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At least 775 records · Page 43

Ka-Band Scanning ARM Cloud Radar (KASACR), 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross Mode (a1-level)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

kasacr2cfrspccwrhixpol (a1)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

Ka-Band Scanning ARM Cloud Radar (KASACR), 2nd Generation CF-Radial Spectral Data, Vertically-Pointing Scan, Cross-Polarization Mode (a1-level)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

kasacr2cfrspccwrhicross (a1)

The Ka-Band Scanning ARM Cloud Radar (KASACR) records cloud properties. ARM's scanning cloud radars are dual-frequency, dual-polarization Doppler radars mounted on a common scanning pedestal. Each pedestal includes a Ka-band radar (2kW peak power) and the deployment location determines whether the second radar is a W-band (1.7 kW peak power) or an X-band (20 kW peak power). Beamwidths for Ka-bands paired with W-bands are roughly matched at 0.3 degrees. The X-band beamwidth is approximately 1 degree. Due to the narrow antenna beamwidth, ARM’s scanning cloud radars use scanning strategies unlike typical weather radars. Rather than focusing on plan position indicator, or PPI, scans, the KASACR uses range height indicator, or RHI, scans at numerous azimuths to obtain cloud volume data. Measurements collected with the KASACR are copolar and cross-polar radar reflectivity, Doppler velocity, spectra width and spectra when not scanning, and linear depolarization ratio. KASACR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

CACTI CSAPR2 Taranis Retrievals

Taranis is an end-to-end processing chain for radar data written in Python with C extension for computation performance. Features include: masking for quality control, specific differential phase (Kdp), attenuation correction for reflectivity factor (Z) and differential reflectivity (Zdr) in rain, and additional geophysical retrievals. Retrievals are mostly drawn from literature or open-source software when appropriate, and have been tested, tuned, and modified to work with one another cohesively rather than using isolated off-the-shelf algorithms. Incorporated algorithms include hydrometeor (echo) identification, rain water content, raindrop mass-weighted mean diameter (gamma size distribution assumption), and rainfall rate (QPE). Taranis data sets exist for CSAPR2 PPI, HSRHI, and sector RHI scans. Cartesian-gridded data sets were also produced as well as a near-surface rain rate retrieval. More details can be found in the README.

54 ENVIRONMENTAL SCIENCES↗

Radar and lidar based cloud type product at the ARM ENA observatory

Following methods outlined in Remillard et al. (2012), we classify seven cloud types using radar reflectivity, best-estimated cloud base, and cloud-layer product from the Active Remotely Sensed Cloud Locations (ARSCL) product (Kollias et al. 2007). A cloud mask is created based on the detectable radar reflectivity (>-40 dBZ) combined with the best-estimated cloud base height. Each cloud object is analyzed individually as contiguous cloudy pixels, and its type is determined based on the cloud’s boundaries and duration. Focusing on marine boundary-layer clouds, low clouds are further classified into four types: shallow cumulus, broken stratocumulus (Sc) or cumulus clouds, single-layer Sc, and multi-layer Sc or Sc coupled with cumulus. The remaining three categories are middle clouds, high clouds, and deep convective clouds. For detailed definition of each cloud type, please refer to Zheng et al. (2024).

54 ENVIRONMENTAL SCIENCES↗

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗

SITCOMTN-164: AnaCal Shear Profile of Abell 360 in LSSTComCam Data Preview 1

This technote presents the measurement of the weak-lensing shear profile for the Abell 360 galaxy cluster using LSSTComCam data processed with the AnaCal pipeline. We detail the procedures involved in bright-star masking, source selection, and the estimation of tangential and cross shear around the cluster center. The resulting shear profiles provide key insights into the mass distribution of Abell 360 and demonstrate the capabilities of AnaCal in processing early LSST data, with the tangential shear profile detected at 5σ significance.

79 ASTRONOMY AND ASTROPHYSICS↗

A dynamic interaction between CD19 and the tetraspanin CD81 controls B cell co-receptor trafficking

CD81 and its binding partner CD19 are core subunits of the B cell co-receptor complex. While CD19 belongs to the extensively studied Ig superfamily, CD81 belongs to a poorly understood family of four-pass transmembrane proteins called tetraspanins. Tetraspanins play important physiological roles by controlling protein trafficking and other processes. Here, we show that CD81 relies on its ectodomain to traffic CD19 to the cell surface. Moreover, the anti-CD81 antibody 5A6, which binds selectively to activated B cells, recognizes a conformational epitope on CD81 that is masked when CD81 is bound to CD19. Mutations of CD81 in this interface suppress its CD19 export activity. These data indicate that the CD81 - CD19 interaction is dynamically regulated upon B cell activation and this dynamism can be exploited to regulate B cell function. These results are not only valuable for understanding B cell biology, but also have important implications for understanding tetraspanin function generally.

