CCA: An R Package to Extend Canonical Correlation Analysis

Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations between two data sets acquired on the same experimental units. The cancor() function in R (R Development Core Team 2007) performs the core of computations but further work was required to provide the user with additional tools to facilitate the interpretation of the results. We implemented an R package, CCA, freely available from the Comprehensive R Archive Network (CRAN, http://CRAN.R-project.org/), to develop numerical and graphical outputs and to enable the user to handle missing values. The CCA package also includes a regularized version of CCA to deal with data sets with more variables than units. Illustrations are given through the analysis of a data set coming from a nutrigenomic study in the mouse.

Thermal quantum electrodynamics of nonrelativistic charged fluids

The theory relevant to the study of matter in equilibrium with the radiation field is thermal quantum electrodynamics (TQED). We present a formulation of the theory, suitable for non relativistic fluids, based on a joint functional integral representation of matter and field variables. In this formalism cluster expansion techniques of classical statistical mechanics become operative. They provide an alternative to the usual Feynman diagrammatics in many-body problems which is not perturbative with respect to the coupling constant. As an application we show that the effective Coulomb interaction between quantum charges is partially screened by thermalized photons at large distances. More precisely one observes an exact cancellation of the dipolar electric part of the interaction, so that the asymptotic particle density correlation is now determined by relativistic effects. It has still the $r^{-6}$ decay typical for quantum charges, but with an amplitude strongly reduced by a relativistic factor.Comment: 32 pages, 0 figures. 2nd versio

Revisiting Proposal-based Object Detection

This paper revisits the pipeline for detecting objects in images with proposals. For any object detector, the obtained box proposals or queries need to be classified and regressed towards ground truth boxes. The common solution for the final predictions is to directly maximize the overlap between each proposal and the ground truth box, followed by a winner-takes-all ranking or non-maximum suppression. In this work, we propose a simple yet effective alternative. For proposal regression, we solve a simpler problem where we regress to the area of intersection between proposal and ground truth. In this way, each proposal only specifies which part contains the object, avoiding a blind inpainting problem where proposals need to be regressed beyond their visual scope. In turn, we replace the winner-takes-all strategy and obtain the final prediction by taking the union over the regressed intersections of a proposal group surrounding an object. Our revisited approach comes with minimal changes to the detection pipeline and can be plugged into any existing method. We show that our approach directly improves canonical object detection and instance segmentation architectures, highlighting the utility of intersection-based regression and grouping.Comment: 10 pages, 7 figure

Microscopic origin of universality in Casimir forces

The microscopic mechanisms for universality of Casimir forces between macroscopic conductors are displayed in a model of classical charged fluids. The model consists of two slabs in empty space at distance $d$ containing classical charged particles in thermal equilibrium (plasma, electrolyte). A direct computation of the average force per unit surface yields, at large distance, the usual form of the Casimir force in the classical limit (up to a factor 2 due to the fact that the model does not incorporate the magnetic part of the force). Universality originates from perfect screening sum rules obeyed by the microscopic charge correlations in conductors. If one of the slabs is replaced by a macroscopic dielectric medium, the result of Lifshitz theory for the force is retrieved. The techniques used are Mayer expansions and integral equations for charged fluids.Comment: 31 pages, 0 figures, submitted to Journal of Statistical Physic

Equilibrium correlations in charged fluids coupled to the radiation field

We provide an exact microscopic statistical treatment of particle and field correlations in a system of quantum charges in equilibrium with a classical radiation field. Using the Feynman-Kac-Ito representation of the Gibbs weight, the system of particles is mapped onto a collection of random charged wires. The field degrees of freedom can be integrated out, providing an effective pairwise magnetic potential. We then calculate the contribution of the transverse field coupling to the large-distance particle correlations. The asymptotics of the field correlations in the plasma are also exactly determined.Comment: 31 pages, 0 figures. PACS 05.30.-d, 05.40.-a, 11.10.Wx. Changes: Improved comparison with existing literature on field correlations. Added Concluding Remarks. References update

Consequences of PPARα Invalidation on Glutathione Synthesis: Interactions with Dietary Fatty Acids

