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Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.MOHC.HadGEM3-GC31-MM.piControl' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

This is a complementary dataset associated with the following publication: Berrang-Ford, Lea, et al. "Systematic Mapping of Global Research on Climate and Health Using Machine Learning." The Lancet Planetary Health. Meta-data are included.

In obese subjects (BMI 33-38kg/m2) completing 12 months of treatment with the CB1 antagonist rimonabant (SR141716) there was an average weight loss from baseline of approximately 8.5 kg. These studies also showed the weight loss was accompanied by a decrease in plasma triglyceride (TG), an increase in HDL cholesterol and an improvement in insulin sensitivity measured by HOMA-IR. When adjusted for weight loss 50% of the improvements in TG, HDL cholesterol, and insulin sensitivity was not attributable to weight loss. This suggests that rimonabant has direct effects on fat metabolism. This study will investigate the direct effects of rimonabant (ie independent of weight loss) in a 2 group randomised study. One group will receive rimonabant for 12 weeks and the other group will have a dietary intervention to match the weight loss in the rimonabant group. Measurements of energy expenditure (using indirect calorimetry and Actiheart monitors),fatty acid and triglyceride metabolism (using stable isotope techniques) and body fat distribution (by magnetic resonance imaging) will be made before and after the intervention. To determine the possible mechanisms of the changes in metabolism, gene expression of key regulators of fatty acid metabolism in adipose and muscle tissue and circulating levels of adipokines will be measured. This study will determine in obese subjects the direct effects of the weight loss drug rimonabant (ie independent of weight loss) on energy expenditure, fat metabolism and and body fat distribution. We hypothesise that rimonabant will increase energy expenditure. The fuel for the increased energy expenditure will come from fat. As a result of burning more fat there will be a decrease in fat in blood and an improvement in the body's response to insulin.

In order to achieve paramount economy, hybrid renewable energy sources are gaining importance, as renewable sources are costless. Over the past few years wind energy incorporation drew more consideration in the electricity market, as wind power took an affirmative role in energy saving as well as sinking emission pollutants. Recently developed Grey wolf optimizer (GWO) algorithm has conspicuous behavior for verdicting global optima, without getting ensnared in premature convergence. In the proposed research the exploitation phase of the grey wolf optimizer has been further improved using random exploratory search algorithm, which uses perturbed solutions vectors along with previously generated solution vectors. The paper presents a hybrid version of Grey Wolf Optimizer algorithm combined with random exploratory search algorithm (hGWO-RES) for the solution of combinatorial scheduling and dispatch problem of electric power systems. To validate the feasibility of the algorithm, the proposed algorithm has been tested on 23 benchmark problems. To verify the feasibility and efficacy of operation of proposed algorithm on generation scheduling and dispatch of electric power systems, small and medium scale power systems consisting of 7-, 10-, 19-, 20- and 40-generating units systems taken into consideration. Commitment and scheduling pattern has been evaluated with and without wind integration and it has been experimentally founded that proposed hybrid algorithm provides superior solution as compared to other recently reported meta-heuristics search algorithms.

This study assessed the hand hygiene performance in French nursing homes using the consumption of alcohol-based hand rubs (AHRs) as a surrogate. Nursing homes from the 17 French regions were contacted to collect their AHR consumption and occupancy in 2018 and 2019. A total of 1290 nursing homes from 15 French regions participated in the survey. The estimated median number of hand hygiene actions per resident-day was 1.48 (interquartile range: 1.04-2.03) in 2018 and 1.60 (1.10-2.26) in 2019. A significantly higher AHR consumption was observed in public nursing homes with an infection control team or link nurse.

With the extensive growth in technology, healthcare sector has benefitted a lot recently. Looking into the academic research and validation in the area of medical image processing and visualization, many platforms and the open-source resources are available. Insight toolkit (ITK) and visualization toolkit (VTK) are extensively used for medical image processing and 3D visualization respectively. Resources used to develop an application using ITK-VTK and same resources be used to deliver it to the users such as, clinicians, doctors etc. This can be achieved by using respective hardware and the infrastructure. In the proposed article, the infrastructure and resource used to build and deploy the application and remote access given to the users are elucidated.

The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

Image dataset used for a colour analysis of coral branches throughout a long-term marine heatwave emulation experiment using machine learning. Article: "Within population variability in coral heat tolerance indicates climate adaptation potential" by Humanes and Lachs et al. Code to analyse the dataset is found at 10.5281/zenodo.6256164. LL received funding from Natural Environment Research Council (NERC) ONE Planet Doctoral Training Partnership (NE/S007512/1).