Multi-Spacecraft Measurement of Turbulence within a Magnetic Reconnection Jet

The relationship between magnetic reconnection and plasma turbulence is investigated using multipoint in-situ measurements from the Cluster spacecraft within a high-speed reconnection jet in the terrestrial magnetotail. We show explicitly that work done by electromagnetic fields on the particles, $\mathbf{J}\cdot\mathbf{E}$, has a non-Gaussian distribution and is concentrated in regions of high electric current density. Hence, magnetic energy is converted to kinetic energy in an intermittent manner. Furthermore, we find the higher-order statistics of magnetic field fluctuations generated by reconnection are characterized by multifractal scaling on magnetofluid scales and non-Gaussian global scale invariance on kinetic scales. These observations suggest $\mathbf{J}\cdot\mathbf{E}$ within the reconnection jet has an analogue in fluid-like turbulence theory in that it proceeds via coherent structures generated by an intermittent cascade. This supports the hypothesis that turbulent dissipation is highly nonuniform, and thus these results could have far reaching implications for space and astrophysical plasmas.Comment: 5 pages, 3 figures, submitted to Physical Review Letter

Solar Wind Turbulence and the Role of Ion Instabilities

International audienc

Scale-dependent Polarization of Solar Wind Velocity Fluctuations at the Inertial and Kinetic Scales

We study the polarization properties of the velocity fluctuations in solar wind turbulence using high-resolution data from the Spektr-R spacecraft. The ratio of perpendicular to parallel velocity fluctuations in the inertial range is smaller than the equivalent ratio for magnetic fluctuations, but gradually increases throughout this range. In the kinetic range, there is a large decrease in the ratio, similar to the magnetic fluctuations. We compare the measurements to numerical solutions for a combination of kinetic Alfvén waves and slow waves, finding that both the slow increase and sharp decrease in the ratio are consistent with a majority population of Alfvén waves and minority population of slow waves in critical balance. Furthermore, the beta-dependence of this scale-dependent ratio can be successfully captured in the model when incorporating a beta-dependent Alfvén to slow wave ratio similar to that observed in the solar wind

Crystal Structures of Malonyl-Coenzyme A Decarboxylase Provide Insights into Its Catalytic Mechanism and Disease-Causing Mutations

Malonyl-coenzyme A decarboxylase (MCD) is found from bacteria to humans, has important roles in regulating fatty acid metabolism and food intake, and is an attractive target for drug discovery. We report here four crystal structures of MCD from human, Rhodopseudomonas palustris, Agrobacterium vitis, and Cupriavidus metallidurans at up to 2.3 Å resolution. The MCD monomer contains an N-terminal helical domain involved in oligomerization and a C-terminal catalytic domain. The four structures exhibit substantial differences in the organization of the helical domains and, consequently, the oligomeric states and intersubunit interfaces. Unexpectedly, the MCD catalytic domain is structurally homologous to those of the GCN5-related N-acetyltransferase superfamily, especially the curacin A polyketide synthase catalytic module, with a conserved His-Ser/Thr dyad important for catalysis. Our structures, along with mutagenesis and kinetic studies, provide a molecular basis for understanding pathogenic mutations and catalysis, as well as a template for structure-based drug design

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Spatio-temporal Consistency for Head Detection in High-Density Scenes

International audienceIn this paper we address the problem of detecting reliably a subset of pedestrian targets (heads) in a high-density crowd exhibiting extreme clutter and homogeneity, with the purpose of obtaining tracking initializations. We investigate the solution provided by discriminative learning where we require that the detections in the image space be localized over most of the target area and temporally stable. The results of our tests show that discriminative learning strategies provide valuable cues about the target localization which may be combined with other complementary strategies in order to bootstrap tracking algorithms in these challenging environments