Glutathione (GSH) derives from cysteine and plays a key role in redox status. GSH synthesis is determined mainly by cysteine availability and γ-glutamate cysteine ligase (γGCL) activity. Because PPARα activation is known to control the metabolism of certain amino acids, GSH synthesis from cysteine and related metabolisms were explored in wild-type (WT) and PPARα-null (KO) mice, fed diets containing either saturated (COCO diet) or 18 : 3 n-3, LIN diet. In mice fed the COCO diet, but not in those fed the LIN diet, PPARα deficiency enhanced hepatic GSH content and γGCL activity, superoxide dismutase 2 mRNA levels, and plasma uric acid concentration, suggesting an oxidative stress. In addition, in WT mice, the LIN diet increased the hepatic GSH pool, without effect on γGCL activity, or change in target gene expression, which rules out a direct effect of PPARα. This suggests that dietary 18 : 3 n-3 may regulate GSH metabolism and thus mitigate the deleterious effects of PPARα deficiency on redox status, without direct PPARα activation

HPC-oriented Canonical Workflows for Machine Learning Applications in Climate and Weather Prediction

Machine learning (ML) applications in weather and climate are gaining momentum as big data and the immense increase in High-performance computing (HPC) power are paving the way. Ensuring FAIR data and reproducible ML practices are significant challenges for Earth system researchers. Even though the FAIR principle is well known to many scientists, research communities are slow to adopt them. Canonical Workflow Framework for Research (CWFR) provides a platform to ensure the FAIRness and reproducibility of these practices without overwhelming researchers. This conceptual paper envisions a holistic CWFR approach towards ML applications in weather and climate, focusing on HPC and big data. Specifically, we discuss Fair Digital Object (FDO) and Research Object (RO) in the DeepRain project to achieve granular reproducibility. DeepRain is a project that aims to improve precipitation forecast in Germany by using ML. Our concept envisages the raster datacube to provide data harmonization and fast and scalable data access. We suggest the Juypter notebook as a single reproducible experiment. In addition, we envision JuypterHub as a scalable and distributed central platform that connects all these elements and the HPC resources to the researchers via an easy-to-use graphical interface

Genomic data provide new insights on the demographic history and the extent of recent material transfers in Norway spruce

Primeval forests are today exceedingly rare in Europe, and transfer of forest reproductive material for afforestation and improvement has been very common, especially over the last two centuries. This can be a serious impediment when inferring past population movements in response to past climate changes such as the last glacial maximum (LGM), some 18,000 years ago. In the present study, we genotyped 1,672 individuals from three Picea species (P. abies, P. obovata, and P. omorika) at 400K SNPs using exome capture to infer the past demographic history of Norway spruce (P. abies) and estimate the amount of recent introduction used to establish the Norway spruce breeding program in southern Sweden. Most of these trees belong to P. abies and originate from the base populations of the Swedish breeding program. Others originate from populations across the natural ranges of the three species. Of the 1,499 individuals stemming from the breeding program, a large proportion corresponds to recent introductions from mainland Europe. The split of P. omorika occurred 23 million years ago (mya), while the divergence between P. obovata and P. abies began 17.6 mya. Demographic inferences retrieved the same main clusters within P. abies than previous studies, that is, a vast northern domain ranging from Norway to central Russia, where the species is progressively replaced by Siberian spruce (P. obovata) and two smaller domains, an Alpine domain and a Carpathian one, but also revealed further subdivision and gene flow among clusters. The three main domains divergence was ancient (15 mya), and all three went through a bottleneck corresponding to the LGM. Approximately 17% of P. abies Nordic domain migrated from P. obovata ~103K years ago, when both species had much larger effective population sizes. Our analysis of genomewide polymorphism data thus revealed the complex demographic history of Picea genus in Western Europe and highlighted the importance of material transfer in Swedish breeding program

Parabolic gratings enhance the X-ray sensitivity of Talbot interferograms

In grating-based X-ray Talbot interferometry, the wave nature of X-ray radiation is exploited to generate phase contrast images of objects that do not generate sufficient contrast in conventional X-ray imaging relying on X-ray absorption. The phase sensitivity of this interferometric technique is proportional to the interferometer length and inversely proportional to the period of gratings. However, the limited spatial coherency of X-rays limits the maximum interferometer length, and the ability to obtain smaller-period gratings is limited by the manufacturing process. Here, we propose a new optical configuration that employs a combination of a converging parabolic micro-lens array and a diverging micro-lens array, instead of a binary phase grating. Without changing the grating period or the interferometer length, the phase signal is enhanced because the beam deflection by a sample is amplified through the array of converging-diverging micro-lens pairs. We demonstrate that the differential phase signal detected by our proposed set-up is twice that of a Talbot interferometer, using the same binary absorption grating, and with the same overall inter-grating distance