A multinomial quadrivariate D-vine copula mixed model for meta-analysis of diagnostic studies in the presence of non-evaluable subjects

Diagnostic test accuracy studies observe the result of a gold standard procedure that defines the presence or absence of a disease and the result of a diagnostic test. They typically report the number of true positives, false positives, true negatives and false negatives. However, diagnostic test outcomes can also be either non-evaluable positives or non-evaluable negatives. We propose a novel model for the meta-analysis of diagnostic studies in the presence of non-evaluable outcomes, which assumes independent multinomial distributions for the true and non-evaluable positives, and, the true and non-evaluable negatives, conditional on the latent sensitivity, specificity, probability of non-evaluable positives and probability of non-evaluable negatives in each study. For the random effects distribution of the latent proportions, we employ a drawable vine copula that can successively model the dependence in the joint tails. Our methodology is demonstrated with an extensive simulation study and applied to data from diagnostic accuracy studies of coronary computed tomography angiography for the detection of coronary artery disease. The comparison of our method with the existing approaches yields findings in the real data application that change the current conclusions

Coupled NASTRAN/boundary element formulation for acoustic scattering

A coupled finite element/boundary element capability is described for calculating the sound pressure field scattered by an arbitrary submerged 3-D elastic structure. Structural and fluid impedances are calculated with no approximation other than discretization. The surface fluid pressures and normal velocities are first calculated by coupling a NASTRAN finite element model of the structure with a discretized form of the Helmholtz surface integral equation for the exterior field. Far field pressures are then evaluated from the surface solution using the Helmholtz exterior integral equation. The overall approach is illustrated and validated using a known analytic solution for scattering from submerged spherical shells

Hybrid Architecture for Engineering Magnonic Quantum Networks

We show theoretically that a network of superconducting loops and magnetic particles can be used to implement magnonic crystals with tunable magnonic band structures. In our approach, the loops mediate interactions between the particles and allow magnetic excitations to tunnel over long distances. As a result, different arrangements of loops and particles allow one to engineer the band structure for the magnonic excitations. Furthermore, we show how magnons in such crystals can serve as a quantum bus for long-distance magnetic coupling of spin qubits. The qubits are coupled to the magnets in the network by their local magnetic-dipole interaction and provide an integrated way to measure the state of the magnonic quantum network.Comment: Manuscript: 4 pages, 3 figures. Supplemental Material: 9 pages, 4 figures. V2: Published version in PRA: 14 pages + 8 figures. Substantial rearrangement of the content of the previous versio

The exceptional Herbig Ae star HD101412: The first detection of resolved magnetically split lines and the presence of chemical spots in a Herbig star

We obtained high-resolution, high signal-to-noise UVES and a few lower quality HARPS spectra revealing the presence of resolved magnetically split lines. HD101412 is the first Herbig Ae star for which the rotational Doppler effect was found to be small in comparison to the magnetic splitting. The measured mean magnetic field modulus varies from 2.5 to 3.5kG, while the mean quadratic field was found to vary in the range of 3.5 to 4.8kG. To determine the period of variations, we used radial velocity, equivalent width, line width, and line asymmetry measurements of variable spectral lines of several elements, as well as magnetic field measurements. The most pronounced variability was detected for spectral lines of He I and the iron peak elements, whereas the spectral lines of CNO elements are only slightly variable. From spectral variations and magnetic field measurements we derived a potential rotation period P_rot=13.86d, which has to be proven in future studies with a larger number of observations. It is the first time that the presence of element spots is detected on the surface of a Herbig Ae/Be star. Our previous study of Herbig Ae stars revealed a trend towards stronger magnetic fields for younger Herbig Ae stars, confirmed by statistical tests. This is in contrast to a few other (non-statistical) studies claiming that magnetic Herbig Ae stars are progenitors of the magnetic Ap stars. New developments in MHD theory show that the measured magnetic field strengths are compatible with a current-driven instability of toroidal fields generated by differential rotation in the stellar interior. This explanation for magnetic intermediate-mass stars could be an alternative to a frozen-in fossil field.Comment: 7 pages, 6 figures, 1 table, to appear in Astronomische Nachrichte

Diffusion algebras

We define the notion of "diffusion algebras". They are quadratic Poincare-Birkhoff-Witt (PBW) algebras which are useful in order to find exact expressions for the probability distributions of stationary states appearing in one-dimensional stochastic processes with exclusion. One considers processes in which one has N species, the number of particles of each species being conserved. All diffusion algebras are obtained. The known examples already used in applications are special cases in our classification. To help the reader interested in physical problems, the cases N=3 and 4 are listed separately.Comment: 29 pages; minor misprints corrected, few references adde

The YEATS family member GAS41 interacts with the general transcription factor TFIIF

<p>Abstract</p> <p>Background</p> <p>In eukaryotes the transcription initiation by RNA polymerase II requires numerous general and regulatory factors including general transcription factors. The general transcription factor TFIIF controls the activity of the RNA polymerase II both at the initiation and elongation stages. The glioma amplified sequence 41 (GAS41) has been associated with TFIIF via its YEATS domain.</p> <p>Results</p> <p>Using GST pull-down assays, we demonstrated that GAS41 binds to both, the small subunit (RAP30) and the large subunit (RAP74) of TFIIF <it>in vitro</it>. The <it>in vivo </it>interaction of GAS41 and endogenous RAP30 and RAP74 was confirmed by co-immunoprecipitation. GAS41 binds to two non-overlapping regions of the C-terminus of RAP30. There is also an ionic component to the binding between GAS41 and RAP30. There was no evidence for a direct interaction between GAS41 and TBP or between GAS41 and RNA polymerase II.</p> <p>Conclusions</p> <p>Our results demonstrate binding between endogenous GAS41 and the endogenous TFIIF subunits (RAP30 and RAP74). Since we did not find evidence for a binding of GAS41 to TBP or RNA polymerase II, GAS41 seems to preferentially bind to TFIIF. GAS41 that does not contain a DNA-binding domain appears to be a co-factor of TFIIF.</p

Progressively excluding mammals of different body size affects community and trait structure of ground beetles

Mammalian grazing induces changes in vegetation properties in grasslands, which can affect a wide variety of other animals including many arthropods. However, the impacts may depend on the type and body size of these mammals. Furthermore, how mammals influence functional trait syndromes of arthropod communities is not well known. We progressively excluded large (e.g. red deer, chamois), medium (e.g. alpine marmot, mountain hare), and small (e.g. mice) mammals using size-selective fences in two vegetation types (short- and tall-grass vegetation) of subalpine grasslands. We then assessed how these exclusions affected the community composition and functional traits of ground beetles (Coleoptera, Carabidae), and which vegetation characteristic mediated the observed effects. Total carabid biomass, the activity densities of carabids with specific traits (i.e. small eyes, short wings), the richness of small-eyed species and the richness of herbivorous species were significantly higher when certain mammals were excluded compared to when all mammals had access, regardless of vegetation type. Excluding large and medium mammals increased the activity density of herbivorous carabid species, but only in short-grass vegetation. Similarly, excluding large mammals (ungulates) altered carabid species composition in the short-, but not in the tall-grass vegetation. All these responses were related to aboveground plant biomass, but not to plant Shannon diversity or vegetation structural heterogeneity. Our results indicate that changes in aboveground plant biomass are key drivers of mammalian grazers' influence on carabids, suggesting that bottom-up forces are important in subalpine grassland systems. The exclusion of ungulates provoked the strongest carabid response. Our results, however, also highlight the ecological significance of smaller herbivorous mammals. Our study furthermore shows that mammalian grazing not only altered carabid community composition, but also caused community-wide functional trait shifts, which could potentially have a wider impact on species interactions and ecosystem functioning

Crop Knowledge Discovery Based on Agricultural Big Data Integration

Nowadays, the agricultural data can be generated through various sources, such as: Internet of Thing (IoT), sensors, satellites, weather stations, robots, farm equipment, agricultural laboratories, farmers, government agencies and agribusinesses. The analysis of this big data enables farmers, companies and agronomists to extract high business and scientific knowledge, improving their operational processes and product quality. However, before analysing this data, different data sources need to be normalised, homogenised and integrated into a unified data representation. In this paper, we propose an agricultural data integration method using a constellation schema which is designed to be flexible enough to incorporate other datasets and big data models. We also apply some methods to extract knowledge with the view to improve crop yield; these include finding suitable quantities of soil properties, herbicides and insecticides for both increasing crop yield and protecting the environment.Comment: 5 page