Evaluation of a Single-Matrix Food Attractant Tephritid Fruit Fly Bait Dispenser for Use in Federal Trap Detection Programs

The use of synthetic food attractant lures for Tephritid fruit fly trapping is presently being incorporated into U.S. state and federal detection programs. These lures consist of ammonium acetate, trimethylamine hydrochloride and putrescine contained in individual packages that are attached to the inside (top) of plastic McPhail-type traps. Two chemical packets are placed in the traps for Anastrepha spp., where as three are attached for Ceratitis capitata. This report presents data on trap captures of the above species comparing the current (individually packaged) baits with a novel dispenser containing either two or three components into a single matrix. Tests were conducted in Florida and Hawaii using hand release of sterile Caribbean fruit fly (Caribfly), Anastrepha suspensa and the Mediterranean fruit fly, Ceratitis capitata (medfly)/ aerially released medfly/ and wild caribfly populations (Florida) and wild medfly (Hawaii). Observations in the Florida study indicated that minor formulation adjustment should increase the efficacy of the Anastrepha attractant, whereas less of an adjustment may be required to capture Ceratitis capitata. Results in open field tests in Hawaii indicated that the three-component synthetic food attractant in a single cone unit was just as effective in capturing wild male and female Medflies as the same food attractants in individual packets. The single matrix has some advantages in handling and ease-of-use, especially with the Multilure trap

ICTV Virus Taxonomy Profile: Arenaviridae 2023

Arenaviridae is a family for ambisense RNA viruses with genomes of about 10.5 kb that infect mammals, snakes, and fish. The arenavirid genome consists of two or three single-stranded RNA segments and encodes a nucleoprotein (NP), a glycoprotein (GP) and a large (L) protein containing RNA-directed RNA polymerase (RdRP) domains; some arenavirids encode a zinc-binding protein (Z). This is a summary of the International Committee on Taxonomy of Viruses (ICTV) report on the family Arenaviridae, which is available at www.ictv.global/report/arenaviridae

Are Compton-Thick AGN the Missing Link Between Mergers and Black Hole Growth?

We examine the host morphologies of heavily obscured active galactic nuclei (AGNs) at z ~ 1 to test whether obscured super-massive black hole growth at this epoch is preferentially linked to galaxy mergers. Our sample consists of 154 obscured AGNs with N_H > 10^(23.5) cm^(-2) and z 1.5. Using visual classifications, we compare the morphologies of these AGNs to control samples of moderately obscured 10^(22) cm^(-2) < N_H < 10^(23.5)cm^(-2) and unobscured (N_H < 10^(22) cm^(-2)) AGN. These control AGNs have similar redshifts and intrinsic X-ray luminosities to our heavily obscured AGN. We find that heavily obscured AGNs are twice as likely to be hosted by late-type galaxies relative to unobscured AGNs (65.3_(-4.6)^(+4.1)%) versus 34.5_(-2.7)^(+2.9)%) and three times as likely to exhibit merger or interaction signatures (21.5_(-3.3)^(+4.2)%) versus 7.8_(-1.3)^(+1.9)%). The increased merger fraction is significant at the 3.8σ level. If we exclude all point sources and consider only extended hosts, we find that the correlation between the merger fraction and obscuration is still evident, although at a reduced statistical significance (2.5σ). The fact that we observe a different disk/spheroid fraction versus obscuration indicates that the viewing angle cannot be the only thing differentiating our three AGN samples, as a simple unification model would suggest. The increased fraction of disturbed morphologies with obscuration supports an evolutionary scenario, in which Compton-thick AGNs are a distinct phase of obscured super-massive black hole (SMBH) growth following a merger/interaction event. Our findings also suggest that some of the merger-triggered SMBH growth predicted by recent AGN fueling models may be hidden among the heavily obscured, Compton-thick population

A Critical Assessment of Stellar Mass Measurement Methods

In this paper we perform a comprehensive study of the main sources of random and systematic errors in stellar mass measurement for galaxies using their Spectral Energy Distributions (SEDs). We use mock galaxy catalogs with simulated multi-waveband photometry (from U-band to mid-infrared) and known redshift, stellar mass, age and extinction for individual galaxies. Given different parameters affecting stellar mass measurement (photometric S/N ratios, SED fitting errors, systematic effects, the inherent degeneracies and correlated errors), we formulated different simulated galaxy catalogs to quantify these effects individually. We studied the sensitivity of stellar mass estimates to the codes/methods used, population synthesis models, star formation histories, nebular emission line contributions, photometric uncertainties, extinction and age. For each simulated galaxy, the difference between the input stellar masses and those estimated using different simulation catalogs, $\Delta\log(M)$, was calculated and used to identify the most fundamental parameters affecting stellar masses. We measured different components of the error budget, with the results listed as follows: (1). no significant bias was found among different codes/methods, with all having comparable scatter; (2). A source of error is found to be due to photometric uncertainties and low resolution in age and extinction grids; (3). The median of stellar masses among different methods provides a stable measure of the mass associated with any given galaxy; (4). The deviations in stellar mass strongly correlate with those in age, with a weaker correlation with extinction; (5). the scatter in the stellar masses due to free parameters are quantified, with the sensitivity of the stellar mass to both the population synthesis codes and inclusion of nebular emission lines studied.Comment: 33 pages, 20 Figures, Accepted for publication in Astrophysical Journa

