Modeling Growing Economies in Equilibrium and Disequilibrium

The papers in this volume were presented and discussed at a meeting held at IIASA. The meeting's goals were to stimulate interaction and collaboration, and to encourage setting research priorities for the future. Indeed, it is in this latter area where the meeting appeared to yield some of its greatest benefits. It became clear from the deliberations that much needs to be done to better specify the microfoundations of general equilibrium models. More realistic specifications of "conflict resolution" in resource allocation, in both market and nonmarket economies, need to be developed. Equally importantly, much work is required to explore the role of economic disequilibrium in economic growth and development. "Equilibrium" and "disequilibrium" are positive, not normative concepts; neither view is right or wrong; neither will necessarily yield desired social outcomes at all stages of development, or across all regions. Rather, they yield quite different outcomes, which themselves should be subjects for scientific inquiry. The meeting pointed out the potential for expanding the conceptions of general equilibrium modeling to incorporate elements of disequilibrium analysis, so that this framework may not only be increasingly relevant to Eastern countries, but so that the possibilities of East-West interaction on critical aspects of resource allocation and economic growth can be enhanced

Clusters of Galaxies: New Results from the CLEF Hydrodynamics Simulation

Preliminary results are presented from the CLEF hydrodynamics simulation, a large (N=2(428)^3 particles within a 200 Mpc/h comoving box) simulation of the LCDM cosmology that includes both radiative cooling and a simple model for galactic feedback. Specifically, we focus on the X-ray properties of the simulated clusters at z=0 and demonstrate a reasonable level of agreement between simulated and observed cluster scaling relations.Comment: 7 pages, 4 figures, accepted for publication in Advances in Space Research (proceedings of the COSPAR 2004 Assembly, Paris

Patients' independence of a nurse for the administration of subcutaneous anti-TNF therapy: A phenomenographic study

Rheumatology nursing supports patients to manage their lives and live as independently as possible without pain, stiffness and functional restrictions. When conventional drugs fail to delay the development of the rheumatic disease, the patient may require biological treatment such as self-administered subcutaneous anti-tumour necrosis factor (TNF) therapy. It is therefore important that the patient perspective focuses on the life-changing situation caused by the administration of regular subcutaneous injections. The aim of this study was to describe variations in how patients with rheumatic diseases experience their independence of a nurse for administration of subcutaneous anti-TNF therapy. The study had a descriptive, qualitative design with a phenomenographic approach and was carried out by means of 20 interviews. Four ways of understanding the patients' experience of their subcutaneous anti-TNF therapy and independence of a nurse emerged: the struggling patient; the learning patient; the participating patient; the independent patient. Achieving independence of a nurse for subcutaneous anti-TNF injections can be understood by the patients in different ways. In their strive for independence, patients progress by learning about and participating in drug treatment, after which they experience that the injections make them independent

The need for carbon emissions-driven climate projections in CMIP7

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), both for idealized model experiments, and for climate projections of different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development of Earth System Model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth System Models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently represented upstream of ESMs in an idealized fashion during scenario development. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use, projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon-climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular sources and sinks of methane) and process-based representation of carbon removal options. Such experiments would allow resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts. Such efforts will provide information on the range of possible future climate states including Earth system processes and feedbacks which are increasingly well-represented in ESMs, thus forming a critical and complementary pillar underpinning proposed km-scale climate modeling activities and calls to better utilize novel machine learning approaches

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease