Gaia Data Release 3 Stellar multiplicity, a teaser for the hidden treasure

Context. The Gaia DR3 catalogue contains, for the first time, about 800 000 solutions with either orbital elements or trend parameters for astrometric, spectroscopic, and eclipsing binaries, and combinations of these three.Aims. With this paper, we aim to illustrate the huge potential of this large non-single-star catalogue. Methods. Using the orbital solutions and models of the binaries, we have built a catalogue of tens of thousands of stellar masses or lower limits thereof, some with consistent flux ratios. Properties concerning the completeness of the binary catalogues are discussed, statistical features of the orbital elements are explained, and a comparison with other catalogues is performed. Results. Illustrative applications are proposed for binaries across the Hertzsprung-Russell Diagram (HRD). Binarity is studied in the giant branch and a search for genuine spectroscopic binaries among long-period variables is performed. The discovery of new EL CVn systems illustrates the potential of combining variability and binarity catalogues. Potential compact object companions are presented, mainly white dwarf companions or double degenerates, but one candidate neutron star is also found. Towards the bottom of the main sequence, the orbits of previously suspected binary ultracool dwarfs are determined and new candidate binaries are discovered. The long awaited contribution of Gaia to the analysis of the substellar regime shows the brown dwarf desert around solar-type stars using true rather than minimum masses, and provides new important constraints on the occurrence rates of substellar companions to M dwarfs. Several dozen new exoplanets are proposed, including two with validated orbital solutions and one super-Jupiter orbiting a white dwarf, all being candidates requiring confirmation. Besides binarity, higher order multiple systems are also found

Interactions of tobacco microtubule-associated protein MAP65-1b with microtubules

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Cellulose synthase interactive protein 1 (CSI1) links microtubules and cellulose synthase complexes

Cellulose synthase (CESA) complexes can be observed by live-cell imaging to move with trajectories that parallel the underlying cortical microtubules. Here we report that CESA interactive protein 1 (CSI1) is a microtubule-associated protein that bridges CESA complexes and cortical microtubules. Simultaneous in vivo imaging of CSI1, CESA complexes, and microtubules demonstrates that the association of CESA complexes and cortical microtubules is dependent on CSI1. CSI1 directly binds to microtubules as demonstrated by in vitro microtubule-binding assay

A collaborative effort towards the accurate prediction of turbulent flow and heat transfer in low-Prandtl number fluids

This article reports the experimental and DNS database that has been generated, within the framework of the EU SESAME and MYRTE projects, for various low-Prandtl flow configurations in different flow regimes. This includes three experiments: confined and unconfined backward facing steps with low-Prandtl fluids, and a forced convection planar jet case with two different Prandtl fluids. In terms of numerical data, seven different flow configurations are considered: a wall-bounded mixed convection flow at low-Prandtl number with varying Richardson number (Ri) values; a wall-bounded mixed and forced convection flow in a bare rod bundle configuration; a forced convection confined backward facing step (BFS) with conjugate heat transfer; a forced convection impinging jet for three different Prandtl fluids corresponding to two different Reynolds numbers of the fully developed planar turbulent jet; a mixed-convection cold-hot\u2013cold triple jet configuration corresponding to Ri = 0.25; an unconfined free shear layer for three different Prandtl fluids; and a forced convection infinite wire-wrapped fuel assembly. This wide range of reference data is used to evaluate, validate and/or further develop different turbulent heat flux modelling approaches, namely simple gradient diffusion hypothesis (SGDH) based on constant and variable turbulent Prandtl number; explicit and implicit algebraic heat flux models; and a second order turbulent heat flux model. Lastly, this article will highlight the current challenges and perspectives of the available turbulence models, in different codes, for the accurate prediction of flow and heat transfer in low-Prandtl fluids

A collaborative effort towards the accurate prediction of turbulent flow and heat transfer in low-Prandtl number fluids

This article reports the experimental and DNS database that has been generated, within the framework of the EU SESAME and MYRTE projects, for various low-Prandtl flow configurations in different flow regimes. This includes three experiments: confined and unconfined backward facing steps with low-Prandtl fluids, and a forced convection planar jet case with two different Prandtl fluids. In terms of numerical data, seven different flow configurations are considered: a wall-bounded mixed convection flow at low-Prandtl number with varying Richardson number (Ri) values; a wall-bounded mixed and forced convection flow in a bare rod bundle configuration for two different Reynolds numbers; a forced convection confined backward facing step (BFS) with conjugate heat transfer; a forced convection impinging jet for three different Prandtl fluids corresponding to two different Reynolds numbers of the fully developed planar turbulent jet; a mixed-convection cold-hot-cold triple jet configuration corresponding to Ri=0.25; an unconfined free shear layer for three different Prandtl fluids; and a forced convection infinite wire-wrapped fuel assembly. This wide range of reference data is used to evaluate, validate and/or further develop different turbulent heat flux modelling approaches, namely simple gradient diffusion hypothesis based on constant and variable turbulent Prandtl number; explicit and implicit algebraic heat flux models; and a second order turbulent heat flux model. Lastly, this article will highlight the current challenges and perspectives of the available turbulence models, in different codes, for the accurate prediction of flow and heat transfer in low-Prandtl fluids