Sampling constrained probability distributions using Spherical Augmentation

Statistical models with constrained probability distributions are abundant in machine learning. Some examples include regression models with norm constraints (e.g., Lasso), probit, many copula models, and latent Dirichlet allocation (LDA). Bayesian inference involving probability distributions confined to constrained domains could be quite challenging for commonly used sampling algorithms. In this paper, we propose a novel augmentation technique that handles a wide range of constraints by mapping the constrained domain to a sphere in the augmented space. By moving freely on the surface of this sphere, sampling algorithms handle constraints implicitly and generate proposals that remain within boundaries when mapped back to the original space. Our proposed method, called {Spherical Augmentation}, provides a mathematically natural and computationally efficient framework for sampling from constrained probability distributions. We show the advantages of our method over state-of-the-art sampling algorithms, such as exact Hamiltonian Monte Carlo, using several examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian bridge regression, reconstruction of quantized stationary Gaussian process, and LDA for topic modeling.Comment: 41 pages, 13 figure

Testing the Nambu-Goldstone Hypothesis for Quarks and Leptons at the LHC

The hierarchy of the Yukawa couplings is an outstanding problem of the standard model. We present a class of models in which the first and second generation fermions are SUSY partners of pseudo-Nambu-Goldstone bosons that parameterize a non-compact Kahler manifold, explaining the small values of these fermion masses relative to those of the third generation. We also provide an example of such a model. We find that various regions of the parameter space in this scenario can give the correct dark matter abundance, and that nearly all of these regions evade other phenomenological constraints. We show that for gluino mass ~700 GeV, model points from these regions can be easily distinguished from other mSUGRA points at the LHC with only 7 fb^(-1) of integrated luminosity at 14 TeV. The most striking signatures are a dearth of b- and tau-jets, a great number of multi-lepton events, and either an "inverted" slepton mass hierarchy, narrowed slepton mass hierarchy, or characteristic small-mu spectrum.Comment: Corresponds to published versio

Monocytes regulate the mechanism of T-cell death by inducing Fas-mediated apoptosis during bacterial infection.

Monocytes and T-cells are critical to the host response to acute bacterial infection but monocytes are primarily viewed as amplifying the inflammatory signal. The mechanisms of cell death regulating T-cell numbers at sites of infection are incompletely characterized. T-cell death in cultures of peripheral blood mononuclear cells (PBMC) showed 'classic' features of apoptosis following exposure to pneumococci. Conversely, purified CD3(+) T-cells cultured with pneumococci demonstrated necrosis with membrane permeabilization. The death of purified CD3(+) T-cells was not inhibited by necrostatin, but required the bacterial toxin pneumolysin. Apoptosis of CD3(+) T-cells in PBMC cultures required 'classical' CD14(+) monocytes, which enhanced T-cell activation. CD3(+) T-cell death was enhanced in HIV-seropositive individuals. Monocyte-mediated CD3(+) T-cell apoptotic death was Fas-dependent both in vitro and in vivo. In the early stages of the T-cell dependent host response to pneumococci reduced Fas ligand mediated T-cell apoptosis was associated with decreased bacterial clearance in the lung and increased bacteremia. In summary monocytes converted pathogen-associated necrosis into Fas-dependent apoptosis and regulated levels of activated T-cells at sites of acute bacterial infection. These changes were associated with enhanced bacterial clearance in the lung and reduced levels of invasive pneumococcal disease

