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Effective access control techniques are in demand, as electronically assisted healthcare services require the patient’s sensitive health records. In emergency situations, where the patient’s well-being is jeopardized, different healthcare actors associated with emergency cases should be granted permission to access Electronic Health Records (EHRs) of patients. The research objective of our study is to develop machine learning techniques based on patients’ time sequential health metrics and integrate them with an Attribute Based Access Control (ABAC) mechanism. We propose an ABAC mechanism that can yield access to sensitive EHRs systems by applying prognostic context handlers where contextual information, is used to identify emergency conditions and permit access to medical records. Specifically, we use patients’ recent health history to predict the health metrics for the next two hours by leveraging Long Short Term Memory (LSTM) Neural Networks (NNs). These predicted health metrics values are evaluated by our personalized fuzzy context handlers, to predict the criticality of patients’ status. The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism with personalized context handlers proved to be a robust tool to enhance the performance of the access control mechanism to modern EHRs System.

This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future). More specifically, it contains: - in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME - in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace - in the `UN` folder, the demographic projections from UN - `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases - `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future '- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6 This data in intended to be downloaded for use together with the package downloadable here. The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).

Miniaturization of electrochemical detection ofPseudomonas aeruginosaquorum sensing molecules at a liquid/liquid interface through facilitated proton transfer reactions.

Abstract An increasing number of studies show that efficiency improvements alone will not be sufficient to attain the substantial emission reductions needed to mitigate global warming to a target of 2 °C. Consumption side changes are likely to be needed to achieve sufficient emission reductions. The United Nations emphasize the importance of developed countries taking the lead in lowering emissions to achieve the sustainable development goals. This paper assess to what extent Norwegian households can lower their carbon footprint consistent with territorial emission reductions towards the 2 °C target of global warming through implementing a set of behavioral actions. We evaluate the efficacy of the set of actions both initially and after considering rebound effects. A multiregional environmentally extended input-output database is linked with the Norwegian consumer expenditure survey to analyze both average and marginal expenditure per unit of increased income. Further, linear programming is applied to examine the changes needed by households to reach different emission reduction targets. We find that households implementing the full set of actions without re-spending can obtain a 58% decrease in their carbon footprint. When accounting for the effect of re-spending, this reduction drops to 24–35%, which is not within the requirements of the 2 °C target. The optimization analysis suggests households can achieve reductions up to 45% by restricting re-spending to specific goods and services. This indicates that curbing the rebound effect is key to achieving real reductions in household carbon footprints. We show that changing consumption patterns can significantly contribute to lowering anthropogenic greenhouse gas emissions without compromising the level of economic activity.

Highlights •Biomass resource constraints impact the effectiveness of bioeconomy policies. •Bioeconomy policies may have an important impact on the sector structure in the long run, but the sector growth remains ultimately constrained by the availability of inputs. •Solutions to reduce the biomass constraint have to be included in innovation policy for the biobased economy.

This study will review the environmental implications of dynamic policy objectives and instruments outlined in the European Union 7th Framework Programme (EU-FP7) Project DYNAmic policy MIXes for absolute decoupling of EU resource use from economic growth (DYNAMIX) to address reductions in food consumption, food waste and a change in waste handling systems. The environmental implications of reductions in protein intake, food waste reductions, food waste management and donations are addressed using a life cycle approach to find the greenhouse gas (GHG) emissions, land use and water consumption. Data are provided from the Statistics Division of the Food and Agriculture Organization (FAOSTAT) food balance sheets for the European Union (EU) with a base year of 2010 and life cycle inventory (LCI) data from a meta-study of available GHG, land use and water consumption data for major food products. The implications are reviewed using a number of scenarios for the years 2030 and 2050 assuming policy instruments are fully effective. Results indicate that reductions in animal-based protein consumption significantly reduce environmental impacts, followed thereafter by reductions in food waste (assuming this also reduces food consumption). Despite the positive implications the policy mixes may have for targets for decoupling, they are not enough to meet GHG emissions targets for the EU outlined in the DYNAMIX project, although land and water use have no significant change compared to 2010 levels.