59 BASIC BIOLOGICAL SCIENCES↗

Structure-guided microbial targeting of antistaphylococcal prodrugs

Carboxy ester prodrugs are widely employed to increase oral absorption and potency of phosphonate antibiotics. Prodrugging can mask problematic chemical features that prevent cellular uptake and may enable tissue-specific compound delivery. However, many carboxy ester promoieties are rapidly hydrolyzed by serum esterases, limiting their therapeutic potential. While carboxy ester-based prodrug targeting is feasible, it has seen limited use in microbes as microbial esterase-specific promoieties have not been described. Here we identify the bacterial esterases, GloB and FrmB, that activate carboxy ester prodrugs in Staphylococcus aureus. Additionally, we determine the substrate specificities for FrmB and GloB and demonstrate the structural basis of these preferences. Finally, we establish the carboxy ester substrate specificities of human and mouse sera, ultimately identifying several promoieties likely to be serum esterase-resistant and microbially labile. These studies will enable structure-guided design of antistaphylococcal promoieties and expand the range of molecules to target staphylococcal pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Regrowth method for fabricating wide-bandgap transistors, and devices made thereby

Methods are provided for fabricating a HEMT (high-electron-mobility transistor) that involve sequential epitaxial growth of III-nitride channel and barrier layers, followed by epitaxial regrowth of further III-nitride material through a window in a mask layer. The regrowth takes place on the barrier layer, only in the access region or regions. Devices made according to the disclosed methods are also provided.

36 MATERIALS SCIENCE↗

System and method for high power diode based additive manufacturing

A system is disclosed for performing an Additive Manufacturing (AM) fabrication process on a powdered material forming a substrate. The system may make use of a diode array for generating an optical signal sufficient to melt a powdered material of the substrate. A mask may be used for preventing a first predetermined portion of the optical signal from reaching the substrate, while allowing a second predetermined portion to reach the substrate. At least one processor may be used for controlling an output of the diode array.

36 MATERIALS SCIENCE↗

Sequential infiltration synthesis for enhancing multiple-patterning lithography

Simplified methods of multiple-patterning photolithography using sequential infiltration synthesis to modify the photoresist such that it withstands plasma etching better than unmodified resist and replaces one or more hard masks and/or a freezing step in MPL processes including litho-etch-litho-etch photolithography or litho-freeze-litho-etch photolithography.

36 MATERIALS SCIENCE↗

Using Diffuse Scattering to Observe X-Ray-Driven Nonthermal Melting

We present results from the SPring-8 Angstrom Compact free electron LAser (SACLA) XFEL facility, using a high intensity ($\sim\!10^{20}\,$W/cm$^2$) X-ray pump X-ray probe scheme to observe changes in the ionic structure of silicon induced by X-ray heating of the electrons. By avoiding Laue spots in the scattering signal from a single crystalline sample, we observe a rapid rise in diffuse scattering, which we attribute to a loss of lattice order and a transition to a liquid state within 100 fs of irradiation, a timescale which agrees well with first principles simulations, but is faster than that predicted by purely inertial behavior. This method is capable of observing liquid scattering without masking or filtering of signal from the ambient solid, allowing the liquid structure to be measured throughout and beyond the phase change.

Hartley, Nicholas J.↗

Patterned electrode catalyst

Disclosed herein are embodiments of a patterned electrode comprising regions of catalyst and segregating regions that separate the regions of catalyst. The segregating regions may be regions of non-catalytic material. The catalyst regions may correspond to the channels of a flow field. The electrode provides improved fuel cell performance, particularly at high current densities. The electrode may be for all suitable applications, such as in a membrane electrode assembly and/or a fuel cell. Also disclosed is a method for making the patterned electrode. The method may comprise using masks to apply the catalyst and non-catalyst material to a substrate.

Macauley, Natalia↗

Formation of antireflective surfaces

Technologies are described for methods and systems effective for etching nanostructures in a substrate. The methods may comprise depositing a patterned block copolymer on the substrate. The patterned block copolymer may include first and second polymer block domains. The methods may comprise applying a precursor to the patterned block copolymer to generate an infiltrated block copolymer. The precursor may infiltrate into the first polymer block domain and generate a material in the first polymer block domain. The methods may comprise applying a removal agent to the infiltrated block copolymer to generate a patterned material. The removal agent may be effective to remove the first and second polymer block domains from the substrate. The methods may comprise etching the substrate. The patterned material on the substrate may mask the substrate to pattern the etching. The etching may be performed under conditions to produce nanostructures in the substrate.

Black, Charles T.↗

Protein and nucleic acid detection for microfluidic devices

The present invention relates to methods for detecting targets by employing a temperature control system with a microfluidic device. The system allows for non-contact heating by employing an infrared emitter. In some instances, the system can be used in conjunction with a centrifugal microfluidic device. Optionally, a mask can be implemented to provide selective heating of desired assay areas of the device.

Koh, Chung-Yan↗

Friction reduction for engine components

The present invention relates to techniques for lowering friction between moving surfaces of, for example, an internal combustion engine. Friction reduction is achieved by adding texture modifications to surfaces that come in contact with each other. Texture modifications that reduce friction in accordance with the present invention include dimples of varying geometries and depths ion the surfaces of components. The present invention also relates to the fabrication technique for applying the texture to the surfaces. In another embodiment, the patterned soft mask is applied onto a large surface (flat or curved including cylindrical rollers surfaces) to be followed by electrochemical etching to imprint the textures onto the component And, in another embodiment, a diamond-like-carbon (DLC) film may be applied to the turbine component to also reduce friction.

Hsu, Stephen M.↗