The Kernel of the Reciprocity Map of Simple Normal Crossing Varieties over Finite Fields

For a smooth and proper variety Y over a finite field k the reciprocity map ρY:\CH0(Y)→π\ab1(Y) is injective with dense image. For a proper simple normal crossing variety this is no longer true in general. In this paper we give a discription of the kernel and cokernel of the reciprocity map in terms of homology groups of a complex filled with descent data using an algebraic Seifert-van-Kampen theorem. Furthermore, we give a new criterion for the injectivity of the reciprocity map for proper simple normal crossing varieties over finite fields

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

Generative flows and diffusion models have been predominantly trained on ordinal data, for example natural images. This paper introduces two extensions of flows and diffusion for categorical data such as language or image segmentation: Argmax Flows and Multinomial Diffusion. Argmax Flows are defined by a composition of a continuous distribution (such as a normalizing flow), and an argmax function. To optimize this model, we learn a probabilistic inverse for the argmax that lifts the categorical data to a continuous space. Multinomial Diffusion gradually adds categorical noise in a diffusion process, for which the generative denoising process is learned. We demonstrate that our method outperforms existing dequantization approaches on text modelling and modelling on image segmentation maps in log-likelihood.Comment: Accepted at Neural Information Processing Systems (NeurIPS 2021

Plastic zone evolution during fatigue crack growth: Digital image correlation coupled with finite elements method

International audienceNonlinearities effects at the crack tip, due to the elastic-plastic material behavior , impact the crack growth rate and path. This paper is devoted to the study of the plastic zone evolution in the crack tip region. The methodology relies on coupling an elastic-plastic Finite Elements Method (FEM) model and experimental displacements measured by Digital Image Correlation (DIC). These latter are introduced as Dirichlet boundary conditions in the finite elements analysis. The considered FEM domain is constant, i.e. the same mesh with a centered crack is moved to each new crack tip position deduced from DIC. The new boundary conditions are updated and the residual stresses and plastic strains of the former computation are interpolated and actualized on the mesh shifted to the new crack tip position in order to incorporate them in the numerical model. The coupling method allowed applying experimental boundary conditions in order to be as close as possible to real experimental conditions and to observe the plasticity evolution from small to large scale yielding conditions. A fatigue test was conducted to validate the proposed approach. The identification residues are proved to be lower than those obtained with an experimental displacements projection onto Williams' series basis, which is a method commonly used with DIC. The coupling results present an attractive similarity with Irwin's model regardless of the crack length. Thus, the definition of the mask needed for the displacements fields projection on Williams' model can be deduced with a reliable estimate of Irwin's plastic radius

High-resolution in situ holographic recording and analysis of marine organisms and particles (HOLOMAR)

We report on the development of a fully- unctioning, prototype, underwater holographic camera (holo-camera) for holographic recording of large-volumes of sea water containing marine plankton and seston within the upper water column The overriding benefit of holographic imaging over other measurement techniques is that it allows non-intrusive and non-destructive, in-situ, recording of living organisms and inanimate particles in their natural environment. Because of the inherently high resolution of holography, its threedimensional imaging properties and the ability to perform "optical sectioning" on the image, it allows identification of particular organisms together with the extraction of sue and relative positional information This information, in turn, affords the ability to gain knowledge of the behaviour of marine biological communities, their relationship with each other and with the particles with which they interact

Harmonic Analysis of Boolean Networks: Determinative Power and Perturbations

Consider a large Boolean network with a feed forward structure. Given a probability distribution on the inputs, can one find, possibly small, collections of input nodes that determine the states of most other nodes in the network? To answer this question, a notion that quantifies the determinative power of an input over the states of the nodes in the network is needed. We argue that the mutual information (MI) between a given subset of the inputs X = {X_1, ..., X_n} of some node i and its associated function f_i(X) quantifies the determinative power of this set of inputs over node i. We compare the determinative power of a set of inputs to the sensitivity to perturbations to these inputs, and find that, maybe surprisingly, an input that has large sensitivity to perturbations does not necessarily have large determinative power. However, for unate functions, which play an important role in genetic regulatory networks, we find a direct relation between MI and sensitivity to perturbations. As an application of our results, we analyze the large-scale regulatory network of Escherichia coli. We identify the most determinative nodes and show that a small subset of those reduces the overall uncertainty of the network state significantly. Furthermore, the network is found to be tolerant to perturbations of its inputs

