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PurposeThe study aims to compare survey recruitment rates between Facebook, Twitter and Qualtrics and to assess the impact of recruitment method on estimates of energy content, food safety, carbon footprint and animal welfare across 29 foods.Design/methodology/approachTwo versions of an online survey were developed on the citizen science platform, Zooniverse. The surveys explored citizen estimations of energy density (kcal) or carbon footprint (Co2) and food safety or animal welfare of 29 commonly eaten foods. Survey recruitment was conducted via paid promotions on Twitter and Facebook and via paid respondent invites on Qualtrics. The study included approximately 500 participants (Facebook, N˜11 (ratings 358), Twitter, N˜85 (ratings 2,184), Qualtrics, N = 398 (ratings 11,910)). Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values and assessed the impact of the variables on estimations.FindingsCitizens were unable to accurately estimate carbon footprint and energy content, with most citizens overestimating values. Citizen estimates were most accurate for meat products. Qualtrics was the most successful recruitment method for the online survey. Citizen estimates between platforms were significantly different, suggesting that Facebook and Twitter may not be suitable recruitment methods for citizen online surveys.Practical implicationsQualtrics was the favourable platform for survey recruitment. However, estimates across all recruitment platforms were poor. As paid recruitment methods such as Qualtrics are costly, the authors recommend continued examination of the social media environment to develop appropriate, affordable and timely online recruitment strategies for citizen science.Originality/valueThe findings indicate that citizens are unable to accurately estimate the carbon footprint and energy content of foods suggesting a focus on consumer education is needed to enable consumers to move towards more sustainable and healthy diets. Essential if we are to meet the 2030 Sustainable Development Goals of zero hunger, good health and wellbeing and responsible consumption and production. The study highlights the utility of Zooniverse for assessing citizen estimates of carbon footprint, energy content, animal welfare and safety of foods.

The challenge of consistent identification of internal structure in galaxies - in particular disc galaxy components like spiral arms, bars, and bulges - has hindered our ability to study the physical impact of such structure across large samples. In this paper we present Galaxy Zoo: 3D (GZ: 3D) a crowdsourcing project built on the Zooniverse platform which we used to create spatial pixel (spaxel) maps that identify galaxy centres, foreground stars, galactic bars and spiral arms for 29831 galaxies which were potential targets of the MaNGA survey (Mapping Nearby Galaxies at Apache Point Observatory, part of the fourth phase of the Sloan Digital Sky Surveys or SDSS-IV), including nearly all of the 10,010 galaxies ultimately observed. Our crowd-sourced visual identification of asymmetric, internal structures provides valuable insight on the evolutionary role of non-axisymmetric processes that is otherwise lost when MaNGA data cubes are azimuthally averaged. We present the publicly available GZ:3D catalog alongside validation tests and example use cases. These data may in the future provide a useful training set for automated identification of spiral arm features. As an illustration, we use the spiral masks in a sample of 825 galaxies to measure the enhancement of star formation spatially linked to spiral arms, which we measure to be a factor of three over the background disc, and how this enhancement increases with radius., Comment: 13 pages, 9 figures. MNRAS accepted

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r=23.6 vs. r=22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314,000 galaxies. 140,000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314,000 galaxies. When measured against confident volunteer classifications, the networks are approximately 99% accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve., Accepted by MNRAS July '21. Open access DOI below. Data at https://doi.org/10.5281/zenodo.4196266. Code at https://www.github.com/mwalmsley/zoobot. Docs at https://zoobot.readthedocs.io/. Interactive viewer at https://share.streamlit.io/mwalmsley/galaxy-poster/gz_decals_mike_walmsley.py

Copyright © 2021 Oakden, Bridge, Armstrong, Reynolds, Wang, Panzone, Rivera, Kause, Ffoulkes, Krawczyk, Miller and Serjeant. To enhance sustainability, the food system requires significant shifts in the production, processing and supply of food. Ideally, a sustainable food system should operate, not only to protect the biosphere, but also to provide nutritious, high-quality food, and to support social values, an equitable economy, and human and animal health. It should also be governed responsibly within a supportive policy environment. Implementing these shifts is a task of immense scale; but citizen participation/engagement has the potential to help make sustainability a reality through distributed learning, dynamic sensing, and knowledge generation. Technological advancements in sensing and data processing have enabled new forms of citizen participation in research. When food system research is embedded within society it can help us to understand which changes towards sustainability work and which do not. Indeed, citizen engagement in food systems research has the potential to help bring citizens on side, supporting the growth of a food culture of resilience and of sustainable practises (including dietary change). This commentary provides examples of how existing research and alternative food production systems and agroecological practises may provide possible frameworks for citizen participation in food system studies. We highlight potential future food and citizen science approaches. Widening citizen participation and encouraging the involvement of other food system actors, including those in local, national and international governance, is essential to capture the full potential of citizen science in enabling transition to a sustainable food system. For the research community citizen science offers engagement and empowerment of wider communities with science; collecting and analysing data; and creating viable solutions to food system and diet issues. STFC Food Network+ pilot funding (ST/P003079/1); STFC 21st Century challenge funding (ST/T001410/1) Piloting Zooniverse for food, health and sustainability citizen science; HEFCE Catalyst-funded N8 AgriFood Resilience Programme and matched funding from the N8 group of Universities; Research England via the project Food based citizen science in UK as a policy tool; Food Standards Agency to conduct an additional Rapid Evidence Assessment in December 2020; ESCAPE—The European Science Cluster of Astronomy &Particle Physics ESFRI Research Infrastructures; European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 824064.

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate., Published by JOSS. The package is available at https://github.com/skypyproject/skypy. Comments, issues and pull requests are welcome

Spiral structure is ubiquitous in the Universe, and the pitch angle of arms in spiral galaxies provide an important observable in efforts to discriminate between different mechanisms of spiral arm formation and evolution. In this paper, we present a hierarchical Bayesian approach to galaxy pitch angle determination, using spiral arm data obtained through the Galaxy Builder citizen science project. We present a new approach to deal with the large variations in pitch angle between different arms in a single galaxy, which obtains full posterior distributions on parameters. We make use of our pitch angles to examine previously reported links between bulge and bar strength and pitch angle, finding no correlation in our data (with a caveat that we use observational proxies for both bulge size and bar strength which differ from other work). We test a recent model for spiral arm winding, which predicts uniformity of the cotangent of pitch angle between some unknown upper and lower limits, finding our observations are consistent with this model of transient and recurrent spiral pitch angle as long as the pitch angle at which most winding spirals dissipate or disappear is larger than 10°.

Reducing COVID-19 transmission relies on controlling droplet and aerosol spread. Fluorescein staining reveals microscopic droplets.To compare the droplet spread in non-laminar and laminar air flow operating theatres.A 'cough-generator' was fixed to a theatre trolley at 45°. Fluorescein-stained 'secretions' were projected on to a series of calibrated targets. These were photographed under UV light and 'source detection' software measured droplet splatter size and distance.The smallest droplet detected was ∼120 μm and the largest ∼24,000 μm. An average of 25,862 spots was detected in the non-laminar theatre, compared with 11,430 in the laminar theatre (56% reduction). The laminar air flow mainly affected the smaller droplets (1000 μm). The surface area covered with droplets was: 6% at 50 cm, 1% at 2 m, and 0.5% at 3 m in the non-laminar air flow; and 3%, 0.5%, and 0.2% in the laminar air flow, respectively.Accurate mapping of droplet spread in clinical environments is possible using fluorescein staining and image analysis. The laminar air flow affected the smaller droplets but had limited effect on larger droplets in our 'aerosol-generating procedure' cough model. Our results indicate that the laminar air flow theatre requires similar post-surgery cleaning to the non-laminar, and staff should consider full personal protective equipment for medium- and high-risk patients.

Multicomponent modeling of galaxies is a valuable tool in the effort to quantitatively understand galaxy evolution, yet the use of the technique is plagued by issues of convergence, model selection, and parameter degeneracies. These issues limit its application over large samples to the simplest models, with complex models being applied only to very small samples. We attempt to resolve this dilemma of “quantity or quality” by developing a novel framework, built inside the Zooniverse citizen-science platform, to enable the crowdsourcing of model creation for Sloan Digital Sky Survey galaxies. We have applied the method, including a final algorithmic optimization step, on a test sample of 198 galaxies, and examine the robustness of this new method. We also compare it to automated fitting pipelines, demonstrating that it is possible to consistently recover accurate models that either show good agreement with, or improve on, prior work. We conclude that citizen science is a promising technique for modeling images of complex galaxies, and release our catalog of models.

© Copyright © 2020 Armstrong, Bridge, Oakden, Reynolds, Wang, Panzone, Rivera, Kause, Ffoulkes, Krawczyk, Miller and Serjeant. There is a food knowledge disconnect between the food research community, and the general population. Food experts know detailed information about foods, but there is a lack of understanding about what citizens know. Citizen science has been used successfully in various fields however, is virtually absent from food research. This pilot study explores the efficacy of Zooniverse citizen science platform as a method of food citizen research, and assesses the impact of response method, food type, portion size and weight information, on estimates of carbon footprint and energy content. Estimates of the carbon footprint (grams of carbon dioxide equivalent) and energy content (Kcal) of 10 foods were measured in a 3 (Between: Response Method; multiple-choice, slider, text box) × 3 (Within: portion size; small, medium, large) × 2 (Between: weight information; present, absent) observational survey. Citizens (N = ~516, unique IP addresses) were recruited via informal email networks. Kruskal–Wallis and Chi-square analyses compared citizen estimations with validated values, and assessed the impact of the variables on estimations. The majority of carbon footprint and energy content estimates were inaccurate, with citizens typically overestimating values. We observe an unexpected correlation between carbon footprint and energy content estimates. Portion size impacts perceptions, with estimations increasing with larger portion sizes. Weight information impacts perceptions, with estimations of carbon footprint being lower, and estimates of energy content being higher when weight information is present. Input method significantly affects observed values, estimates of carbon footprint and energy content estimates were lowest using the text box, followed by the slider tool, highest estimates were given using multiple choice. Citizens are unable to accurately estimate the carbon footprint and energy content of foods, though citizens may possess understanding of the hierarchy of values. These compelling findings highlight the need for consumer education, with a focus on carbon footprint, to precede interventions intended to move consumers toward more sustainable and healthy diets. We have demonstrated that citizen science can be used to measure food carbon footprint and energy content perceptions, and the slider tool offers greater sensitivity of estimation and functionality than other input methods. This work was funded by STFC Food Network+ pilot funding (ST/P003079/1), and STFC twenty-first century challenge funding (ST/T001410/1) Piloting Zooniverse for food, health, and sustainability citizen science. CR was supported from the HEFCE Catalyst-funded N8 AgriFood Resilience Programme and matched funding from the N8 group of Universities. Additional funding was provided by Research England via the project Food based citizen science in UK as a policy tool.

Dust attenuation in star-forming spiral galaxies affects stars and gas in different ways due to local variations in dust geometry. We present spatially resolved measurements of dust attenuation for a sample of 232 such star-forming spiral galaxies, derived from spectra acquired by the SDSS-IV MaNGA survey. The dust attenuation affecting the stellar populations of these galaxies (obtained using full spectrum stellar population fitting methods) is compared with the dust attenuation in the gas (derived from the Balmer decrement). Both of these attenuation measures increase for local regions of galaxies with higher star formation rates; the dust attenuation affecting the stellar populations increases more so than the dust attenuation in the gas, causing the ratio of the dust attenuation affecting the stellar populations to the dust attenuation in the gas to decrease for local regions of galaxies with higher star formation rate densities. No systematic difference is discernible in any of these dust attenuation quantities between the spiral arm and inter-arm regions of the galaxies. While both the dust attenuation in the gas and the dust attenuation affecting the stellar populations decrease with galactocentric radius, the ratio of the two quantities does not vary with radius. This ratio does, however, decrease systematically as the stellar mass of the galaxy increases. Analysis of the radial profiles of the two dust attenuation measures suggests that there is a disproportionately high concentration of birth clouds (incorporating gas, young stars and clumpy dust) nearer to the centres of star-forming spiral galaxies., Comment: 17 pages, 8 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society

While online crowdsourced text transcription projects have proliferated in the last decade, there is a need within the broader field to understand differences in project outcomes as they relate to task design, as well as to experiment with different models of online crowdsourced transcription that have not yet been explored. The experiment discussed in this paper involves the evaluation of newly-built tools on the Zooniverse.org crowdsourcing platform, attempting to answer the research question: "Does the current Zooniverse methodology of multiple independent transcribers and aggregation of results render higher-quality outcomes than allowing volunteers to see previous transcriptions and/or markings by other users? How does each methodology impact the quality and depth of analysis and participation?" To answer these questions, the Zooniverse team ran an A/B experiment on the project Anti-Slavery Manuscripts at the Boston Public Library. This paper will share results of this study, and also describe the process of designing the experiment and the metrics used to evaluate each transcription method. These include the comparison of aggregate transcription results with ground truth data; evaluation of annotation methods; the time it took for volunteers to complete transcribing each dataset; and the level of engagement with other project elements such as posting on the message board or reading supporting documentation. Particular focus will be given to the (at times) competing goals of data quality, efficiency, volunteer engagement, and user retention, all of which are of high importance for projects that focus on data from galleries, libraries, archives and museums. Ultimately, this paper aims to provide a model for impactful, intentional design and study of online crowdsourcing transcription methods, as well as shed light on the associations between project design, methodology and outcomes.

