The microgravity environment of the Space Shuttle Columbia middeck during STS-32

Four hours of three-axis microgravity accelerometer data were successfully measured at the MA9F locker location in the Orbiter middeck of Columbia as part of the Microgravity Disturbances Experiment (MDE) on STS-32. These data were measured using the Honeywell In-Space Accelerometer, a small three-axis accelerometer that was hard-mounted onto the Fluid Experiment Apparatus to record the microgravity environment at the exact location of the MDE. Data were recorded during specific mission events such as Orbiter quiescent periods, crew exercise on the treadmill, and numerous Orbiter engine burns. Orbiter background levels were measured to be in the 3 x 10(exp -5) to 2 x 10(exp -4) G range, treadmill operations in the 6 x 10(exp -4) to 5 x 10(exp -3) G range, and Orbiter engine burns from 4 x 10(exp -3) to in excess of 1 x 10(exp -2) G. These data represent some of the first microgravity accelerometer data ever recorded in the middeck area of the Orbiter

MOVELETS: A DICTIONARY OF MOVEMENT

Recent technological advances provide researchers a way of gathering real-time information on an individual’s movement through the use of wearable devices that record acceleration. In this paper, we propose a method for identifying activity types, like walking, standing, and resting, from acceleration data. Our approach decomposes movements into short components called “movelets”, and builds a reference for each activity type. Unknown activities are predicted by matching new movelets to the reference. We apply our method to data collected from a single, three-axis accelerometer and focus on activities of interest in studying physical function in elderly populations. An important technical advantage of our methods is that they allow identification of short activities, such as taking two or three steps and then stopping, as well as low frequency rare activities, such as sitting on a chair. Based on our results we provide simple and actionable recommendations for the design and implementation of large epidemiological studies that could collect accelerometry data for the purpose of predicting the time series of activities and connecting it to health outcomes

Bifenthrin Baseline Susceptibility and Evaluation of Simulated Aerial Applications in \u3ci\u3eStriacosta albicosta\u3c/i\u3e (Lepidoptera: Noctuidae)

Striacosta albicosta (Smith) is a maize pest that has recently expanded its geographical range into the eastern United States and southeastern Canada. Aerial application of pyrethroids, such as bifenthrin, has been a major practice adopted to manage this pest. Reports of field failure of pyrethroids have increased since 2013. Striacosta albicosta populations were collected in 2016 and 2017 from maize fields in Nebraska, Kansas, and Canada and screened with bifenthrin active ingredient in larval contact dose-response bioassays. Resistance ratios estimated were generally low in 2016 (1.04- to 1.32-fold) with the highest LC50 in North Platte, NE (66.10 ng/cm2) and lowest in Scottsbluff, NE (50.10 ng/cm2). In 2017, O’Neill, NE showed the highest LC50 (100.66 ng/cm2) and Delhi, Canada exhibited the lowest (6.33 ng/cm2), resulting in a resistance ratio variation of 6.02- to 15.90-fold. Implications of bifenthrin resistance levels were further investigated by aerial application simulations. Experiments were conducted with a spray chamber where representative S. albicosta populations were exposed to labeled rates of a commercial bifenthrin formulation. Experiments resulted in 100% mortality for all populations, instars, insecticide rates, and carrier volumes, suggesting that levels of resistance estimated for bifenthrin active ingredient did not seem to impact the efficacy of the correspondent commercial product under controlled conditions. Results obtained from this research indicate that control failures reported in Nebraska could be associated with factors other than insecticide resistance, such as issues with the application technique, environmental conditions during and/or after application, or the insect’s natural behavior. Data generated will assist future S. albicosta resistance management programs

Improving alpine-region spectral unmixing with optimal-fit snow endmembers

Surface albedo and snow-covered-area (SCA) are crucial inputs to the hydrologic and climatologic modeling of alpine and seasonally snow-covered areas. Because the spectral albedo and thermal regime of pure snow depend on grain size, areal distribution of snow grain size is required. Remote sensing has been shown to be an effective (and necessary) means of deriving maps of grain size distribution and snow-covered-area. Developed here is a technique whereby maps of grain size distribution improve estimates of SCA from spectral mixture analysis with AVIRIS data