Semi-automatic selection of summary statistics for ABC model choice

A central statistical goal is to choose between alternative explanatory models of data. In many modern applications, such as population genetics, it is not possible to apply standard methods based on evaluating the likelihood functions of the models, as these are numerically intractable. Approximate Bayesian computation (ABC) is a commonly used alternative for such situations. ABC simulates data x for many parameter values under each model, which is compared to the observed data xobs. More weight is placed on models under which S(x) is close to S(xobs), where S maps data to a vector of summary statistics. Previous work has shown the choice of S is crucial to the efficiency and accuracy of ABC. This paper provides a method to select good summary statistics for model choice. It uses a preliminary step, simulating many x values from all models and fitting regressions to this with the model as response. The resulting model weight estimators are used as S in an ABC analysis. Theoretical results are given to justify this as approximating low dimensional sufficient statistics. A substantive application is presented: choosing between competing coalescent models of demographic growth for Campylobacter jejuni in New Zealand using multi-locus sequence typing data

Multi-Spectral Visual Crop Assessment Under Limited Data Constraints

In an era of climate change and global population growth, deep learning based multi-spectral imaging has the potential to significantly assist in production management across a wide range of agricultural and food production domains. A key challenge however in applying state-of-the-art methods is that they, unlike classical hand crafted methods, are usually thought of as being only useful when significant amounts of data are available. In this paper we investigate this hypothesis by examining the performance of state-of-the-art deep learning methods when applied to a restricted data set that is not easily bootstrapped through pre-trained image processing networks. We demonstrate that significant result improvement can be obtained from deep residual networks over a baseline image processing model -- even in the case where data collection is highly expensive and pre-trained networks cannot be easily built upon. Our work also constitutes a useful contribution to understanding the benefit of applying deep image multi-spectral processing techniques to the agri-food domain

TRANSFER LEARNING PERFORMANCE FOR REMOTE PASTURELAND TRAIT ESTIMATION IN REAL-TIME FARM MONITORING

In precision agriculture, having knowledge of pastureland forage biomass and moisture content prior to an ensiling process enables pastoralists to enhance silage production. While traditional trait measurement estimation methods relied on hand-crafted vegetation indices, manual measurements, or even destructive methods, remote sensing technology coupled with state-of-the-art deep learning algorithms can enable estimation using a broader spectrum of data, but generally require large volumes of labelled data, which is lacking in this domain. This work investigates the performance of a range of deep learning algorithms on a small dataset for biomass and moisture estimation that was collected with a compact remote sensing system designed to work in real time. Our results showed that applying transfer learning to Inception ResNet improved minimum mean average percentage error from 45.58% on a basic CNN, to 28.07% on biomass, and from 29.33% to 8.03% on moisture content. From scratch models and models optimised for mobile remote sensing applications (MobileNet) failed to produce the same level of improvement

Experimental Infection of a North American Raptor, American Kestrel (Falco sparverius), with Highly Pathogenic Avian Influenza Virus (H5N1)

Several species of wild raptors have been found in Eurasia infected with highly pathogenic avian influenza virus (HPAIV) subtype H5N1. Should HPAIV (H5N1) reach North America in migratory birds, species of raptors are at risk not only from environmental exposure, but also from consuming infected birds and carcasses. In this study we used American kestrels as a representative species of a North American raptor to examine the effects of HPAIV (H5N1) infection in terms of dose response, viral shedding, pathology, and survival. Our data showed that kestrels are highly susceptible to HPAIV (H5N1). All birds typically died or were euthanized due to severe neurologic disease within 4–5 days of inoculation and shed significant amounts of virus both orally and cloacally, regardless of dose administered. The most consistent microscopic lesions were necrosis in the brain and pancreas. This is the first experimental study of HPAIV infection in a North American raptor and highlights the potential risks to birds of prey if HPAIV (H5N1) is introduced into North America