Mannose-binding lectin deficiency is associated with early onset of polyarticular juvenile rheumatoid arthritis: a cohort study

BACKGROUND: Mannose-binding lectin (MBL) is an innate immune protein. The aim of our study was to determine whether genetically determined MBL deficiency is associated with susceptibility to juvenile rheumatoid arthritis (JRA) and whether MBL2 genotypes are associated with JRA severity. METHODS: In a retrospective cohort study of 218 patients with polyarthritis (n = 67) and oligoarthritis (n = 151), clinical and laboratory disease variables were obtained by clinical examination and chart reviews. Healthy Caucasian adults (n = 194) served as control individuals. MBL2 gene mutations were determined by Taqman analysis to identify genotypes with high, medium and low expression of MBL. Functional MBL plasma concentrations were measured using enzyme-linked immunosorbent assay. Associations between clinical and laboratory variables and MBL2 genotypes were determined by Kruskal-Wallis and χ(2 )tests. RESULTS: MBL2 genotype frequencies were similar in polyarthritis and oligoarthritis patients as compared with control individuals. MBL plasma concentrations were associated with the high, medium and low MBL genotype expression groups (P < 0.01). In polyarthritis patients, the presence of low-expressing (deficient) MBL2 genotypes was associated with early age at onset of disease (P = 0.03). In oligoarthritis patients, patients with low-expressing MBL2 genotypes were more often in remission (81%) than patients in the medium (54%) and high (56%) genotype groups (P = 0.02). The remaining clinical and laboratory variables, such as arthritis severity index, presence of radiographic erosions and antinuclear antibody positivity, were not associated with MBL2 genotypes. CONCLUSION: Genetically determined MBL deficiency does not increase susceptibility to JRA, but MBL deficiency is associated with a younger age at onset of juvenile polyarthritis. On the other hand, MBL-deficient children with juvenile oligoarthritis are more often in remission. Therefore, MBL appears to play a dual role in JRA

Antigen-Specific Blocking of CD4-Specific Immunological Synapse Formation Using BPI and Current Therapies for Autoimmune Diseases

This is the peer reviewed version of the following article: Manikwar, P., Kiptoo, P., Badawi, A. H., Büyüktimkin, B. and Siahaan, T. J. (2012), Antigen-specific blocking of CD4-Specific immunological synapse formation using BPI and current therapies for autoimmune diseases. Med Res Rev, 32: 727–764. doi:10.1002/med.20243, which has been published in final form at http://doi.org/10.1002/med.20243. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this review, we discuss T-cell activation, etiology, and the current therapies of autoimmune diseases (i.e., MS, T1D, and RA). T-cells are activated upon interaction with antigen-presenting cells (APC) followed by a “bull’s eye”-like formation of the immunological synapse (IS) at the T-cell–APC interface. Although the various disease-modifying therapies developed so far have been shown to modulate the IS and thus help in the management of these diseases, they are also known to present some undesirable side effects. In this study, we describe a novel and selective way to suppress autoimmunity by using a bifunctional peptide inhibitor (BPI). BPI uses an intercellular adhesion molecule-1 (ICAM-1)-binding peptide to target antigenic peptides (e.g., proteolipid peptide, glutamic acid decarboxylase, and type II collagen) to the APC and therefore modulate the immune response. The central hypothesis is that BPI blocks the IS formation by simultaneously binding to major histocompatibility complex-II and ICAM-1 on the APC and selectively alters the activation of T cells from TH1 to Treg and/or TH2 phenotypes, leading to tolerance