Temporal variability of diazotroph community composition in the upwelling region off NW Iberia.

Knowledge of the ecology of N2-fixing (diazotrophic) plankton is mainly limited to oligotrophic (sub)tropical oceans. However, diazotrophs are widely distributed and active throughout the global ocean. Likewise, relatively little is known about the temporal dynamics of diazotrophs in productive areas. Between February 2014 and December 2015, we carried out 9 one-day samplings in the temperate northwestern Iberian upwelling system to investigate the temporal and vertical variability of the diazotrophic community and its relationship with hydrodynamic forcing. In downwelling conditions, characterized by deeper mixed layers and a homogeneous water column, non-cyanobacterial diazotrophs belonging mainly to nifH clusters 1G (Gammaproteobacteria) and 3 (putative anaerobes) dominated the diazotrophic community. In upwelling and relaxation conditions, affected by enhanced vertical stratification and hydrographic variability, the community was more heterogeneous vertically but less diverse, with prevalence of UCYN-A (unicellular cyanobacteria, subcluster 1B) and non-cyanobacterial diazotrophs from clusters 1G and 3. Oligotyping analysis of UCYN-A phylotype showed that UCYN-A2 sublineage was the most abundant (74%), followed by UCYN-A1 (23%) and UCYN-A4 (2%). UCYN-A1 oligotypes exhibited relatively low frequencies during the three hydrographic conditions, whereas UCYN-A2 showed higher abundances during upwelling and relaxation. Our findings show the presence of a diverse and temporally variable diazotrophic community driven by hydrodynamic forcing in an upwelling system

Cost-efficient fenced reserves for conservation: single large or two small?

Fences that exclude alien invasive species are used to reduce predation pressure on reintroduced threatened wildlife. Planning these continuously managed systems of reserves raises an important extension of the Single Large or Several Small (SLOSS) reserve planning framework: the added complexity of ongoing management. We investigate the long-term cost-efficiency of a single large or two small predator exclusion fences in the arid Australian context of reintroducing bilbies Macrotis lagotis, and we highlight the broader significance of our results with sensitivity analysis. A single fence more frequently results in a much larger net cost than two smaller fences. We find that the cost-efficiency of two fences is robust to strong demographic and environmental uncertainty, which can help managers to mitigate the risk of incurring high costs over the entire life of the project

Galactic halo cusp-core: tidal compression in mergers

We explain in simple terms how the buildup of dark haloes by merging compact satellites, as in the CDM cosmology, inevitably leads to an inner cusp of density profile $\rho \propto r^{-\alpha}$ with \alpha \gsim 1, as seen in cosmological N-body simulations. A flatter halo core with $\alpha <1$ exerts on the satellites tidal compression in all directions, which prevents deposit of stripped satellite material in the core region. This makes the satellite orbits decay from the radius where $\alpha \sim 1$ to the halo centre with no local tidal mass transfer and thus causes a rapid steepening of the inner profile to $\alpha >1$. These tidal effects, the resultant steepening of the profile to a cusp, and the stability of this cusp to tandem mergers with compact satellites, are demonstrated using N-body simulations. The transition at $\alpha \sim 1$ is then addressed using toy models in the limiting cases of impulse and adiabatic approximations and using tidal radii for satellites on radial and circular orbits. In an associated paper we address the subsequent slow convergence from either side to an asymptotic stable cusp with \alpha \gsim 1. Our analysis thus implies that an inner cusp is enforced when small haloes are typically more compact than larger haloes, as in the CDM scenario, such that enough satellite material makes it intact into the inner halo and is deposited there. We conclude that a necessary condition for maintaining a flat core, as indicated by observations, is that the inner regions of the CDM satellite haloes be puffed up by about 50% such that when they merge into a bigger halo they would be disrupted outside the halo core. This puffing up could be due to baryonic feedback processes in small haloes, which may be stimulated by the tidal compression in the halo cores.Comment: 19 pages, Latex, mn2e.cls, some revisions, MNRAS in pres

Emergent dynamic chirality in a thermally driven artificial spin ratchet

Modern nanofabrication techniques have opened the possibility to create novel functional materials, whose properties transcend those of their constituent elements. In particular, tuning the magnetostatic interactions in geometrically frustrated arrangements of nanoelements called artificial spin ice1, 2 can lead to specific collective behaviour3, including emergent magnetic monopoles4, 5, charge screening6, 7 and transport8, 9, as well as magnonic response10, 11, 12. Here, we demonstrate a spin-ice-based active material in which energy is converted into unidirectional dynamics. Using X-ray photoemission electron microscopy we show that the collective rotation of the average magnetization proceeds in a unique sense during thermal relaxation. Our simulations demonstrate that this emergent chiral behaviour is driven by the topology of the magnetostatic field at the edges of the nanomagnet array, resulting in an asymmetric energy landscape. In addition, a bias field can be used to modify the sense of rotation of the average magnetization. This opens the possibility of implementing a magnetic Brownian ratchet13, 14, which may find applications in novel nanoscale devices, such as magnetic nanomotors, actuators, sensors or memory cells

Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling

Performance modeling for large-scale data analytics workloads can improve the efficiency of cluster resource allocations and job scheduling. However, the performance of these workloads is influenced by numerous factors, such as job inputs and the assigned cluster resources. As a result, performance models require significant amounts of training data. This data can be obtained by exchanging runtime metrics between collaborating organizations. Yet, not all organizations may be inclined to publicly disclose such metadata. We present a privacy-preserving approach for sharing runtime metrics based on differential privacy and data synthesis. Our evaluation on performance data from 736 Spark job executions indicates that fully anonymized training data largely maintains performance prediction accuracy, particularly when there is minimal original data available. With 30 or fewer available original data samples, the use of synthetic training data resulted only in a one percent reduction in performance model accuracy on average.Comment: 4 pages, 4 figures, presented at the WOSP-C workshop at ICPE 202

Political Expression and Action on Social Media:Exploring the Relationship Between Lower- and Higher-Threshold Political Activities Among Twitter Users in Italy

Scholars and commentators have debated whether lower‐threshold forms of political engagement on social media should be treated as being conducive to higher‐threshold modes of political participation or a diversion from them. Drawing on an original survey of a representative sample of Italians who discussed the 2013 election on Twitter, we demonstrate that the more respondents acquire political information via social media and express themselves politically on these platforms, the more they are likely to contact politicians via e‐mail, campaign for parties and candidates using social media, and attend offline events to which they were invited online. These results suggest that lower‐threshold forms of political engagement on social media do not distract from higher‐threshold activities, but are strongly associated with them

New hyperekplexia mutations provide insight into glycine receptor assembly, trafficking, and activation mechanisms

Background: Hyperekplexia mutations have provided much information about glycine receptor structure and function. Results: Weidentified and characterized nine new mutations. Dominant mutations resulted in spontaneous activation, whereas recessive mutations precluded surface expression. Conclusion: These data provide insight into glycine receptor activation mechanisms and surface expression determinants. Significance: The results enhance our understanding of hyperekplexia pathology and glycine receptor structure-function. © 2013 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A

The Value of Resolving Uncertainty in Social-Ecological Systems

Conservation is increasingly framed or analyzed as a coupled social-ecological problem. However, considering the broader links between social and ecological systems reveals additional and increasing dimensions of uncertainty for conservation management. Reducing uncertainty is expected to lead to improved management decisions, however collecting more data or lengthening project time frames to reduce uncertainty is not without cost. In this study we analyze where conservation managers should invest resources to improve management outcomes by decreasing uncertainty in a coupled social-ecological system. We consider five system components: social and ecological nodes and links, and social-ecological links. We find that the expected value of improving information for any one component is always highest for the component which is most directly acted upon by managers. Our results can help guide conservation investment to reduce uncertainty where improved knowledge of a social-ecological system will provide the greatest improvement in management outcomes

Influence of adversarial training on super-resolution turbulence reconstruction

Supervised super-resolution deep convolutional neural networks (CNNs) have gained significant attention for their potential in reconstructing velocity and scalar fields in turbulent flows. Despite their popularity, CNNs currently lack the ability to accurately produce high-frequency and small-scale features, and tests of their generalizability to out-of-sample flows are not widespread. Generative adversarial networks (GANs), which consist of two distinct neural networks (NNs), a generator and discriminator, are a promising alternative, allowing for both semi-supervised and unsupervised training. The difference in the flow fields produced by these two NN architectures has not been thoroughly investigated, and a comprehensive understanding of the discriminator's role has yet to be developed. This study assesses the effectiveness of the unsupervised adversarial training in GANs for turbulence reconstruction in forced homogeneous isotropic turbulence. GAN-based architectures are found to outperform supervised CNNs for turbulent flow reconstruction for in-sample cases. The reconstruction accuracy of both architectures diminishes for out-of-sample cases, though the GAN's discriminator network significantly improves the generator's out-of-sample robustness using either an additional unsupervised training step with large eddy simulation input fields and a dynamic selection of the most suitable upsampling factor. These enhance the generator's ability to reconstruct small-scale gradients, turbulence intermittency, and velocity-gradient probability density functions. The extrapolation capability of the GAN-based model is demonstrated for out-of-sample flows at higher Reynolds numbers. Based on these findings, incorporating discriminator-based training is recommended to enhance the reconstruction capability of super-resolution CNNs