Nazarbayev University multigrasp hand with bidirectional tendon actuation

Robotic hands are being used in various areas such as industrial automation, medical robotics, and defense. In this work, we are presenting the Nazarbayev University Multigrasp Robot Hand with an integrated RGB-Depth camera for intelligent object manipulation. The novelty ofthe project is seen in the creation of an end effector system which obtains higher level autonomy from the base manipulator, being able to recognize target objects, generate approach trajectories and apply corresponding grasping patterns to capture the object

Preventing female genital mutilation in high income countries: A systematic review of the evidence

© 2019 The Author(s). Background: Female genital mutilation (FGM) is prevalent in communities of migration. Given the harmful effects of the practice and its illegal status in many countries, there have been concerted primary, secondary and tertiary prevention efforts to protect girls from FGM. However, there is paucity of evidence concerning useful strategies and approaches to prevent FGM and improve the health and social outcomes of affected women and girls. Methods: We analysed peer-reviewed and grey literature to extract the evidence for FGM prevention interventions from a public health perspective in high income countries by a systematic search of bibliographic databases and websites using appropriate keywords. Identified publications were screened against selection criteria, following the PRISMA guidelines. We examined the characteristics of prevention interventions, including their programmatic approaches and strategies, target audiences and evaluation findings using an apriori template. Findings: Eleven documents included in this review described primary and secondary prevention activities. High income countries have given attention to legislative action, bureaucratic interventions to address social injustice and protect those at risk of FGM, alongside prevention activities that favour health persuasion, foster engagement with the local community through outreach and the involvement of community champions, healthcare professional training and capacity strengthening. Study types are largely process evaluations that include measures of short-term outcomes (pre- and post-changes in attitude, knowledge and confidence or audits of practices). There is a dearth of evaluative research focused on empowerment-oriented preventative activities that involve individual women and girls who are affected by FGM. Beattie's framework provides a useful way of articulating negotiated and authoritative prevention actions required to address FGM at national and local levels. Conclusion: FGM is a complex and deeply rooted sociocultural issue that requires a multifaceted response that encompasses socio-economic, physical and environmental factors, education and learning, health services and facilities, and community mobilisation activities. Investment in the rigorous longitudinal evaluation of FGM health prevention efforts are needed to provide strong evidence of impact to guide future decision making. A national evidence-based framework would bring logic, clarity, comprehension, evidence and economically more effective response for current and future prevention interventions addressing FGM in high income countries

AutoAD II: The Sequel - who, when, and what in movie audio description

Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences. For movies, this presents notable challenges -- AD must occur only during existing pauses in dialogue, should refer to characters by name, and ought to aid understanding of the storyline as a whole. To this end, we develop a new model for automatically generating movie AD, given CLIP visual features of the frames, the cast list, and the temporal locations of the speech; addressing all three of the `who', `when', and `what' questions: (i) who -- we introduce a character bank consisting of the character's name, the actor that played the part, and a CLIP feature of their face, for the principal cast of each movie, and demonstrate how this can be used to improve naming in the generated AD; (ii) when -- we investigate several models for determining whether an AD should be generated for a time interval or not, based on the visual content of the interval and its neighbours; and (iii) what -- we implement a new vision-language model for this task, that can ingest the proposals from the character bank, whilst conditioning on the visual features using cross-attention, and demonstrate how this improves over previous architectures for AD text generation in an apples-to-apples comparison

Asynchronous Interaction Aggregation for Action Detection

Understanding interaction is an essential part of video action detection. We propose the Asynchronous Interaction Aggregation network (AIA) that leverages different interactions to boost action detection. There are two key designs in it: one is the Interaction Aggregation structure (IA) adopting a uniform paradigm to model and integrate multiple types of interaction; the other is the Asynchronous Memory Update algorithm (AMU) that enables us to achieve better performance by modeling very long-term interaction dynamically without huge computation cost. We provide empirical evidence to show that our network can gain notable accuracy from the integrative interactions and is easy to train end-to-end. Our method reports the new state-of-the-art performance on AVA dataset, with 3.7 mAP gain (12.6% relative improvement) on validation split comparing to our strong baseline. The results on dataset UCF101-24 and EPIC-Kitchens further illustrate the effectiveness of our approach. Source code will be made public at: https://github.com/MVIG-SJTU/AlphAction

Competing Ultrafast Energy Relaxation Pathways in Photoexcited Graphene

For most optoelectronic applications of graphene a thorough understanding of the processes that govern energy relaxation of photoexcited carriers is essential. The ultrafast energy relaxation in graphene occurs through two competing pathways: carrier-carrier scattering -- creating an elevated carrier temperature -- and optical phonon emission. At present, it is not clear what determines the dominating relaxation pathway. Here we reach a unifying picture of the ultrafast energy relaxation by investigating the terahertz photoconductivity, while varying the Fermi energy, photon energy, and fluence over a wide range. We find that sufficiently low fluence ($\lesssim$ 4 $\mu$J/cm$^2$) in conjunction with sufficiently high Fermi energy ($\gtrsim$ 0.1 eV) gives rise to energy relaxation that is dominated by carrier-carrier scattering, which leads to efficient carrier heating. Upon increasing the fluence or decreasing the Fermi energy, the carrier heating efficiency decreases, presumably due to energy relaxation that becomes increasingly dominated by phonon emission. Carrier heating through carrier-carrier scattering accounts for the negative photoconductivity for doped graphene observed at terahertz frequencies. We present a simple model that reproduces the data for a wide range of Fermi levels and excitation energies, and allows us to qualitatively assess how the branching ratio between the two distinct relaxation pathways depends on excitation fluence and Fermi energy.Comment: Nano Letters 201

Monocular Expressive Body Regression through Body-Driven Attention

To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image. Most existing methods focus only on parts of the body. A few recent approaches reconstruct full expressive 3D humans from images using 3D body models that include the face and hands. These methods are optimization-based and thus slow, prone to local optima, and require 2D keypoints as input. We address these limitations by introducing ExPose (EXpressive POse and Shape rEgression), which directly regresses the body, face, and hands, in SMPL-X format, from an RGB image. This is a hard problem due to the high dimensionality of the body and the lack of expressive training data. Additionally, hands and faces are much smaller than the body, occupying very few image pixels. This makes hand and face estimation hard when body images are downscaled for neural networks. We make three main contributions. First, we account for the lack of training data by curating a dataset of SMPL-X fits on in-the-wild images. Second, we observe that body estimation localizes the face and hands reasonably well. We introduce body-driven attention for face and hand regions in the original image to extract higher-resolution crops that are fed to dedicated refinement modules. Third, these modules exploit part-specific knowledge from existing face- and hand-only datasets. ExPose estimates expressive 3D humans more accurately than existing optimization methods at a small fraction of the computational cost. Our data, model and code are available for research at https://expose.is.tue.mpg.de .Comment: Accepted in ECCV'20. Project page: http://expose.is.tue.mpg.d

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino