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At least 1,549 records · Page 86

Horizontal transfer of chromosomal DNA mediated by an integrative and conjugative element generates frequent localized recombination in Novosphingobium aromaticivorans

Horizontal gene transfer is an important evolutionary process by which DNA is exchanged between cells that are physically co-located but not direct evolutionary descendants. Horizontal transfer of highly divergent DNA is relatively easy to detect and can produce major phenotypic changes, exemplified by the acquisition of antibiotic resistance determinants. However, transfer of high-identity DNA, for example, between strains of the same species, is likely to be more frequent, harder to detect, and highly impactful in aggregate. In this work, we demonstrate that soil isolates of the alphaproteobacterium Novosphingobium aromaticivorans can exchange chromosomal DNA, leading to multiple unselected recombination events spanning approximately 10% of the chromosome. Chromosomal recombination was directional and more efficient near an integrative and conjugative element (ICE), and required a relaxase found in the ICE. Recombination could not be observed in strains from closely related Novosphingobium species. In combination, these results suggest that ICE-mediated recombination can efficiently recombine DNA within N. aromaticivorans, increasing the adaptive potential of the species while also enforcing species boundaries through preferential intraspecific recombination.

Allemann, Marco [ORNL]↗

Characterization of inexpensive metal oxide sensor performance for trace methane detection

Abstract. Methane, a major contributor to climate change, is emitted by a variety of natural and anthropogenic sources. Commercially available lab-grade instruments for sensing trace methane are expensive, and previous efforts to develop inexpensive, field-deployable trace methane sensors have had mixed results. Industrial and commercial metal oxide (MOx) methane sensors, which are intended for leak detection and safety monitoring, can potentially be repurposed and adapted for low-concentration sensing. As an initial step towards developing a low-cost sensing system, we characterize the performance of five off-the-shelf MOx sensors for 2–10 ppm methane detection in a laboratory setting (Figaro Engineering TGS2600, TGS2602, TGS2611-C00, TGS2611-E00, and Henan Hanwei Electronics MQ4). We identify TGS2611-C00, TGS2611-E00, and MQ4 as promising for trace methane sensing but show that variations in ambient humidity and temperature pose a challenge for the sensors in this application.

54 ENVIRONMENTAL SCIENCES↗

Inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Eucalyptus tree stands killed by low temperatures in December 1972 were outlined by image enhancement of two separate dates of ERTS-1 images (January 22, 1973-I.D. 1183-18175 and April 22, 1973-I.D. 1273-18183). Three stands larger than 500 meters in size were detected very accurately. In Colorado, range and grassland communities were analyzed by visual interpretation of color composite scene I.D. 1028-17135. It was found that mixtures of plant litter, amount and kind of bare soil, and plant foliage cover made classification of grasslands very difficult. Changes in forest land use were detected on areas as small as 5 acres when ERTS-1 color composite scene 1264-15445 (April 13, 1973) was compared with 1966 ASCS index mosaics (scale 1:60,000). Verification of the changes were made from RB-57 underflight CIR transparencies (scale 1:120,000).

Heller, R. C.↗

MODIS Collection 6 MAIAC Algorithm

This paper describes the latest version of the algorithm MAIAC (Multi-Angle Implementation of Atmospheric Correction) used for processing the MODIS (Moderate-resolution Imaging Spectroradiometer) Collection6 data record. Since initial publication in 2011-2012, MAIAC has changed considerably to adapt to global processing and improve cloud/snow detection, aerosol retrievals and atmospheric correction of MODIS data. The main changes include (1) transition from a 25 to 1 km scale for retrieval of the spectral regression coefficient (SRC) which helped to remove occasional blockiness at 25 km scale in the aerosol optical depth (AOD) and in the surface reflectance, (2) continuous improvements of cloud detection, (3) introduction of smoke and dust tests to discriminate absorbing fine- and coarse mode aerosols, (4) adding over-water processing, (5) general optimization of the LUT (LookUp-Table)-based radiative transfer for the global processing, and others. MAIAC provides an interdisciplinary suite of atmospheric and land products, including cloud mask (CM), column water vapor (CWV), AOD at 0.47 and 0.55 m, aerosol type (background, smoke or dust) and fine-mode fraction over water; spectral bidirectional reflectance factors (BRF), parameters of Ross-thick Lisparse (RTLS) bidirectional reflectance distribution function (BRDF) model and instantaneous albedo. For snow-covered surfaces, we provide subpixel snow fraction and snow grain size. All products come in standard HDF4 (software library) format at 1 km resolution, except for BRF, which is also provided at 500 m resolution on a sinusoidal grid adopted by the MODIS Land team. All products are provided on per-observation basis in daily files except for the BRDF/Albedo product, which is reported every 8 days. Because MAIAC uses a time series approach, BRDF/Albedo is naturally gap-filled over land where missing values are filled-in with results from the previous retrieval. While the BRDF model is reported for MODIS Land bands 1-7 and ocean band 8, BRF is reported for both land and ocean bands 1-12. This paper focuses on MAIAC cloud detection, aerosol retrievals and atmospheric correction and describes MCD19 data products and quality assurance (QA) flags.

MAIAC Algorithm↗

Improved Flaw Detection and Characterization with Difference Thermography

Flaw detection and characterization with thermographic techniques in graphite polymer composites is often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, variations in fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These variations result in a noise floor that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing thermographic responses taken before and after a change in state in a composite to improve the detection of subsurface flaws. A method is presented for registration of the responses before finding the difference. A significant improvement in the detectability is achieved by comparing the differences in response. Examples of changes in state due to application of a load and impact are presented.

Winfree, William P.↗

Fiberoptic sensing technique employing RF modulated interferometry

A detection technique for intensity type fiberoptic sensors is described. It employs a multimode fiber interferometer, with the sensor in one arm, excited by an LED modulated at RF frequencies f(o) and 2f(o). Sensor induced changes in intensity result in corresponding changes in the ratio of the detected f(o) and 2f(o) signals, thus eliminating various common mode effects. Results obtained with a displacement sensor and preliminary results from a pressure sensor illustrate the capabilities of this technique.

Eustace, John G.↗

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

AVHRR (ADVANCED VERY HIGH RESOLUTION RADIOMETER)↗

Cepstral Analysis Detects Ball-Cage Wear

Report discusses application of cepstral analysis to diagnosis of wear in ball-bearing cages in rotating machinery. Ball-cage vibrations and changes in vibrations symptomatic of wear is detected earlier in test than by more conventional methods based on strain-gauge measurements. Particularly useful in diagnoses of gearboxes and rolling-element bearing.

Weese, Gary E.↗

Land use mapping and modelling for the Phoenix Quadrangle

The author has identified the following significant results. Comparison of 9 x 9 MSS band images and color composites made from bands 4, 5, and 6 showing vegetated areas near Phoenix during the summer, fall, and winter seasons aided in definitely establishing that certain land areas were being used as agricultural land and not as rangeland. Agricultural land, which appeared to be fallow, idle, or not irrigated, often became more readily identifiable as agricultural land when comparing different images of identical land areas which have been affected by seasonal vegetation changes. Experimentation with the Bausch and Lomb Zoom Transferscope using MSS images of identical areas in the same spectral band from different time periods, with a quick flip method of alternately viewing the frame areas, enabled rapid detection of a major land use change from agricultural to urban use on the northwest fringe of the metropolitan Phoenix area. The best results in this case were obtained when comparing MSS band 5 images. Examination of MSS transparencies and color composites allowed further updating of a map of land use change in the Phoenix Quadrangle.

Place, J. L.↗

Gravitational Changes of the Earth's Free Oscillation From Earthquakes: Theory and Feasibility Study Using GRACE Inter‐Satellite Tracking

GRACE satellites have detected regional‐scale preseismic, coseismic, and postseismic gravity changes associated with great earthquakes during the GRACE era (2002‐2017). Earthquakes also excite global‐scale transient gravity changes associated with free oscillations that may be discerned for a few days. In this study, we examine such global gravity changes due to Earth's free oscillations and quantify how they affect GRACE measurements. We employ the normal mode formalism to synthesize the global gravity changes after the 2004 Sumatra earthquake and simulate the (gravitational) free oscillation signals manifested in the GRACE K‐band ranging (KBR) measurements. Using the Kaula orbit perturbation theory, we show how GRACE inter‐satellite distances are perturbed through a complex coupling of eigenfrequencies of the normal modes with the Earth's rotation rate and the GRACE satellites' orbital frequency. It is found that a few gravest normal modes can generate range‐rate perturbations as large as 0.2 μm/s, which are comparable to actual errors of GRACE KBR ranging and accelerometer instruments. Wavelet time‐frequency analysis of the GRACE KBR residual data in December 2004 reveals the existence of a significant transient signal after the 2004 Sumatra earthquake. This transient signal is characterized by a frequency of ~0.022 mHz that could be potentially associated with the largest excitation due to the “football” mode of the Earth's free oscillation. However, the results are also affected by low‐frequency noise of the GRACE accelerometers. Improved space‐borne gravitational instrumentation may open new opportunities to study the Earth's interior and earthquakes independently from global seismological analysis.

Ghobadi-Far, Khosro↗

A Continuation of Base-Line Studies for Environmentally Monitoring Space Transportation System (STS) at John F. Kennedy Space Center: Terrestrial Community Analysis - Volume 1

Vegetation and small mammal populations in or around the Merritt Island area were studied. Thirty sites were selected from plant communities which were relatively free of logging, grazing, and clearing operations. The vegetative analysis was designed to yield a quantitative description and ecological explanation of the major types of upland vegetation in order to determine the possible future effects of NASA space activities on them. Changes in the relative abundance of small mammal populations, species diversity, standing crop biomass, reproductive activity, and other demographic features were documented in order to gather sufficient information on these populations so that it would be possible to detect even the smaller nonnatural behavior changes in the mammals which might be attributable to NASA space activities.

Stout, I. J.↗

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Spruce, Joseph P.↗

Developing a self-diagnostic system for piezoelectric sensors

Measurement techniques for developing a self-diagnostic system for piezoelectric sensors are presented. The self-diagnostic system uses two types of measurement techniques based on passive and active evaluation of the piezoelectric element. Both hard and soft failures can be detected by this system. Hard failures such as loss of sensor signal and change in sensor output resistance are determined by monitoring the sensor's output resistance, voltage or current. These are passive measurements of the sensor's output condition. Soft failures include changes in sensor calibration and mounting conditions. Soft failures are detected by measuring structural/electrical impedance of the piezoelectric sensor. Active measurement techniques are used to calculate changes in piezoelectric element properties related to soft failures. This paper describes the general operating principles of a self-diagnostic system and discusses the design of an active/passive measurement technique required for this system to function. Experimental results using two types of piezoelectric accelerometers are presented.

Flanagan, Patrick M.↗

Invisible ship tracks show large cloud sensitivity to aerosol

Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction, but these changes are subject to large uncertainties. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol–cloud interactions. However, only a small fraction of the clouds polluted by shipping show ship tracks. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.

54 ENVIRONMENTAL SCIENCES↗

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

54 ENVIRONMENTAL SCIENCES↗

Detection of Flooding Responses at the River Basin Scale Enhanced by Land use Change

The Georges Creek watershed (area 187.5 sq km) in western Maryland (United States) has experienced land use changes (>17% of area) associated with surface mining of coal. The adjacent Savage River watershed (area 127.2 sq km) is unmined. Moments of flood frequency distributions indicated that climatic variability affected both watersheds similarly. Normalizing annual maximum flows by antecedent streamflow and causative precipitation helped identify trends in flooding response. Analysis of contemporary storm events using Next Generation Weather Radar (NEXRAD) stage III precipitation data showed that Georges Creek floods are characterized by higher peak runoff and a shorter centroid lag than Savage River floods, likely attributable to differences in current land use. Interestingly, Georges Creek produces only two thirds of the storm-flow volume as Savage River, apparently because of infiltration into abandoned deep mine workings and an associated transbasin diversion constructed circa 1900. Empirical trend analysis is thus complicated by both hydroclimatic variability and the legacy of deep mining in the basin.

McCormick, Brian C.↗

Probing boron vacancy defects in hBN via single spin relaxometry

Spin defects in solids offer promising platforms for quantum sensing and memory due to their long coherence times and optical addressability. Here, we integrate a single nitrogen-vacancy (NV) center in diamond with scanning probe microscopy to detect, read out, and spatially map spin-based quantum sensors at the nanoscale. Using the boron vacancy ($V$$^{–}_{B}$) center in hexagonal boron nitride—an emerging two-dimensional spin system—as a model, we detect its electron spin resonance indirectly via changes in the spin relaxation time (T 1 ) of a nearby NV center, eliminating the need for optical excitation or fluorescence detection of the $V$$^{–}_{B}$. Cross-relaxation between NV and $V$$^{–}_{B}$ ensembles significantly reduces NV T1, enabling quantitative nanoscale mapping of defect densities beyond the optical diffraction limit and clear resolution of hyperfine splitting in isotopically enriched h 10 B 15 N. Our method demonstrates interactions between spin sensors in 3D and 2D materials, establishing NV centers as versatile probes for characterizing otherwise inaccessible spin defects.

Quantum metrology↗

Generating Landslide Density Heatmaps for Rapid Detection Using Open-access Satellite Radar Data in Google Earth Engine

Rapid detection of landslides is critical for emergency response, disaster mitigation, and improving our understanding of landslide dynamics. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days of a triggering event, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a SAR backscatter change approach in the cloud-based Google Earth Engine (GEE) that uses multi-temporal stacks of freely available data from the Copernicus Sentinel-1 satellites to generate landslide density heatmaps for rapid detection. We test our GEE-based approach on multiple recent rainfall- and earthquake-triggered landslide events. Our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries and applying topographic masks to remove flat areas unlikely to experience landslides. Importantly, our GEE approach does not require downloading a large volume of data to a local system or specialized processing software, which allows the broader hazard and landslide community to utilize and advance these state-of-the-art remote sensing data for improved situational awareness of landslide hazards.

Alexander L Handwerger↗