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On August 14, 2019, the LIGO and Virgo detectors observed GW190814, a gravitational-wave signal originating from the merger of a $\simeq 23 M_\odot$ black hole with a $\simeq 2.6 M_\odot$ compact object. GW190814's compact-binary source is atypical both in its highly asymmetric masses and in its lower-mass component lying between the heaviest known neutron star and lightest known black hole in a compact-object binary. If formed through isolated binary evolution, the mass of the secondary is indicative of its mass at birth. We examine the formation of such systems through isolated binary evolution across a suite of assumptions encapsulating many physical uncertainties in massive-star binary evolution. We update how mass loss is implemented for the neutronization process during the collapse of the proto-compact object to eliminate artificial gaps in the mass spectrum at the transition between neutron stars and black holes. We find it challenging for population modeling to match the empirical rate of GW190814-like systems whilst simultaneously being consistent with the rates of other compact binary populations inferred by gravitational-wave observations. Nonetheless, the formation of GW190814-like systems at any measurable rate requires a supernova engine model that acts on longer timescales such that the proto-compact object can undergo substantial accretion immediately prior to explosion, hinting that if GW190814 is the result of massive-star binary evolution, the mass gap between neutron stars and black holes may be narrower or nonexistent. Comment: 19 pages (9 pages main text + 8 pages appendices/references), 6 figures, 1 table, published in ApJL

We have derived values of the Ultraviolet Index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between −5.9% and 10.6%. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2–4%) in the tropical belt (30°N-30°S). For the mid-latitudes, we observed a 1.8 to 3.4 % increase in the Southern Hemisphere for RCP 2.6, 4.5 and 6.0, and found a 2.3% decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 to 5.5% for RCP 2.6, 4.5 and 6.0 and they are lower by 7.9% for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960–2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does.

We present a novel approach to computing Hamming distance and its kernelisation within Topological Quantum Computation. This approach is based on an encoding of two binary strings into a topological Hilbert space, whose inner product yields a natural Hamming distance kernel on the two strings. Kernelisation forges a link with the field of Machine Learning, particularly in relation to binary classifiers such as the Support Vector Machine (SVM). This makes our approach of potential interest to the quantum machine learning community.

Frontiers in immunology 12, 701275 (2021). doi:10.3389/fimmu.2021.701275 Published by Frontiers Media, Lausanne

We present the design of a mesh quality indicatorthat can predict the behavior of the Virtual Element Method (VEM) on a given mesh family or a finite sequence of polyhedral meshes (dataset). The mesh quality indicator is designed to measure the violation of the mesh regularity assumptions that are normally considered in the convergence analysis. We investigate the behavior of this new mathematical tool on the lowest-order conforming approximation of the three-dimensional Poisson equation. This work also assesses the convergence rate of the VEM when applied to very general polyhedral meshes, including non-convex and skewed three-dimensional elements. Such meshes are created within an original mesh generation framework, which is designed to allow the generation of meshes with very different sizes, connectivity, and geometrical properties. The obtained results show a significant correlation between the quality measured a priori by the indicator and the effective performance of the VEM.

Long exposure to overload and vibration transmission on the upper limb are among the high risk injury factors in industrial environments. They contribute to the development of musculoskeletal disorders, which can lead to economic and social setbacks. To address this issue, robotic systems have been developed that act either as an autonomous system or in collaboration with the workers. In this direction, and with the aim to develop a system that contributes to a simultaneous reduction of the overloading and vibration transmission, we present a novel wearable soft robotic hand-arm system. Preliminary experimental results in a vibrational tool use are reported to shown the potential of the system in improving worker ergonomics.

Fluorescence is a powerful tool for mapping biological events in real-time with high spatial resolution. Ultra-bright probes are needed in order to achieve high sensitivity: these probes are typically obtained by gathering a huge number of fluorophores in a single nanoparticle (NP). Unfortunately this assembly produces quenching of the fluorescence because of short-range intermolecular interactions. Here we demonstrate that rational structural modification of a well-known molecular fluorophore N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) (NBD) produces fluorophores that self-assemble in nanoparticles in the biocompatible environment without any dramatic decrease of the fluorescence quantum yield. Most importantly, the resulting NP show, in an aqueous environment, a brightness which is more than six orders of magnitude higher than the molecular component in the organic solvent. Moreover, the NP are prepared by nanoprecipitation and they are stabilized only via non-covalent interaction, they are surprisingly stable and can be observed as individual bright spots freely diffusing in solution at a concentration as low as 1 nM. The suitability of the NP as biocompatible fluorescent probes was demonstrated in the case of HeLa cells by fluorescence confocal microscopy and MTS assays.