Optimized Photometric Redshifts for the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS)

We present the first comprehensive release of photometric redshifts (photo- z's) from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) team. We use statistics based upon the Quantile-Quantile (Q-Q) plot to identify biases and signatures of underestimated or overestimated errors in photo- z probability density functions (PDFs) produced by six groups in the collaboration; correcting for these effects makes the resulting PDFs better match the statistical definition of a PDF. After correcting each group’s PDF, we explore three methods of combining the different groups’ PDFs for a given object into a consensus curve. Two of these methods are based on identifying the minimum f-divergence curve, i.e., the PDF that is closest in aggregate to the other PDFs in a set (analogous to the median of an array of numbers). We demonstrate that these techniques yield improved results using sets of spectroscopic redshifts independent of those used to optimize PDF modifications. The best photo- z PDFs and point estimates are achieved with the minimum f-divergence using the best four PDFs for each object (mFDa4) and the hierarchical Bayesian (HB4) methods, respectively. The HB4 photo- z point estimates produced σ NMAD = 0.0227/0.0189 and ∣Δz/(1 + z)∣ &gt; 0.15 outlier fraction = 0.067/0.019 for spectroscopic and 3D Hubble Space Telescope redshifts, respectively. Finally, we describe the structure and provide guidance for the use of the CANDELS photo- z catalogs, which are available at https://archive.stsci.edu/prepds/candels/.</p

Optimized Photometric Redshifts for the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS)

We present the first comprehensive release of photometric redshifts (photo-z's) from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) team. We use statistics based upon the Quantile-Quantile (Q--Q) plot to identify biases and signatures of underestimated or overestimated errors in photo-z probability density functions (PDFs) produced by six groups in the collaboration; correcting for these effects makes the resulting PDFs better match the statistical definition of a PDF. After correcting each group's PDF, we explore three methods of combining the different groups' PDFs for a given object into a consensus curve. Two of these methods are based on identifying the minimum f-divergence curve, i.e., the PDF that is closest in aggregate to the other PDFs in a set (analogous to the median of an array of numbers). We demonstrate that these techniques yield improved results using sets of spectroscopic redshifts independent of those used to optimize PDF modifications. The best photo-z PDFs and point estimates are achieved with the minimum f-divergence using the best 4 PDFs for each object (mFDa4) and the Hierarchical Bayesian (HB4) methods, respectively. The HB4 photo-z point estimates produced $\sigma_{\rm NMAD} = 0.0227/0.0189$ and $|\Delta z/(1+z)| > 0.15$ outlier fraction = 0.067/0.019 for spectroscopic and 3D-HST redshifts, respectively. Finally, we describe the structure and provide guidance for the use of the CANDELS photo-z catalogs, which are available at https://archive.stsci.edu/hlsp/candels.Comment: 35 pages, 19 figures, submitted to ApJ, data available at https://archive.stsci.edu/hlsp/candel

Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS

We present quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications, the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of ‘smooth’ galaxies with parametric morphologies to select a sample of featureless discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs

Taxonomy of the order Bunyavirales : second update 2018

In October 2018, the order Bunyavirales was amended by inclusion of the family Arenaviridae, abolishment of three families, creation of three new families, 19 new genera, and 14 new species, and renaming of three genera and 22 species. This article presents the updated taxonomy of the order Bunyavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).Non peer reviewe

Taxonomy of the family Arenaviridae and the order Bunyavirales : update 2018

In 2018, the family Arenaviridae was expanded by inclusion of 1 new genus and 5 novel species. At the same time, the recently established order Bunyavirales was expanded by 3 species. This article presents the updated taxonomy of the family Arenaviridae and the order Bunyavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV) and summarizes additional taxonomic proposals that may affect the order in the near future.Peer reviewe

2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales. Archives of Virology (2021) 166:3567–3579. https://doi.org/10.1007/s00705-021-05266-wIn March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.This work was supported in part through Laulima Government Solutions, LLC prime contract with the US National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C. J.H.K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. This work was also supported in part with federal funds from the National Cancer Institute (NCI), National Institutes of Health (NIH), under Contract No. 75N91019D00024, Task Order No. 75N91019F00130 to I.C., who was supported by the Clinical Monitoring Research Program Directorate, Frederick National Lab for Cancer Research. This work was also funded in part by Contract No. HSHQDC-15-C-00064 awarded by DHS S&T for the management and operation of The National Biodefense Analysis and Countermeasures Center, a federally funded research and development center operated by the Battelle National Biodefense Institute (V.W.); and NIH contract HHSN272201000040I/HHSN27200004/D04 and grant R24AI120942 (N.V., R.B.T.). S.S. acknowledges partial support from the Special Research Initiative of Mississippi Agricultural and Forestry Experiment Station (MAFES), Mississippi State University, and the National Institute of Food and Agriculture, US Department of Agriculture, Hatch Project 1021494. Part of this work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001030), the UK Medical Research Council (FC001030), and the Wellcome Trust (FC001030).S