Above–belowground herbivore interactions in mixed plant communities are influenced by altered precipitation patterns

Root- and shoot-feeding herbivores have the capacity to influence one another by modifying the chemistry of the shared host plant. This can alter rates of nutrient mineralization and uptake by neighboring plants and influence plant–plant competition, particularly in mixtures combining grasses and legumes. Root herbivory-induced exudation of nitrogen (N) from legume roots, for example, may increase N acquisition by co-occurring grasses, with knock-on effects on grassland community composition. Little is known about how climate change may affect these interactions, but an important and timely question is how will grass–legume mixtures respond in a future with an increasing reliance on legume N mineralization in terrestrial ecosystems. Using a model grass–legume mixture, this study investigated how simultaneous attack on lucerne (Medicago sativa) by belowground weevils (Sitona discoideus) and aboveground aphids (Acyrthosiphon pisum) affected a neighboring grass (Phalaris aquatica) when subjected to drought, ambient, and elevated precipitation. Feeding on rhizobial nodules by weevil larvae enhanced soil water retention under ambient and elevated precipitation, but only when aphids were absent. While drought decreased nodulation and root N content in lucerne, grass root and shoot chemistry were unaffected by changes in precipitation. However, plant communities containing weevils but not aphids showed increased grass height and N concentrations, most likely associated with the transfer of N from weevil-attacked lucerne plants containing more nodules and higher root N concentrations compared with insect-free plants. Drought decreased aphid abundance by 54% but increased total and some specific amino acid concentrations (glycine, lysine, methionine, tyrosine, cysteine, histidine, arginine, aspartate, and glutamate), suggesting that aphid declines were being driven by other facets of drought (e.g., reduced phloem hydraulics). The presence of weevil larvae belowground decreased aphid numbers by 30%, likely associated with a significant reduction in proline in weevil-treated lucerne plants. This study demonstrates how predicted changes to precipitation patterns and indirect interactions between herbivores can alter the outcome of competition between N-fixing legumes and non-N-fixing grasses, with important implications for plant community structure and productivity

How residents and interns utilise and perceive the personal digital assistant and UpToDate

<p>Abstract</p> <p>Background</p> <p>In this era of evidence-based medicine, doctors are increasingly using information technology to acquire medical knowledge. This study evaluates how residents and interns utilise and perceive the personal digital assistant (PDA) and the online resource UpToDate.</p> <p>Methods</p> <p>This is a questionnaire survey of all residents and interns in a tertiary teaching hospital.</p> <p>Results</p> <p>Out of 168 doctors, 134 (79.8%) responded to the questionnaire. Only 54 doctors (40.3%) owned a PDA. Although these owners perceived that the PDA was most useful for providing drug information, followed by medical references, scheduling and medical calculators, the majority of them did not actually have medical software applications downloaded on their PDAs. The greatest concerns highlighted for the PDA were the fear of loss and breakage, and the preference for working with desktop computers and paper. Meanwhile, only 76 doctors (56.7%) used UpToDate, even though the hospital had an institutional subscription for it. Although 93.4% of these users would recommend UpToDate to a colleague, only 57.9% stated that the use of UpToDate had led to a change in their management of patients.</p> <p>Conclusion</p> <p>Although UpToDate and various PDA software applications were deemed useful by some of the residents and interns in our study, both digital tools were under-utilised. More should be done to facilitate the use of medical software applications on PDAs, to promote awareness of tools for evidence-based medicine such as UpToDate, and to facilitate the application of evidence-based medicine in daily clinical practice.</p

The challenge to professionals of using social media: teachers in England negotiating personal-professional identities

Social media are a group of technologies such as Twitter, Facebook and LinkedIn which offer people chances to interact with one another in new ways. Teachers, like other members of society, do not all use social media. Some avoid, some experiment with and others embrace social media enthusiastically. As a means of communication available to everyone in modern society, social media is challenging teachers, as other professionals in society, to decide whether to engage with these tools and, if so, on what basis – as an individual (personally), or as a teacher (professionally). Although teachers are guided by schools and codes of practice, teachers as individuals are left to decide whether and how to explore social media for either their own or their students' learning. This paper analyses evidence from interviews with 12 teachers from England about their use of social media as to the challenges they experience in relation to using the media as professional teachers.. Teachers are in society’s spotlight in terms of examples of inappropriate use of social media but also under peer pressure to connect. This paper explores their agency in responding. The paper focuses on how teachers deal with tensions between their personal and professional use of social media. These tensions are not always perceived as negative and some teachers' accounts revealed a unity in their identities when using social media. The paper reflects on the implications of such teachers' identities in relation to the future of social media use in education

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License