Discovery and Early Evolution of ASASSN-19bt, the First TDE Detected by TESS

We present the discovery and early evolution of ASASSN-19bt, a tidal disruption event (TDE) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of $d\simeq115$ Mpc and the first TDE to be detected by TESS. As the TDE is located in the TESS Continuous Viewing Zone, our dataset includes 30-minute cadence observations starting on 2018 July 25, and we precisely measure that the TDE begins to brighten $\sim8.3$ days before its discovery. Our dataset also includes 18 epochs of Swift UVOT and XRT observations, 2 epochs of XMM-Newton observations, 13 spectroscopic observations, and ground data from the Las Cumbres Observatory telescope network, spanning from 32 days before peak through 37 days after peak. ASASSN-19bt thus has the most detailed pre-peak dataset for any TDE. The TESS light curve indicates that the transient began to brighten on 2019 January 21.6 and that for the first 15 days its rise was consistent with a flux $\propto t^2$ power-law model. The optical/UV emission is well-fit by a blackbody SED, and ASASSN-19bt exhibits an early spike in its luminosity and temperature roughly 32 rest-frame days before peak and spanning up to 14 days that has not been seen in other TDEs, possibly because UV observations were not triggered early enough to detect it. It peaked on 2019 March 04.9 at a luminosity of $L\simeq1.3\times10^{44}$ ergs s$^{-1}$ and radiated $E\simeq3.2\times10^{50}$ ergs during the 41-day rise to peak. X-ray observations after peak indicate a softening of the hard X-ray emission prior to peak, reminiscent of the hard/soft states in X-ray binaries.Comment: 23 pages, 14 figures, 5 tables. A machine-readable table containing the host-subtracted photometry presented in this manuscript is included as an ancillary fil

Whole-Genome Comparison of Two Campylobacter jejuni Isolates of the Same Sequence Type Reveals Multiple Loci of Different Ancestral Lineage

Campylobacter jejuni ST-474 is the most important human enteric pathogen in New Zealand, and yet this genotype is rarely found elsewhere in the world. Insight into the evolution of this organism was gained by a whole genome comparison of two ST-474, flaA SVR-14 isolates and other available C. jejuni isolates and genomes. The two isolates were collected from different sources, human (H22082) and retail poultry (P110b), at the same time and from the same geographical location. Solexa sequencing of each isolate resulted in 1.659 Mb (H22082) and 1.656 Mb (P110b) of assembled sequences within 28 (H22082) and 29 (P110b) contigs. We analysed 1502 genes for which we had sequences within both ST-474 isolates and within at least one of 11 C. jejuni reference genomes. Although 94.5% of genes were identical between the two ST-474 isolates, we identified 83 genes that differed by at least one nucleotide, including 55 genes with non-synonymous substitutions. These covered 101 kb and contained 672 point differences. We inferred that 22 (3.3%) of these differences were due to mutation and 650 (96.7%) were imported via recombination. Our analysis estimated 38 recombinant breakpoints within these 83 genes, which correspond to recombination events affecting at least 19 loci regions and gives a tract length estimate of 2 kb. This includes a 12 kb region displaying non-homologous recombination in one of the ST-474 genomes, with the insertion of two genes, including ykgC, a putative oxidoreductase, and a conserved hypothetical protein of unknown function. Furthermore, our analysis indicates that the source of this recombined DNA is more likely to have come from C. jejuni strains that are more closely related to ST-474. This suggests that the rates of recombination and mutation are similar in order of magnitude, but that recombination has been much more important for generating divergence between the two ST-474 isolates

Study protocol: can a school gardening intervention improve children's diets?

BACKGROUND: The current academic literature suggests there is a potential for using gardening as a tool to improve children's fruit and vegetable intake. This study is two parallel randomised controlled trials (RCT) devised to evaluate the school gardening programme of the Royal Horticultural Society (RHS) Campaign for School Gardening, to determine if it has an effect on children's fruit and vegetable intake. METHOD/DESIGN: Trial One will consist of 26 schools; these schools will be randomised into two groups, one to receive the intensive intervention as "Partner Schools" and the other to receive the less intensive intervention as "Associate Schools". Trial Two will consist of 32 schools; these schools will be randomised into either the less intensive intervention "Associate Schools" or a comparison group with delayed intervention. Baseline data collection will be collected using a 24-hour food diary (CADET) to collect data on dietary intake and a questionnaire exploring children's knowledge and attitudes towards fruit and vegetables. A process measures questionnaire will be used to assess each school's gardening activities. DISCUSSION: The results from these trials will provide information on the impact of the RHS Campaign for School Gardening on children's fruit and vegetable intake. The evaluation will provide valuable information for designing future research in primary school children's diets and school based interventions. TRIAL REGISTRATION: ISRCTN11396528

The Sloan Digital Sky Survey Quasar Catalog I. Early Data Release

We present the first edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog consists of the 3814 objects (3000 discovered by the SDSS) in the initial SDSS public data release that have at least one emission line with a full width at half maximum larger than 1000 km/s, luminosities brighter than M_i^* = -23, and highly reliable redshifts. The area covered by the catalog is 494 square degrees; the majority of the objects were found in SDSS commissioning data using a multicolor selection technique. The quasar redshifts range from 0.15 to 5.03. For each object the catalog presents positions accurate to better than 0.2" rms per coordinate, five band (ugriz) CCD-based photometry with typical accuracy of 0.05 mag, radio and X-ray emission properties, and information on the morphology and selection method. Calibrated spectra of all objects in the catalog, covering the wavelength region 3800 to 9200 Angstroms at a spectral resolution of 1800-2100, are also available. Since the quasars were selected during the commissioning period, a time when the quasar selection algorithm was undergoing frequent revisions, the sample is not homogeneous and is not intended for statistical analysis.Comment: 27 pages, 4 figures, 4 tables, accepted by A

The First Hour of Extra-galactic Data of the Sloan Digital Sky Survey Spectroscopic Commissioning: The Coma Cluster

On 26 May 1999, one of the Sloan Digital Sky Survey (SDSS) fiber-fed spectrographs saw astronomical first light. This was followed by the first spectroscopic commissioning run during the dark period of June 1999. We present here the first hour of extra-galactic spectroscopy taken during these early commissioning stages: an observation of the Coma cluster of galaxies. Our data samples the Southern part of this cluster, out to a radius of 1.5degrees and thus fully covers the NGC 4839 group. We outline in this paper the main characteristics of the SDSS spectroscopic systems and provide redshifts and spectral classifications for 196 Coma galaxies, of which 45 redshifts are new. For the 151 galaxies in common with the literature, we find excellent agreement between our redshift determinations and the published values. As part of our analysis, we have investigated four different spectral classification algorithms: spectral line strengths, a principal component decomposition, a wavelet analysis and the fitting of spectral synthesis models to the data. We find that a significant fraction (25%) of our observed Coma galaxies show signs of recent star-formation activity and that the velocity dispersion of these active galaxies (emission-line and post-starburst galaxies) is 30% larger than the absorption-line galaxies. We also find no active galaxies within the central (projected) 200 h-1 Kpc of the cluster. The spatial distribution of our Coma active galaxies is consistent with that found at higher redshift for the CNOC1 cluster survey. Beyond the core region, the fraction of bright active galaxies appears to rise slowly out to the virial radius and are randomly distributed within the cluster with no apparent correlation with the potential merger of the NGC 4839 group. [ABRIDGED]Comment: Accepted in AJ, 65 pages, 20 figures, 5 table

Colors of 2625 Quasars at 0<z<5 Measured in the Sloan Digital Sky Survey Photometric System

We present an empirical investigation of the colors of quasars in the Sloan Digital Sky Survey (SDSS) photometric system. The sample studied includes 2625 quasars with SDSS photometry. The quasars are distributed in a 2.5 degree wide stripe centered on the Celestial Equator covering $\sim529$ square degrees. Positions and SDSS magnitudes are given for the 898 quasars known prior to SDSS spectroscopic commissioning. New SDSS quasars represent an increase of over 200% in the number of known quasars in this area of the sky. The ensemble average of the observed colors of quasars in the SDSS passbands are well represented by a power-law continuum with $\alpha_{\nu} = -0.5$ ($f_{\nu} \propto \nu^{\alpha}$). However, the contributions of the $3000 {\rm \AA}$ bump and other strong emission lines have a significant effect upon the colors. The color-redshift relation exhibits considerable structure, which may be of use in determining photometric redshifts for quasars. The range of colors can be accounted for by a range in the optical spectral index with a distribution $\alpha_{\nu}=-0.5\pm0.65$ (95% confidence), but there is a red tail in the distribution. This tail may be a sign of internal reddening. Finally, we show that there is a continuum of properties between quasars and Seyfert galaxies and we test the validity of the traditional division between the two classes of AGN.Comment: 66 pages, 15 figures (3 color), accepted by A