Equilibrium statistical mechanics and energy partition for the shallow water model

The aim of this paper is to use large deviation theory in order to compute the entropy of macrostates for the microcanonical measure of the shallow water system. The main prediction of this full statistical mechanics computation is the energy partition between a large scale vortical flow and small scale fluctuations related to inertia-gravity waves. We introduce for that purpose a discretized model of the continuous shallow water system, and compute the corresponding statistical equilibria. We argue that microcanonical equilibrium states of the discretized model in the continuous limit are equilibrium states of the actual shallow water system. We show that the presence of small scale fluctuations selects a subclass of equilibria among the states that were previously computed by phenomenological approaches that were neglecting such fluctuations. In the limit of weak height fluctuations, the equilibrium state can be interpreted as two subsystems in thermal contact: one subsystem corresponds to the large scale vortical flow, the other subsystem corresponds to small scale height and velocity fluctuations. It is shown that either a non-zero circulation or rotation and bottom topography are required to sustain a non-zero large scale flow at equilibrium. Explicit computation of the equilibria and their energy partition is presented in the quasi-geostrophic limit for the energy-enstrophy ensemble. The possible role of small scale dissipation and shocks is discussed. A geophysical application to the Zapiola anticyclone is presented.Comment: Journal of Statistical Physics, Springer Verlag, 201

Modeling and simulation of drying operation in PVC powder production line: a pneumatic dryer model

A one-dimensional steady-state model is developed to simulate drying of PVC powder in a pneumatic dryer. In this model, a two-phase continuum model was used to describe the steady-state flow of a dilute dispersed phase (wet PVC powder) and a continuous phase (humid air) through dryer. The particle scale kinetics was obtained by immersion of a fixed mass of wet PVC’s particles (cake) in a batch dense fluidized bed containing inert hot particles (glass bead). The drying kinetics was described by a shrinking core type model and integrated in pneumatic dryer model. The results show that the inlet temperature is the most important parameter in the operation. The drying rate is controlled by a two-stage process. The first stage corresponds to the surface water evaporation, and the second to the pore water evaporation

HTLV-3/STLV-3 and HTLV-4 Viruses: Discovery, Epidemiology, Serology and Molecular Aspects

Human T cell leukemia/lymphoma virus Type 1 and 2 (HTLV-1 and HTLV-2), together with their simian counterparts (STLV-1, STLV-2), belong to the Primate T lymphotropic viruses group (PTLV). The high percentage of homologies between HTLV-1 and STLV-1 strains, led to the demonstration that most HTLV-1 subtypes arose from interspecies transmission between monkeys and humans. STLV-3 viruses belong to the third PTLV type and are equally divergent from both HTLV-1 and HTLV-2. They are endemic in several monkey species that live in West, Central and East Africa. In 2005, we, and others reported the discovery of the human homolog (HTLV-3) of STLV-3 in two asymptomatic inhabitants from South Cameroon whose sera exhibited HTLV indeterminate serologies. More recently, two other cases of HTLV-3 infection in persons living in Cameroon were reported suggesting that this virus is not extremely rare in the human population living in Central Africa. Together with STLV-3, these human viral strains belong to the PTLV-3 group. A fourth HTLV type (HTLV-4) was also discovered in the same geographical area. The overall PTLV-3 and PTLV-4 genomic organization is similar to that of HTLV-1 and HTLV-2 with the exception of their long terminal repeats (LTRs) that contain only two 21 bp repeats. As in HTLV-1, HTLV-3 Tax contains a PDZ binding motif while HTLV-4 does not. An antisense transcript was also described in HTLV-3 transfected cells. PTLV-3 molecular clones are now available and will allow scientists to study the viral cycle, the tropism and the possible pathogenicity in vivo. Current studies are also aimed at determining the prevalence, distribution, and modes of transmission of these viruses, as well as their possible association with human diseases. Here we will review the characteristics of these new simian and human retroviruses, whose discovery has opened new avenues of research in the retrovirology field

Transcriptomic analyses reveal that the cellular Gem protein promotes HTLV-1 infected cell migration and viral transmission

International audienc

Leveraging Neural Radiance Fields for Pose Estimation of an Unknown Space Object during Proximity Operations

We address the estimation of the 6D pose of an unknown target spacecraft relative to a monocular camera, a key step towards the autonomous rendezvous and proximity operations required by future Active Debris Removal missions. We present a novel method that enables an "off-the-shelf" spacecraft pose estimator, which is supposed to known the target CAD model, to be applied on an unknown target. Our method relies on an in-the wild NeRF, i.e., a Neural Radiance Field that employs learnable appearance embeddings to represent varying illumination conditions found in natural scenes. We train the NeRF model using a sparse collection of images that depict the target, and in turn generate a large dataset that is diverse both in terms of viewpoint and illumination. This dataset is then used to train the pose estimation network. We validate our method on the Hardware-In-the-Loop images of SPEED+ that emulate lighting conditions close to those encountered on orbit. We demonstrate that our method successfully enables the training of an off-the-shelf spacecraft pose estimation network from a sparse set of images. Furthermore, we show that a network trained using our method performs similarly to a model trained on synthetic images generated using the CAD model of the target.Comment: Accepted at IEEE International Conference on Space Robotics 2024 (ISpaRo 2024), Workshop on Advances in Orbital Robotics: In Orbit Manipulation, Servicing, and Assembl

Domain Generalization for In-Orbit 6D Pose Estimation

We address the problem of estimating the relative 6D pose, i.e., position and orientation, of a target spacecraft, from a monocular image, a key capability for future autonomous Rendezvous and Proximity Operations. Due to the difficulty of acquiring large sets of real images, spacecraft pose estimation networks are exclusively trained on synthetic ones. However, because those images do not capture the illumination conditions encountered in orbit, pose estimation networks face a domain gap problem, i.e., they do not generalize to real images. Our work introduces a method that bridges this domain gap. It relies on a novel, end-to-end, neural-based architecture as well as a novel learning strategy. This strategy improves the domain generalization abilities of the network through multi-task learning and aggressive data augmentation policies, thereby enforcing the network to learn domain-invariant features. We demonstrate that our method effectively closes the domain gap, achieving state-of-the-art accuracy on the widespread SPEED+ dataset. Finally, ablation studies assess the impact of key components of our method on its generalization abilities