A common nomenclature for assessing low-carbon transition pathways

We present ongoing work in the Horizon 2020 project openENTRANCE to develop a common nomenclature for integrated-assessment and energy system scenario results/data. This effort is based on the IAMC data template and the list of variables used in IAM comparison projects (CD-LINKS, ENGAGE, NAVIGATE) and scenario ensemble compilations (IAMC 1.5°C Scenario Data supporting the IPCC SR15). The nomenclature is developed in an interactive process on GitHub comprising technical-engineering, economic and social dimensions and seeks to bridge a user-focused, easy-to-read file format with a structure that can be used in scripted workflows. To facilitate an open discussion and for making it easy for non-experts to get an understanding of the code lists and related definitions, the nomenclature is implemented using the yaml-file format for listing variables and regions together with definitions and additional information. We also implemented an installable Python package providing several validation and utility functions of conforming to the nomenclature, so that definitions and mappings can be easily used in scripted scientific workflows for automated scenario processing. More information: https://github.com/openENTRANCE/nomenclatur

Massive Field-Theory Approach to Surface Critical Behavior in Three-Dimensional Systems

The massive field-theory approach for studying critical behavior in fixed space dimensions $d<4$ is extended to systems with surfaces.This enables one to study surface critical behavior directly in dimensions $d<4$ without having to resort to the $\epsilon$ expansion. The approach is elaborated for the representative case of the semi-infinite |\bbox{\phi}|^4 $n$-vector model with a boundary term {1/2} c_0\int_{\partial V}\bbox{\phi}^2 in the action. To make the theory uv finite in bulk dimensions $3\le d<4$, a renormalization of the surface enhancement $c_0$ is required in addition to the standard mass renormalization. Adequate normalization conditions for the renormalized theory are given. This theory involves two mass parameter: the usual bulk `mass' (inverse correlation length) $m$, and the renormalized surface enhancement $c$. Thus the surface renormalization factors depend on the renormalized coupling constant $u$ and the ratio $c/m$. The special and ordinary surface transitions correspond to the limits $m\to 0$ with $c/m\to 0$ and $c/m\to\infty$, respectively. It is shown that the surface-enhancement renormalization turns into an additive renormalization in the limit $c/m\to\infty$. The renormalization factors and exponent functions with $c/m=0$ and $c/m=\infty$ that are needed to determine the surface critical exponents of the special and ordinary transitions are calculated to two-loop order. The associated series expansions are analyzed by Pad\'e-Borel summation techniques. The resulting numerical estimates for the surface critical exponents are in good agreement with recent Monte Carlo simulations. This also holds for the surface crossover exponent $\Phi$.Comment: Revtex, 40 pages, 3 figures, and 8 pictograms (included in equations

Correlation functions near Modulated and Rough Surfaces

In a system with long-ranged correlations, the behavior of correlation functions is sensitive to the presence of a boundary. We show that surface deformations strongly modify this behavior as compared to a flat surface. The modified near surface correlations can be measured by scattering probes. To determine these correlations, we develop a perturbative calculation in the deformations in height from a flat surface. Detailed results are given for a regularly patterned surface, as well as for a self-affinely rough surface with roughness exponent $\zeta$. By combining this perturbative calculation in height deformations with the field-theoretic renormalization group approach, we also estimate the values of critical exponents governing the behavior of the decay of correlation functions near a self-affinely rough surface. We find that for the interacting theory, a large enough $\zeta$ can lead to novel surface critical behavior. We also provide scaling relations between roughness induced critical exponents for thermodynamic surface quantities.Comment: 31 pages, 2 figure

From the development of an open-source energy modelling tool to its application and the creation of communities of practice: The example of OSeMOSYS

In the last decades, energy modelling has supported energy planning by offering insights into the dynamics between energy access, resource use, and sustainable development. Especially in recent years, there has been an attempt to strengthen the science-policy interface and increase the involvement of society in energy planning processes. This has, both in the EU and worldwide, led to the development of open-source and transparent energy modelling practices. This paper describes the role of an open-source energy modelling tool in the energy planning process and highlights its importance for society. Specifically, it describes the existence and characteristics of the relationship between developing an open-source, freely available tool and its application, dissemination and use for policy making. Using the example of the Open Source energy Modelling System (OSeMOSYS), this work focuses on practices that were established within the community and that made the framework's development and application both relevant and scientifically grounded

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios [version 2; peer review: 3 approved]

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications

PIK3CA mutations are common in lobular carcinoma in situ, but are not a biomarker of progression

Sample and data collection were funded by Cancer Research UK. Analysis was funded by Breast Cancer Now, the Rosetrees Trust, Guys & St Thomas’ Charity (CanHelp) and the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation Trust and King’s College London

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

GENeSYS-MOD China: Technology, demand, and renewable data

This dataset contains renewable potentials, timeseries, technology data, and additional data tables and figures for the article "Decarbonizing China’s Energy System - Modeling the Transformation of the Electricity, Transportation, Heat, and Industrial sectors"

GENeSYS-MOD China: Technology, demand, and renewable data

This dataset contains renewable potentials, timeseries, technology data, and additional data tables and figures for the article "Decarbonizing China’s Energy System - Modeling the Transformation of the Electricity, Transportation, Heat, and Industrial sectors"

GENeSYS-MOD China: Technology, demand, and renewable data

This dataset contains renewable potentials, timeseries, technology data, and additional data tables and figures for the article "Decarbonizing China’s Energy System - Modeling the Transformation of the Electricity, Transportation, Heat, and Industrial sectors"