MOST Space Telescope Photometry of the 2010 January Transit of Extrasolar Planet HD80606b

We present observations of the full January 2010 transit of HD80606b from the Canadian microsatellite, Microvariability and Oscillations of Stars (MOST). By employing a space-based telescope, we monitor the entire transit thus limiting systematic errors that result from ground observations. We determine measurements for the planetary radius (R_{p}=0.987\pm0.061R_{Jup}) and inclination (i=89.283^{o}\pm0.024) by constraining our fits with the observed parameters of different groups. Our measured mid-transit time of 2455210.6449\pm0.0034 HJD is consistant with the 2010 Spitzer results and is 20 minutes earlier than predicted by groups who observed the June 2009 transit.Comment: 3 figure

The Diffusion of Second Generation Statistical Techniques in Information Systems Research from 1990-2008

Second generation statistical techniques like Structural Equation Modeling (SEM) are being used more frequently by IS researchers to evaluate theoretical models. The purpose of this study is three-fold. First, we aim to ascertain whether there is a “fit” between IS researchers choice of analytic method and theoretical models when they use second generation techniques. Second, we seek to determine the degree to which IS researchers have internalized knowledge about second generation techniques. Finally, we want to see how these factors have changed over time. Analysis of four leading IS journals between 1990 and 2008 matched the use of second generation techniques to rational reasons for using a specific analytic technique and the degree of knowledge internalization found in 265 published empirical articles. In the early period (1990-2002), we found the use of second generation techniques was not associated with rational choices or reasons for their use. In the later period (2003-2008), we found their use was associated with rational choice and there was a higher degree of knowledge internalization. Our findings suggest that, over time, researchers were able to leverage their internalized knowledge of second generation techniques when testing mediation and moderation models as indicated by the higher ratio of internal to external method citations. The paper concludes with implications for IS research

Pulsar Wind Nebulae in EGRET Error Boxes

A remarkable number of pulsar wind nebulae (PWN) are coincident with EGRET gamma-ray sources. X-ray and radio imaging studies of unidentified EGRET sources have resulted in the discovery of at least 6 new pulsar wind nebulae (PWN). Stationary PWN (SPWN) appear to be associated with steady EGRET sources with hard spectra, typical for gamma-ray pulsars. Their toroidal morphologies can help determine the geometry of the pulsar which is useful for constraining models of pulsed gamma-ray emission. Rapidly moving PWN (RPWN) with more cometary morphologies seem to be associated with variable EGRET sources in regions where the ambient medium is dense compared to what is typical for the ISM.Comment: 8 pages, 5 figures, to appear in the proceedings of "The Multiwavelength Approach to Unidentified Sources", ed. G. Romero & K.S. Chen

DynaSim: a MATLAB toolbox for neural modeling and simulation

[EN] DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.This material is based upon research supported by the U.S. Army Research Office under award number ARO W911NF-12-R-0012-02, the U.S. Office of Naval Research under award number ONR MURI N00014-16-1-2832, and the National Science Foundation under award number NSF DMS-1042134 (Cognitive Rhythms Collaborative: A Discovery Network)Sherfey, JS.; Soplata, AE.; Ardid-Ramírez, JS.; Roberts, EA.; Stanley, DA.; Pittman-Polletta, BR.; Kopell, NJ. (2018). DynaSim: a MATLAB toolbox for neural modeling and simulation. Frontiers in Neuroinformatics. 12:1-15. https://doi.org/10.3389/fninf.2018.00010S11512Bokil, H., Andrews, P., Kulkarni, J. E., Mehta, S., & Mitra, P. P. (2010). Chronux: A platform for analyzing neural signals. Journal of Neuroscience Methods, 192(1), 146-151. doi:10.1016/j.jneumeth.2010.06.020Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J. M., … Destexhe, A. (2007). Simulation of networks of spiking neurons: A review of tools and strategies. Journal of Computational Neuroscience, 23(3), 349-398. doi:10.1007/s10827-007-0038-6Börgers, C., & Kopell, N. (2005). Effects of Noisy Drive on Rhythms in Networks of Excitatory and Inhibitory Neurons. Neural Computation, 17(3), 557-608. doi:10.1162/0899766053019908Ching, S., Cimenser, A., Purdon, P. L., Brown, E. N., & Kopell, N. J. (2010). Thalamocortical model for a propofol-induced  -rhythm associated with loss of consciousness. Proceedings of the National Academy of Sciences, 107(52), 22665-22670. doi:10.1073/pnas.1017069108Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. 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NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail. PLoS Computational Biology, 6(6), e1000815. doi:10.1371/journal.pcbi.1000815Goodman, D. (2008). Brian: a simulator for spiking neural networks in Python. Frontiers in Neuroinformatics, 2. doi:10.3389/neuro.11.005.2008Goodman, D. F. M. (2009). The Brian simulator. Frontiers in Neuroscience, 3(2), 192-197. doi:10.3389/neuro.01.026.2009Hines, M. L., & Carnevale, N. T. (1997). The NEURON Simulation Environment. Neural Computation, 9(6), 1179-1209. doi:10.1162/neco.1997.9.6.1179Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500-544. doi:10.1113/jphysiol.1952.sp004764Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., … Wang. (2003). The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 19(4), 524-531. doi:10.1093/bioinformatics/btg015Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on Neural Networks, 14(6), 1569-1572. doi:10.1109/tnn.2003.820440Kopell, N., Ermentrout, G. B., Whittington, M. A., & Traub, R. D. (2000). Gamma rhythms and beta rhythms have different synchronization properties. Proceedings of the National Academy of Sciences, 97(4), 1867-1872. doi:10.1073/pnas.97.4.1867Kramer, M. A., Roopun, A. K., Carracedo, L. M., Traub, R. D., Whittington, M. A., & Kopell, N. J. (2008). Rhythm Generation through Period Concatenation in Rat Somatosensory Cortex. PLoS Computational Biology, 4(9), e1000169. doi:10.1371/journal.pcbi.1000169Lorenz, E. N. (1963). Deterministic Nonperiodic Flow. 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Modelling the Response of Ice Shelf Basal Melting to Different Ocean Cavity Environmental Regimes

