Integrated network models for predicting ecological thresholds::Microbial – carbon interactions in coastal marine systems

7siThis proof of concept study presents a Bayesian Network (BN) approach that integrates relevant biological and physical-chemical variables across spatial (two water layers) and temporal scales to identify the main contributing microbial mechanisms regulating POC accumulation in the northern Adriatic Sea. Three scenario tests (diatom, nanoflagellate and dinoflagellate blooms) using the BN predicted diatom blooms to produce high chlorophyll a at the water surface while nanoflagellate blooms were predicted to occur also at lower depths (>5 m) in the water column and to produce lower chlorophyll a concentrations. A sensitivity analysis using all available data identified the variables with the greatest influence on POC accumulation being the enzymes, which highlights the importance of microbial community interactions. However, the incorporation of experimental and field data changed the sensitivity of the model nodes ≥25% in the BN and therefore, is an important consideration when combining manipulated data sets in data limited conditions.noneopenMcDonald K.S.; Turk V.; Mozetic P.; Tinta T.; Malfatti F.; Hannah D.M.; Krause S.Mcdonald, K. S.; Turk, V.; Mozetic, P.; Tinta, T.; Malfatti, F.; Hannah, D. M.; Krause, S

Dispersal similarly shapes both population genetics and community patterns in the marine realm.

Dispersal plays a key role to connect populations and, if limited, is one of the main processes to maintain and generate regional biodiversity. According to neutral theories of molecular evolution and biodiversity, dispersal limitation of propagules and population stochasticity are integral to shaping both genetic and community structure. We conducted a parallel analysis of biological connectivity at genetic and community levels in marine groups with different dispersal traits. We compiled large data sets of population genetic structure (98 benthic macroinvertebrate and 35 planktonic species) and biogeographic data (2193 benthic macroinvertebrate and 734 planktonic species). We estimated dispersal distances from population genetic data (i.e., FST vs. geographic distance) and from β-diversity at the community level. Dispersal distances ranked the biological groups in the same order at both genetic and community levels, as predicted by organism dispersal ability and seascape connectivity: macrozoobenthic species without dispersing larvae, followed by macrozoobenthic species with dispersing larvae and plankton (phyto- and zooplankton). This ranking order is associated with constraints to the movement of macrozoobenthos within the seabed compared with the pelagic habitat. We showed that dispersal limitation similarly determines the connectivity degree of communities and populations, supporting the predictions of neutral theories in marine biodiversity patterns.RADIALES (IEO)Versión del edito

Plasma-wall interaction studies within the EUROfusion consortium: Progress on plasma-facing components development and qualification

This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission.The provision of a particle and power exhaust solution which is compatible with first-wall components and edge-plasma conditions is a key area of present-day fusion research and mandatory for a successful operation of ITER and DEMO. The work package plasma-facing components (WP PFC) within the European fusion programme complements with laboratory experiments, i.e. in linear plasma devices, electron and ion beam loading facilities, the studies performed in toroidally confined magnetic devices, such as JET, ASDEX Upgrade, WEST etc. The connection of both groups is done via common physics and engineering studies, including the qualification and specification of plasma-facing components, and by modelling codes that simulate edge-plasma conditions and the plasma-material interaction as well as the study of fundamental processes. WP PFC addresses these critical points in order to ensure reliable and efficient use of conventional, solid PFCs in ITER (Be and W) and DEMO (W and steel) with respect to heat-load capabilities (transient and steady-state heat and particle loads), lifetime estimates (erosion, material mixing and surface morphology), and safety aspects (fuel retention, fuel removal, material migration and dust formation) particularly for quasi-steady-state conditions. Alternative scenarios and concepts (liquid Sn or Li as PFCs) for DEMO are developed and tested in the event that the conventional solution turns out to not be functional. Here, we present an overview of the activities with an emphasis on a few key results: (i) the observed synergistic effects in particle and heat loading of ITER-grade W with the available set of exposition devices on material properties such as roughness, ductility and microstructure; (ii) the progress in understanding of fuel retention, diffusion and outgassing in different W-based materials, including the impact of damage and impurities like N; and (iii), the preferential sputtering of Fe in EUROFER steel providing an in situ W surface and a potential first-wall solution for DEMO.European Commission; Consortium for Ocean Leadership 633053; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART

Twitter sentiment around the Earnings Announcement events.

We investigate the relationship between social media, Twitter in particular, and stock market. We provide an in-depth analysis of the Twitter volume and sentiment about the 30 companies in the Dow Jones Industrial Average index, over a period of three years. We focus on Earnings Announcements and show that there is a considerable difference with respect to when the announcements are made: before the market opens or after the market closes. The two different timings of the Earnings Announcements were already investigated in the financial literature, but not yet in the social media. We analyze the differences in terms of the Twitter volumes, cumulative abnormal returns, trade returns, and earnings surprises. We report mixed results. On the one hand, we show that the Twitter sentiment (the collective opinion of the users) on the day of the announcement very well reflects the stock moves on the same day. We demonstrate this by applying the event study methodology, where the polarity of the Earnings Announcements is computed from the Twitter sentiment. Cumulative abnormal returns are high (2-4%) and statistically significant. On the other hand, we find only weak predictive power of the Twitter sentiment one day in advance. It turns out that it is important how to account for the announcements made after the market closes. These after-hours announcements draw high Twitter activity immediately, but volume and price changes in trading are observed only on the next day. On the day before the announcements, the Twitter volume is low, and the sentiment has very weak predictive power. A useful lesson learned is the importance of the proper alignment between the announcements, trading and Twitter data