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Individuals who have suffered neurotrauma like a stroke or brachial plexus injury often experience reduced limb functionality. Soft robotic exoskeletons have been successful in assisting rehabilitative treatment and improving activities of daily life but restoring dexterity for tasks such as playing musical instruments has proven challenging. This research presents a soft robotic hand exoskeleton coupled with machine learning algorithms to aid in relearning how to play the piano by ‘feeling’ the difference between correct and incorrect versions of the same song. The exoskeleton features piezoresistive sensor arrays with 16 taxels integrated into each fingertip. The hand exoskeleton was created as a single unit, with polyvinyl acid (PVA) used as a stent and later dissolved to construct the internal pressure chambers for the five individually actuated digits. Ten variations of a song were produced, one that was correct and nine containing rhythmic errors. To classify these song variations, Random Forest (RF), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) algorithms were trained with data from the 80 taxels combined from the tactile sensors in the fingertips. Feeling the differences between correct and incorrect versions of the song was done with the exoskeleton independently and while the exoskeleton was worn by a person. Results demonstrated that the ANN algorithm had the highest classification accuracy of 97.13% ± 2.00% with the human subject and 94.60% ± 1.26% without. These findings highlight the potential of the smart exoskeleton to aid disabled individuals in relearning dexterous tasks like playing musical instruments. 

ABSTRACT Understanding the natal kicks received by neutron stars (NSs) during formation is a critical component of modelling the evolution of massive binaries. Natal kicks are an integral input parameter for population synthesis codes, and have implications for the formation of double NS systems and their subsequent merger rates. However, many of the standard observational kick distributions that are used are obtained from samples created only from isolated NSs. Kick distributions derived in this way overestimate the intrinsic NS kick distribution. For NSs in binaries, we can only directly estimate the effect of the natal kick on the binary system, instead of the natal kick received by the NS itself. Here, for the first time, we present a binary kick distribution for NSs with low-mass companions. We compile a catalogue of 145 NSs in low-mass binaries with the best available constraints on proper motion, distance, and systemic radial velocity. For each binary, we use a three-dimensional approach to estimate its binary kick. We discuss the implications of these kicks on system formation, and provide a parametric model for the overall binary kick distribution, for use in future theoretical modelling work. We compare our results with other work on isolated NSs and NSs in binaries, finding that the NS kick distributions fit using only isolated pulsars underestimate the fraction of NSs that receive low kicks. We discuss the implications of our results on modelling double NS systems, and provide suggestions on how to use our results in future theoretical works. 

Abstract. River erosion affects the carbon cycle and thus climate by exporting terrigenous carbon to seafloor sediment and by nourishing CO2-consuming marine life. The Yukon River–Bering Sea system preserves rare source-to-sink records of these processes across profound changes in global climate during the past 5 million years (Ma). Here, we expand the terrestrial erosion record by dating terraces along the Charley River, Alaska, and explore linkages among previously published Yukon Rivertributary incision chronologies and Bering Sea sedimentation. Cosmogenic26Al/10Be isochron burial ages of Charley River terraces match previously documented central Yukon River tributary incision from 2.6 to 1.6 Ma during Pliocene–Pleistocene glacial expansion, and at 1.1 Ma during the 1.2–0.7 Ma Middle Pleistocene climate transition. Bering Sea sediments preserve 2–4-fold rate increases of Yukon River-derived continental detritus, terrestrial and marine organic carbon, and silicate microfossil deposition at 2.6–2.1 and 1.1–0.8 Ma. These tightly coupled records demonstrate elevated terrigenous nutrient and carbon export and concomitant Bering Sea productivity in response to climate-forced Yukon River incision. Carbon burial related to accelerated terrestrial erosion may contribute to CO2 drawdown across the Pliocene–Pleistocene and Middle Pleistocene climate transitions observed in many proxy records worldwide. 

Abstract Disease transmission and behaviour change are both fundamentally social phenomena. Behaviour change can have profound consequences for disease transmission, and epidemic conditions can favour the more rapid adoption of behavioural innovations. We analyse a simple model of coupled behaviour change and infection in a structured population characterised by homophily and outgroup aversion. Outgroup aversion slows the rate of adoption and can lead to lower rates of adoption in the later-adopting group or even behavioural divergence between groups when outgroup aversion exceeds positive ingroup influence. When disease dynamics are coupled to the behaviour-adoption model, a wide variety of outcomes are possible. Homophily can either increase or decrease the final size of the epidemic depending on its relative strength in the two groups and on R 0 for the infection. For example, if the first group is homophilous and the second is not, the second group will have a larger epidemic. Homophily and outgroup aversion can also produce dynamics suggestive of a ‘second wave’ in the first group that follows the peak of the epidemic in the second group. Our simple model reveals dynamics that are suggestive of the processes currently observed under pandemic conditions in culturally and/or politically polarised populations such as the USA. 

ABSTRACT Owing to their quiet evolutionary histories, nearby dwarf galaxies (stellar masses $$M_\star \lesssim 3 \times 10^9 \, \mathrm{M}_\odot$$) have the potential to teach us about the mechanism(s) that ‘seeded’ the growth of supermassive black holes, and also how the first stellar mass black holes formed and interacted with their environments. Here, we present high spatial resolution observations of three dwarf galaxies in the X-ray (Chandra), the optical/near-infrared (Hubble Space Telescope), and the radio (Karl G. Jansky Very Large Array). These three galaxies were previously identified as hosting candidate active galactic nuclei on the basis of lower resolution X-ray imaging. With our new observations, we find that X-ray sources in two galaxies (SDSS J121326.01+543631.6 and SDSS J122111.29+173819.1) are off-nuclear and lack corresponding radio emission, implying they are likely luminous X-ray binaries. The third galaxy (Mrk 1434) contains two X-ray sources (each with LX ≈ 1040 erg s−1) separated by 2.8 arcsec, has a low metallicity [12 + log(O/H)  = 7.8], and emits nebular He ii λ4686 line emission. The northern source has spatially coincident point-like radio emission at 9.0 GHz and extended radio emission at 5.5 GHz. We discuss X-ray binary interpretations (where an ultraluminous X-ray source blows a ‘radio bubble’) and active galactic nucleus interpretations (where an $$\approx 4\times 10^5 \, \mathrm{M}_\odot$$ black hole launches a jet). In either case, we find that the He ii emission cannot be photoionized by the X-ray source, unless the source was ≈30–90 times more luminous several hundred years ago.