Structure of the hDmc1-ssDNA filament reveals the principles of its architecture

In eukaryotes, meiotic recombination is a major source of genetic diversity, but its defects in humans lead to abnormalities such as Down's, Klinefelter's and other syndromes. Human Dmc1 (hDmc1), a RecA/Rad51 homologue, is a recombinase that plays a crucial role in faithful chromosome segregation during meiosis. The initial step of homologous recombination occurs when hDmc1 forms a filament on single-stranded (ss) DNA. However the structure of this presynaptic complex filament for hDmc1 remains unknown. To compare hDmc1-ssDNA complexes to those known for the RecA/Rad51 family we have obtained electron microscopy (EM) structures of hDmc1-ssDNA nucleoprotein filaments using single particle approach. The EM maps were analysed by docking crystal structures of Dmc1, Rad51, RadA, RecA and DNA. To fully characterise hDmc1-DNA complexes we have analysed their organisation in the presence of Ca2+, Mg2+, ATP, AMP-PNP, ssDNA and dsDNA. The 3D EM structures of the hDmc1-ssDNA filaments allowed us to elucidate the principles of their internal architecture. Similar to the RecA/Rad51 family, hDmc1 forms helical filaments on ssDNA in two states: extended (active) and compressed (inactive). However, in contrast to the RecA/Rad51 family, and the recently reported structure of hDmc1-double stranded (ds) DNA nucleoprotein filaments, the extended (active) state of the hDmc1 filament formed on ssDNA has nine protomers per helical turn, instead of the conventional six, resulting in one protomer covering two nucleotides instead of three. The control reconstruction of the hDmc1-dsDNA filament revealed 6.4 protein subunits per helical turn indicating that the filament organisation varies depending on the DNA templates. Our structural analysis has also revealed that the N-terminal domain of hDmc1 accomplishes its important role in complex formation through domain swapping between adjacent protomers, thus providing a mechanistic basis for coordinated action of hDmc1 protomers during meiotic recombination

Fine Tuning of Ca(V)1.3 Ca2+ Channel Properties in Adult Inner Hair Cells Positioned in the Most Sensitive Region of the Gerbil Cochlea

Hearing relies on faithful signal transmission by cochlear inner hair cells (IHCs) onto auditory fibres over a wide frequency and intensity range. Exocytosis at IHC ribbon synapses is triggered by Ca2+ inflow through CaV1.3 (L-type) Ca2+ channels. We investigated the macroscopic (whole-cell) and elementary (cell-attached) properties of Ca2+ currents in IHCs positioned at the middle turn (frequency ,2 kHz) of the adult gerbil cochlea, which is their most sensitive hearing region. Using near physiological recordings conditions (body temperature and a Na+ based extracellular solution), we found that the macroscopic Ca2+ current activates and deactivates very rapidly (time constant below 1 ms) and inactivates slowly and only partially. Single-channel recordings showed an elementary conductance of 15 pS, a sub-ms latency to first opening, and a very low steady-state open probability (Po: 0.024 in response to 500-ms depolarizing steps at ,218 mV). The value of Po was significantly larger (0.06) in the first 40 ms of membrane depolarization, which corresponds to the time when most Ca2+ channel openings occurred clustered in bursts (mean burst duration: 19 ms). Both the Po and the mean burst duration were smaller than those previously reported in high-frequency basal IHCs. Finally, we found that middle turn IHCs are likely to express about 4 times more Ca2+ channels per ribbon than basal cells. We propose that middle-turn IHCs finely-tune CaV1.3 Ca2+ channel gating in order to provide reliable information upon timing and intensity of lower-frequency sounds

Radiative contribution to neutrino masses and mixing in μν\mu\nuSSM

In an extension of the minimal supersymmetric standard model (popularly known as the $\mu\nu$SSM), three right handed neutrino superfields are introduced to solve the $\mu$-problem and to accommodate the non-vanishing neutrino masses and mixing. Neutrino masses at the tree level are generated through $R-$parity violation and seesaw mechanism. We have analyzed the full effect of one-loop contributions to the neutrino mass matrix. We show that the current three flavour global neutrino data can be accommodated in the $\mu\nu$SSM, for both the tree level and one-loop corrected analyses. We find that it is relatively easier to accommodate the normal hierarchical mass pattern compared to the inverted hierarchical or quasi-degenerate case, when one-loop corrections are included.Comment: 51 pages, 14 figures (58 .eps files), expanded introduction, other minor changes, references adde

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A framework for Distributional Formal Semantics

Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language. As such, a considerable amount of research has sought to unify them, either by augmenting formal semantic systems with a distributional component, or by defining a formal system on top of distributed representations. Arriving at such a unified framework has, however, proven extremely challenging. One reason for this is that formal and distributional semantics operate on a fundamentally different `representational currency': formal semantics defines meaning in terms of models of the world, whereas distributional semantics defines meaning in terms of linguistic co-occurrence. Here, we pursue an alternative approach by deriving a vector space model that defines meaning in a distributed manner relative to formal models of the world. We will show that the resulting Distributional Formal Semantics offers probabilistic distributed representations that are also inherently compositional, and that naturally capture quantification and entailment. We moreover show that, when used as part of a neural network model, these representations allow for capturing incremental meaning construction and probabilistic inferencing. This framework thus lays the groundwork for an integrated distributional and formal approach to meaning