LIGO Lo(g)Normal MACHO: Primordial Black Holes survive SN lensing constraints

It has been claimed in Ref.[arXiv:1712.02240] that massive primordial black holes (PBH) cannot constitute all of the dark matter (DM), because their gravitational-lensing imprint on the Hubble diagram of type Ia supernovae (SN) would be incompatible with present observations. In this paper, we critically review those constraints and find several caveats on the analysis. First of all, the constraints on the fraction $\alpha$ of PBH in matter seem to be driven by a very restrictive choice of priors on the cosmological parameters. In particular, the degeneracy between $\Omega_{\rm M}$ and $\alpha$ is ignored and thus, by fixing $\Omega_{\rm M}$, transferred the constraining power of SN magnitudes to $\alpha$. Furthermore, by considering more realistic physical sizes for the type-Ia supernovae, we find an effect on the SN lensing magnification distribution that leads to significantly looser constraints. Moreover, considering a wide mass spectrum of PBH, such as a lognormal distribution, further softens the constraints from SN lensing. Finally, we find that the fraction of PBH that could constitute DM today is bounded by $f_{\rm PBH} < 1.09\ (1.38)$, for JLA (Union 2.1) catalogs, and thus it is perfectly compatible with an all-PBH dark matter scenario in the LIGO band.Comment: 7 pages, 7 figure

Self-stabilization in self-organized multihop wireless networks

International audienceIn large scale multihop wireless networks, flat architectures are not scalable. In order to overcome this major drawback, clusterization is introduced to support self-organization and to enable hierarchical routing. When dealing with multihop wireless networks the robustness is a main issue due to the dynamicity of such networks. Several algorithms have been designed for the clusterization process. As far as we know, very few studies check the robustness feature of their clusterization protocols. Moreover, when it is the case, the evaluation is driven by simulations and never by a theoretical approach. In this paper, we show that a clusterization algorithm, that seems to present good properties of robustness, is self-stabilizing. We propose several enhancements to reduce the stabilization time and to improve stability. The use of a Directed Acyclic Graph ensures that the self-stabilizing properties always hold regardless of the underlying topology. These extra criterion are tested by simulations

Self-stabilization in self-organized multihop wireless networks

International audienceIn large scale multihop wireless networks, flat architectures are not scalable. In order to overcome this major drawback, clusterization is introduced to support self-organization and to enable hierarchical routing. When dealing with multihop wireless networks the robustness is a main issue due to the dynamicity of such networks. Several algorithms have been designed for the clusterization process. As far as we know, very few studies check the robustness feature of their clusterization protocols. Moreover, when it is the case, the evaluation is driven by simulations and never by a theoretical approach. In this paper, we show that a clusterization algorithm, that seems to present good properties of robustness, is self-stabilizing. We propose several enhancements to reduce the stabilization time and to improve stability. The use of a Directed Acyclic Graph ensures that the self-stabilizing properties always hold regardless of the underlying topology. These extra criterion are tested by simulations

Dynamique des populations d'azobé, Lophira alata Banks ex C. F. Gaertn., et implications pour sa gestion durable au Cameroun

L'impact de l'exploitation forestière sur le renouvellement du stock de bois d'oeuvre reste largement méconnu en Afrique centrale du fait du manque de données sur la dynamique des populations d'arbres exploités. C'est en particulier le cas pour l'azobé, Lophira alata, un bois d'oeuvre de grande valeur commerciale. L'objectif de cette étude est double : quantifier l'effet du type forestier et de l'exploitation sur la croissance de l'azobé et simuler l'évolution du stock exploitable et du taux de reconstitution après exploitation. Nous avons effectué pendant trois ans un suivi annuel de la croissance et de la mortalité dans trois types forestiers au Cameroun : en forêt sempervirente, en forêt mixte et en forêt semi-caducifoliée. Le recrute-ment a été étudié uniquement en forêt mixte, sous deux conditions : en milieu exploité et non exploité. Nous avons calibré, avec ces données, un modèle matriciel de Usher. Douze scénarios d'exploitation ont été simulés en faisant varier le diamètre minimum d'exploitation de 60, 70 et 80 cm, et l'intensité de prélèvement des arbres de 100 à 40 %. La croissance de l'azobé est influencée à la fois par le type forestier et l'exploitation. Les arbres de forêt sempervirente ont une croissance plus faible jusqu'à 50 cm de dia-mètre, alors que la croissance maximale prédite pour ce type forestier est la plus élevée. L'exploitation a par ailleurs stimulé la croissance. Enfin, l'exploitation de l'azobé ne respecte pas le principe du rendement soutenu : ses taux de croissance à long terme varient entre 0,54 et 0,83 %. Pour garantir la durabilité de son exploitation au Cameroun, une sylviculture dynamisant la croissance des futurs arbres exploitables, ainsi que leur régé-nération, s'avère indispensable

Biomacromolecules

Three-dimensional (3D) bioprinting offers a great alternative to traditional techniques in tissue reconstruction, based on seeding cells manually into a scaffold, to better reproduce organs' complexity. When a suitable bioink is engineered with appropriate physicochemical properties, such a process can advantageously provide a spatial control of the patterning that improves tissue reconstruction. The design of an adequate bioink must fulfill a long list of criteria including biocompatibility, printability, and stability. In this context, we have developed a bioink containing a precisely controlled recombinant biopolymer, namely, elastin-like polypeptide (ELP). This material was further chemoselectively modified with cross-linkable moieties to provide a 3D network through photopolymerization. ELP chains were additionally either functionalized with a peptide sequence Gly-Arg-Gly-Asp-Ser (GRGDS) or combined with collagen I to enable cell adhesion. Our ELP-based bioinks were found to be printable, while providing excellent mechanical properties such as stiffness and elasticity in their cross-linked form. Besides, they were demonstrated to be biocompatible, showing viability and adhesion of dermal normal human fibroblasts (NHF). Expressions of specific extracellular matrix (ECM) protein markers as pro-collagen I, elastin, fibrillin, and fibronectin were revealed within the 3D network containing cells after only 18 days of culture, showing the great potential of ELP-based bioinks for tissue engineering

Effects of DDT and permethrin on rat hepatocytes cultivated in microfluidic biochips: Metabolomics and gene expression study

Dichlorodiphenyl-trichloroethane (DDT) and permethrin (PMT) are amongst most prevalent pesticides in the environment. Although their toxicity has been extensively studied, molecular mechanisms and metabolic effects remain unclear, including in liver where their detoxification occurs. Here, we used metabolomics, coupled to RT-qPCR analysis, to examine effects of DDT and PMT on hepatocytes cultivated in biochips. At 150 μM, DDT caused cell death, cytochrome P450 induction and modulation of estrogen metabolism. Metabolomics analysis showed an increase in some lipids and sugars after 6 h, and a decrease in fatty acids (tetradecanoate, octanoate and linoleate) after 24 h exposure. We also found a change in expression associated with genes involved in hepatic estrogen, lipid, and sugar metabolism. PMT at 150 μM perturbed lipid/sugar homeostasis and estrogen signaling pathway, between 2 and 6 h. After 24 h, lipids and sugars were found to decrease, suggesting continuous energy demand to detoxify PMT. Finally, at 15 μM, DDT and PMT appeared to have a small effect on metabolism and were detoxified after 24 h. Our results show a time-dependent perturbation of sugar/lipid homeostasis by DDT and PMT at 150 μM. Furthermore, DDT at high dose led to cell death, inflammatory response and oxidative stress.The study was supported by the French Agency for Food, Environmental and Occupational Health & Safety (ANSES, project IMITOMICS-N°EST-2014/1/093). The molds to fabricate the PDMS devices used in this study were built by the LAAS in the frame of the RENATECH French network

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Human Action Recognition from Body-Part Directional Velocity using Hidden Markov Models

International audienceThis paper introduces a novel approach for early recognition of human actions using 3D skeleton joints extracted from 3D depth data. We propose a novel, frame-by-frame and real-time descriptor called Body-part Directional Velocity (BDV) calculated by considering the algebraic velocity produced by different body-parts. A real-time Hidden Markov Models algorithm with Gaussian Mixture Models state-output distributions is used to carry out the classification. We show that our method outperforms various state-of-the-art skeleton-based human action recognition approaches on MSRAction3D and Florence3D datasets. We also proved the suitability of our approach for early human action recognition by deducing the decision from a partial analysis of the sequence