70 results match your criteria architecture expressive


Learning emotions latent representation with CVAE for text-driven expressive audiovisual speech synthesis.

Neural Netw 2021 Apr 21;141:315-329. Epub 2021 Apr 21.

Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France. Electronic address:

Great improvement has been made in the field of expressive audiovisual Text-to-Speech synthesis (EAVTTS) thanks to deep learning techniques. However, generating realistic speech is still an open issue and researchers in this area have been focusing lately on controlling the speech variability. In this paper, we use different neural architectures to synthesize emotional speech. Read More

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Partial corneal recovery following selective trabeculoplasty-induced keratopathy: Longitudinal analysis through scheimpflug imaging.

Am J Ophthalmol Case Rep 2021 Jun 26;22:101062. Epub 2021 Feb 26.

Glaucoma Unit, Hospital Medicina dos Olhos, 207, Salem Bechara Street, Osasco, São Paulo, 06018-180, Brazil.

Purpose: To report an uncommon case of hyperopic shift and corneal haze, flattening and thinning following a single session of selective laser trabeculoplasty (SLT), and provide longitudinal clinical data and serial analyses of corneal profile through Scheimpflug imaging. Furthermore, a careful literature review was undertaken to determine possible risk factors for this complication.

Observations: A 47-year-old woman presented with blurred vision and mild corneal edema and haze three days following routine SLT. Read More

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The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition.

PLoS Genet 2021 02 12;17(2):e1009144. Epub 2021 Feb 12.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Individual differences in early-life vocabulary measures are heritable and associated with subsequent reading and cognitive abilities, although the underlying mechanisms are little understood. Here, we (i) investigate the developmental genetic architecture of expressive and receptive vocabulary in early-life and (ii) assess timing of emerging genetic associations with mid-childhood verbal and non-verbal skills. We studied longitudinally assessed early-life vocabulary measures (15-38 months) and later-life verbal and non-verbal skills (7-8 years) in up to 6,524 unrelated children from the population-based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Read More

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February 2021

Coping on the inside: Design for therapeutic incarceration interventions - A case study.

Work 2021 ;68(1):97-106

University of Washington Department of Landscape Architecture, College of the Built Environments, Seattle, WA, USA.

Background: Adjusting to incarceration is traumatic. An under-utilized strategy understood to buffer and counteract the negative impacts of incarceration are nature interventions.

Objective: Outcomes of an interdisciplinary design studio course focused on developing masterplans for a women's prison in the Pacific Northwest (US) are presented. Read More

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January 2021

XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study.

JMIR Form Res 2020 Oct 16;4(10):e17512. Epub 2020 Oct 16.

Department of Humanities in Medicine, Texas A&M University, Bryan, TX, United States.

Background: Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. Read More

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October 2020

QRICH1 variants in Ververi-Brady syndrome-delineation of the genotypic and phenotypic spectrum.

Clin Genet 2021 Jan 10;99(1):199-207. Epub 2020 Nov 10.

Institute of Human Genetics, Heinrich-Heine-University, Düsseldorf, Germany.

Ververi-Brady syndrome (VBS, # 617982) is a rare developmental disorder, and loss-of-function variants in QRICH1 were implicated in its etiology. Furthermore, a recognizable phenotype was proposed comprising delayed speech, learning difficulties and dysmorphic signs. Here, we present four unrelated individuals with one known nonsense variant (c. Read More

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January 2021

The developmental origins of genetic factors influencing language and literacy: Associations with early-childhood vocabulary.

J Child Psychol Psychiatry 2021 Jun 14;62(6):728-738. Epub 2020 Sep 14.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Background: The heritability of language and literacy skills increases from early-childhood to adolescence. The underlying mechanisms are little understood and may involve (a) the amplification of genetic influences contributing to early language abilities, and/or (b) the emergence of novel genetic factors (innovation). Here, we investigate the developmental origins of genetic factors influencing mid-childhood/early-adolescent language and literacy. Read More

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Mimicry Embedding Facilitates Advanced Neural Network Training for Image-Based Pathogen Detection.

mSphere 2020 09 9;5(5). Epub 2020 Sep 9.

MRC-Laboratory for Molecular Cell Biology, University College London, London, United Kingdom

The use of deep neural networks (DNNs) for analysis of complex biomedical images shows great promise but is hampered by a lack of large verified data sets for rapid network evolution. Here, we present a novel strategy, termed "mimicry embedding," for rapid application of neural network architecture-based analysis of pathogen imaging data sets. Embedding of a novel host-pathogen data set, such that it mimics a verified data set, enables efficient deep learning using high expressive capacity architectures and seamless architecture switching. Read More

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September 2020

Nitrogen-Enriched CrAlN Multilayer-Like Coatings Manufactured by Dynamic Glancing Angle Direct Current Magnetron Sputtering.

