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At least 829 records · Page 46

Switch-like activation of Bruton’s tyrosine kinase by membrane-mediated dimerization

The transformation of molecular binding events into cellular decisions is the basis of most biological signal transduction. A fundamental challenge faced by these systems is that reliance on protein–ligand chemical affinities alone generally results in poor sensitivity to ligand concentration, endangering the system to error. Here, we examine the lipid-binding pleckstrin homology and Tec homology (PH-TH) module of Bruton’s tyrosine kinase (Btk). Using fluorescence correlation spectroscopy (FCS) and membrane-binding kinetic measurements, we identify a phosphatidylinositol (3–5)-trisphosphate (PIP 3 ) sensing mechanism that achieves switch-like sensitivity to PIP 3 levels, surpassing the intrinsic affinity discrimination of PIP 3 :PH binding. This mechanism employs multiple PIP 3 binding as well as dimerization of Btk on the membrane surface. Studies in live cells confirm that mutations at the dimer interface and peripheral site produce effects comparable to that of the kinase-dead Btk in vivo. These results demonstrate how a single protein module can institute an allosteric counting mechanism to achieve high-precision discrimination of ligand concentration. Furthermore, this activation mechanism distinguishes Btk from other Tec family member kinases, Tec and Itk, which we show are not capable of dimerization through their PH-TH modules. This suggests that Btk plays a critical role in the stringency of the B cell response, whereas T cells rely on other mechanisms to achieve stringency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performance of Laser-Based Electronic Devices for Structural Analysis of Amazonian Terra-Firme Forests

Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (<10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass.

54 ENVIRONMENTAL SCIENCES↗

Satellite passive microwave rain measurement techniques for land and ocean

Multiseasonal rainfall was found to be measurable over land with satellite passive microwave data, based upon comparisons between Nimbus 7 Scanning Multichannel Microwave Radiometer (SMME) brightness temperatures (T sub B) and operational WSR-57 radar rain rates. All of the SMMR channels (bipolarized 37, 21, 18, 10.7, and 6.6. GHz T sub B) were compared to radar reflectivities for 25 SMMR passes and 234 radar scans over the U.S. during the spring, summer, and fall of 1979. It was found that the radar rain rates were closely related to the difference between 37 and 21 GHz T sub B. This result is due to the volume scattering effects of precipitation which cause emissivity decreases with frequency, as opposed to emissive surfaces (e.g., water) whose emissivities increase with frequency. Two frequencies also act to reduce the effects of thermometric temperature variations on T sub B to a miminum. During summer and fall, multiple correlation coefficients of 0.80 and 0.75 were obtained. These approach the limit of correlation that can be expected to exist between two very different data sources, especially in light of the errors attributable to manual digitization of PPI photographs of variable quality from various operational weather radar not calibrated for research purposes. During the spring, a significantly lower (0.63) correlation was found. This poorer performance was traced to cases of wet, unvegetated soil being sensed at the lower frequencies through light rain, partly negating the rain scattering signal.

Spencer, R. W.↗

Evaluation of very long baseline interferometry atmospheric modeling improvements

We determine the improvement in baseline length precision and accuracy using new atmospheric delay mapping functions and MTT by analyzing the NASA Crustal Dynamics Project research and development (R&D) experiments and the International Radio Interferometric Surveying (IRIS) A experiments. These mapping functions reduce baseline length scatter by about 20% below that using the CfA2.2 dry and Chao wet mapping functions. With the newer mapping functions, average station vertical scatter inferred from observed length precision (given by length repeatabilites) is 11.4 mm for the 1987-1990 monthly R&D series of experiments and 5.6 mm for the 3-week-long extended research and development experiment (ERDE) series. The inferred monthly R&D station vertical scatter is reduced by 2 mm or by 7 mm is a root-sum-square (rss) sense. Length repeatabilities are optimum when observations below a 7-8 deg elevation cutoff are removed from the geodetic solution. Analyses of IRIS-A data from 1984 through 1991 and the monthly R&D experiments both yielded a nonatmospheric unmodeled station vertical error or about 8 mm. In addition, analysis of the IRIS-A exeriments revealed systematic effects in the evolution of some baseline length measurements. The length rate of change has an apparent acceleration, and the length evolution has a quasi-annual signature. We show that the origin of these effects is unlikely to be related to atmospheric modeling errors. Rates of change of the transatlantic Westford-Wettzell and Richmond-Wettzell baseline lengths calculated from 1988 through 1991 agree with the NUVEL-1 plate motion model (Argus and Gordon, 1991) to within 1 mm/yr. Short-term (less than 90 days) variations of IRIS-A baseline length measurements contribute more than 90% of the observed scatter about a best fit line, and this short-term scatter has large variations on an annual time scale.

