Deep Space Positioning System

A single, compact, lower power deep space positioning system (DPS) configured to determine a location of a spacecraft anywhere in the solar system, and provide state information relative to Earth, Sun, or any remote object. For example, the DPS includes a first camera and, possibly, a second camera configured to capture a plurality of navigation images to determine a state of a spacecraft in a solar system. The second camera is located behind, or adjacent to, a secondary reflector of a first camera in a body of a telescope

AutoGNC Testbed

A simulation testbed architecture was developed and implemented for the integration, test, and development of a TRL-6 flight software set called Auto- GNC. The AutoGNC software will combine the TRL-9 Deep Impact AutoNAV flight software suite, the TRL-9 Virtual Machine Language (VML) executive, and the TRL-3 G-REX guidance, estimation, and control algorithms. The Auto- GNC testbed was architected to provide software interface connections among the AutoNAV and VML flight code written in C, the G-REX algorithms in MATLAB and C, stand-alone image rendering algorithms in C, and other Fortran algorithms, such as the OBIRON landmark tracking suite. The testbed architecture incorporates software components for propagating a high-fidelity truth model of the environment and the spacecraft dynamics, along with the flight software components for onboard guidance, navigation, and control (GN&C). The interface allows for the rapid integration and testing of new algorithms prior to development of the C code for implementation in flight software. This testbed is designed to test autonomous spacecraft proximity operations around small celestial bodies, moons, or other spacecraft. The software is baselined for upcoming comet and asteroid sample return missions. This architecture and testbed will provide a direct improvement upon the onboard flight software utilized for missions such as Deep Impact, Stardust, and Deep Space 1

Detection of untreated sewage discharges to watercourses using machine learning

Monitoring and regulating discharges of wastewater pollution in water bodies in England is the duty of the Environment Agency. Identification and reporting of pollution events from wastewater treatment plants is the duty of operators. Nevertheless, in 2018, over 400 sewage pollution incidents in England were reported by the public. We present novel pollution event reporting methodologies to identify likely untreated sewage spills from wastewater treatment plants. Daily effluent flow patterns at two wastewater treatment plants were supplemented by operator-reported incidents of untreated sewage discharges. Using machine learning, known spill events served as training data. The probability of correctly classifying a randomly selected pair of ‘spill’ and ‘no-spill’ effluent patterns was above 96%. Of 7160 days without operator-reported spills, 926 were classified as involving a ‘spill’. The analysis also suggests that both wastewater treatment plants made non-compliant discharges of untreated sewage between 2009 and 2020. This proof-of-principle use of machine learning to detect untreated wastewater discharges can help water companies identify malfunctioning treatment plants and inform agencies of unsatisfactory regulatory oversight. Real-time, open access flow and alarm data and analytical approaches will empower professional and citizen scientific scrutiny of the frequency and impact of untreated wastewater discharges, particularly those unreported by operators

Clinical Heterogeneity in Patients With FOXP3 Mutations Presenting With Permanent Neonatal Diabetes

OBJECTIVE—Immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome is caused by FOXP3 mutations. We aimed to determine the prevalence, genetics, and clinical phenotype of FOXP3 mutations in a large cohort with permanent neonatal diabetes (PNDM)

Characterization of the structure and control of the blood-nerve barrier identifies avenues for therapeutic delivery

The blood barriers of the nervous system protect neural environments but can hinder therapeutic accessibility. The blood-brain barrier (BBB) is well characterized, consisting of endothelial cells with specialized tight junctions and low levels of transcytosis, properties conferred by contacting pericytes and astrocytes. In contrast, the blood-nerve barrier (BNB) of the peripheral nervous system is poorly defined. Here, we characterize the structure of the mammalian BNB, identify the processes that confer barrier function, and demonstrate how the barrier can be opened in response to injury. The homeostatic BNB is leakier than the BBB, which we show is due to higher levels of transcytosis. However, the barrier is reinforced by macrophages that specifically engulf leaked materials, identifying a role for resident macrophages as an important component of the BNB. Finally, we demonstrate the exploitation of these processes to effectively deliver RNA-targeting therapeutics to peripheral nerves, indicating new treatment approaches for nervous system pathologies

Locus Reference Genomic sequences: an improved basis for describing human DNA variants