Materials (Basel) 2020 Aug 18;13(16). Epub 2020 Aug 18.

São Carlos School of Engineering-EESC, University of São Paulo-USP, São Carlos-SP 13563-120, Brazil.

Multilayer-like CrN and CrAlN coatings with different Al contents were deposited onto a stainless steel substrate using dynamic glancing angle deposition direct current magnetron sputtering (DGLAD dcMS) in a N rich atmosphere to understand the role of Al on the growth of the films and mechanical properties of the nitrides with a multilayer architecture. Chemical analysis by means of energy dispersive analysis (EDS) and glow discharge optical emission spectroscopy (GDOES) depth profiling revealed that while CrN samples were close to stoichiometric, the CrAlN coatings presented excess N between 70 and 80% at. An expressive change in texture was observed as the CrN coating changed its preferred orientation from (111) to (200) with the addition of Al, followed by a modification in morphology from grains with faceted pyramidal tops in CrN to dome-shaped grains in CrAlN coatings. Read More

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k-hop graph neural networks.

Neural Netw 2020 Oct 10;130:195-205. Epub 2020 Jul 10.

École Polytechnique, France; Athens University of Economics and Business, Greece. Electronic address:

Graph neural networks (GNNs) have emerged recently as a powerful architecture for learning node and graph representations. Standard GNNs have the same expressive power as the Weisfeiler-Lehman test of graph isomorphism in terms of distinguishing non-isomorphic graphs. However, it was recently shown that this test cannot identify fundamental graph properties such as connectivity and triangle freeness. Read More

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October 2020

An End-to-End Reliability Framework of the Internet of Things.

Sensors (Basel) 2020 Apr 25;20(9). Epub 2020 Apr 25.

EI Research Team, École Nationale des Sciences Appliquées d'Oujda (ENSAO), Université Mohammed Premier (UMP), 60000 Oujda, Morocco.

The Internet of Things (IoT) paradigm feeds from many scientific and engineering fields. This involves a diversity and heterogeneity of its underlying systems. When considering End-to-End IoT systems, we can identify the emergence of new classes of problems. Read More

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A Methodology for Assessing the Probability of Occurrence of Undesired Events in the Tietê-Paraná Inland Waterway Based on Expert Opinion.

Risk Anal 2020 06 17;40(6):1279-1301. Epub 2020 Mar 17.

Department of Mechanical Engineering, University of Chile, Santiago, Chile.

The market share of Tietê-Paraná inland waterway (TPIW) in the transport matrix of the São Paulo state, Brazil, is currently only 0.6%, but it is expected to increase to 6% over the next 20 years. In this scenario, to identify and explore potential undesired events a risk assessment is necessary. Read More

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A Multimodal Emotional Human-Robot Interaction Architecture for Social Robots Engaged in Bidirectional Communication\vspace*7pt.

IEEE Trans Cybern 2020 Mar 6. Epub 2020 Mar 6.

For social robots to effectively engage in human-robot interaction (HRI), they need to be able to interpret human affective cues and to respond appropriately via display of their own emotional behavior. In this article, we present a novel multimodal emotional HRI architecture to promote natural and engaging bidirectional emotional communications between a social robot and a human user. User affect is detected using a unique combination of body language and vocal intonation, and multimodal classification is performed using a Bayesian Network. Read More

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A Compositional Neural Architecture for Language.

Authors:
Andrea E Martin

J Cogn Neurosci 2020 08 28;32(8):1407-1427. Epub 2020 Feb 28.

Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.

Hierarchical structure and compositionality imbue human language with unparalleled expressive power and set it apart from other perception-action systems. However, neither formal nor neurobiological models account for how these defining computational properties might arise in a physiological system. I attempt to reconcile hierarchy and compositionality with principles from cell assembly computation in neuroscience; the result is an emerging theory of how the brain could convert distributed perceptual representations into hierarchical structures across multiple timescales while representing interpretable incremental stages of (de)compositional meaning. Read More

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Universal approximation with quadratic deep networks.

Neural Netw 2020 Apr 18;124:383-392. Epub 2020 Jan 18.

Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA. Electronic address:

Recently, deep learning has achieved huge successes in many important applications. In our previous studies, we proposed quadratic/second-order neurons and deep quadratic neural networks. In a quadratic neuron, the inner product of a vector of data and the corresponding weights in a conventional neuron is replaced with a quadratic function. Read More

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Deep Autoregressive Models for the Efficient Variational Simulation of Many-Body Quantum Systems.