Bars in galaxies are thought to stimulate both inflow of material and radial mixing along them. Observational evidence for this mixing has been inconclusive so far however, limiting the evaluation of the impact of bars on galaxy evolution. We now use results from the MaNGA integral field spectroscopic survey to characterise radial stellar age and metallicity gradients along the bar and outside the bar in 128 strongly barred galaxies. We find that age and metallicity gradients are flatter in the barred regions of almost all barred galaxies when compared to corresponding disk regions at the same radii. Our results re-emphasize the key fact that by azimuthally averaging integral field spectroscopic data one loses important information from non-axisymmetric galaxy components such as bars and spiral arms. We interpret our results as observational evidence that bars are radially mixing material in galaxies of all stellar masses, and for all bar morphologies and evolutionary stages., 6 pages, 2 figures, accepted for publication in MNRAS Letters

The exact nature of the arms of spiral galaxies is still an open question. It has been widely assumed that spiral arms in galaxies with two distinct symmetrical arms are the products of density waves that propagate around the disk, with the spiral arms being visibly enhanced by the star formation that is triggered as the passing wave compresses gas in the galaxy disk. Such a persistent wave would propagate with an approximately constant angular speed, its pattern speed Op. The quasi-stationary density wave theory can be tested by measuring this quantity and showing that it does not vary with radius in the galaxy. Unfortunately, this measurement is difficult because Op is only indirectly connected to observables such as the stellar rotation speed. Here, we use the detailed information on stellar populations of the grand-design spiral galaxy UGC 3825, extracted from spectral mapping, to measure the offset between young stars of a known age and the spiral arm in which they formed, allowing the first direct measure of Op at a range of radii. The offset in this galaxy is found to be as expected for a pattern speed that varies little with radius, indicating consistency with a quasi-stationary density wave, and lending credence to this new method., 24 pages, 4 figures. This is a post-peer-review, pre-copyedit version of an article published in Nature Astronomy. The final authenticated version is available online at: http://dx.doi.org/10.1038/s41550-018-0627-5

We present new evidence for AGN feedback in a subset of 69 quenched low-mass galaxies ($M_{\star} \lesssim 5\times10^{9}$ M$_{\odot}$, $M_{\rm{r}} > -19$) selected from the first two years of the SDSS-IV MaNGA survey. The majority (85 per cent) of these quenched galaxies appear to reside in a group environment. We find 6 galaxies in our sample that appear to have an active AGN that is preventing on-going star-formation; this is the first time such a feedback mechanism has been observed in this mass range. Interestingly, five of these six galaxies have an ionised gas component that is kinematically offset from their stellar component, suggesting the gas is either recently accreted or outflowing. We hypothesise these six galaxies are low-mass equivalents to the "red geysers" observed in more massive galaxies. Of the other 63 galaxies in the sample, we find 8 do appear for have some low-level, residual star formation, or emission from hot, evolved stars. The remaining galaxies in our sample have no detectable ionised gas emission throughout their structures, consistent with them being quenched. This work shows the potential for understanding the detailed physical properties of dwarf galaxies through spatially resolved spectroscopy., Comment: 20 pages, 11 figures, accepted for publication in MNRAS

Nicolas J. Bonne and the Tactile Universe team describe their work to engage the vision-impaired community with accessible astrophysics.

We identify 885,503 type 1 quasar candidates to i3.5 than the traditional mid-IR selection "wedges" and to 2.23. This catalog paves the way for luminosity-dependent clustering investigations of large numbers of faint, high-redshift quasars and for further machine learning quasar selection using Spitzer and WISE data combined with other large-area optical imaging surveys., Comment: 54 pages, 17 figures; accepted by ApJS Data for tables 1 and 2 available at http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/master_quasar_catalogs.011414.fits.bz2 and http://www.physics.drexel.edu/~gtr/outgoing/optirqsos/data/optical_ir_quasar_candidates.052015.fits.bz2