Search

In a plasma accelerator, a laser or particle beam excites a plasma wave that can sustain orders of magnitude higher electric fields than the RF-cavities of conventional accelerators. These compact devices have the potential to drive next-generation free-electron lasers (FEL) of reduced size and cost. However, the highly sensitive FEL mechanism imposes strict requirements on the electron beam properties. So far, the quality of plasma accelerated beams cannot compete with that of conventional accelerators. Successfully driving the self-amplifying process demands the development of methods with increased control of the beam’s phase space - in combination with novel FEL designs that leverage the unique features of the plasma accelerated beams. Demonstrating a plasma-driven FEL therefore heavily relies on theoretical studies and requires numerical models that correctly represent the physics involved under the restriction of limited computational resources. Here, we present our recent work towards a plasma-driven FEL, based on the particle-in-cell (PIC) code FBPIC, and the non-averaging 3D FEL code PUFFIN.

Many abstracts of diagnostic accuracy studies are currently insufficiently informative. We extended the STARD (Standards for Reporting Diagnostic Accuracy) statement by developing a list of essential items that authors should consider when reporting diagnostic accuracy studies in journal or conference abstracts. After a literature review of published guidance for reporting biomedical studies, we identified 39 items potentially relevant to report in an abstract. We then selected essential items through a two round web based survey among the 85 members of the STARD Group, followed by discussions within an executive committee. Seventy three STARD Group members responded (86%), with 100% completion rate. STARD for Abstracts is a list of 11 quintessential items, to be reported in every abstract of a diagnostic accuracy study. We provide examples of complete reporting, and developed template text for writing informative abstracts.

The role of the ocean has been pivotal in modulating rising atmospheric CO2 levels since the industrial revolution, sequestering nearly half of all fossil-fuel derived CO2 emissions. Net oceanic uptake of CO2 has roughly doubled between the 1960s (~1 Pg C yr−1) and 2000s (~2 Pg C yr−1), with expectations that it will continue to absorb even more CO2 with rising future atmospheric CO2 levels. However, recent CO2 observational analyses along with numerous model predictions suggest the rate of oceanic CO2 uptake is already slowing, largely as a result of a natural decadal-scale outgassing signal. This recent CO2 outgassing signal represents a significant shift in our understanding of the oceans role in modulating atmospheric CO2. Current tracer-based estimates for the ocean storage of anthropogenic CO2 assume the ocean circulation and biology is in steady state, thereby missing the new and potentially important "non-steady state" CO2 outgassing signal. By combining data-based techniques that assume the ocean is in a steady state, with techniques that constrain the net oceanic CO2 uptake signal, we show how to extract the non-steady state CO2 signal from observations. Over the entire industrial era, the non-steady state CO2 outgassing signal (~13 ± 10 Pg C) is estimated to represent about 9% of the total net CO2 inventory change (~142 Pg C). However, between 1989 and 2007, the non-steady state CO2 outgassing signal (~6.3 Pg C) has likely increased to be ~18% of net oceanic CO2 storage over that period (~36 Pg C). The present uncertainty of our data-based techniques for oceanic CO2 uptake limit our capacity to quantify the non-steady state CO2 signal, however with more data and better certainty estimates across a range of diverse methods, this important and growing CO2 signal could be better constrained in the future.

Plasma-based accelerators are promising candidates to drive next-generation compact freeelectronlasers (FEL) with unique X-ray properties. The correct modelling of the physics in thelaser-plasma accelerator and of the FEL amplification from plasma-generated electron bunchesthereby forms the basis for any application driven by these beams. Both problems are, however,extremely challenging. They heavily rely on computer simulations and, in fact, act as sciencedrivers for the development of the latest generation of high-performance, highly parallel andefficient simulation codes. Here, we present our work towards a plasma-driven FEL, based onthe particle-in-cell (PIC) codes VSIM and WARP, and the non-averaging 3D FEL code PUFFIN.

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.