Understanding Gesture Expressivity through Muscle Sensing

Expressivity is a visceral capacity of the human body. To understand what makes a gesture expressive, we need to consider not only its spatial placement and orientation, but also its dynamics and the mechanisms enacting them. We start by defining gesture and gesture expressivity, and then present fundamental aspects of muscle activity and ways to capture information through electromyography (EMG) and mechanomyography (MMG). We present pilot studies that inspect the ability of users to control spatial and temporal variations of 2D shapes and that use muscle sensing to assess expressive information in gesture execution beyond space and time. This leads us to the design of a study that explores the notion of gesture power in terms of control and sensing. Results give insights to interaction designers to go beyond simplistic gestural interaction, towards the design of interactions that draw upon nuances of expressive gesture

A Search for Extended Ultraviolet Disk (XUV-disk) Galaxies in the Local Universe

We have initiated a search for extended ultraviolet disk (XUV-disk) galaxies in the local universe. Herein, we compare GALEX UV and visible--NIR images of 189 nearby (D$<$40 Mpc) S0--Sm galaxies included in the GALEX Atlas of Nearby Galaxies and present the first catalogue of XUV-disk galaxies. We find that XUV-disk galaxies are surprisingly common but have varied relative (UV/optical) extent and morphology. Type~1 objects (\ga20% incidence) have structured, UV-bright/optically-faint emission features in the outer disk, beyond the traditional star formation threshold. Type~2 XUV-disk galaxies ($\sim$10% incidence) exhibit an exceptionally large, UV-bright/optically-low-surface-brightness (LSB) zone having blue $UV-K_s$ outside the effective extent of the inner, older stellar population, but not reaching extreme galactocentric distance. If the activity occuring in XUV-disks is episodic, a higher fraction of present-day spirals could be influenced by such outer disk star formation. Type~1 disks are associated with spirals of all types, whereas Type~2 XUV-disks are predominantly found in late-type spirals. Type~2 XUV-disks are forming stars quickly enough to double their [presently low] stellar mass in the next Gyr (assuming a constant SF rate). XUV-disk galaxies of both types are systematically more gas-rich than the general galaxy population. Minor external perturbation may stimulate XUV-disk incidence, at least for Type~1 objects. XUV-disks are the most actively evolving galaxies growing via inside-out disk formation in the current epoch, and may constitute a segment of the galaxy population experiencing significant, continued gas accretion from the intergalactic medium or neighboring objects.Comment: 83 pages, 16 figures, 2 tables. Appearing in the GALEX special issue of ApJS. (A version with high quality figures and proof corrections can be found at http://www.journals.uchicago.edu/toc/apjs/173/2

Measurement of the azimuthal anisotropy of charged-particle production in Xe+Xe collisions at sNN =5.44 TeV with the ATLAS detector

This paper describes the measurements of flow harmonics v2-v6 in 3μb-1 of Xe+Xe collisions at sNN=5.44 TeV performed using the ATLAS detector at the Large Hadron Collider (LHC). Measurements of the centrality, multiplicity, and pT dependence of the vn obtained using two-particle correlations and the scalar product technique are presented. The measurements are also performed using a template-fit procedure, which was developed to remove nonflow correlations in small collision systems. This nonflow removal is shown to have a significant influence on the measured vn at high pT, especially in peripheral events. Comparisons of the measured vn with measurements in Pb+Pb collisions and p+Pb collisions at sNN=5.02 TeV are also presented. The vn values in Xe+Xe collisions are observed to be larger than those in Pb+Pb collisions for n=2, 3, and 4 in the most central events. However, with decreasing centrality or increasing harmonic order n, the vn values in Xe+Xe collisions become smaller than those in Pb+Pb collisions. The vn in Xe+Xe and Pb+Pb collisions are also compared as a function of the mean number of participating nucleons, (Npart), and the measured charged-particle multiplicity in the detector. The v3 values in Xe+Xe and Pb+Pb collisions are observed to be similar at the same (Npart) or multiplicity, but the other harmonics are significantly different. The ratios of the measured vn in Xe+Xe and Pb+Pb collisions, as a function of centrality, are also compared to theoretical calculations

Search for diboson resonances in hadronic final states in 139 fb −1 of pp collisions at s = 13 TeV with the ATLAS detector

Abstract: Narrow resonances decaying into W W, W Z or ZZ boson pairs are searched for in 139 fb−1 of proton-proton collision data at a centre-of-mass energy of s = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider from 2015 to 2018. The diboson system is reconstructed using pairs of high transverse momentum, large-radius jets. These jets are built from a combination of calorimeter- and tracker-inputs compatible with the hadronic decay of a boosted W or Z boson, using jet mass and substructure properties. The search is performed for diboson resonances with masses greater than 1.3 TeV. No significant deviations from the background expectations are observed. Exclusion limits at the 95% confidence level are set on the production cross-section times branching ratio into dibosons for resonances in a range of theories beyond the Standard Model, with the highest excluded mass of a new gauge boson at 3.8 TeV in the context of mass-degenerate resonances that couple predominantly to gauge bosons

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Search for squarks and gluinos in final states with same-sign leptons and jets using 139 fb−1^{-1} of data collected with the ATLAS detector

A search for supersymmetric partners of gluons and quarks is presented, involving signatures with jets and either two isolated leptons (electrons or muons) with the same electric charge, or at least three isolated leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb$^{-1}$, is used for the search. No significant excess over the Standard Model expectation is observed. The results are interpreted in simplified supersymmetric models featuring both R-parity conservation and R-parity violation, raising the exclusion limits beyond those of previous ATLAS searches to 1600 GeV for gluino masses and 750 GeV for bottom and top squark masses in these scenarios

Observation of the associated production of a top quark and a Z boson in pp collisions at s = 13 TeV with the ATLAS detector

Abstract: Single top-quark production in association with a Z boson, where the Z boson decays to a pair of charged leptons, is measured in the trilepton channel. The proton-proton collision data collected by the ATLAS experiment from 2015 to 2018 at a centre-of-mass energy of 13 TeV are used, corresponding to an integrated luminosity of 139 fb−1. Events containing three isolated charged leptons (electrons or muons) and two or three jets, one of which is identified as containing a b-hadron, are selected. The main backgrounds are from tt¯Z and diboson production. Neural networks are used to improve the background rejection and extract the signal. The measured cross-section for tℓ+ℓ−q production, including non-resonant dilepton pairs with mℓ+ℓ−> 30 GeV, is 97 ± 13 (stat.) ± 7 (syst.) fb, consistent with the Standard Model prediction

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost