Documentation of the INDOT Experience and Construction of the Bridge Decks Containing Internal Curing in 2013

The Indiana Department of Transportation (INDOT) constructed four bridge decks utilizing internally cured, high performance concrete (IC HPC) during the summer of 2013. These decks implement research findings from the research presented in the FHWA/IN/JTRP-2010/10 report where internal curing was proposed as one method to reduce the potential for shrinkage cracking, leading to improved durability. The objective of this research was to document the construction of the four IC HPC bridge decks that were constructed in Indiana during 2013 and quantify the properties and performance of these decks. This report contains documentation of the production and construction of IC HPC concrete for the four bridge decks in this study. In addition, samples of the IC HPC used in construction were compared with a reference high performance concrete (HPC) which did not utilize internal curing. These samples were transported to the laboratory where the mechanical properties, resistance to chloride migration, and potential for shrinkage and cracking was assessed. Using experimental results and mixture proportions, the diffusion based service life of the bridge decks was able to be estimated. Collectively, the results indicate that the IC HPC mixtures that were produced as a part of this study exhibit the potential to more than triple the service life of the typical bridge deck in Indiana while reducing the early age autogenous shrinkage by more than 80% compared to non-internally cured concretes

Efficiency of TTAC's ORTEC IDM

ORNL's Technical Testing and Analysis Center (TTAC) acquired a High Purity Germanium Detector (HPGe) from ORTEC - a variant called an Interchangeable Detection Module (IDM). This detector has excellent energy resolution as well as high intrinsic efficiency. The purpose of this report is to detail the determination of the efficiency curve of the IDM, so future measurements can quantify the (otherwise unknown) activity of sources. Without such a curve, the activity cannot be directly reported by use of the IDM alone - a separate device such as an ion chamber would be required. This builds upon the capability of TTAC. The method for determining the energy-dependent intrinsic efficiency is laid-out in this report. It's noteworthy that this basic technique can be applied to any spectroscopic radiation detector, independent of the specific type (e.g. NaI, CzT, ClYC)

Prefrontal oscillations modulate the propagation of neuronal activity required for working memory