Macmillan, D. S.↗

Remote sensing by ERTS satellite of vegetational resources believed to be under possible threat of environmental stress

The distribution of natural vegetation types on North Merritt Island, Florida, was studied by analysis of ERTS multispectral scanner data on the image-100 computer system. The boundaries of six distinct plant associations were located on photos made on the image analyzer, with an insignificant mean error of -24.38 meters. The six plant associations are described; each had a characteristic spectral signature. The difference in average reflectance grey level between the lowest of the four spectral scanning bands and the highest spectral scanning band for the six vegetation types was determined. The decreasing trend of the differences is strongly negatively correlated with height of land.

Poonai, P.↗

Common-Path Interferometric Wavefront Sensing for Space Telescopes

This paper presents an optical configuration for a common-path phase-shifting interferometric wavefront sensor.1 2 This sensor has a host of attractive features which make it well suited for space-based adaptive optics. First, it is strictly reflective and therefore operates broadband, second it is common mode and therefore does not suffer from systematic errors (like vibration) that are typical in other interferometers, third it is a phase-shifting interferometer and therefore benefits from both the sensitivity of interferometric sensors as well as the noise rejection afforded by synchronous detection. Unlike the Shack-Hartman wavefront sensor, it has nearly uniform sensitivity to all pupil modes. Optical configuration, theory and simulations for such a system will be discussed along with predicted performance.

wavefront sensors↗

Multispectral data acquisition and classification - Statistical models for system design

In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.

Huck, F. O.↗

Gpm Level 1 Science Requirements: Science and Performance Viewed from the Ground

GPM meets Level 1 science requirements for rain estimation based on the strong performance of its radar algorithms. Changes in the V5 GPROF algorithm should correct errors in V4 and will likely resolve GPROF performance issues relative to L1 requirements. L1 FOV Snow detection largely verified but at unknown SWE rate threshold (likely < 0.5 –1 mm/hr/liquid equivalent). Ongoing work to improve SWE rate estimation for both satellite and GV remote sensing.

Precipitation↗

Application of Frequency Division Multiplexing and Neural Networks in the Operation and Diagnosis of the Stator Current and Shaft Position Sensors Used in Electric/Hybrid Vehicles

Fast, precise and robust sensing of currents and motor shaft angle is essential for the excellent performance of electric and hybrid vehicles (EV/HEV). Multiplexing techniques are commonly applied in data acquisition systems (DAQs) to digitize the signals sensed in EV/HEV drives. Frequency-division multiplexing (FDM) applied to get the signals from current sensors and resolver angular position sensor has advantages over conventional multiplexing approaches. However, problems such as aging and mechanical imperfections distort the outputs of those sensors, producing measurement errors of the angular position and currents. Conventional techniques designed to compensate for those errors cannot be applied in signals multiplexed in frequency. This paper proposes online techniques to detect and compensate for the distortions in the resolver sensor and current sensors. The demultiplexing process was adjusted to allow distortion detection and compensation. An auto-associative neural network (ANN) compensates for the current measurement error, while an energy-based technique is applied to compensate for the distortions in the resolver outputs. The obtained results show that the distortions were compensated, allowing a more accurate estimation of stator currents and angular position when FDM is applied in EV/HEV DAQs.

Pereira Pinto, Joao↗

Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.

Lin, Bing↗

Recent Improvements in Retrieving Near-Surface Air Temperature and Humidity Using Microwave Remote Sensing

Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.

Roberts, J. Brent↗

Cramer-Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing

Signals of opportunity (SoOp) reflectometry (SoOp-R) is a maturing field for geophysical remote sensing as evidenced by the growing number of airborne and spaceborne experiments. As this approach receives more attention, it is worth analyzing SoOp-R’s capabilities to retrieve subsurface soil moisture (SM) by leveraging communication and navigation satellite transmitters. In this research, the CRLB is used to identify the effects of variable SoOp-R parameters on the best achievable estimation error for root-zone soil moisture (RZSM). This study investigates the use of multiple frequency, polarization, and incidence angle measurement configurations on a two-layered dielectric profile. The results also detail the effects of variable SM conditions on the capability of SoOp-R systems to predict subsurface SM. The most prevalent observation is the importance of using at least two frequencies to limit uncertainties from subsurface SM estimates. If at least two frequencies are used, the CRLB of a profile is retrievable within the root-zone depending on the surface SM content as well as the number of independent measurements of the profile. For a depth of 30 cm, it is observed that a CRLB corresponding to 4% RZSM estimation accuracy is achievable with as few as 2 dual-frequency-based SoOp-R measurements. For this depth, increasing number of measurements provided by polarization and incidence angle allow for sensing of increasingly wet SM profile structures. This study, overall, details a methodology by which SoOp-R receiver system can be designed to achieve a desired CRLB using a trade-off study between the available measurements and SM profile.

Signals of Opportunity (SoOp)↗

Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a

Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.

