Design and Verification of a Clock System for Orbital Radio Interferometry

Radio interferometry using multiple small satellites will enable measurements with high angular resolution for remote sensing and astronomy. The NASA sponsored Auroral Emissions Radio Explorer (AERO) and Vector Interferometry Space Technology using AERO (VISTA) CubeSats will demonstrate orbital interferometry from 0.1 MHz to 15 MHz, frequencies which are largely blocked by the ionosphere. We report on the design and testing of a clock system for radio interferometry between these orbital receivers. We discuss the clock system design up to PCB fabrication, including requirements flow and major hardware trades. The performance of the timing components has been verified using a phase noise test set with a high-quality benchtop crystal. While these results are presented for the AERO-VISTA mission payload, they are more generally applicable to any orbital interferometry platform with multiple satellites

Data Mining and Machine Learning in Astronomy

We review the current state of data mining and machine learning in astronomy. 'Data Mining' can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black-box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those where data mining techniques directly resulted in improved science, and important current and future directions, including probability density functions, parallel algorithms, petascale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm, and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.Comment: Published in IJMPD. 61 pages, uses ws-ijmpd.cls. Several extra figures, some minor additions to the tex

Serratamolide is a hemolytic factor produced by Serratia marcescens

Serratia marcescens is a common contaminant of contact lens cases and lenses. Hemolytic factors of S. marcescens contribute to the virulence of this opportunistic bacterial pathogen. We took advantage of an observed hyper-hemolytic phenotype of crp mutants to investigate mechanisms of hemolysis. A genetic screen revealed that swrW is necessary for the hyper-hemolysis phenotype of crp mutants. The swrW gene is required for biosynthesis of the biosurfactant serratamolide, previously shown to be a broad-spectrum antibiotic and to contribute to swarming motility. Multicopy expression of swrW or mutation of the hexS transcription factor gene, a known inhibitor of swrW expression, led to an increase in hemolysis. Surfactant zones and expression from an swrW-transcriptional reporter were elevated in a crp mutant compared to the wild type. Purified serratamolide was hemolytic to sheep and murine red blood cells and cytotoxic to human airway and corneal limbal epithelial cells in vitro. The swrW gene was found in the majority of contact lens isolates tested. Genetic and biochemical analysis implicate the biosurfactant serratamolide as a hemolysin. This novel hemolysin may contribute to irritation and infections associated with contact lens use. © 2012 Shanks et al

The contribution of tropical cyclones to the atmospheric branch of Middle America's hydrological cycle using observed and reanalysis tracks

Middle America is affected by tropical cyclones (TCs) from the Eastern Pacific and the North Atlantic Oceans. We characterize the regional climatology (1998-2016) of the TC contributions to the atmospheric branch of the hydrological cycle, from May to December. TC contributions to rainfall are quantified using Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product 3B42 and TC tracks derived from three sources: the International Best Track Archive for Climate Stewardship (IBTrACS), and an objective feature tracking method applied to the Japanese 55-year and ERA-Interim reanalyses. From July to October, TCs contribute 10-30% of rainfall over the west and east coast of Mexico and central Mexico, with the largest monthly contribution during September over the Baja California Peninsula (up to 90%). TCs are associated with 40-60% of daily extreme rainfall (above the 95th percentile) over the coasts of Mexico. IBTrACS and reanalyses agree on TC contributions over the Atlantic Ocean but disagree over the Eastern Pacific Ocean and continent; differences over the continent are mainly attributed to discrepancies in TC tracks in proximity to the coast and TC lifetime. Reanalysis estimates of TC moisture transports show that TCs are an important moisture source for the regional water budget. TC vertically integrated moisture flux (VIMF) convergence can turn regions of weak VIMF divergence by the mean circulation into regions of weak VIMF convergence. We discuss deficiencies in the observed and reanalysis TC tracks, which limit our ability to quantify robustly the contribution of TCs to the regional hydrological cycle

An “Electronic Fluorescent Pictograph” Browser for Exploring and Analyzing Large-Scale Biological Data Sets

Background. The exploration of microarray data and data from other high-throughput projects for hypothesis generation has become a vital aspect of post-genomic research. For the non-bioinformatics specialist, however, many of the currently available tools provide overwhelming amounts of data that are presented in a non-intuitive way. Methodology/Principal Findings. In order to facilitate the interpretation and analysis of microarray data and data from other large-scale data sets, we have developed a tool, which we have dubbed the electronic Fluorescent Pictograph – or eFP – Browser, available a

