Geography, institutions and development: a review ofthe long-run impacts of climate change

The links between climate change, economic growth and economic development have gained increasing attention over recent years in both the academic and policy literature. However, most of the existing literature has tended to focus on direct, short run effects of climate change on the economy, for example due to extreme weather events and changes in agricultural growing conditions. In this paper we review potential effects of climate change on the prospects for long-run economic development. These effects might operate directly, via the role of geography (including climate) as a fundamental determinant of relative prosperity, or indirectly by modifying the environmental context in which political and economic institutions evolve. We consider potential mechanisms from climate change to long-run economic development that have been relatively neglected to date, including, for instance, effects on the distribution of income and political power. We conclude with some suggestions for areas of future research

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

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

Acoustic and photographic studies of injected bubbles

When gas bubbles are injected into a liquid, their behaviour can be markedly different from the single, isolated, spherical oscillating bubble, since shape oscillations can distort the bubble. In addition, the process of bubble formation can lead to multiple excitations of the bubble oscillations, for example when the newly formed bubble contacts and absorbs the bubble being formed at the nozzle. This gives rise to corresponding features in the acoustic output. In this study the photographic and acoustic data from such events are correlated. This undergraduate-level experiment provides useful data in a field of current interes

Economic consideration for reducing hospital presentations among patients with decompensated cirrhosis: not all presentations avoided can be considered equal

Individuals with decompensated cirrhosis and ascites requiring paracentesis utilize exceptionally high levels of hospital resources. Consequently, potential modifications to existing models of healthcare to assist patients in the management of their liver disease and reduce the need for hospital encounters have potential to improve patients’ health and reduce demand on acute hospital services. However, there is a paucity of data examining how much healthcare resources could be re-directed to interventions that prevent hospitalizations without net annual budgetary disadvantage (from the hospital’s perspective). The purpose of this study was to probabilistically examine how much healthcare resourcing could be saved per hospital presentation avoided among this clinical population