[EN] Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream effectors that carry out the response. In this work, we used biophysically-detailed modeling to explore the hypothesis that network oscillations in prefrontal cortex (PFC), leveraging local inhibition, can independently gate responses to items in WM. The key role of local inhibition was to control the period between spike bursts in the outputs, and to produce an oscillatory response no matter whether the WM item was maintained in an asynchronous or oscillatory state. We found that the WM item that induced an oscillatory population response in the PFC output layer with the shortest period between spike bursts was most reliably propagated. The network resonant frequency (i.e., the input frequency that produces the largest response) of the output layer can be flexibly tuned by varying the excitability of deep layer principal cells. Our model suggests that experimentally-observed modulation of PFC beta-frequency (15-30 Hz) and gamma -frequency (30-80 Hz) oscillations could leverage network resonance and local inhibition to govern the flexible routing of signals in service to cognitive processes like gating outputs from working memory and the selection of rule-based actions. Importantly, we show for the first time that nonspecific changes in deep layer excitability can tune the output gate's resonant frequency, enabling the specific selection of signals encoded by populations in asynchronous or fast oscillatory states. More generally, this represents a dynamic mechanism by which adjusting network excitability can govern the propagation of asynchronous and oscillatory signals throughout neocortex.This work was supported by the U.S. Army Research Office under award number ARO W911NF-12-R-0012-02 to N. K., the U.S. Office of Naval Research under award number ONR MURI N00014-16-1-2832 to M. H. and E. M., the National Institute of Mental Health under award number NIMH R37MH087027 to E. M., and The MIT Picower Institute Faculty Innovation Fund to E. M. We would like to acknowledge Joachim Hass and Michelle McCarthy for early discussions of our modeling results, as well as Andre Bastos and Mikael Lundqvist for discussions relating our modeling work to their experiments.Sherfey, J.; Ardid-Ramírez, JS.; Miller, EK.; Hasselmo, ME.; Kopell, NJ. (2020). Prefrontal oscillations modulate the propagation of neuronal activity required for working memory. Neurobiology of Learning and Memory. 173:1-13. https://doi.org/10.1016/j.nlm.2020.107228113173Adams, N. E., Sherfey, J. S., Kopell, N. J., Whittington, M. A., & LeBeau, F. E. N. (2017). Hetereogeneity in Neuronal Intrinsic Properties: A Possible Mechanism for Hub-Like Properties of the Rat Anterior Cingulate Cortex during Network Activity. eneuro, 4(1), ENEURO.0313-16.2017. doi:10.1523/eneuro.0313-16.2017Akam, T., & Kullmann, D. M. (2010). Oscillations and Filtering Networks Support Flexible Routing of Information. Neuron, 67(2), 308-320. doi:10.1016/j.neuron.2010.06.019Amiez, C., Joseph, J.-P., & Procyk, E. (2005). Anterior cingulate error-related activity is modulated by predicted reward. European Journal of Neuroscience, 21(12), 3447-3452. doi:10.1111/j.1460-9568.2005.04170.xArdid, S., Sherfey, J. S., McCarthy, M. M., Hass, J., Pittman-Polletta, B. R., & Kopell, N. (2019). Biased competition in the absence of input bias revealed through corticostriatal computation. Proceedings of the National Academy of Sciences, 116(17), 8564-8569. doi:10.1073/pnas.1812535116Ardid, S., & Wang, X.-J. (2013). A Tweaking Principle for Executive Control: Neuronal Circuit Mechanism for Rule-Based Task Switching and Conflict Resolution. Journal of Neuroscience, 33(50), 19504-19517. doi:10.1523/jneurosci.1356-13.2013Ardid, S., Wang, X.-J., & Compte, A. (2007). An Integrated Microcircuit Model of Attentional Processing in the Neocortex. Journal of Neuroscience, 27(32), 8486-8495. doi:10.1523/jneurosci.1145-07.2007Ardid, S., Wang, X.-J., Gomez-Cabrero, D., & Compte, A. (2010). Reconciling Coherent Oscillation with Modulationof Irregular Spiking Activity in Selective Attention:Gamma-Range Synchronization between Sensoryand Executive Cortical Areas. Journal of Neuroscience, 30(8), 2856-2870. doi:10.1523/jneurosci.4222-09.2010Baddeley, A. D. and Hitch, G. (1974). Working Memory. In Bower, G.H., editor, Psychology of Learning and Motivation, volume 8, pages 47–89. Academic Press.Badre, D., & Frank, M. J. (2011). Mechanisms of Hierarchical Reinforcement Learning in Cortico-Striatal Circuits 2: Evidence from fMRI. Cerebral Cortex, 22(3), 527-536. doi:10.1093/cercor/bhr117Barbas, H. (2015). General Cortical and Special Prefrontal Connections: Principles from Structure to Function. Annual Review of Neuroscience, 38(1), 269-289. doi:10.1146/annurev-neuro-071714-033936Bhandari, A., & Badre, D. (2018). Learning and transfer of working memory gating policies. Cognition, 172, 89-100. doi:10.1016/j.cognition.2017.12.001Brette, R., & Guigon, E. (2003). Reliability of Spike Timing Is a General Property of Spiking Model Neurons. Neural Computation, 15(2), 279-308. doi:10.1162/089976603762552924Börgers, C., & Kopell, N. (2005). Effects of Noisy Drive on Rhythms in Networks of Excitatory and Inhibitory Neurons. Neural Computation, 17(3), 557-608. doi:10.1162/0899766053019908Brincat, S. L., & Miller, E. K. (2016). 