Prediction of acute myeloid leukaemia risk in healthy individuals

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure(1). The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion(2,3). However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)(4-8). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention

Olaparib and celarasertib (AZD6738) in patients with triple negative advanced breast cancer: results from Cohort E of the plasmaMATCH trial (CRUK/15/010)

Background Approximately 10-15% of triple negative breast cancers (TNBCs) have deleterious mutations in BRCA1 and BRCA2 and may benefit from polyadenosine 5’diphosphoribose polymerase (PARP) inhibitor treatment. PARP inhibitors may also increase exogenous replication stress and thereby increase sensitivity to inhibitors of ataxia telangiectasia and Rad3-related protein (ATR). This phase II study examined the activity of the combination of PARP inhibitor, Olaparib, and ATR inhibitor, celerasertib (AZD6738), in patients with advanced TNBC. Patients and methods Patients with TNBC on most recent biopsy who had received 1 or 2 lines of chemotherapy for advanced disease or had relapsed within 12 months of (neo)adjuvant chemotherapy were eligible. Treatment was olaparib 300mg twice a day continuously and celarasertib 160mg on days 1–7 on a 28 day cycle until disease progression. The primary endpoint was confirmed objective response rate (ORR). Tissue and plasma biomarker analyses were pre-planned to identify predictors of response. Results 70 evaluable patients were enrolled. Germline BRCA1/2 mutations were present in 10 (14%) patients and 3 (4%) patients had somatic BRCA mutations. The confirmed ORR was 12/70; 17.1% (95%CI: 10.4-25.5). Responses were observed in patients without germline or somatic BRCA1/2 mutations, including patients with mutations in other homologous recombination repair genes and tumours with functional homologous recombination deficiency by RAD51 foci. Conclusion The response rate to olaparib and ceralasertib did not meet pre-specified criteria for activity in the overall evaluable population, but responses were observed in patients who would not be expected to respond to Olaparib monotherapy

Another Shipment of Six Short-Period Giant Planets from TESS

We present the discovery and characterization of six short-period, transiting giant planets from NASA's Transiting Exoplanet Survey Satellite (TESS) -- TOI-1811 (TIC 376524552), TOI-2025 (TIC 394050135), TOI-2145 (TIC 88992642), TOI-2152 (TIC 395393265), TOI-2154 (TIC 428787891), & TOI-2497 (TIC 97568467). All six planets orbit bright host stars (8.9 <G< 11.8, 7.7 <K< 10.1). Using a combination of time-series photometric and spectroscopic follow-up observations from the TESS Follow-up Observing Program (TFOP) Working Group, we have determined that the planets are Jovian-sized (R$_{P}$ = 1.00-1.45 R$_{J}$), have masses ranging from 0.92 to 5.35 M$_{J}$, and orbit F, G, and K stars (4753 $<$ T$_{eff}$ $<$ 7360 K). We detect a significant orbital eccentricity for the three longest-period systems in our sample: TOI-2025 b (P = 8.872 days, $e$ = $0.220\pm0.053$), TOI-2145 b (P = 10.261 days, $e$ = $0.182^{+0.039}_{-0.049}$), and TOI-2497 b (P = 10.656 days, $e$ = $0.196^{+0.059}_{-0.053}$). TOI-2145 b and TOI-2497 b both orbit subgiant host stars (3.8 $<$ $\log$ g $<$4.0), but these planets show no sign of inflation despite very high levels of irradiation. The lack of inflation may be explained by the high mass of the planets; $5.35^{+0.32}_{-0.35}$ M$_{\rm J}$ (TOI-2145 b) and $5.21\pm0.52$ M$_{\rm J}$ (TOI-2497 b). These six new discoveries contribute to the larger community effort to use {\it TESS} to create a magnitude-complete, self-consistent sample of giant planets with well-determined parameters for future detailed studies.Comment: 20 Pages, 6 Figures, 8 Tables, Accepted by MNRA

The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z<0.5$ cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using $>1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.Comment: 41 pages, 27 figures, accepted for publication by MNRA

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants