Suchergebnisse

Participatory budgeting (PB) is a novel way to understand the ways in which local projects are funded. Citizens engage in direct participation at every level of the project from designing, evaluating, modifying, and eventually disbursing funds. In short, PB is a fair and practical way for citizens to participate in direct democracy, rather than passive engagement through voting and waiting for elected officials to render a decision. In addition, due to its commitment to community-based philosophy, PB represents a radical move toward social justice.

Diese Arbeit verwendet den Begriff des "Familienleitbilds" als Zugang, um die Verknüpfung von Familienwandel und Familienpolitik besser zu erklären. Familienleitbilder umfassen differenzierte institutionelle Komplexe, nämlich Partnerschaft und Elternschaft. Ferner fungieren Familienleitbilder als ein Ansatzpunkt zur Gestaltung der Familienpolitik, und sie bilden den familienpolitischen Rahmen, also politische Frames. Deswegen implizieren die Varianten familienpolitischer Typologien Unterschiede in ihren jeweiligen Familienleitbildern. Um den Forschungsansatz dieser Arbeit zu konturieren, wird das Konzept "politisches Framing" als ein interpretativer und strategischer Prozess konzipiert. Diese Studie analysiert den Wandel der Familienleitbilder in (Ost-/West-) Deutschland und Südkorea und untersucht die Verankerung der Familienleitbilder mittels politischer Ideen durch das Framing der Familienpolitik.

Zum Erreichen einer minimalen Messunsicherheit ist es in der industriellen Computertomographie (CT) nötig, der Messaufgabe angemessene Einstellungen zu wählen. Aufgrund der vielfältigen Einstellmöglichkeiten müssen die richtigen Einstellungen langwierig durch systematische Variation ermittelt werden. Der Artikel schlägt unter Berücksichtigung der CT-spezifischen Eigenheiten ein Vorgehen vor, wie solche Unsicherheitsstudien mit einem möglichst geringen Aufwand durchgeführt werden können.
 
In industrial computer tomography (CT), it is necessary to select appropriate settings for the measurement task in order to achieve a minimal measurement uncertainty. Due to the various setting options, the correct settings have to be determined by systematic variation. This article proposes an approach to realize such uncertainty studies with as little effort as possible, taking the CT-specific characteristics into account.

<b><i>Background:</i></b> Knowledge about hereditary colorectal cancer (CRC) can aid cancer screening and prevention in high-risk patients. Genetic testing, once conducted primarily at academic centers, is now routinely performed in a variety of clinics. Nonacademic physicians may not be aware of hereditary CRC standards of care. <b><i>Methods:</i></b> From August to November 2012, a survey was administered to predominantly primary care physicians evaluating academic center affiliation, past training in genetics and knowledge regarding hereditary CRC. <b><i>Results:</i></b> One hundred forty physicians completed the survey. Knowledge of hereditary CRC was neither associated with academic affiliation nor with training during medical school or residency, but with continuing medical education (CME) training. Those with CME training were more likely to know that screening could be enhanced for patients with a hereditary cancer risk (OR = 4.49, 95% CI = 1.40-14.38) and that an individual with hereditary CRC would have different screening recommendations (OR = 7.49, 95% CI = 1.37-40.81). Residency training and CME training were associated with more frequent hereditary risk assessment. <b><i>Conclusion:</i></b> Genetics training may be associated with physicians' knowledge and assessment of hereditary CRC. Training at the CME level in particular may be integral to the delivery of genetic services in clinical practice.

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design. ; CRESCENDO project members (CDJ, PF, LB, VB, TI, SZ) acknowledge funding received from the Horizon 2020 European Union's Framework Programme for Research and Innovation under grant agreement no. 641816. CDJ was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). HDG was supported by a Marie Curie Career Integration Grant from the European Commission. JP is supported by the German Research Foundation's Emmy Noether Program (PO 1751/1-1).

To meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature's contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

To meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature's contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

Measurements of the inclusive J/ψ yield as a function of charged-particle pseudorapidity density dNch/dη in pp collisions at √s = 13 TeV with ALICE at the LHC are reported. The J/ψ meson yield is measured at midrapidity (|y|<0.9) in the dielectron channel, for events selected based on the charged-particle multiplicity at midrapidity (|η|<1) and at forward rapidity ( -3.7 < η < -1.7 and 2.8 < η < 5.1); both observables are normalized to their corresponding averages in minimum bias events. The increase of the normalized J/ψ yield with normalized dNch/dη is significantly stronger than linear and dependent on the transverse momentum. The data are compared to theoretical predictions, which describe the observed trends well, albeit not always quantitatively. ; A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC), Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; The Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; Danish Council for Independent Research Natural Sciences, the Villum Fonden and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l'Énergie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research Development and Innovation Office, Hungary; Department of Atomic Energy, Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology, Nagasaki Institute of Applied Science (IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA, UNAM), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Science and Higher Education, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics and Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Center "Kurchatov Institute", Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America.