Unilever has stated that it will use only cage-free eggs in its products. Walmart and Costco have announced that their private-brand eggs are 100% cage free. Subway recently announced that it has ...begun the process of switching to 100% cagefree eggs. And other restaurant chains also have begun using cage-free eggs. The Humane Society of the United States (HSUS), which aims to foster animal-friendly policies, assisted most of the companies as they made these strides. One thing that HSUS shares is the belief that all animals, including those raised for food, deserve some semblance of protection from abuse.
The morphological classification of radio sources is important to gain a full understanding of galaxy evolution processes and their relation with local environmental properties. Furthermore, the ...complex nature of the problem, its appeal for citizen scientists and the large data rates generated by existing and upcoming radio telescopes combine to make the morphological classification of radio sources an ideal test case for the application of machine learning techniques. One approach that has shown great promise recently is Convolutional Neural Networks (CNNs). Literature, however, lacks two major things when it comes to CNNs and radio galaxy morphological classification. Firstly, a proper analysis of whether overfitting occurs when training CNNs to perform radio galaxy morphological classification using a small curated training set is needed. Secondly, a good comparative study regarding the practical applicability of the CNN architectures in literature is required. Both of these shortcomings are addressed in this paper. Multiple performance metrics are used for the latter comparative study, such as inference time, model complexity, computational complexity and mean per class accuracy. As part of this study we also investigate the effect that receptive field, stride length and coverage has on recognition performance. For the sake of completeness, we also investigate the recognition performance gains that we can obtain by employing classification ensembles. A ranking system based upon recognition and computational performance is proposed. MCRGNet, Radio Galaxy Zoo and ConvXpress (novel classifier) are the architectures that best balance computational requirements with recognition performance.
To report our experience using Version 2 of the Cochrane risk-of-bias tool for randomised trials (RoB2).
Two reviewers independently applied RoB2 to results of interest in a large systematic review ...of complex interventions and reached consensus. We recorded time taken, and noted and discussed our difficulties using the tool, and the resolutions we adopted. We explored time taken with regression analysis and summarised our experience of implementing the tool.
We assessed risk of bias in 860 results of interest in 113 studies. Staff resource averaged 358 minutes per study (SD 183). Number of results (β=22) and reports (β=14) per study and experience of the team (β=-6) significantly affected assessment time. To implement the tool consistently we developed cut-points for missingness and considerations of balance regarding missingness, assumed some concerns with intervention deviations unless otherwise prevented or investigated, some concerns with measurements from unblinded self-reporting participants, and judged low risk of selection for certain dichotomous outcomes despite the absence of an analysis plan.
The RoB2 tool and guidance are useful but resource-intensive and challenging to implement. Critical appraisal tools and reporting guidelines should detail risk-of-bias implementation. Improved guidance focussing on implementation could assist reviewers.
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