456 research outputs found
Inner Space Preserving Generative Pose Machine
Image-based generative methods, such as generative adversarial networks
(GANs) have already been able to generate realistic images with much context
control, specially when they are conditioned. However, most successful
frameworks share a common procedure which performs an image-to-image
translation with pose of figures in the image untouched. When the objective is
reposing a figure in an image while preserving the rest of the image, the
state-of-the-art mainly assumes a single rigid body with simple background and
limited pose shift, which can hardly be extended to the images under normal
settings. In this paper, we introduce an image "inner space" preserving model
that assigns an interpretable low-dimensional pose descriptor (LDPD) to an
articulated figure in the image. Figure reposing is then generated by passing
the LDPD and the original image through multi-stage augmented hourglass
networks in a conditional GAN structure, called inner space preserving
generative pose machine (ISP-GPM). We evaluated ISP-GPM on reposing human
figures, which are highly articulated with versatile variations. Test of a
state-of-the-art pose estimator on our reposed dataset gave an accuracy over
80% on PCK0.5 metric. The results also elucidated that our ISP-GPM is able to
preserve the background with high accuracy while reasonably recovering the area
blocked by the figure to be reposed.Comment: http://www.northeastern.edu/ostadabbas/2018/07/23/inner-space-preserving-generative-pose-machine
Some closure operations in Zariski-Riemann spaces of valuation domains: a survey
In this survey we present several results concerning various topologies that
were introduced in recent years on spaces of valuation domains
Learning 3D Human Pose from Structure and Motion
3D human pose estimation from a single image is a challenging problem,
especially for in-the-wild settings due to the lack of 3D annotated data. We
propose two anatomically inspired loss functions and use them with a
weakly-supervised learning framework to jointly learn from large-scale
in-the-wild 2D and indoor/synthetic 3D data. We also present a simple temporal
network that exploits temporal and structural cues present in predicted pose
sequences to temporally harmonize the pose estimations. We carefully analyze
the proposed contributions through loss surface visualizations and sensitivity
analysis to facilitate deeper understanding of their working mechanism. Our
complete pipeline improves the state-of-the-art by 11.8% and 12% on Human3.6M
and MPI-INF-3DHP, respectively, and runs at 30 FPS on a commodity graphics
card.Comment: ECCV 2018. Project page: https://www.cse.iitb.ac.in/~rdabral/3DPose
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Determination of the vacancy formation enthalpy in chromium by positron annihilation
Doppler broadening of the positron annihilation lineshape in 99.99 at. % pure chromium was measured over the temperature range 296 to 2049/sup 0/K. The chromium sample was encapsulated in sapphire owing to its high vapor pressure near melting. Saturation-like behavior of the lineshape was observed near the melting temperature (2130/sup 0/K). A two-state trapping model fit to the data yielded a vacancy formation enthalpy of 2.0 +- 0.2 eV. This result is discussed in relation to extant empirical relations for vacancy migration and self-diffusion in metals and to data from previous self-diffusion and annealing experiments in chromium. It is concluded that the observed vacancy ensemble is unlikely to be responsible for the measured self-diffusion behavior. The implications of the present results in terms of our understanding of mechanisms for self-diffusion in chromium and other refractory bcc metals are discussed
Regulation of Cytosolic Phospholipase A 2 Activation and Cyclooxygenase 2 Expression in Macrophages by the β-Glucan Receptor
Phagocytosis of non-opsonized microorganisms by macrophages initiates innate immune responses for host defense against infection. Cytosolic phospholipase A(2) is activated during phagocytosis, releasing arachidonic acid for production of eicosanoids, which initiate acute inflammation. Our objective was to identify pattern recognition receptors that stimulate arachidonic acid release and cyclooxygenase 2 (COX2) expression in macrophages by pathogenic yeast and yeast cell walls. Zymosan- and Candida albicans-stimulated arachidonic acid release from resident mouse peritoneal macrophages was blocked by soluble glucan phosphate. In RAW264.7 cells arachidonic acid release, COX2 expression, and prostaglandin production were enhanced by overexpressing the beta-glucan receptor, dectin-1, but not dectin-1 lacking the cytoplasmic tail. Pure particulate (1, 3)-beta-D-glucan stimulated arachidonic acid release and COX2 expression, which were augmented in a Toll-like receptor 2 (TLR2)-dependent manner by macrophage-activating lipopeptide-2. However, arachidonic acid release and leukotriene C(4) production stimulated by zymosan and C. albicans were TLR2-independent, whereas COX2 expression and prostaglandin production were partially blunted in TLR2(-/-) macrophages. Inhibition of Syk tyrosine kinase blocked arachidonic acid release and COX2 expression in response to zymosan, C. albicans, and particulate (1, 3)-beta-D-glucan. The results suggest that cytosolic phospholipase A(2) activation triggered by the beta-glucan component of yeast is dependent on the immunoreceptor tyrosine-based activation motif-like domain of dectin-1 and activation of Syk kinase, whereas both TLR2 and Syk kinase regulate COX2 expression
Regulation of Cytosolic Phospholipase a\u3csub\u3e2\u3c/sub\u3e Activation and Cyclooxygenase 2 Expression in Macrophages by the β-Glucan Receptor
Phagocytosis of non-opsonized microorganisms bymacrophages initiates innate immune responses for host defense against infection. Cytosolic phospholipase A2 is activated during phagocytosis, releasing arachidonic acid for production of eicosanoids, which initiate acute inflammation. Our objective was to identify pattern recognition receptors that stimulate arachidonic acid release and cyclooxygenase 2 (COX2) expression in macrophages by pathogenic yeast and yeast cell walls. Zymosan- and Candida albicans-stimulated arachidonic acid release from resident mouse peritoneal macrophages was blocked by soluble glucan phosphate. In RAW264.7 cells arachidonic acid release, COX2 expression, and prostaglandin production were enhanced by overexpressing the β-glucan receptor, dectin-1, but not dectin-1 lacking the cytoplasmic tail. Pure particulate (1, 3)-β-D-glucan stimulated arachidonic acid release and COX2 expression, which were augmented in a Toll-like receptor 2 (TLR2)-dependent manner by macrophage-activating lipopeptide-2. However, arachidonic acid release and leukotriene C4 production stimulated by zymosan and C. albicans were TLR2-independent, whereas COX2 expression and prostaglandin production were partially blunted in TLR2-/- macrophages. Inhibition of Syk tyrosine kinase blocked arachidonic acid release and COX2 expression in response to zymosan, C. albicans, and particulate (1, 3)-β-D-glucan. The results suggest that cytosolic phospholipase A2 activation triggered by the β-glucan component of yeast is dependent on the immunoreceptor tyrosine-based activation motif-like domain of dectin-1 and activation of Syk kinase, whereas both TLR2 and Syk kinase regulate COX2 expression
Auto-labelling of Markers in Optical Motion Capture by Permutation Learning
Optical marker-based motion capture is a vital tool in applications such as
motion and behavioural analysis, animation, and biomechanics. Labelling, that
is, assigning optical markers to the pre-defined positions on the body is a
time consuming and labour intensive postprocessing part of current motion
capture pipelines. The problem can be considered as a ranking process in which
markers shuffled by an unknown permutation matrix are sorted to recover the
correct order. In this paper, we present a framework for automatic marker
labelling which first estimates a permutation matrix for each individual frame
using a differentiable permutation learning model and then utilizes temporal
consistency to identify and correct remaining labelling errors. Experiments
conducted on the test data show the effectiveness of our framework
Good Friends, Bad News - Affect and Virality in Twitter
The link between affect, defined as the capacity for sentimental arousal on
the part of a message, and virality, defined as the probability that it be sent
along, is of significant theoretical and practical importance, e.g. for viral
marketing. A quantitative study of emailing of articles from the NY Times finds
a strong link between positive affect and virality, and, based on psychological
theories it is concluded that this relation is universally valid. The
conclusion appears to be in contrast with classic theory of diffusion in news
media emphasizing negative affect as promoting propagation. In this paper we
explore the apparent paradox in a quantitative analysis of information
diffusion on Twitter. Twitter is interesting in this context as it has been
shown to present both the characteristics social and news media. The basic
measure of virality in Twitter is the probability of retweet. Twitter is
different from email in that retweeting does not depend on pre-existing social
relations, but often occur among strangers, thus in this respect Twitter may be
more similar to traditional news media. We therefore hypothesize that negative
news content is more likely to be retweeted, while for non-news tweets positive
sentiments support virality. To test the hypothesis we analyze three corpora: A
complete sample of tweets about the COP15 climate summit, a random sample of
tweets, and a general text corpus including news. The latter allows us to train
a classifier that can distinguish tweets that carry news and non-news
information. We present evidence that negative sentiment enhances virality in
the news segment, but not in the non-news segment. We conclude that the
relation between affect and virality is more complex than expected based on the
findings of Berger and Milkman (2010), in short 'if you want to be cited: Sweet
talk your friends or serve bad news to the public'.Comment: 14 pages, 1 table. Submitted to The 2011 International Workshop on
Social Computing, Network, and Services (SocialComNet 2011
General Automatic Human Shape and Motion Capture Using Volumetric Contour Cues
Markerless motion capture algorithms require a 3D body with properly personalized skeleton dimension and/or body shape and appearance to successfully track a person. Unfortunately, many tracking methods consider model personalization a different problem and use manual or semi-automatic model initialization, which greatly reduces applicability. In this paper, we propose a fully automatic algorithm that jointly creates a rigged actor model commonly used for animation - skeleton, volumetric shape, appearance, and optionally a body surface - and estimates the actor's motion from multi-view video input only. The approach is rigorously designed to work on footage of general outdoor scenes recorded with very few cameras and without background subtraction. Our method uses a new image formation model with analytic visibility and analytically differentiable alignment energy. For reconstruction, 3D body shape is approximated as Gaussian density field. For pose and shape estimation, we minimize a new edge-based alignment energy inspired by volume raycasting in an absorbing medium. We further propose a new statistical human body model that represents the body surface, volumetric Gaussian density, as well as variability in skeleton shape. Given any multi-view sequence, our method jointly optimizes the pose and shape parameters of this model fully automatically in a spatiotemporal way
The Effect of Iron Limitation on the Transcriptome and Proteome of Pseudomonas fluorescens Pf-5
One of the most important micronutrients for bacterial growth is iron, whose bioavailability in soil is limited. Consequently, rhizospheric bacteria such as Pseudomonas fluorescens employ a range of mechanisms to acquire or compete for iron. We investigated the transcriptomic and proteomic effects of iron limitation on P. fluorescens Pf-5 by employing microarray and iTRAQ techniques, respectively. Analysis of this data revealed that genes encoding functions related to iron homeostasis, including pyoverdine and enantio-pyochelin biosynthesis, a number of TonB-dependent receptor systems, as well as some inner-membrane transporters, were significantly up-regulated in response to iron limitation. Transcription of a ribosomal protein L36-encoding gene was also highly up-regulated during iron limitation. Certain genes or proteins involved in biosynthesis of secondary metabolites such as 2,4-diacetylphloroglucinol (DAPG), orfamide A and pyrrolnitrin, as well as a chitinase, were over-expressed under iron-limited conditions. In contrast, we observed that expression of genes involved in hydrogen cyanide production and flagellar biosynthesis were down-regulated in an iron-depleted culture medium. Phenotypic tests revealed that Pf-5 had reduced swarming motility on semi-solid agar in response to iron limitation. Comparison of the transcriptomic data with the proteomic data suggested that iron acquisition is regulated at both the transcriptional and post-transcriptional levels
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