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Cerebral Cortex, 10(9), 910-923. doi:10.1093/cercor/10.9.910DeFelipe, J. (1997). Types of neurons, synaptic connections and chemical characteristics of cells immunoreactive for calbindin-D28K, parvalbumin and calretinin in the neocortex. Journal of Chemical Neuroanatomy, 14(1), 1-19. doi:10.1016/s0891-0618(97)10013-8Douglas, R. J., & Martin, K. A. C. (2004). NEURONAL CIRCUITS OF THE NEOCORTEX. Annual Review of Neuroscience, 27(1), 419-451. doi:10.1146/annurev.neuro.27.070203.144152Durstewitz, D., & Seamans, J. K. (2002). The computational role of dopamine D1 receptors in working memory. Neural Networks, 15(4-6), 561-572. doi:10.1016/s0893-6080(02)00049-7Durstewitz, D., Seamans, J. K., & Sejnowski, T. J. (2000). Dopamine-Mediated Stabilization of Delay-Period Activity in a Network Model of Prefrontal Cortex. Journal of Neurophysiology, 83(3), 1733-1750. doi:10.1152/jn.2000.83.3.1733Frank, M. J., & Badre, D. (2011). Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis. Cerebral Cortex, 22(3), 509-526. doi:10.1093/cercor/bhr114FRANK, M. J., LOUGHRY, B., & O’REILLY, R. C. (2001). Interactions between frontal cortex and basal ganglia in working memory: A computational model. Cognitive, Affective, & Behavioral Neuroscience, 1(2), 137-160. doi:10.3758/cabn.1.2.137Hasselmo, M. E., & Stern, C. E. (2018). A network model of behavioural performance in a rule learning task. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1744), 20170275. doi:10.1098/rstb.2017.0275Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735-1780. doi:10.1162/neco.1997.9.8.1735Kaski, S., & Kohonen, T. (1994). Winner-take-all networks for physiological models of competitive learning. Neural Networks, 7(6-7), 973-984. doi:10.1016/s0893-6080(05)80154-6Kerns, J. G., Cohen, J. D., MacDonald, A.W., Cho, R.Y., Stenger, V.A., and Carter, C.S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science (New York, N.Y.), 303(5660):1023–1026.Komorowski, R. W., Garcia, C. G., Wilson, A., Hattori, S., Howard, M. W., & Eichenbaum, H. (2013). Ventral Hippocampal Neurons Are Shaped by Experience to Represent Behaviorally Relevant Contexts. Journal of Neuroscience, 33(18), 8079-8087. doi:10.1523/jneurosci.5458-12.2013Kriete, T., & Noelle, D. C. (2011). Generalisation benefits of output gating in a model of prefrontal cortex. Connection Science, 23(2), 119-129. doi:10.1080/09540091.2011.569881Kritzer, M. F., & Goldman-Rakic, P. S. (1995). Intrinsic circuit organization of the major layers and sublayers of the dorsolateral prefrontal cortex in the rhesus monkey. The Journal of Comparative Neurology, 359(1), 131-143. doi:10.1002/cne.903590109Levitt, J. B., Lewis, D. A., Yoshioka, T., & Lund, J. S. (1993). Topography of pyramidal neuron intrinsic connections in macaque monkey prefrontal cortex (areas 9 and 46). The Journal of Comparative Neurology, 338(3), 360-376. doi:10.1002/cne.903380304Lundqvist, M., Compte, A., & Lansner, A. (2010). Bistable, Irregular Firing and Population Oscillations in a Modular Attractor Memory Network. PLoS Computational Biology, 6(6), e1000803. doi:10.1371/journal.pcbi.1000803Lundqvist, M., Herman, P., Warden, M. R., Brincat, S. L., & Miller, E. K. (2018). Gamma and beta bursts during working memory readout suggest roles in its volitional control. Nature Communications, 9(1). doi:10.1038/s41467-017-02791-8Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K. (2016). Gamma and Beta Bursts Underlie Working Memory. Neuron, 90(1), 152-164. doi:10.1016/j.neuron.2016.02.028Mante, V., Sussillo, D., Shenoy, K. V., & Newsome, W. T. (2013). Context-dependent computation by recurrent dynamics in prefrontal cortex. 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Google-Books-ID: fUv54as56_8C.Renart, A., Rocha, J. d. l., Bartho, P., Hollender, L., Parga, N., Reyes, A., Harris, K. D. (2010). The Asynchronous State in Cortical Circuits. Science, 327(5965):587–590.Richardson, M. J. E., Brunel, N., & Hakim, V. (2003). From Subthreshold to Firing-Rate Resonance. Journal of Neurophysiology, 89(5), 2538-2554. doi:10.1152/jn.00955.2002Rotstein, H. G. (2017). Spiking Resonances In Models With The Same Slow Resonant And Fast Amplifying Currents But Different Subthreshold Dynamic Properties. bioRxiv, page 128611.Seamans, J. K., Lapish, C. C., & Durstewitz, D. (2008). Comparing the prefrontal cortex of rats and primates: Insights from electrophysiology. Neurotoxicity Research, 14(2-3), 249-262. doi:10.1007/bf03033814Shen, Z., Popov, V., Delahay, A. B., & Reder, L. M. (2017). Item strength affects working memory capacity. Memory & Cognition, 46(2), 204-215. doi:10.3758/s13421-017-0758-4Sherfey, J. S., Ardid, S., Hass, J., Hasselmo, M. E., & Kopell, N. J. 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Restoration of rotational invariance of bound states on the light front

