Hexagon (United States)

We present draft genome sequences of five endophytic fungi from Lactuca serriola L., a wild relative of cultivated lettuce: Alternaria postmessia, two Alternaria alternata variants, Fusarium falciforme, and Aspergillus terreus. Isolates were obtained from field-grown plants in Arizona, USA, and whole-genome sequenced using Illumina NovaSeq 6000 at ≥50× coverage.

We are developing a real-time X-ray pulse processor for the Line Emission Mapper (LEM) mission, a NASA X-ray probe concept for imaging and spectroscopy in the 0.2 to 2 keV range. The main detector is a hybrid Transition Edge Sensor (TES) array with a 33' outer array with “Hydra” multiplexing and a 7' × 7' inner subarray. The ∼4,000 TES sensors are read out using time-division multiplexing (TDM) technology. We are developing room-temperature digital readout electronics based on laboratory TDM electronics, where all X-ray pulses are processed in real-time to reduce the size of the data transmission. The process includes pulse triggering, grading, extraction, and optimal filtering performed in the FPGA of the TDM column electronics. In this paper we describe the real-time pulse processing firmware for a LEM flight-like prototype electronics and demonstrate count rate capability. We also demonstrate that it provides identical performance compared to conventional offline pulse-processing.

The ribosome is essential for protein synthesis and targeting its function serves as a platform for many therapies. Resistance gene-guided genome mining for a priori target identification has emerged as a useful workflow in natural product drug discovery, allowing for identification of a compound's target before the time-consuming work of isolation and characterization is performed. In this work, we identify the previously unknown lig biosynthetic gene cluster (BGC) which contains a predicted resistance gene that shares sequence identity with the gene for human ribosomal protein RPL10. Through both heterologous expression and in situ BGC engineering, we identify ligustrone A (1) as this BGC's product. Utilizing chemical genetics and chemoproteomics, we validate that 1 engages RPL10. Taken together, via resistance gene-guided mining we both discover a new target for a known natural product and elucidate its biosynthesis.

The X-ray Integral Field Unit on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Athena</i> will be subject to a cosmic-ray induced thermal background on orbit, with energy depositions into the detector wafer leading to thermal bath fluctuations. Such fluctuations have the potential to degrade energy resolution performance of the transition-edge sensor based microcalorimeter. This problem was previously studied in simulations that modeled thermal bath fluctuations induced by cosmic-ray events and evaluated the resulting energy resolution degradation due to a simulated timeline of such events. Now taking an experimental approach, we present results using a collimated Am-241 alpha particle source to deposit a known energy to specific locations on the detector wafer. Thermal pulses induced by the alpha particle energy depositions are measured at various detector pixels for several different experimental configurations, including for energy deposited into the inter-pixel structure of the wafer, as well as the frame area outside the pixel array. Further, we also test both with and without a thick backside heatsinking metallization layer that is baselined for the instrument. In each case results are compared to expectations based on the thermal model developed for the previous study.

The MLHat workshop aims to bring together academic researchers and industry practitioners to discuss the open challenges, potential solutions, and best practices to deploy machine learning at scale for security defense. The workshop will discuss related topics from both defender perspectives (white-hat) and the attacker perspectives (black-hat). We call the workshop MLHats, to serve as a place for people who are interested in using machine learning to solve practical security problems. The workshop will focus on defining new machine learning paradigms under various security application contexts and identifying exciting new future research directions. At the same time, the workshop will also have a strong industry presence to provide insights into the challenges in deploying and maintaining machine learning models and the much-needed discussion on the capabilities that the state-of-the-arts failed to provide.

The Advanced Topographic Laser Altimetry System (ATLAS) is the sole instrument on the Ice, Cloud, and land Elevation Satellite 2 (ICESat‐2). Without some method of reducing the transmitted data, the volume of ATLAS telemetry would far exceed the normal X‐band downlink capability or require many more ground station contacts. The ATLAS Onboard Flight Science Receiver Algorithms (hereinafter Receiver Algorithms or Algorithms) control the amount of science data that is telemetered from the instrument, limiting the data volume by distinguishing surface echoes from background noise, and allowing the instrument to telemeter data from only a small vertical region about the signal. This is accomplished through the transfer of the spacecraft's location and attitude to the instrument every second, use of an onboard Digital Elevation Model, implementation of signal processing techniques, and use of onboard relief and surface type reference maps. Extensive ground testing verified the performance of the Algorithms. On‐orbit analysis shows that the Algorithms are working as expected from the ground testing; they are performing well and meeting the mission requirements.

There is a constant search for a more accurate measurement, which generally leads to higher cost, greater complexity, or devices that do not lend themselves to manufacturing environments. We present a method of using statistical sampling to improve metrological accuracy without these undesirable effects. For metrology of flat surfaces and steps between flat surfaces, this method demonstrated precision improvement up to a factor of 55, and accuracy increase of at least a factor of 10. The corresponding precision and accuracy improvements on a spherical surface were both factors of 8. Since this accuracy improvement can be implemented in software, it does not affect the speed of measurement or the complexity of the hardware, and it can be used to improve the accuracy of a wide range of metrology systems.