MERIS timeseries↗

Active Compensation of Radiation Effects on Optical Fibers for Sensing Applications

Neutron and gamma irradiation is known to compact silica, resulting in macroscopic changes in refractive index (RI) and geometric structure. The change in RI and linear compaction in a radiation environment is caused by three well-known mechanisms: (i) radiation-induced attenuation (RIA), (ii) radiation-induced compaction (RIC), and (iii) radiation-induced emission (RIE). These macroscopic changes induce errors in monitoring physical parameters such as temperature, pressure, and strain in optical fiber-based sensors, which limit their application in radiation environments. We present a cascaded Fabry–Perot interferometer (FPI) technique to measure macroscopic properties, such as radiation-induced change in RI and length compaction in real time to actively account for sensor drift. The proposed cascaded FPI consists of two cavities: the first cavity is an air cavity, and the second is a silica cavity. The length compaction from the air cavity is used to deduce the RI change within the silica cavity. We utilize fast Fourier transform (FFT) algorithm and two bandpass filters for the signal extraction of each cavity. Inclusion of such a simple cascaded FPI structure will enable accurate determination of physical parameters under the test.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Differential absorption lidars for remote sensing of atmospheric pressure and temperature profiles

A near infrared differential absorption lidar technique is developed using atmospheric oxygen as a tracer for high resolution vertical profiles of pressure and temperature with high accuracy. Solid-state tunable lasers and high-resolution spectrum analyzers are developed to carry out ground-based and airborne measurement demonstrations and results of the measurements presented. Numerical error analysis of high-altitude airborne and spaceborne experiments is carried out, and system concepts developed for their implementation.

Korb, C. Laurence↗

Sun Glint and Sea Surface Salinity Remote Sensing

A new mission in space, called Aquarius/SAC-D, is being built to measure the salinity of the world's oceans. Salinity is an important parameter for understanding movement of the ocean water. This circulation results in the transportation of heat and is important for understanding climate and climate change. Measuring salinity from space requires precise instruments and a careful accounting for potential sources of error. One of these sources of error is radiation from the sun that is reflected from the ocean surface to the sensor in space. This paper examines this reflected radiation and presents an advanced model for describing this effect that includes the effects of ocean waves on the reflection.

Dinnat, Emmanuel P.↗

DOE Energy Frontiers Research Center for Heterogeneous Functional Materials; the “HeteroFoaM Center”

Synopsis of five year accomplishments: Devices that convert and store energy are generally made from heterogeneous constituent materials that act and interact to selectively conduct, transport, and separate mass, heat, and charge. Controlling these actions and interactions enables the technical breakthroughs that have made fuel cells, batteries, and solid state membranes, for example, essential parts of our society. In the biological sense, these materials are ‘vascular’ rather than primitive ‘cellular’ materials, in which the arrangements and configurations of the constituents (including their void phases) play essential and definitive roles in their functional capabilities. In 2009 a group of investigators, with lifetime investments of effort in the understanding of heterogeneous materials, recognized that the design of such material systems is not an optimization problem as such. Local interactions of the constituents create “emergent” properties and responses that are not part of the formal set of constituent characteristics, in much the same sense that society and culture is created by the group interactions of the people involved. The design of emergent properties is an open question in all formal science, but for energy materials the lack of this foundation science relegates development tasks to Edisonian trial and error, with anecdotal success and frequent costly failures. That group defined, for the first time, multi-scale heterogeneous functional materials with functional disordered and void phase regions as “HeteroFoaM,” and formed the first multidisciplinary research team to define and codify the foundation science of that material class. The primary goal of the HeteroFoaM Center was, and is, to create and establish the multi-scale fundamental knowledge and related methodology required for the rational and systematic multiphysics design of heterogeneous functional materials and their interfaces and surfaces for applications in energy transformation and storage. The scope of the HeteroFoaM center was focused on the discovery and development of the control science of key phenomena across multiple length scales that create functionality in heterogeneous materials and their structured interfaces, boundaries, and surfaces for applications in energy technologies. The HeteroFoaM Center defined a critical path and established an essential foundation for progress in the field of heterogeneous functional materials. Perhaps the single most important element of progress was the establishment of the capability to design, characterize, and model heterogeneous functional materials at the conformal level, i.e., for a limited set of material systems, the HeteroFoaM team defined how to control the order / disorder at the atomic level, the surfaces, and the interfaces for selected constituent morphologies, and to use multiphysical models to explain the remarkable property variations resulting from that control science for several heterogeneous material systems. For those cases we defined “meso-structures” (at various scales) where the interactive physics of constituent phases acted to create emergent properties, e.g., strongly emergent mixed conductor behavior and ionic transport. The general approach used by this EFRC is shown in Fig. 1. The HeteroFoaM Center created the genre of Heterogeneous Functional Materials with functional surfaces and interfaces (including void phases) called HeteroFoaM as a science platform to enable rational analysis and design of functional material systems by focusing on the meso-interactions that drive emergent response. The team firmly established this approach with over 180 archival publications (see “Publications” section), 7 patent applications, and over 100 invited lectures in 15 countries on this topic, enabled by building a remarkably effective and uniquely coherent research team. Indeed, our team was our principal strength; this problem eluded solution earlier because such a team was not available.

36 MATERIALS SCIENCE↗