Phys Rev Lett 2020 Jan;124(2):020503

The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.

Artificial neural networks were recently shown to be an efficient representation of highly entangled many-body quantum states. In practical applications, neural-network states inherit numerical schemes used in variational Monte Carlo method, most notably the use of Markov-chain Monte Carlo (MCMC) sampling to estimate quantum expectations. The local stochastic sampling in MCMC caps the potential advantages of neural networks in two ways: (i) Its intrinsic computational cost sets stringent practical limits on the width and depth of the networks, and therefore limits their expressive capacity; (ii) its difficulty in generating precise and uncorrelated samples can result in estimations of observables that are very far from their true value. Read More

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January 2020

Emotion recognition ability: Evidence for a supramodal factor and its links to social cognition.

Cognition 2020 04 15;197:104166. Epub 2020 Jan 15.

Department of Psychology, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK.

Accurate recognition of others' emotions is an important skill for successful social interaction. Unsurprisingly, it has been an enduring topic of interest, and notable individual differences have been observed. Despite this focus, the underlying functional architecture of this ability has not been thoroughly investigated, particularly concerning emotion recognition across different sensory domains and stimulus modalities. Read More

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Multi-Scale Learned Iterative Reconstruction.

IEEE Trans Comput Imaging 2020 27;6:843-856. Epub 2020 Apr 27.

Department of Mathematics, KTH - Royal Institute of Technology, Stockholm, Sweden.

Model-based learned iterative reconstruction methods have recently been shown to outperform classical reconstruction algorithms. Applicability of these methods to large scale inverse problems is however limited by the available memory for training and extensive training times, the latter due to computationally expensive forward models. As a possible solution to these restrictions we propose a multi-scale learned iterative reconstruction scheme that computes iterates on discretisations of increasing resolution. Read More

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Small angle X-ray scattering based structure, modeling and molecular dynamics analyses of family 43 glycoside hydrolase α-L-arabinofuranosidase from .

J Biomol Struct Dyn 2021 Jan 30;39(1):209-218. Epub 2019 Dec 30.

Carbohydrate Enzyme Biotechnology Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India.

Enzymes that participate in the hydrolysis of complex carbohydrates display a modular architecture, although the significance of enzyme modularity to flexibility and catalytic efficacy is not fully understood. α-L-arabinofuranosidase from (Araf43) catalyzes the release of α-1,2-, α-1,3-, or α-1,5- linked L-arabinose from arabinose decorated polysaccharides. Araf43 comprises an N-terminal catalytic domain (Abf43A) connected with two family 6 carbohydrate-binding modules (CBMs), termed as CBM6A and CBM6B, through flexible linker peptides. Read More

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January 2021

The Nature of the Task Influences Intrinsic Connectivity Networks: An Exploratory fMRI Study in Healthy Subjects.

Int IEEE EMBS Conf Neural Eng 2019 Mar 20;2019:489-493. Epub 2019 May 20.

Research Centre for Motor Control and Neuroplasticity, KU Leuven.

Task-induced variations in neural activity and their effects on the topological architecture of intrinsic connectivity networks (ICNs) of the brain are still a matter of ongoing research. In this exploratory study, we used spatial independent component analysis (ICA) as a data-driven technique to characterize ICNs related to two different tasks in healthy subjects who underwent 3T blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI). The fMRI tasks consisted of (a) a viscerosensory stimulation of an internal organ (interoceptive task), and (b) passive viewing of emotionally expressive faces and pictures from the International Affective Picture System (exteroceptive emotion task). Read More

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Feature Pyramid Reconfiguration with Consistent Loss for Object Detection.

IEEE Trans Image Process 2019 May 24. Epub 2019 May 24.

Taking the feature pyramids into account has become a crucial way to boost the object detection performance. While various pyramid representations have been developed, previous works are still inefficient to integrate the semantical information over different scales. Moreover, recent object detectors are suffering from accurate object location applications, mainly due to the coarse definition of the "positive" examples at training and predicting phases. Read More

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Direct automated quantitative measurement of spine by cascade amplifier regression network with manifold regularization.

Med Image Anal 2019 07 22;55:103-115. Epub 2019 Apr 22.

Department of Medical Imaging, Western University, ON, Canada; Digital Image Group, London, ON, Canada. Electronic address:

Automated quantitative measurement of the spine (i.e., multiple indices estimation of heights, widths, areas, and so on for the vertebral body and disc) plays a significant role in clinical spinal disease diagnoses and assessments, such as osteoporosis, intervertebral disc degeneration, and lumbar disc herniation, yet still an unprecedented challenge due to the variety of spine structure and the high dimensionality of indices to be estimated. Read More

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Segmenting and classifying activities in robot-assisted surgery with recurrent neural networks.

Int J Comput Assist Radiol Surg 2019 Nov 29;14(11):2005-2020. Epub 2019 Apr 29.

Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.

Purpose: Automatically segmenting and classifying surgical activities is an important prerequisite to providing automated, targeted assessment and feedback during surgical training. Prior work has focused almost exclusively on recognizing gestures, or short, atomic units of activity such as pushing needle through tissue, whereas we also focus on recognizing higher-level maneuvers, such as suture throw. Maneuvers exhibit more complexity and variability than the gestures from which they are composed, however working at this granularity has the benefit of being consistent with existing training curricula. Read More

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November 2019

Combining MRF-based deformable registration and deep binary 3D-CNN descriptors for large lung motion estimation in COPD patients.

Int J Comput Assist Radiol Surg 2019 Jan 14;14(1):43-52. Epub 2018 Nov 14.

Institute of Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.

Purpose: Deep convolutional neural networks in their various forms are currently achieving or outperforming state-of-the-art results on several medical imaging tasks. We aim to make these developments available to the so far unsolved task of accurate correspondence finding-especially with regard to image registration.

Methods: We propose a two-step hybrid approach to make deep learned features accessible to a discrete optimization-based registration method. Read More

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January 2019

Functional Networks for Social Communication in the Macaque Monkey.

Neuron 2018 07 12;99(2):413-420.e3. Epub 2018 Jul 12.

The Laboratory of Neural Systems, The Rockefeller University, New York, NY 10065, USA. Electronic address:

All primates communicate. To dissect the neural circuits of social communication, we used fMRI to map non-human primate brain regions for social perception, second-person (interactive) social cognition, and orofacial movement generation. Face perception, second-person cognition, and face motor networks were largely non-overlapping and acted as distinct functional units rather than an integrated feedforward-processing pipeline. Read More

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Pomona Large Vessel Occlusion Screening Tool for Prehospital and Emergency Room Settings.

Interv Neurol 2018 Apr 13;7(3-4):196-203. Epub 2018 Feb 13.

Pomona Valley Hospital, Pomona, California, USA.

Background: Early identification of patients with acute ischemic strokes due to large vessel occlusions (LVO) is critical. We propose a simple risk score model to predict LVO.

Method: The proposed scale (Pomona Scale) ranges from 0 to 3 and includes 3 items: gaze deviation, expressive aphasia, and neglect. Read More

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Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors.

Sensors (Basel) 2018 Feb 13;18(2). Epub 2018 Feb 13.

Nextel S. A., Technological Park of Bizkaia 207B, 1B, 48170 Zamudio, Spain.

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Read More

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February 2018

The Roles of Left Versus Right Anterior Temporal Lobes in Semantic Memory: A Neuropsychological Comparison of Postsurgical Temporal Lobe Epilepsy Patients.

Cereb Cortex 2018 04;28(4):1487-1501

Neuroscience and Aphasia Research Unit (NARU), University of Manchester, Manchester M13 9PL, UK.

The presence and degree of specialization between the anterior temporal lobes (ATLs) is a key issue in debates about the neural architecture of semantic memory. Here, we comprehensively assessed multiple aspects of semantic cognition in a large group of postsurgical temporal lobe epilepsy (TLE) patients with left versus right anterior temporal lobectomy (n = 40). Both subgroups showed deficits in expressive and receptive verbal semantic tasks, word and object recognition, naming and recognition of famous faces and perception of faces and emotions. Read More

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Expressive Faces Confuse Identity.

Iperception 2017 Sep-Oct;8(5):2041669517731115. Epub 2017 Sep 19.

University of Bristol, UK.

We used highly variable, so-called 'ambient' images to test whether expressions affect the identity recognition of real-world facial images. Using movie segments of two actors unknown to our participants, we created image pairs - each image within a pair being captured from the same film segment. This ensured that, within pairs, variables such as lighting were constant whilst expressiveness differed. Read More

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September 2017

Error bounds for approximations with deep ReLU networks.

Authors:
Dmitry Yarotsky

Neural Netw 2017 Oct 13;94:103-114. Epub 2017 Jul 13.

Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Building 3, Moscow 143026, Russia; Institute for Information Transmission Problems, Bolshoy Karetny per. 19, Building 1, Moscow 127051, Russia. Electronic address:

We study expressive power of shallow and deep neural networks with piece-wise linear activation functions. We establish new rigorous upper and lower bounds for the network complexity in the setting of approximations in Sobolev spaces. In particular, we prove that deep ReLU networks more efficiently approximate smooth functions than shallow networks. Read More

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October 2017