FRMAC Gamma Spectroscopist Training : Environmental in-situ gamma spectroscopy (Revision 01)
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Enghauser, Michael (ORCID:0009000470534902)↗
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FRMAC Gamma Spectroscopist Training : Source modeling for quantitative spectral analysis (Revision 01)
Explore the source record for details and available documents.
Enghauser, Michael (ORCID:0009000470534902)↗
Optode Images, and Dissolved Oxygen Data from Sand and Sediment Flow-through Column Experiments associated with: "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns"
This data package is associated with the publication "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns" submitted to Frontiers in Water (Garayburu-Caruso et al., 2022). This work presents a novel application of planar optode technology to sediment columns that allows the study of well-constrained flow fields without the need to assume completely homogeneous flow. We introduce a flow-through column with the interior coated in an oxygen sensing film and a series of sampling ports as a unique tool capable of capturing changes in dissolved oxygen (DO) at high frequency (10 s) and spatial (< 1 mm) resolution across the length of a column. In addition, we provide custom scripts that allows image processing steps to be automated and consistently reproduced over a variety of experimental conditions. This dataset is comprised of four folders (1) 01_Riverbed_Sediment_Experiment, (2) 02_Sand_Experiment, (3) 01_Riverbed_Sediment_Raw_Images, and (4) 02_Sand_Experiment_Raw_Images. 01_Riverbed_Sediment_Experiment contains (1) a subfolder with csv files that contain statistical parameters from the linear regressions applied to each optode image, (2) a subfolder with csv files from DO data measured by in-line sensors, (3) a subfolder with csv files containing column and injection specific input parameters for the image processing script, and (4) a subfolder with scripts used to process the images and create associated figures. 02_Sand_Experiment contains (1) a subfolder with csv files containing column and injection-specific input parameters for the image processing script, and (2) a subfolder with scripts used to process the images and create associated figures. 01_Riverbed_Sediment_Raw_Images (spited in 3 parts due to size) contains a subfolder with raw red, and green images from the optode system during the MilliQ Injection, Vanillin Injection or Vanillin + Sampling Injection respectively. 02_Sand_Experiment_Raw_Images contains a subfolder with raw red, and green images from the optode system. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package.
54 ENVIRONMENTAL SCIENCES↗
Combined Mesonet and Tracker
Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]
54 ENVIRONMENTAL SCIENCES↗
Hydrophobic interactions dominate the recognition of a KRAS G12V neoantigen
Specificity remains a major challenge to current therapeutic strategies for cancer. Mutation associated neoantigens (MANAs) are products of genetic alterations, making them highly specific therapeutic targets. MANAs are HLA-presented (pHLA) peptides derived from intracellular mutant proteins that are otherwise inaccessible to antibody-based therapeutics. Here, we describe the cryo-EM structure of an antibody-MANA pHLA complex. Specifically, we determine a TCR mimic (TCRm) antibody bound to its MANA target, the KRAS G12V peptide presented by HLA-A*03:01. Hydrophobic residues appear to account for the specificity of the mutant G12V residue. We also determine the structure of the wild-type G12 peptide bound to HLA-A*03:01, using X-ray crystallography. Based on these structures, we perform screens to validate the key residues required for peptide specificity. These experiments led us to a model for discrimination between the mutant and the wild-type peptides presented on HLA-A*03:01 based exclusively on hydrophobic interactions.
36 MATERIALS SCIENCE↗
Anisotropic electrical properties of NiO x /β-Ga 2 O 3 p-n heterojunctions on (2̅01), (001), and (010) crystal orientations
Abstract NiO x / β -Ga 2 O 3 p-n heterojunctions fabricated on ( 2 ̅ 01 ) , ( 001 ) , and ( 010 ) β -Ga 2 O 3 substrates show distinctly anisotropic electrical properties. All three devices exhibited excellent rectification ≥10 9 , and turn-on voltages >2.0 V. The ( 010 ) device showed very different turn-on voltage, specific on-resistance, and reverse recovery time compared with ( 2 ̅ 01 ) and ( 001 ) devices. Moreover, it is calculated that the interface trap state densities for ( 2 ̅ 01 ) , ( 001 ) , and ( 010 ) plane devices are 4.3 × 10 10 , 7.4 × 10 10 , and 1.6 × 10 11 eV –1 cm –2 , respectively. These differences in the NiO x / β -Ga 2 O 3 heterojunctions are attributed to the different atomic configurations, the density of dangling bonds, and interface trap state densities.
Physics↗
Gas Hydrate Saturation Estimation Form Acoustic Log Data in the 2018 Alaska North Slope Hydrate-01 Stratigraphic Test
Completed in December 2018, the Alaska North Slope Hydrate 01 stratigraphic test well provides a wealth of logging-while-drilling (LWD) data for strata to below the base of gas hydrate stability (BGHS). This well is intended to be the first of three wells drilled for a comprehensive long-term gas hydrate production test conducted by the National Energy Technology Laboratory, the Japan Oil, Gas and Metals National Corporation, and the U.S. Geological Survey (USGS). The Hydrate 01 stratigraphic test well confirmed the presence of gas hydrate in two sand reservoirs within the hydrate stability zone, indicating the suitability of this location for a long-term gas hydrate production test.<p>The USGS, using an effective-medium-theory rock-physics approach, has estimated gas hydrate saturations from compressional (P) and shear (S) wave log data acquired in the Hydrate 01 well. We assume that gas hydrate occurs as pore-filling load-bearing material (i.e., part of the grain matrix). For Unit D, approximately 500 feet above the BGHS, both P-wave and S-wave acoustic logs indicate moderate gas hydrate saturations with S-wave results slightly lower than those for P-waves. For the Unit B, located just above the BGHS, we obtain moderate to high gas hydrate saturation estimates from both sonic logs. Our P-wave saturation estimates agree well with results from electrical-resistivity-based estimates, whereas estimates from nuclear magnetic resonance LWD data generally suggest 5 to 10 percent higher saturations; our S-wave results suggest lower saturations. These differences likely indicate complexities in the form of gas hydrate occurrence within the sediment pore space, potentially including differences between hydrate occurrence in Units D and B.</p>
Haines, Seth↗
Three-dimensional atomic scale characterization of {11$\overline{2}$2} twin boundaries in titanium
The {11$\overline{2}$2}<11$\overline{23}$> compression twin can accommodate a considerable amount of strain under c-axis compression in Ti. However, unlike the tensile twin, the structure of the {10$\overline{1}$2}$\langle$$\overline{1}$011$\rangle$ compressive twins has not been completely characterized. In this study, we apply a combined technique of HR-TEM characterization, topological analysis, and atomistic simulations to explore the facets that bound the {11$\overline{2}$2}<11$\overline{23}$> twin in Ti. In addition to the currently known facets (CTB and B-Py), six new facets are observed and categorized for the first time from atomic-scale TEM observations along five crystallographic directions. The six new facets are (11$\overline{2}$0)//(11$\overline{2}$6), PrPr1, PyPy1, (2$\overline{11}$1)//($\overline{1}$2$\overline{1}$2), (1$\overline{1}$04)//(01$\overline{11}$), and (01$\overline{1}$0)//(2$\overline{11}$4). Results from the topological and computational analysis are in reasonable agreement with and support the HRTEM observations. Specifically, (1) the observed facets align with low-index interfaces in both twin and matrix domains, (2) the facets with lower surface energies are found to form extended interfaces, and (3) high-surface-energy facets are found at the twin tip region and explained by the fact that the energy of the combined facet and facet junction configuration is energetically preferred in the twin tip region. These results not only provide a comprehensive understanding of the 3D structure of the {11$\overline{2}$2}<11$\overline{23}$> compressive twins in Ti, but also validate the MD procedure and the Ti interatomic potential employed. This is extremely important for future study of the {11$\overline{2}$2} twin mobility and interactions with other defects, both features that remain extremely challenging to capture in experiments.
36 MATERIALS SCIENCE↗
Structural basis of glycan276-dependent recognition by HIV-1 broadly neutralizing antibodies
Recognition of N-linked glycan at residue N276 (glycan276) at the periphery of the CD4-binding site (CD4bs) on the HIV-envelope trimer is a formidable challenge for many CD4bs-directed antibodies. To understand how this glycan can be recognized, here we isolate two lineages of glycan276-dependent CD4bs antibodies. Antibody CH540-VRC40.01 (named for donor-lineage.clone) neutralizes 81% of a panel of 208 diverse strains, while antibody CH314-VRC33.01 neutralizes 45%. Cryo-electron microscopy (cryo-EM) structures of these two antibodies and 179NC75, a previously identified glycan276-dependent CD4bs antibody, in complex with HIV-envelope trimer reveal substantially different modes of glycan276 recognition. Despite these differences, binding of glycan276-dependent antibodies maintains a glycan276 conformation similar to that observed in the absence of glycan276-binding antibodies. By contrast, glycan276-independent CD4bs antibodies, such as VRC01, displace glycan276 upon binding. These results provide a foundation for understanding antibody recognition of glycan276 and suggest its presence may be crucial for priming immunogens seeking to initiate broad CD4bs recognition.
59 BASIC BIOLOGICAL SCIENCES↗
Thermal Conductivity of β-Phase Ga 2 O 3 and (Al x Ga 1– x ) 2 O 3 Heteroepitaxial Thin Films
Heteroepitaxy of β-phase gallium oxide (β-Ga 2 O 3 ) thin films on foreign substrates shows promise for the development of next-generation deep ultraviolet solar blind photodetectors and power electronic devices. In this work, the influences of the film thickness and crystallinity on the thermal conductivity of ($\bar{2}01$)-oriented β-Ga 2 O 3 heteroepitaxial thin films were investigated. Unintentionally doped β-Ga 2 O 3 thin films were grown on c-plane sapphire substrates with off-axis angles of 0° and 6° toward $\langle$$11\bar{2}0$$\rangle$ via metal–organic vapor phase epitaxy (MOVPE) and low-pressure chemical vapor deposition. The surface morphology and crystal quality of the β-Ga 2 O 3 thin films were characterized using scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. The thermal conductivities of the β-Ga 2 O 3 films were measured via time-domain thermoreflectance. The interface quality was studied using scanning transmission electron microscopy. The measured thermal conductivities of the submicron-thick β-Ga 2 O 3 thin films were relatively low as compared to the intrinsic bulk value. The measured thin film thermal conductivities were compared with the Debye–Callaway model incorporating phononic parameters derived from first-principles calculations. The comparison suggests that the reduction in the thin film thermal conductivity can be partially attributed to the enhanced phonon-boundary scattering when the film thickness decreases. They were found to be a strong function of not only the layer thickness but also the film quality, resulting from growth on substrates with different offcut angles. Growth of β-Ga 2 O 3 films on 6° offcut sapphire substrates was found to result in higher crystallinity and thermal conductivity than films grown on on-axis c-plane sapphire. However, the β-Ga 2 O 3 films grown on 6° offcut sapphire exhibit a lower thermal boundary conductance at the β-Ga 2 O 3 /sapphire heterointerface. In addition, the thermal conductivity of MOVPE-grown ($\bar{2}01$)-oriented β-(Al x Ga 1–x ) 2 O 3 thin films with Al compositions ranging from 2% to 43% was characterized. Because of phonon-alloy disorder scattering, the β-(Al x Ga 1–x ) 2 O 3 films exhibit lower thermal conductivities (2.8–4.7 W/m∙K) than the β-Ga 2 O 3 thin films. The dominance of the alloy disorder scattering in β-(Al x Ga 1–x ) 2 O 3 is further evidenced by the weak temperature dependence of the thermal conductivity. This work provides fundamental insight into the physical interactions that govern phonon transport within heteroepitaxially grown β-phase Ga 2 O 3 and (Al x Ga 1–x ) 2 O 3 thin films and lays the groundwork for the thermal modeling and design of β-Ga 2 O 3 electronic and optoelectronic devices.
36 MATERIALS SCIENCE↗
Evidence of a South Asian Proto‐Monsoon During the Oligocene‐Miocene Transition
Abstract The geological history of the South Asian monsoon (SAM) before the Pleistocene is not well‐constrained, primarily due to a lack of available continuous sediment archives. Previous studies have noted an intensification of SAM precipitation and atmospheric circulation during the middle Miocene (∼14 Ma), but no records are available to test how the monsoon changed prior to this. In order to improve our understanding of monsoonal evolution, geochemical and sedimentological data were generated for the Oligocene‐early Miocene (30–20 Ma) from Indian National Gas Hydrate Expedition 01 Site NGHP‐01‐01A in the eastern Arabian Sea, at 2,674 m water depth. We find the initial glaciation phase (23.7–23.0 Ma) of the Oligocene‐Miocene transition (OMT) to be associated with an increase in water column ventilation and water mass mixing, suggesting an increase in winter monsoon type atmospheric circulation, possibly driven by a relative southward shift of the intertropical convergence zone. During the latter part of the OMT, or “deglaciation” phase (23.0–22.7 Ma), a long‐term decrease in Mn (suggestive of deoxygenation), increase in Ti/Ca and dissolution of the biogenic carbonate fraction suggest an intensification of a proto‐summer SAM system, characterized by the formation of an oxygen minimum zone in the eastern Arabian Sea and a relative increase of terrigenous material delivered by runoff to the site. With no evidence at this site for an active SAM prior to the OMT we suggest that changes in orbital parameters, as well as possibly changing Tethyan/Himalayan tectonics, caused this step change in the proto‐monsoon system at this intermediate‐depth site.
Beasley, C.↗
Electronic structure in a transition metal dipnictide TaAs 2
Abstract The family of transition-metal dipnictides has been of theoretical and experimental interest because this family hosts topological states and extremely large magnetoresistance (MR). Recently, T a A s 2 , a member of this family, has been predicted to support a topological crystalline insulating state. Here, by using high-resolution angle-resolved photoemission spectroscopy (ARPES), we reveal both closed and open pockets in the metallic Fermi surface (FS) and linearly dispersive bands on the ( 2 ‾ 01 ) surface, along with the presence of extreme MR observed from magneto-transport measurements. A comparison of the ARPES results with first-principles computations shows that the linearly dispersive bands on the measured surface of T a A s 2 are trivial bulk bands. The absence of symmetry-protected surface state on the ( 2 ‾ 01 ) surface indicates its topologically dark nature. The presence of open FS features suggests that the open-orbit fermiology could contribute to the extremely large MR of T a A s 2 .
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
The kinematics, metallicities, and orbits of six recently discovered Galactic star clusters with Magellan/M2FS spectroscopy
ABSTRACT We present Magellan/M2FS spectroscopy of four recently discovered Milky Way star clusters (Gran 3/Patchick 125, Gran 4, Garro 01, and LP 866) and two newly discovered open clusters (Gaia 9 and Gaia 10) at low Galactic latitudes. We measure line-of-sight velocities and stellar parameters ([Fe/H], log g, Teff, and [Mg/Fe]) from high-resolution spectroscopy centred on the Mg triplet and identify 20–80 members per star cluster. We determine the kinematics and chemical properties of each cluster and measure the systemic proper motion and orbital properties by utilizing Gaia astrometry. We find Gran 3 to be an old, metal-poor (mean metallicity of [Fe/H] = −1.83) globular cluster located in the Galactic bulge on a retrograde orbit. Gran 4 is an old, metal-poor ([Fe/H] = −1.84) globular cluster with a halo-like orbit that happens to be passing through the Galactic plane. The orbital properties of Gran 4 are consistent with the proposed LMS-1/Wukong and/or Helmi streams merger events. Garro 01 is metal-rich ([Fe/H] = −0.30) and on a near-circular orbit in the outer disc but its classification as an open cluster or globular cluster is ambiguous. Gaia 9 and Gaia 10 are among the most distant known open clusters at $R_{\mathrm{GC}}\sim 18,~21.2~\mathrm{\, kpc}$ and most metal-poor with [Fe/H] ∼−0.50, −0.34 for Gaia 9 and Gaia 10, respectively. LP 866 is a nearby, metal-rich open cluster ([Fe/H] = +0.10). The discovery and confirmation of multiple star clusters in the Galactic plane shows the power of Gaia astrometry and the star cluster census remains incomplete.
Pace, Andrew B. (ORCID:0000000260218760)↗
Jeankempite, Ca 5 (AsO 4 ) 2 (AsO 3 OH) 2 (H 2 O) 7 , a new arsenate mineral from the Mohawk Mine, Keweenaw County, Michigan, USA
Abstract Jeankempite, Ca 5 (AsO 4 ) 2 (AsO 3 OH) 2 (H 2 O) 7 , is a new mineral species (IMA2018-090) discovered amongst coatings of arsenate minerals on oxidised copper arsenides from the Mohawk No. 2 mine, Mohawk, Keweenaw County, Michigan, USA. The new mineral occurs as lamellar bundles of colourless to white plates up to 1 mm wide and is visually indistinguishable from guérinite, with which it forms intergrowths. Jeankempite is transparent to translucent with a waxy lustre and white streak, is non-fluorescent under longwave and shortwave ultraviolet illumination, has a Mohs hardness of ~1.5 and brittle tenacity with uneven fracture. Crystals are flattened on {01 $\bar{1}$ } and exhibit perfect cleavage on {01 $\bar{1}$ }. Optically, jeankempite is biaxial (+), α = 1.601(2), β = 1.607(2), γ = 1.619(2) (white light); 2V meas. = 72(2)° and 2V calc. = 71.0°. The empirical formula is (Ca 4.97 Na 0.013 Mg 0.017 )(As 3.99 S 0.01 ) 4 O 23 H 16 , based on 23 O and 16 H atoms per formula unit. Thermogravimetric analysis indicates that jeankempite undergoes four weight losses totalling 16.82%, close to the expected loss of 16.30%, corresponding to eight H 2 O. Jeankempite is triclinic, P $\bar{1}$ , a = 6.710(6), b = 14.901(14), c = 15.940(15) Å, α = 73.583(12)°, β = 81.984(12)°, γ = 82.754(12)°, V = 1507(2) Å 3 and Z = 3. The final structure was refined to R 1 = 0.0591 for 2781 reflections with I obs > 3σ I . The crystal structure of jeankempite is built from a network of edge- and vertex-sharing CaO 6 , CaO 7 and AsO 4 polyhedra, and we hypothesise that the new mineral has formed due to a topotactic reaction brought on by dehydration of preexisting guérinite.
Mineralogy↗
WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates
This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.
54 ENVIRONMENTAL SCIENCES↗
Insights into regulatory T-cell and type-I interferon roles in determining abacavir-induced hypersensitivity or immune tolerance
Introduction Clinical use of several small molecule drugs may lead to severe T-cell-mediated idiosyncratic drug hypersensitivity reactions (iDHR) linked to HLA alleles, including abacavir (ABC) with HLA-B*57:01. Due to study limitations in humans, pathogenic networks in iDHR remain elusive. HLA transgenic murine models have been proposed to bridge knowledge gaps in tolerance and susceptibility to drugs. Methods Mice expressing HLA-B*57:01 and Foxp3-DTR/EGFP were generated to selectively deplete regulatory T-cells (Treg) with diphtheria toxin. ABC was administered for 8 days alone or together with cell- and cytokine-depleting antibodies. Cellular and transcriptomic responses were analyzed by RNA, flow cytometry and fluorescence methods. Results While CD8 + T-cell responses to ABC require HLA presentation, ABC also triggered mitochondrial stress in macrophagesin vitro, independently of HLA.In vivo, Treg were the primary mechanism of drug tolerance controlling HLA presentation and costimulation by antigen presenting cells. Treg ablation uncovered immune adverse events linked to activation and proliferation of both drug-specific and bystander CD8 + T-cells through CD28-mediated pathways with support from CD4 + non-Treg. Type-I interferon (IFN-I) and cellular-stress pathways influenced the fate of lymph node cells responding to ABC, implicating innate immune cells such as macrophages and plasmacytoid dendritic cells in the development of T-cell responses against the drug. IFN-I and IL-2 were necessary for CD8 + T-cell differentiation and ABC-induced adverse reactions. Conclusions This study unveils novel immune mechanisms driven by drug and host-related factors required forin vivoreactions and sheds light on potential biomarker and therapeutic targets for managing and preventing severe and life-threatening iDHR.
Immunology↗
Coal Fired Power Plant Configuration and Operation Impact on Plant Effluent Contaminants and Conditions
The primary objective of this project is to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. This project was in response to the U.S. Department of Energy (DOE) Solicitation DE-FOA-0001842. The project duration was between September 01, 2018, and December 31, 2021 (no-cost extension filed, due to the Covid-19 pandemic restrictions, and approved). Field and lab test program was conducted with the main goal to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. In this project, the team of Lehigh University (prime recipient) and Western Kentucky University identified two suitable Thermoelectric Power Plants (TTPs) firing bituminous and sub-bituminous coals respectively, designed test plans, and performed sample collection. Sampling included coal from each TTPs power generation units, Wet Flue Gas Desulfurization (WFGD) slurry material and waste-water samples taken from the outlet of the water treatment tank prior to discharge and other pertinent locations. Coal samples are dried, crushed, and pulverized according to the American Society for Testing and Materials (ASTM) methods. The prepared coal samples are analyzed for normal proximate and ultimate analysis tests in addition to the toxic metals and anions according to ASTM methods. The FGD slurry materials are analyzed for toxic metals and anions according to Electric Power Research Institute (EPRI) or Environmental Protection Agency (EPA) methods, as appropriate. The wastewater samples from the water treatment tank outlet are analyzed for toxic metals and anions according to EPA methods. The effluent species analyzed include mercury, arsenic, selenium, nitrate/nitrite, bromide, and chlorine. This project provided results of effluent conditions as a function of coal type, unit configuration, and unit operation profile, and identified the levels of uncertainty in the effluent results.
01 COAL, LIGNITE, AND PEAT↗
High Velocity, Low‐Voltage Collective In‐Plane Switching in (100) BaTiO 3 Thin Films
Abstract Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly‐correlated electrical and elastic coupling that elicit fast and efficient collective switching. Designing domain structures with advantageous properties is difficult because the mechanisms involved in collective switching are poorly understood and difficult to investigate. Collective switching is a hierarchical process where the nano‐ and mesoscale responses control the macroscopic properties. Using chemical solution synthesis, epitaxially nearly‐relaxed (100) BaTiO 3 films are synthesized. Thermal strain induces a strongly‐correlated domain structure with alternating domains of polarization along the [010] and [001] in‐plane axes and 90° domain walls along the [011] or [01] directions. Simultaneous capacitance–voltage measurements and band‐excitation piezoresponse force microscopy revealed strong collective switching behavior. Using a deep convolutional autoencoder, hierarchical switching is automatically tracked and the switching pathway is identified. The collective switching velocities are calculated to be ≈500 cm s −1 at 5 V (7 kV cm −1 ), orders‐of‐magnitude faster than expected. These combinations of properties are promising for high‐speed tunable dielectrics and low‐voltage ferroelectric memories and logic.
36 MATERIALS SCIENCE↗