Growing Critical: Self-Organized Criticality in a Developing Neural System

Experiments in various neural systems found avalanches: bursts of activity with characteristics typical for critical dynamics. A possible explanation for their occurrence is an underlying network that self-organizes into a critical state. We propose a simple spiking model for developing neural networks, showing how these may "grow into" criticality. Avalanches generated by our model correspond to clusters of widely applied Hawkes processes. We analytically derive the cluster size and duration distributions and find that they agree with those of experimentally observed neuronal avalanches.Comment: 6 pages, 4 figures, supplemental material: 10 pages, 7 figure

A summary of the users perspective of LANDSAT-D and reference document of LANDSAT users

There are no author-identified significant results in this report

Dual-Fiberoptic Microcantilever Proximity Sensor

Microcantilevers are key components of many Micro-Electro-Mechanical Systems (MEMS) and Micro-Optical-Electro-Mechanical Systems (MOEMS) because slight changes to them physically or chemically lead to changes in mechanical characteristics. An inexpensive dual-fiberoptic microcantilever proximity sensor and model to predict its performance are reported here. Motion of a magnetic-material-coated cantilever is the basis of a system under development for measuring magnetic fields. The dual fiber proximity sensor will be used to monitor the motion of the cantilever. The specific goal is to sense induction fields produced by a current carrying conductor. The proximity sensor consists of two fibers side by side with claddings in contact. The fiber core diameter, 50 microns, and cladding thickness, 10 microns, are as small as routinely available commercially with the exception of single mode fiber. Light is launched into one fiber from a light-emitting diode (LED). It emerges from that fiber and reflects from the cantilever into the adjacent receiving fiber connected to a detector. The sensing end is cast molded with a diameter of 3-mm over the last 20-mm, yielding a low profile sensor. This reflective triangulation approach is probably the oldest and simplest fiber proximity sensing approach, yet the novelty here is in demonstrating high sensitivity at low expense from a triangular microstructure with amorphous magnetic coatings of iron, cobalt, permalloy, etc. The signal intensity versus distance curve yields an approximate gaussian shape. For a typical configuration, the signal grows from 10% to 90% of maximum in traversing from 6 to 50 microns from a coated cantilever. With signal levels exceeding a volt, nanometer resolution should be readily achievable for periodic signals

Prioritizing county-level well-being: Moving toward assessment of Gulf Coast counties impacted by the Deepwater Horizon Industrial Disaster

To develop a portfolio of indicators and measures that could best measure changes in the social, economic, environmental and health dimensions of well-being in coastal counties we convened a group of experts March 8-9, 2011 in Charleston, SC, U.S.A. The region of interest was of the northern Gulf of Mexico, specifically, those coastal counties most impacted during the explosion and subsequent oil spill from the Macondo Prospect wellhead during the summer of 2010. Over the course of the two-day workshop participants moved through presentations and facilitated sessions to identify and prioritize potential indicators and measures deemed most valuable for capturing changes in well-being related to changes in or disruption of ecosystem services. The experts reached consensus on a list of indicators that are now being operationalized by NOAA researchers. The ultimate goal of this research project is to determine whether a meaningful set of social and economic indicators can be developed to document changes in well-being that occur as a result of changes in ecosystem services. The outcomes and outputs from the workshop that is the subject of this report helped us to identify high-quality indicators useful for measuring well-being

Monitoring well-being and changing environmental conditions in coastal communities: development of an assessment method

The intersection of social and environmental forces is complex in coastal communities. The well-being of a coastal community is caught up in the health of its environment, the stability of its economy, the provision of services to its residents, and a multitude of other factors. With this in mind, the project investigators sought to develop an approach that would enable researchers to measure these social and environmental interactions. The concept of well-being proved extremely useful for this purpose. Using the Gulf of Mexico as a regional case study, the research team developed a set of composite indicators to be used for monitoring well-being at the county-level. The indicators selected for the study were: Social Connectedness, Economic Security, Basic Needs, Health, Access to Social Services, Education, Safety, Governance, and Environmental Condition. For each of the 37 sample counties included in the study region, investigators collected and consolidated existing, secondary data representing multiple aspects of objective well-being. To conduct a longitudinal assessment of changing wellbeing and environmental conditions, data were collected for the period of 2000 to 2010. The team focused on the Gulf of Mexico because the development of a baseline of well-being would allow NOAA and other agencies to better understand progress made toward recovery in communities affected by the Deepwater Horizon oil spill. However, the broader purpose of the project was to conceptualize and develop an approach that could be adapted to monitor how coastal communities are doing in relation to a variety of ecosystem disruptions and associated interventions across all coastal regions in the U.S. and its Territories. The method and models developed provide substantial insight into the structure and significance of relationships between community well-being and environmental conditions. Further, this project has laid the groundwork for future investigation, providing a clear path forward for integrated monitoring of our nation’s coasts. The research and monitoring capability described in this document will substantially help counties, local organizations, as well state and federal agencies that are striving to improve all facets of community well-being

MicroRNA 7 Impairs Insulin Signaling and Regulates Aβ Levels through Posttranscriptional Regulation of the Insulin Receptor Substrate 2, Insulin Receptor, Insulin-Degrading Enzyme, and Liver X Receptor Pathway

Brain insulin resistance is a key pathological feature contributing to obesity, diabetes, and neurodegenerative disorders, including Alzheimer’s disease (AD). Besides the classic transcriptional mechanism mediated by hormones, posttranscriptional regulation has recently been shown to regulate a number of signaling pathways that could lead to metabolic diseases. Here, we show that microRNA 7 (miR-7), an abundant microRNA in the brain, targets insulin receptor (INSR), insulin receptor substrate 2 (IRS-2), and insulin-degrading enzyme (IDE), key regulators of insulin homeostatic functions in the central nervous system (CNS) and the pathology of AD. In this study, we found that insulin and liver X receptor (LXR) activators promote the expression of the intronic miR-7-1 in vitro and in vivo, along with its host heterogeneous nuclear ribonucleoprotein K (HNRNPK) gene, encoding an RNA binding protein (RBP) that is involved in insulin action at the posttranscriptional level. Our data show that miR-7 expression is altered in the brains of diet-induced obese mice. Moreover, we found that the levels of miR-7 are also elevated in brains of AD patients; this inversely correlates with the expression of its target genes IRS-2 and IDE. Furthermore, overexpression of miR-7 increased the levels of extracellular Aβ in neuronal cells and impaired the clearance of extracellular Aβ by microglial cells. Taken together, these results represent a novel branch of insulin action through the HNRNPK–miR-7 axis and highlight the possible implication of these posttranscriptional regulators in a range of diseases underlying metabolic dysregulation in the brain, from diabetes to Alzheimer’s disease