Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available

Using Genetic Programming to Investigate a Novel Model of Resting Energy Expenditure for Bariatric Surgery Patients

Traditionally, models developed to estimate resting energy expenditure (REE) in the bariatric population have been limited to linear modelling based on data from `normal' or `overweight' individuals - not `obese'. This type of modelling can be restrictive and yield functions which poorly estimate this important physiological outcome.Linear and nonlinear models of REE for individuals after bariatric surgery are developed with linear regression and symbolic regression via genetic programming. Features not traditionally used in REE modelling were also incorporated and analyzed and genetic programming's intrinsic feature selection was used as a measure of feature importance.A collection of effective new linear and nonlinear models were generated. The linear models generated outperformed the nonlinear on testing data, although the nonlinear models fit the training data better. Ultimately, the newly developed linear models showed an improvement over existing models and the feature importance analysis suggested that the typically used features (age, weight, and height) were the most important

Breast Milk, a Source of Beneficial Microbes and Associated Benefits for Infant Health

peer-reviewedHuman breast milk is considered the optimum feeding regime for newborn infants due to its ability to provide complete nutrition and many bioactive health factors. Breast feeding is associated with improved infant health and immune development, less incidences of gastrointestinal disease and lower mortality rates than formula fed infants. As well as providing fundamental nutrients to the growing infant, breast milk is a source of commensal bacteria which further enhance infant health by preventing pathogen adhesion and promoting gut colonisation of beneficial microbes. While breast milk was initially considered a sterile fluid and microbes isolated were considered contaminants, it is now widely accepted that breast milk is home to its own unique microbiome. The origins of bacteria in breast milk have been subject to much debate, however, the possibility of an entero-mammary pathway allowing for transfer of microbes from maternal gut to the mammary gland is one potential pathway. Human milk derived strains can be regarded as potential probiotics; therefore, many studies have focused on isolating strains from milk for subsequent use in infant health and nutrition markets. This review aims to discuss mammary gland development in preparation for lactation as well as explore the microbial composition and origins of the human milk microbiota with a focus on probiotic development

Deep brain stimulation for levodopa-refractory benign tremulous parkinsonism

Benign tremulous parkinsonism (BTP) is characterized by prominent resting tremor combined with action and postural components, and with only subtle rigidity and bradykinesia. This tremor is frequently disabling and poorly responsive to therapy with levodopa. Thus, BTP could be considered either as a distinct clinical disorder or a variant of PD. We present a case of a 57-year-old man who had a 3-year history of severe and functionally disabling resting tremor with action and postural features bilaterally but with left dominant hand predominance. There was only very mild rigidity and bradykinesia and no postural instability. His tremor was refractory to dopaminergic therapy, including carbidopa/levodopa. The dopamine transporter (DAT) imaging showed reduced tracer uptake in the putamen bilaterally, more so on the right side. He was treated with deep brain stimulation (DBS) targeting the right ventral intermediate nucleus of the thalamus. His tremor resolved immediately after procedure. The DAT imaging abnormalities indicate the presynaptic dopamine deficiency. In some autopsied BTP cases classic alpha-synuclein pathology of PD was observed. Thus, despite the lack of levodopa responsiveness BTP likely represents a variant of PD and not a distinct neurodegenerative disorder. DBS should be considered for patients with BTP PD variant despite their poor responsiveness to levodopa treatment

Can Collegiate Hockey Players Accurately Predict Regional and Total Body Physiologic Changes throughout the Competitive Season?

A collegiate athlete’s body composition can fluctuate due to factors such as nutrition, sleep, and training load. As changes in body composition can affect an athlete’s level of performance, it may be beneficial if athlete’s can accurately predict these changes throughout a season. The purpose of this study was to determine how well a group of 23 male collegiate hockey players (age = 22.44 ± 1.16 years, height = 181.30 ± 6.99 cm, weight = 86.41 ± 8.32 kg) could predict their regional and total body lean and fat tissue mass throughout a hockey season (September to March). Total body, trunk, lower body, and upper body compositional changes were measured at the beginning and at the end of the competitive season using dual energy X-Ray absorptiometry (DXA). At the end of the season, a questionnaire was completed by each participant to explore how they perceived their body composition changes (losses or gains in lean tissue and fat mass) throughout the season. Overall, players had a difficult time identifying actual changes in lean tissue and fat mass throughout the season. Upper body fat and lean tissue changes were perceived most accurately, while perceptions of body fat were related to android adiposity but not visceral adiposity. These findings suggest that some regional areas of body composition changes may happen without being noticed. For strength and conditioning coaches, if athletes are made aware of these changes before they become exaggerated, proper dietary, and training adaptations can be made to enhance performance

Stennis Space Center Verification & Validation Capabilities

Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data