Alien Registration- Culbert, Ella M. (Lincoln, Penobscot County)

https://digitalmaine.com/alien_docs/7425/thumbnail.jp

Human-Robot Control Strategies for the NASA/DARPA Robonaut

The Robotic Systems Technology Branch at the NASA Johnson Space Center (JSC) is currently developing robot systems to reduce the Extra-Vehicular Activity (EVA) and planetary exploration burden on astronauts. One such system, Robonaut, is capable of interfacing with external Space Station systems that currently have only human interfaces. Robonaut is human scale, anthropomorphic, and designed to approach the dexterity of a space-suited astronaut. Robonaut can perform numerous human rated tasks, including actuating tether hooks, manipulating flexible materials, soldering wires, grasping handrails to move along space station mockups, and mating connectors. More recently, developments in autonomous control and perception for Robonaut have enabled dexterous, real-time man-machine interaction. Robonaut is now capable of acting as a practical autonomous assistant to the human, providing and accepting tools by reacting to body language. A versatile, vision-based algorithm for matching range silhouettes is used for monitoring human activity as well as estimating tool pose

Combining heterogeneous features for time series prediction

© 2017 IEEE. Time series prediction is a challenging task in reality, and various methods have been proposed for it. However, only the historical series of values are exploited in most of existing methods. Therefore, the predictive models might be not effective in some cases, due to: (1) the historical series of values is not sufficient usually, and (2) features from heterogeneous sources such as the intrinsic features of data samples themselves, which could be very useful, are not take into consideration. To address these issues, we proposed a novel method in this paper which learns the predictive model based on the combination of dynamic features extracted from series of historical values and static features of data samples. To evaluate the performance of our proposed method, we compare it with linear regression and boosted trees, and the experimental results validate our method's superiority

Toward an automated signature recognition toolkit for mission operations

Signature recognition is the problem of identifying an event or events from its time series. The generic problem has numerous applications to science and engineering. At NASA's Johnson Space Center, for example, mission control personnel, using electronic displays and strip chart recorders, monitor telemetry data from three-phase electrical buses on the Space Shuttle and maintain records of device activation and deactivation. Since few electrical devices have sensors to indicate their actual status, changes of state are inferred from characteristic current and voltage fluctuations. Controllers recognize these events both by examining the waveform signatures and by listening to audio channels between ground and crew. Recently the authors have developed a prototype system that identifies major electrical events from the telemetry and displays them on a workstation. Eventually the system will be able to identify accurately the signatures of over fifty distinct events in real time, while contending with noise, intermittent loss of signal, overlapping events, and other complications. This system is just one of many possible signature recognition applications in Mission Control. While much of the technology underlying these applications is the same, each application has unique data characteristics, and every control position has its own interface and performance requirements. There is a need, therefore, for CASE tools that can reduce the time to implement a running signature recognition application from months to weeks or days. This paper describes our work to date and our future plans

Combined effects of heat waves and droughts on avian communities across the conterminous United States

Increasing surface temperatures and climatic variability associated with global climate change are expected to produce more frequent and intense heat waves and droughts in many parts of the world. Our goal was to elucidate the fundamental, but poorly understood, effects of these extreme weather events on avian communities across the conterminous United States. Specifically, we explored: (1) the effects of timing and duration of heat and drought events, (2) the effects of jointly occurring drought and heat waves relative to these events occurring in isolation, and (3) how effects vary among functional groups related to nest location and migratory habit, and among ecoregions with differing precipitation and temperature regimes. Using data from remote sensing, meteorological stations, and the North American Breeding Bird Survey, we used mixed effects models to quantify responses of overall and functional group abundance to heat waves and droughts (occurring alone or in concert) at two key periods in the annual cycle of birds: breeding and post-fledging. We also compared responses among species with different migratory and nesting characteristics, and among 17 ecoregions of the conterminous United States. We found large changes in avian abundances related to 100-year extreme weather events occurring in both breeding and post-fledging periods, but little support for an interaction among time periods. We also found that jointly-, rather than individually-occurring heat waves and droughts were both more common and more predictive of abundance changes. Declining abundance was the only significant response to post-fledging events, while responses to breeding period events were larger but could be positive or negative. Negative responses were especially frequent in the western U.S., and among ground-nesting birds and Neotropical migrants, with the largest single-season declines (36%) occurring among ground-nesting birds in the desert Southwest. These results indicate the importance of functional traits, timing, and geography in determining avian responses to weather extremes. Because dispersal to other regions appears to be an important avian response, it may be essential to maintain habitat refugia in a more climatically variable future