As our knowledge of the complexity of gene architecture grows, and we increase our understanding of the subtleties of gene expression, the process of accurately describing disease-causing gene variants has become increasingly problematic. In part, this is due to current reference DNA sequence formats that do not fully meet present needs. Here we present the Locus Reference Genomic (LRG) sequence format, which has been designed for the specific purpose of gene variant reporting. The format builds on the successful National Center for Biotechnology Information (NCBI) RefSeqGene project and provides a single-file record containing a uniquely stable reference DNA sequence along with all relevant transcript and protein sequences essential to the description of gene variants. In principle, LRGs can be created for any organism, not just human. In addition, we recognize the need to respect legacy numbering systems for exons and amino acids and the LRG format takes account of these. We hope that widespread adoption of LRGs - which will be created and maintained by the NCBI and the European Bioinformatics Institute (EBI) - along with consistent use of the Human Genome Variation Society (HGVS)-approved variant nomenclature will reduce errors in the reporting of variants in the literature and improve communication about variants affecting human health. Further information can be found on the LRG web site: http://www.lrg-sequence.org

Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids

A spacecraft guidance, navigation, and control (GN&C) system is needed to enable a spacecraft to descend to a surface, take a sample using a touch-and-go (TAG) sampling approach, and then safely ascend. At the time of this reporting, a flyable GN&C system that can accomplish these goals is beyond state of the art. This article describes AutoGNC, which is a GN&C system capable of addressing these goals, which has recently been developed and demonstrated to a maturity TRL-5-plus. The AutoGNC solution matures and integrates two previously existing JPL capabilities into a single unified GN&C system. The two capabilities are AutoNAV and GREX. AutoNAV is JPL s current flight navigation system, and is fairly mature with respect to flybys and rendezvous with small bodies, but is lacking capability for close surface proximity operations, sampling, and contact. G-REX is a suite of low-TRL algorithms and capabilities that enables spacecraft operations in close surface proximity and for performing sampling/contact. The development and integration of AutoNAV and G-REX components into AutoGNC provides a single, unified GN&C capability for addressing the autonomy, close-proximity, and sampling/contact aspects of small-body sample return missions. AutoGNC is an integrated capability comprising elements that were developed separately. The main algorithms and component capabilities that have been matured and integrated are autonomy for near-surface operations, terrain-relative navigation (TRN), real-time image-based feedback guidance and control, and six degrees of freedom (6DOF) control of the TAG sampling event. Autonomy is achieved based on an AutoGNC Executive written in Virtual Machine Language (VML) incorporating high-level control, data management, and fault protection. In descending to the surface, the AutoGNC system uses camera images to determine its position and velocity relative to the terrain. This capability for TRN leverages native capabilities of the original AutoNAV system, but required advancements that integrate the separate capabilities for shape modeling, state estimation, image rendering, defining a database of onboard maps, and performing real-time landmark recognition against the stored maps. The ability to use images to guide the spacecraft requires the capability for image-based feedback control. In Auto- GNC, navigation estimates are fed into an onboard guidance and control system that keeps the spacecraft guided along a desired path, as it descends towards its targeted landing or sampling site. Once near the site, AutoGNC achieves a prescribed guidance condition for TAG sampling (position/orientation, velocity), and a prescribed force profile on the sampling end-effector. A dedicated 6DOF TAG control then implements the ascent burn while recovering from sampling disturbances and induced attitude rates. The control also minimizes structural interactions with flexible solar panels and disallows any part of the spacecraft from making contact with the ground (other than the intended end-effector)

Stem Cells, Cell Therapies, and Bioengineering in Lung Biology and Disease 2021

The 9th biennial conference titled “Stem Cells, Cell Therapies, and Bioengineering in Lung Biology and Diseases” was hosted virtually, due to the ongoing COVID-19 pandemic, in collaboration with the University of Vermont Larner College of Medicine, the National Heart, Lung, and Blood Institute, the Alpha-1 Foundation, the Cystic Fibrosis Foundation, and the International Society for Cell & Gene Therapy. The event was held from July 12th through 15th, 2021 with a pre-conference workshop held on July 9th. As in previous years, the objectives remained to review and discuss the status of active research areas involving stem cells (SCs), cellular therapeutics, and bioengineering as they relate to the human lung. Topics included 1) technological advancements in the in situ analysis of lung tissues, 2) new insights into stem cell signaling and plasticity in lung remodeling and regeneration, 3) the impact of extracellular matrix in stem cell regulation and airway engineering in lung regeneration, 4) differentiating and delivering stem cell therapeutics to the lung, 5) regeneration in response to viral infection, and 6) ethical development of cell-based treatments for lung diseases. This selection of topics represents some of the most dynamic and current research areas in lung biology

