in PRC as a Rapid communicatio

Laser microprobe study of cosmic dust (IDPs) and potential source materials

The study of cosmic dust or interplanetary dust particles (IDP) can provide vital information about primitive materials derived primarily from comets and asteroids along with a small unknown fraction from the nearby interstellar medium. The study of these particles can enhance our understanding of comets along with the decoding of the history of the early solar system. In addition the study of the cosmic dust for IDP particles can assist in the elucidation of the cosmic history of the organogenic elements which are vital to life processes. Studies to date on these particles have shown that they are complex, heterogeneous assemblages of both amorphous and crystalline components. In order to understand the nature of these particles, any analytical measurements must be able to distinguish between the possible sources of these particles. A study was undertaken using a laser microprobe interfaced to a quadrupole mass spectrometer for the analysis of the volatile components present in cosmic dust particles, terrestrial contaminants present in the upper atmosphere, and primitive carbonaceous chondrites. From the study of the volatiles released from the carbonaceous materials it is hoped that one could distinguish between components and sources in the IDP particles analyzed. The technique is briefly described and results for the CI, CM, and CV chondrites and cosmic dust particle W7027B8 are presented

When is an error not a prediction error? An electrophysiological investigation

A recent theory holds that the anterior cingulate cortex (ACC) uses reinforcement learning signals conveyed by the midbrain dopamine system to facilitate flexible action selection. According to this position, the impact of reward prediction error signals on ACC modulates the amplitude of a component of the event-related brain potential called the error-related negativity (ERN). The theory predicts that ERN amplitude is monotonically related to the expectedness of the event: It is larger for unexpected outcomes than for expected outcomes. However, a recent failure to confirm this prediction has called the theory into question. In the present article, we investigated this discrepancy in three trial-and-error learning experiments. All three experiments provided support for the theory, but the effect sizes were largest when an optimal response strategy could actually be learned. This observation suggests that ACC utilizes dopamine reward prediction error signals for adaptive decision making when the optimal behavior is, in fact, learnable

ROAM: a Radial-basis-function Optimization Approximation Method for diagnosing the three-dimensional coronal magnetic field

The Coronal Multichannel Polarimeter (CoMP) routinely performs coronal polarimetric measurements using the Fe XIII 10747 $\AA$ and 10798 $\AA$ lines, which are sensitive to the coronal magnetic field. However, inverting such polarimetric measurements into magnetic field data is a difficult task because the corona is optically thin at these wavelengths and the observed signal is therefore the integrated emission of all the plasma along the line of sight. To overcome this difficulty, we take on a new approach that combines a parameterized 3D magnetic field model with forward modeling of the polarization signal. For that purpose, we develop a new, fast and efficient, optimization method for model-data fitting: the Radial-basis-functions Optimization Approximation Method (ROAM). Model-data fitting is achieved by optimizing a user-specified log-likelihood function that quantifies the differences between the observed polarization signal and its synthetic/predicted analogue. Speed and efficiency are obtained by combining sparse evaluation of the magnetic model with radial-basis-function (RBF) decomposition of the log-likelihood function. The RBF decomposition provides an analytical expression for the log-likelihood function that is used to inexpensively estimate the set of parameter values optimizing it. We test and validate ROAM on a synthetic test bed of a coronal magnetic flux rope and show that it performs well with a significantly sparse sample of the parameter space. We conclude that our optimization method is well-suited for fast and efficient model-data fitting and can be exploited for converting coronal polarimetric measurements, such as the ones provided by CoMP, into coronal magnetic field data.Comment: 23 pages, 12 figures, accepted in Frontiers in Astronomy and Space Science

A Survey of Coronal Cavity Density Profiles

Coronal cavities are common features of the solar corona that appear as darkened regions at the base of coronal helmet streamers in coronagraph images. Their darkened appearance indicates that they are regions of lowered density embedded within the comparatively higher density helmet streamer. Despite interfering projection effects of the surrounding helmet streamer (which we refer to as the cavity rim), Fuller et al. have shown that under certain conditions it is possible to use a Van de Hulst inversion of white-light polarized brightness (pB) data to calculate the electron density of both the cavity and cavity rim plasma. In this article, we apply minor modifications to the methods of Fuller et al. in order to improve the accuracy and versatility of the inversion process, and use the new methods to calculate density profiles for both the cavity and cavity rim in 24 cavity systems. We also examine trends in cavity morphology and how departures from the model geometry affect our density calculations. The density calculations reveal that in all 24 cases the cavity plasma has a flatter density profile than the plasma of the cavity rim, meaning that the cavity has a larger density depletion at low altitudes than it does at high altitudes. We find that the mean cavity density is over four times greater than that of a coronal hole at an altitude of 1.2 R_☉ and that every cavity in the sample is over twice as dense as a coronal hole at this altitude. Furthermore, we find that different cavity systems near solar maximum span a greater range in density at 1.2 R_☉ than do cavity systems near solar minimum, with a slight trend toward higher densities for systems nearer to solar maximum. Finally, we found no significant correlation of cavity density properties with cavity height—indeed, cavities show remarkably similar density depletions—except for the two smallest cavities that show significantly greater depletion

Data-Optimized Coronal Field Model: I. Proof of Concept

Deriving the strength and direction of the three-dimensional (3D) magnetic field in the solar atmosphere is fundamental for understanding its dynamics. Volume information on the magnetic field mostly relies on coupling 3D reconstruction methods with photospheric and/or chromospheric surface vector magnetic fields. Infrared coronal polarimetry could provide additional information to better constrain magnetic field reconstructions. However, combining such data with reconstruction methods is challenging, e.g., because of the optical-thinness of the solar corona and the lack and limitations of stereoscopic polarimetry. To address these issues, we introduce the Data-Optimized Coronal Field Model (DOCFM) framework, a model-data fitting approach that combines a parametrized 3D generative model, e.g., a magnetic field extrapolation or a magnetohydrodynamic model, with forward modeling of coronal data. We test it with a parametrized flux rope insertion method and infrared coronal polarimetry where synthetic observations are created from a known "ground truth" physical state. We show that this framework allows us to accurately retrieve the ground truth 3D magnetic field of a set of force-free field solutions from the flux rope insertion method. In observational studies, the DOCFM will provide a means to force the solutions derived with different reconstruction methods to satisfy additional, common, coronal constraints. The DOCFM framework therefore opens new perspectives for the exploitation of coronal polarimetry in magnetic field reconstructions and for developing new techniques to more reliably infer the 3D magnetic fields that trigger solar flares and coronal mass ejections.Comment: 14 pages, 6 figures; Accepted for publication in Ap

Hyperdiffusion as a Mechanism for Solar Coronal Heating

A theory for the heating of coronal magnetic flux ropes is developed. The dissipated magnetic energy has two distinct contributions: (1) energy injected into the corona as a result of granule-scale, random footpoint motions, and (2) energy from the large-scale, nonpotential magnetic field of the flux rope. The second type of dissipation can be described in term of hyperdiffusion, a type of magnetic diffusion in which the helicity of the mean magnetic field is conserved. The associated heating rate depends on the gradient of the torsion parameter of the mean magnetic field. A simple model of an active region containing a coronal flux rope is constructed. We find that the temperature and density on the axis of the flux rope are lower than in the local surroundings, consistent with observations of coronal cavities. The model requires that the magnetic field in the flux rope is stochastic in nature, with a perpendicular length scale of the magnetic fluctuations of order 1000 km.Comment: 9 pages (emulateapj style), 4 figures, ApJ, in press (v. 679; June 1, 2008