Weight Management Program for Fire Fighters: Feasibility Pilot

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The Heliogyro Reloaded

The heliogyro is a high-performance, spinning solar sail architecture that uses long - order of kilometers - reflective membrane strips to produce thrust from solar radiation pressure. The heliogyro s membrane blades spin about a central hub and are stiffened by centrifugal forces only, making the design exceedingly light weight. Blades are also stowed and deployed from rolls; eliminating deployment and packaging problems associated with handling extremely large, and delicate, membrane sheets used with most traditional square-rigged or spinning disk solar sail designs. The heliogyro solar sail concept was first advanced in the 1960s by MacNeal. A 15 km diameter version was later extensively studied in the 1970s by JPL for an ambitious Comet Halley rendezvous mission, but ultimately not selected due to the need for a risk-reduction flight demonstration. Demonstrating system-level feasibility of a large, spinning heliogyro solar sail on the ground is impossible; however, recent advances in microsatellite bus technologies, coupled with the successful flight demonstration of reflectance control technologies on the JAXA IKAROS solar sail, now make an affordable, small-scale heliogyro technology flight demonstration potentially feasible. In this paper, we will present an overview of the history of the heliogyro solar sail concept, with particular attention paid to the MIT 200-meter-diameter heliogyro study of 1989, followed by a description of our updated, low-cost, heliogyro flight demonstration concept. Our preliminary heliogyro concept (HELIOS) should be capable of demonstrating an order-of-magnitude characteristic acceleration performance improvement over existing solar sail demonstrators (HELIOS target: 0.5 to 1.0 mm/s2 at 1.0 AU); placing the heliogyro technology in the range required to enable a variety of science and human exploration relevant support missions

An analysis of technology gaps and priorities in support of probe-scale coronagraph and starshade missions

This paper provides a survey of the state-of-the-art in coronagraph and starshade technologies and highlights areas where advances are needed to enable future NASA exoplanet missions. An analysis is provided of the remaining technology gaps and the relative priorities of technology investments leading to a mission that could follow JWST. This work is being conducted in support of NASAs Astrophysics Division and the NASA Exoplanet Exploration Program (ExEP), who are in the process of assessing options for future missions. ExEP has funded Science and Technology Definition Teams to study coronagraphs and starshade mission concepts having a lifecycle cost cap of less than $1B. This paper provides a technology gap analysis for these concepts

Spatial representation of temporal information through spike timing dependent plasticity

We suggest a mechanism based on spike time dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model system of simplified integrate-and-fire type neurons densely connected by STDP synapses. All synapses are modified according to the so-called normal STDP rule observed in various real biological synapses. After conditioning through repeated input of a limited number of of temporal sequences the system is able to complete the temporal sequence upon receiving the input of a fraction of them. This is an example of effective unsupervised learning in an biologically realistic system. We investigate the dependence of learning success on entrainment time, system size and presence of noise. Possible applications include learning of motor sequences, recognition and prediction of temporal sensory information in the visual as well as the auditory system and late processing in the olfactory system of insects.Comment: 13 pages, 14 figures, completely revised and augmented versio

Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression

Changes in synaptic efficacies need to be long-lasting in order to serve as a substrate for memory. Experimentally, synaptic plasticity exhibits phases covering the induction of long-term potentiation and depression (LTP/LTD) during the early phase of synaptic plasticity, the setting of synaptic tags, a trigger process for protein synthesis, and a slow transition leading to synaptic consolidation during the late phase of synaptic plasticity. We present a mathematical model that describes these different phases of synaptic plasticity. The model explains a large body of experimental data on synaptic tagging and capture, cross-tagging, and the late phases of LTP and LTD. Moreover, the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency. The stabilization of potentiated synapses during the transition from early to late LTP occurs by protein synthesis dynamics that are shared by groups of synapses. The functional consequence of this shared process is that previously stabilized patterns of strong or weak synapses onto the same postsynaptic neuron are well protected against later changes induced by LTP/LTD protocols at individual synapses

Long-Term Potentiation: One Kind or Many?

Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation (LTP). I argue that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds

State based model of long-term potentiation and synaptic tagging and capture

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file