We present simulation results from a version of the Regional Ocean Modeling System modified for ice shelf/ocean interaction, including the parameterisation of basal melting by molecular diffusion alone. Simulations investigate the differences in melting for an idealised ice shelf experiencing a range of cold to hot ocean cavity conditions. Both the pattern of melt and the location of maximum melt shift due to changes in the buoyancy-driven circulation, in a different way to previous studies. Tidal forcing increases both the circulation strength and melting, with the strongest impact on the cold cavity case. Our results highlight the importance of including a complete melt parameterisation and tidal forcing. In response to the 2.4 degrees C ocean warming initially applied to a cold cavity ice shelf, we find that melting will increase by about an order of magnitude (24 x with tides and 41 x without tides)

Deterministic Factors Overwhelm Stochastic Environmental Fluctuations as Drivers of Jellyfish Outbreaks

16 pages, 4 figures, 1 table, supporting Information http://dx.doi.org/10.1371/journal.pone.0141060Jellyfish outbreaks are increasingly viewed as a deterministic response to escalating levels of environmental degradation and climate extremes. However, a comprehensive understanding of the influence of deterministic drivers and stochastic environmental variations favouring population renewal processes has remained elusive. This study quantifies the deterministic and stochastic components of environmental change that lead to outbreaks of the jellyfish Pelagia noctiluca in the Mediterranen Sea. Using data of jellyfish abundance collected at 241 sites along the Catalan coast from 2007 to 2010 we: (1) tested hypotheses about the influence of time-varying and spatial predictors of jellyfish outbreaks; (2) evaluated the relative importance of stochastic vs. deterministic forcing of outbreaks through the environmental bootstrap method; and (3) quantified return times of extreme events. Outbreaks were common in May and June and less likely in other summer months, which resulted in a negative relationship between outbreaks and SST. Cross- and along-shore advection by geostrophic flow were important concentrating forces of jellyfish, but most outbreaks occurred in the proximity of two canyons in the northern part of the study area. This result supported the recent hypothesis that canyons can funnel P. noctiluca blooms towards shore during upwelling. This can be a general, yet unappreciated mechanism leading to outbreaks of holoplanktonic jellyfish species. The environmental bootstrap indicated that stochastic environmental fluctuations have negligible effects on return times of outbreaks. Our analysis emphasized the importance of deterministic processes leading to jellyfish outbreaks compared to the stochastic component of environmental variation. A better understanding of how environmental drivers affect demographic and population processes in jellyfish species will increase the ability to anticipate jellyfish outbreaks in the futureThe authors gratefully acknowledge financial support by the European Community Seventh Framework Programme (FP7/2007–2013) for the project VECTORS (grant agreement no. 266445) (URL: http://cordis.europa.eu/fp7/home_en.html). AC was supported by a doctoral fellowship from the Chilean National Commission for Scientific and Technological Research (CONICYT – PFCHA/Doctorado al Extranjero 4a Convocatoria, 72120016).Peer Reviewe

Serum Creatinine and Tacrolimus Assessment With VAMS Finger-Prick Microsampling: A Diagnostic Test Study

Rationale & Objective: Kidney transplant recipients require frequent venipunctures. Microsampling methods that use a finger-prick draw of capillary blood, like volumetric absorptive microsamplers (VAMS), have the potential to reduce the pain, inconvenience, and volume of blood loss associated with venipuncture. This study aimed to provide diagnostic accuracy using VAMS for measurement of tacrolimus and creatinine compared to gold standard venous blood in adult kidney transplant recipients. Study Design: Diagnostic test study. Prospective blood samples for measurement of tacrolimus and creatinine were collected using Mitra VAMS and venipuncture immediately before and 2 hours after tacrolimus dosing. Setting & Participants: A convenience sample of 40 adult kidney transplant participants in the outpatient setting. Tests Compared: Method comparison was assessed by Passing-Bablok regression and Bland-Altman analysis. The predictive performance of VAMS measurement compared to venipuncture was also assessed through estimation of the median prediction error and median absolute percentage prediction error. Results: A total of 74 tacrolimus samples and 70 creatinine samples were analyzed from 40 participants. Passing-Bablok regression showed a systematic difference between VAMS and venipuncture when measuring tacrolimus and creatinine with a slope of 1.08 (95% CI, 1.03-1.13) and a slope of 0.65 (95% CI, 0.6-0.7), respectively. These values were then corrected for the systematic difference. When used for Bland-Altman analysis, corrected values of tacrolimus and creatinine showed a bias of -0.1 μg/L and 0.04 mg/dL, respectively. Tacrolimus (corrected) and creatinine (corrected) microsampling values when compared to corresponding venipuncture values met median prediction error and median absolute percentage prediction error predefined acceptability limits of <15%. Limitations: This study was conducted in a controlled environment using a trained nurse to collect VAMS samples. Conclusions: In this study, VAMS was used to reliably measured tacrolimus and creatinine. This represents a clear opportunity for more frequent and less invasive sampling for patients