Plant–environment response pathway regulation uncovered by investigating non-typical legume symbiosis and nodulation

Nitrogen is an essential element needed for plants to survive, and legumes are well known to recruit rhizobia to fix atmospheric nitrogen. In this widely studied symbiosis, legumes develop specific structures on the roots to host specific symbionts. This review explores alternate nodule structures and their functions outside of the more widely studied legume–rhizobial symbiosis, as well as discussing other unusual aspects of nodulation. This includes actinorhizal-Frankia, cycad-cyanobacteria, and the non-legume Parasponia andersonii-rhizobia symbioses. Nodules are also not restricted to the roots, either, with examples found within stems and leaves. Recent research has shown that legume–rhizobia nodulation brings a great many other benefits, some direct and some indirect. Rhizobial symbiosis can lead to modifications in other pathways, including the priming of defence responses, and to modulated or enhanced resistance to biotic and abiotic stress. With so many avenues to explore, this review discusses recent discoveries and highlights future directions in the study of nodulation

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

A summary of the ComParE COVID-19 challenges

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals’ respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).</p

A summary of the ComParE COVID-19 challenges.

Peer reviewed: TrueThe COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS)

Mass Reproducibility and Replicability: A New Hope

This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes