First year nursing students use of social media within education: results of a survey

Introduction – Social media rapidly disseminates information but is a controversial learning platform in nurse education. This study aimed to explore how students viewed the use of Twitter, and other social media, in their first year of a nursing degree. Aim - The aim of this study was to evaluate first year student nurses’ use of social media, before and after commencing a pre-registration programme, where Twitter was used in a module Methodology – A cross-sectional approach using a descriptive survey was completed. Methods – An online survey, that included Likert scale and open questions, was open for one month in 2016 Sample – All students on Nursing Undergraduate Degrees, in Adult, Child and Mental Health, who were in the first year of their programme were eligible to participate. 121 students took part with a response rate of 32%. Results –Most students were positive about using social media as they found it an engaging way to promote discussion and share information. Students use of Twitter changed in the first year with 19.8% using it once or more per week on commencement of the programme which increased to 45.5%; other social media platforms remained static. Most students (57.8%) understood the purpose of using Twitter although 14% reported that it was not used within their module; thus, not all students gained experience of using the social media. 81% of students said that using Twitter had been beneficial to increase awareness of nursing issues within their course. However, there were areas that students found difficult such as time, and not knowing what to say. Conclusion –The study suggests that teaching about social media, and incorporating it into learning activities, may be beneficial for students. However, more research into the subject using an experimental design to assess changes over time would be useful

Evaluation of onset, cessation and seasonal precipitation of the Southeast Asia rainy season in CMIP5 regional climate models and HighResMIP global climate models

Representing the rainy season of the maritime continent is a challenge for global and regional climate models. Here, we compare regional climate models (RCMs) based on the coupled model intercomparison project phase 5 (CMIP5) model generation with high-resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. The onset and the total precipitation of the rainy season for both model experiments are compared against observational datasets for Southeast Asia. A realistic representation of the monsoon rainfall is essential for agriculture in Southeast Asia as a delayed onset jeopardizes the possibility of having three annual crops. In general, the coupled historical runs (Hist-1950) and the historical force atmosphere run (HighresSST) of the high-resolution model intercomparison project (HighResMIP) suite were consistently closer to the observations than the RCM of CMIP5 used in this study. We find that for the whole of Southeast Asia, the HighResMIP models simulate the onset date and the total precipitation of the rainy season over the region closer to the observations than the other model sets used in this study. High-resolution models in the HighresSST experiment showed a similar performance to their low-resolution equivalents in simulating the monsoon characteristics. The HighresSST experiment simulated the anomaly of the onset date and the total precipitation for different El Niño-southern oscillation conditions best, although the magnitude of the onset date anomaly was underestimated. © 2021 The Authors. International Journal of Climatology published by John Wiley Sons Ltd on behalf of Royal Meteorological Society

Development and exploitation of a controlled vocabulary in support of climate modelling

There are three key components for developing a metadata system: a container structure laying out the key semantic issues of interest and their relationships; an extensible controlled vocabulary providing possible content; and tools to create and manipulate that content. While metadata systems must allow users to enter their own information, the use of a controlled vocabulary both imposes consistency of definition and ensures comparability of the objects described. Here we describe the controlled vocabulary (CV) and metadata creation tool built by the METAFOR project for use in the context of describing the climate models, simulations and experiments of the fifth Coupled Model Intercomparison Project (CMIP5). The CV and resulting tool chain introduced here is designed for extensibility and reuse and should find applicability in many more projects

The METAFOR project: preserving data through metadata standards for climate models and simulations

Climate modeling is a complex process, requiring accurate and complete metadata in order to identify, assess and use climate data stored in digital repositories. The preservation of such data is increasingly important given the development of ever-increasingly complex models to predict the effects of global climate change. The EU METAFOR project has developed a Common Information Model (CIM) to describe climate data and the models and modelling environments that produce this data. There is a wide degree of variability between different climate models and modelling groups. To accommodate this, the CIM has been designed to be highly generic and flexible, with extensibility built in. METAFOR describes the climate modelling process simply as "an activity undertaken using software on computers to produce data." This process has been described as separate UML packages (and, ultimately, XML schemas). This fairly generic structure canbe paired with more specific "controlled vocabularies" in order to restrict the range of valid CIM instances. The CIM will aid digital preservation of climate models as it will provide an accepted standard structure for the model metadata. Tools to write and manage CIM instances, and to allow convenient and powerful searches of CIM databases,. Are also under development. Community buy-in of the CIM has been achieved through a continual process of consultation with the climate modelling community, and through the METAFOR team’s development of a questionnaire that will be used to collect the metadata for the Intergovernmental Panel on Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs

Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100–200 to ∼25–50 km, and ocean resolution increases from (eddy-parametrized) to (eddy-present). For one model, ocean resolution also reaches ∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25∘, or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary

Prognostic evaluation in patients with advanced cancer in the last months of life:ESMO Clinical Practice Guideline

: • This ESMO Clinical Practice Guideline provides key recommendations for using prognostic estimates in advanced cancer. • The guideline covers recommendations for patients with cancer and an expected survival of months or less. • An algorithm for use of clinical predictions, prognostic factors and multivariable risk prediction models is presented. • The author group encompasses a multidisciplinary group of experts from different institutions in Europe, USA and Asia. • Recommendations are based on available scientific data and the authors’ collective expert opinion

The art of video MashUp: supporting creative users with an innovative and smart application

In this paper, we describe the development of a new and innovative tool of video mashup. This application is an easy to use tool of video editing integrated in a cross-media platform; it works taking the information from a repository of videos and puts into action a process of semi-automatic editing supporting users in the production of video mashup. Doing so it gives vent to their creative side without them being forced to learn how to use a complicated and unlikely new technology. The users will be further helped in building their own editing by the intelligent system working behind the tool: it combines semantic annotation (tags and comments by users), low level features (gradient of color, texture and movements) and high level features (general data distinguishing a movie: actors, director, year of production, etc.) to furnish a pre-elaborated editing users can modify in a very simple way