A Uq(gl^(2∣2))1U_q\bigl(\hat{gl}(2|2)\bigr)_1-Vertex Model: Creation Algebras and Quasi-Particles I

The infinite configuration space of an integrable vertex model based on $U_q\bigl(\hat{gl}(2|2)\bigr)_1$ is studied at $q=0$. Allowing four particular boundary conditions, the infinite configurations are mapped onto the semi-standard supertableaux of pairs of infinite border strips. By means of this map, a weight-preserving one-to-one correspondence between the infinite configurations and the normal forms of a pair of creation algebras is established for one boundary condition. A pair of type-II vertex operators associated with an infinite-dimensional $U_q\bigl(gl(2|2)\bigr)$-module $\mathring V$ and its dual $\mathring V^*$ is introduced. Their existence is conjectured relying on a free boson realization. The realization allows to determine the commutation relation satisfied by two vertex operators related to the same $U_q\bigl(gl(2|2)\bigr)$-module. Explicit expressions are provided for the relevant R-matrix elements. The formal $q\to0$ limit of these commutation relations leads to the defining relations of the creation algebras. Based on these findings it is conjectured that the type II vertex operators associated with $\mathring V$ and $\mathring V^*$ give rise to part of the eigenstates of the row-to-row transfer matrix of the model. A partial discussion of the R-matrix elements introduced on $\mathring V\otimes \mathring V^*$ is given.Comment: 45 pages, 5 figures, to appear in Nucl. Phys.

The Uq(sl^(2/1))1U_q(\hat{sl}(2/1))_1-module V(Λ2)V(\Lambda_2) and a Corner Transfer Matrix at q=0

The north-west corner transfer matrix of an inhomogeneous integrable vertex model constructed from the vector representation of $U_q\bigl(sl(2/1)\bigr)$ and its dual is investigated. In the limit $q\to0$, the spectrum can be obtained. Based on an analysis of the half-infinite tensor products related to all CTM-eigenvalues $\geq -4$, it is argued that the eigenvectors of the corner transfer matrix are in one-to-one correspondance with the weight states of the $U_q\bigl((\hat{sl}(2/1)\bigr)_1-$module $V(\Lambda_2)$ at level one. This is supported by a comparison of the comlete set of eigenvectors with a nondegenerate triple of eigenvalues of the CTM-Hamiltonian and the generators of the Cartan-subalgebra of $U_q\bigl(sl(2|1)\bigr)$ to the weight states of $V(\Lambda_2)$ with multiplicity one.Comment: 28 pages, revtex accepted for publication in Nuclear Physics

Unexpected distribution of ν1f7/2 strength in Ca 49

The calcium isotopes have emerged as a critical testing ground for new microscopically derived shell-model interactions, and a great deal of experimental and theoretical focus has been directed toward this region. We investigate the relative spectroscopic strengths associated with 1f7/2 neutron hole states in Ca47,49 following one-neutron knockout reactions from Ca48,50. The observed reduction of strength populating the 7/21- state in Ca49, as compared to Ca47, is inconsistent with shell-model calculations using both phenomenological interactions such as GXPF1, and interactions derived from microscopically based two- and three-nucleon forces. The result suggests a fragmentation of the l=3 strength to higher-lying states as suggested by the microscopic calculations, but the observed magnitude of the reduction is not reproduced in any shell-model description

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

A macroscopic soil-water transport model to simulate root water uptake in the presence of water and disease stress

Macroscopic modeling approaches based on the solution of the Richards equation with root water uptake (RWU) as a sink term can help in understanding soil-water-plant interactions within the rhizosphere. However, these models currently cannot capture the differences in RWU attributed to variations in plant health. Errors in simulating RWU from unhealthy plants are significant when disease-causing fungus inhibits water uptake rather than other usually considered plant stresses. We developed RWU reduction functions to simulate plant transpiration under combined water and disease stress conditions using linear and non-linear response models. The developed functions were implemented in the numerical model HYDRUS (2D/3D) to simulate water uptake from a root system in a radially symmetrical flow domain. Field experiments were conducted in the Vidarbha region of central India for one crop cycle on four citrus trees with varying disease intensities (healthy to severely diseased). The proposed model was rigorously tested by comparing its results with measured soil water contents and plant transpiration fluxes under various water and disease limiting conditions. Error in simulating RWU fluxes from unhealthy trees by ignoring the disease stress factor was found to be significant (15% for slightly diseased to 26% for the severely diseased tree). Parameters of the spatial root distribution and the disease stress response functions were optimized for each scenario using a genetic algorithm approach. Our results indicate that calibration targets to validate uptake reduction functions should be chosen cautiously based on the dominant stress experienced by the plant root system