We study bound states in a model with scalar nucleons interacting via an exchanged scalar meson using the Hamiltonian formalism on the light front. In this approach manifest rotational invariance is broken when the Fock space is truncated. By considering an effective Hamiltonian that takes into account two meson exchanges, we find that this breaking of rotational invariance is decreased from that which occurs when only one meson exchange is included. The best improvement occurs when the states are weakly bound.Comment: 20 pages, 6 figures, uses feynMF; changed typos, clarified use of angular momentu

Young Stellar Objects in the Gould Belt

We present the full catalog of Young Stellar Objects (YSOs) identified in the 18 molecular clouds surveyed by the Spitzer Space Telescope "cores to disks" (c2d) and "Gould Belt" (GB) Legacy surveys. Using standard techniques developed by the c2d project, we identify 3239 candidate YSOs in the 18 clouds, 2966 of which survive visual inspection and form our final catalog of YSOs in the Gould Belt. We compile extinction corrected SEDs for all 2966 YSOs and calculate and tabulate the infrared spectral index, bolometric luminosity, and bolometric temperature for each object. We find that 326 (11%), 210 (7%), 1248 (42%), and 1182 (40%) are classified as Class 0+I, Flat-spectrum, Class II, and Class III, respectively, and show that the Class III sample suffers from an overall contamination rate by background AGB stars between 25% and 90%. Adopting standard assumptions, we derive durations of 0.40-0.78 Myr for Class 0+I YSOs and 0.26-0.50 Myr for Flat-spectrum YSOs, where the ranges encompass uncertainties in the adopted assumptions. Including information from (sub)millimeter wavelengths, one-third of the Class 0+I sample is classified as Class 0, leading to durations of 0.13-0.26 Myr (Class 0) and 0.27-0.52 Myr (Class I). We revisit infrared color-color diagrams used in the literature to classify YSOs and propose minor revisions to classification boundaries in these diagrams. Finally, we show that the bolometric temperature is a poor discriminator between Class II and Class III YSOs.Comment: Accepted for publication in ApJS. 29 pages, 11 figures, 14 tables, 4 appendices. Full versions of data tables (to be published in machine-readable format by ApJS) available at the end of the latex source cod

Return of the EMC Effect: Finite Nuclei

A light front formalism for deep inelastic lepton scattering from finite nuclei is developed. In particular, the nucleon plus momentum distribution and a finite system analog of the Hugenholtz-van Hove theorem are presented. Using a relativistic mean field model, numerical results for the plus momentum distribution and ratio of bound to free nucleon structure functions for Oxygen, Calcium and Lead are given. We show that we can incorporate light front physics with excellent accuracy while using easily computed equal time wavefunctions. Assuming nucleon structure is not modified in-medium we find that the calculations are not consistent with the binding effect apparent in the data not only in the magnitude of the effect, but in the dependence on the number of nucleons.Comment: 11 pages, 6 figure

A human antibody against Zika virus crosslinks the E protein to prevent infection

The recent Zika virus (ZIKV) epidemic has been linked to unusual and severe clinical manifestations including microcephaly in fetuses of infected pregnant women and Guillian-Barré syndrome in adults. Neutralizing antibodies present a possible therapeutic approach to prevent and control ZIKV infection. Here we present a 6.2 Å resolution three-dimensional cryo-electron microscopy (cryoEM) structure of an infectious ZIKV (strain H/PF/2013, French Polynesia) in complex with the Fab fragment of a highly therapeutic and neutralizing human monoclonal antibody, ZIKV-117. The antibody had been shown to prevent fetal infection and demise in mice. The structure shows that ZIKV-117 Fabs cross-link the monomers within the surface E glycoprotein dimers as well as between neighbouring dimers, thus preventing the reorganization of E protein monomers into fusogenic trimers in the acidic environment of endosomes

Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds

The area burned annually by wildfires is expected to increase worldwide due to climate change. Burned areas increase soil erosion rates within watersheds, which can increase sedimentation in downstream rivers and reservoirs. However, which watersheds will be impacted by future wildfires is largely unknown. Using an ensemble of climate, fire, and erosion models, we show that postfire sedimentation is projected to increase for nearly nine tenths of watersheds by \u3e10% and for more than one third of watersheds by \u3e100% by the 2041 to 2050 decade in the western USA. The projected increases are statistically significant for more than eight tenths of the watersheds. In the western USA, many human communities rely on water from rivers and reservoirs that originates in watersheds where sedimentation is projected to increase. Increased sedimentation could negatively impact water supply and quality for some communities, in addition to affecting stream channel stability and aquatic ecosystems

Real-Time and Post-Processed Orbit Determination and Positioning

Novel methods and systems for the accurate and efficient processing of real-time and latent global navigation satellite systems (GNSS) data are described. Such methods and systems can perform orbit determination of GNSS satellites, orbit determination of satellites carrying GNSS receivers, positioning of GNSS receivers, and environmental monitoring with GNSS data

A critical role of hepatic GABA in the metabolic dysfunction and hyperphagia of obesity

Hepatic lipid accumulation is a hallmark of type II diabetes (T2D) associated with hyperinsulinemia, insulin resistance, and hyperphagia. Hepatic synthesis of GABA, catalyzed by GABA-transaminase (GABA-T), is upregulated in obese mice. To assess the role of hepatic GABA production in obesity-induced metabolic and energy dysregulation, we treated mice with two pharmacologic GABA-T inhibitors and knocked down hepatic GABA-T expression using an antisense oligonucleotide. Hepatic GABA-T inhibition and knockdown decreased basal hyperinsulinemia and hyperglycemia and improved glucose intolerance. GABA-T knockdown improved insulin sensitivity assessed by hyperinsulinemic-euglycemic clamps in obese mice. Hepatic GABA-T knockdown also decreased food intake and induced weight loss without altering energy expenditure in obese mice. Data from people with obesity support the notion that hepatic GABA production and transport are associated with serum insulin, homeostatic model assessment for insulin resistance (HOMA-IR), T2D, and BMI. These results support a key role for hepatocyte GABA production in the dysfunctional glucoregulation and feeding behavior associated with obesity