Uncommon mixed outbreak of pneumococcal and meningococcal meningitis in Jirapa District, Upper West Region, Ghana, 2016

Objective: The Jirapa District in Ghana falls within the African meningitis belt where over 500 million people are at risk of epidemic meningitis. The district suffered an outbreak of Neisseria meningitides, W (NMW) in 2012 and a mixed outbreak of Streptococcus pneumonia and NMW in early 2016. We investigated the outbreak to identify the source, causative agents, and magnitude and assess health facility preparedness and propose control measures.Design and Setting: We conducted a descriptive study in all sub-districts of Jirapa, between 28th February to10th April 2016. We reviewed records at health facilities, assessed health facility preparedness, searched for cases, traced contacts of case to administer chemoprophylaxis and collect CSF for laboratory analysis. Data were entered in Microsoft excel cleaned, and exported to stata-13 for analysis by person place and time.Results: A total 233 meningitis cases were reported with mean age of 22.4years and standard deviation 21.6. Males were (57%), females (43%) and 60.8% were less than 19 years. Attack rate of meningitis was 214/100,000 with case fatality rate (CFR) of 12.4% (29/233). Causative agents were NMW (69.5%) and streptococcus pneumonia (27.1%), mainly serotype STN1 and H. influenza (3.4%). The index case had travel history to dollar power, close to Tain District which is the epicentre for the 2016 meningitis outbreak in Ghana.Conclusion: The Jirapa district experienced a mixed outbreak of streptococcal and meningococcal meningitis in early 2016, facilitated by migration. Active surveillance and mass vaccination with multivalent vaccines is required to protect the population.Funding: Ghana Field Epidemiology and Laboratory Training Programme (GFELTP)Keywords: Meningitis, outbreak, surveillance, Jirapa, CS

Effects of drought on avian community structure

Droughts are expected to become more frequent under global climate change. Avifauna depend on precipitation for hydration, cover, and food. While there are indications that avian communities respond negatively to drought, little is known about the response of birds with differing functional and behavioral traits, what time periods and indicators of drought are most relevant, or how response varies geographically at broad spatial scales. Our goals were thus to determine (1) how avian abundance and species richness are related to drought, (2) whether community variations are more related to vegetation vigor or precipitation deviations and at what time periods relationships were strongest, (3) how response varies among avian guilds, and (4) how response varies among ecoregions with different precipitation regimes. Using mixed effect models and 1989–2005 North American Breeding Bird Survey data over the central United States, we examined the response to 10 precipitation- and greenness based metrics by abundance and species richness of the avian community overall, and of four behavioral guilds. Drought was associated with the most negative impacts on avifauna in the semiarid Great Plains, while positive responses were observed in montane areas. Our models predict that in the plains, Neotropical migrants respond the most negatively to extreme drought, decreasing by 13.2% and 6.0% in abundance and richness, while permanent resident abundance and richness increase by 11.5% and 3.6%, respectively in montane areas. In most cases, response of abundance was greater than richness and models based on precipitation metrics spanning 32-week time periods were more supported than those covering shorter time periods and those based on greenness. While drought is but one of myriad environmental variations birds encounter, our results indicate that drought is capable of imposing sizable shifts in abundance, richness, and composition on avian communities, an important implication of a more climatically variable future