Co-ordinated Airborne Studies in the Tropics (CAST)

This is the author accepted manuscript. The final version is available from the American Meteorological Society via http://dx.doi.org/10.1175/BAMS-D-14-00290.1The Co-ordinated Airborne Studies in the Tropics (CAST) project is studying the chemical composition of the atmosphere in the Tropical Warm Pool region to improve understanding of trace gas transport in convection. The main field activities of the CAST (Co-ordinated Airborne Studies in the Tropics) campaign took place in the West Pacific in January/February 2014. The field campaign was based in Guam (13.5°N, 144.8°E) using the UK FAAM BAe-146 atmospheric research aircraft and was coordinated with the ATTREX project with the unmanned Global Hawk and the CONTRAST campaign with the Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical West Pacific as well as the importance of trace gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights between 1°S-14°N and 130°-155°E. It was used to sample at altitudes below 8 km with much of the time spent in the marine boundary layer. It measured a range of chemical species, and sampled extensively within the region of main inflow into the strong West Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project focussing on the design and operation of the West Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on the Global Hawk in February/March 2015.CAST is funded by NERC and STFC, with grant NE/ I030054/1 (lead award), NE/J006262/1, NE/J006238/1, NE/J006181/1, NE/J006211/1, NE/J006061/1, NE/J006157/1, NE/J006203/1, NE/J00619X/1, and NE/J006173/1. N. R. P. Harris was supported by a NERC Advanced Research Fellowship (NE/G014655/1). P. I. Palmer acknowledges his Royal Society Wolfson Research Merit Award. The BAe-146-301 Atmospheric Research Aircraft is flown by Directflight Ltd and managed by the Facility for Airborne Atmospheric Measurements, which is a joint entity of the Natural Environment Research Council and the Met Office. The authors thank the staff at FAAM, Directflight and Avalon Aero who worked so hard toward the success of the aircraft deployment in Guam, especially for their untiring efforts when spending an unforeseen 9 days in Chuuk. We thank the local staff at Chuuk and Palau, as well as the authorities in the Federated States of Micronesia for their help in facilitating our research flights. Special thanks go to the personnel associated with the ARM facility at Manus, Papua New Guinea without whose help the ground-based measurements would not have been possible. Thanks to the British Atmospheric Data Centre (BADC) for hosting our data and the NCAS Atmospheric Measurement Facility for providing the radiosonde and ground-based ozone equipment. Chlorophyll-a data used in Figure 1 were extracted using the Giovanni online data system, maintained by the NASA GES DISC. We also acknowledge the MODIS mission scientists and associated NASA personnel for the production of this data set. Finally we thank many individual associated with the ATTREX and CONTRAST campaigns for their help in the logistical planning, and we would like to single out Jim Bresch for his excellent and freely provided meteorological advice

Identification of Mendel's White Flower Character

BACKGROUND: The genetic regulation of flower color has been widely studied, notably as a character used by Mendel and his predecessors in the study of inheritance in pea. METHODOLOGY/PRINCIPAL FINDINGS: We used the genome sequence of model legumes, together with their known synteny to the pea genome to identify candidate genes for the A and A2 loci in pea. We then used a combination of genetic mapping, fast neutron mutant analysis, allelic diversity, transcript quantification and transient expression complementation studies to confirm the identity of the candidates. CONCLUSIONS/SIGNIFICANCE: We have identified the pea genes A and A2. A is the factor determining anthocyanin pigmentation in pea that was used by Gregor Mendel 150 years ago in his study of inheritance. The A gene encodes a bHLH transcription factor. The white flowered mutant allele most likely used by Mendel is a simple G to A transition in a splice donor site that leads to a mis-spliced mRNA with a premature stop codon, and we have identified a second rare mutant allele. The A2 gene encodes a WD40 protein that is part of an evolutionarily conserved regulatory complex