Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A Nature Research Journal. The symmetry, magnitude and origin of spin—orbit torques SOTshowever, remain a matter of debate. We provide a general scheme to measure the amplitude and direction of SOTs as a function of the magnetization direction.

Such torques include strongly anisotropic field-like and spin transfer-like components, which depend on the type of heavy metal layer and annealing treatment. These results call for SOT models that go beyond the spin Hall and Rashba effects investigated thus far.

Chappert, C. The emergence of spin electronics in data storage. Nature Mater. Brataas, A. Current-induced torques in magnetic materials. Ralph, D. Spin transfer torques. Chernyshov, A. Evidence for reversible control of magnetization in a ferromagnetic material by means of spin—orbit magnetic field.

Nature Phys. Miron, I. Current-driven spin torque induced by the Rashba effect in a ferromagnetic metal layer. Pi, U. Tilting of the spin orientation induced by Rashba effect in ferromagnetic metal layer.

International Journal of Clinical Virology

Fang, D. Spin—orbit-driven ferromagnetic resonance. Nature Nanotech. Suzuki, T. Perpendicular switching of a single ferromagnetic layer induced by in-plane current injection. Nature— Kajiwara, Y. Transmission of electrical signals by spin—wave interconversion in a magnetic insulator. Kurebayashi, H.

Controlled enhancement of spin-current emission by three-magnon splitting. Liu, L.PDF Code Slides. PDF Code. PDF supp.

PDF Source Document. PDF Code supp. PDF Code Dataset. Type Conference paper Journal article Report Book section. Date Huan LiZhouchen Lin.

ijcv 2013 article

JMLR, CVPR, AAAI, JSC, TNNLS, TPAMI, ICCV, Yan ZhengZhouchen Lin. TIP, Subspace Clustering under Complex Noise. TCSVT, Subspace Clustering by Block Diagonal Representation. Lifted Proximal Operator Machines. NN, PRCV, ICML, Two-weight and three-weight linear codes based on Weil sums. FFTA, COLT, PAMI, ECCV, JSTSP, Antiviral activity of Eucalyptus camaldulensis leaves ethanolic extract on herpes viruses infection. Int J Clin Virol. DOI: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Eucalyptus camaldulensis Ec is considered as a traditional medicinal plant with valuable therapeutic effects. Here we evaluated the antiviral activity of its ethanolic leave extract on different herpes viruses. Vero cells were infected with either of the tested viruses [herpes simplex virus -1 and 2 HSV-1, HSV-2 and Varicella-Zoster Virus VZV ] with or without treatment with Ec extract and viral infection development was evaluated by plaque assay.

Our results showed significant antiviral activity of the examined extract against all tested viruses. The highest antiviral effect of this fraction was obtained mainly when it was added during and post infection p. Viral infections are considered as one of the major causes of death worldwide despite the significant progress made in antiviral drug development [1,3].

Herpes viruses are DNA v belonging to the family Herpesviridae and are responsible for a variety of mild to severe human diseases, which are sometimes life threatening particularly in immune-comprised patients and neonates [4,5].

After the acute infection, herpes viruses establish latency and persist in different cells of the body, according to the infecting virus, for the life-time. The latent virus is reactivated spontaneously causing recurrent infections in infected patients [6]. Although it can effectively be treated with nucleoside analogs such as acyclovir ACVbut still the search for new effective anti-herpetic drugs is important due to the development of ACV - resistant herpes viruses mutants particularly in immunosuppressed and in immunodeficiency syndrome patients [].

In addition, ACV and other available nucleoside analogs have different undesired side effects like nausea, vomiting, headache and others [16] and are not highly effective against reactivated herpes viruses [17,18].

Therefore, there is a need for novel effective anti-herpetic drugs with different mode of action from nucleoside derivatives. Many natural products are known with their antiviral activity and part of them has been already used for the treatment of human viral infections with RNA and DNA viruses [18,22]. Different secondary plant metabolites such as flavonoids, saponins, lignans, tannins, alkoloids, polyines, thiophenes, phenolic acids and different sugars were found to have significant antiviral activity against variety of viruses [23,25].

Despite the fact that many plant extracts were previously reported for their antiviral activities, their antiviral mechanism of action is still poorly understood. Eucalyptus camaldulensis Ec is an Australian native tree of the genus Eucalyptus and spread in many parts of the world [26]. According to the World Health Organization and different previous studies Eucalyptus leaves and oil have medicinal use for treatment of mild respiratory tract inflammation, bronchitis, asthma, fever and inflammation of the throat [27,28].

In addition, eight different components were isolated from Eucalyptus globulus leaves and found to have antiviral activity against Epstein Barr virus [29].

The main biologically active components in Eucalyptus essential oil are erpenes and phenylpropanoids [31,33].Computational Vision at UC Irvine. We present an extensive three year study on economically annotating video with crowdsourced marketplaces. Our public framework has annotated thousands of real world videos, including massive data sets unprecedented for their size, complexity, and cost.

To accomplish this, we designed a state-of-the-art video annotation user interface and demonstrate that, despite common intuition, many contemporary interfaces are sub-optimal. We present several user studies that evaluate different aspects of our system and demonstrate that minimizing the cognitive load of the user is crucial when designing an annotation platform. We then deploy this interface on Amazon Mechanical Turk and discover expert and talented workers who are capable of annotating difficult videos with dense and closely cropped labels.

We argue that video annotation requires specialized skill; most workers are poor annotators, mandating robust quality control protocols. We show that traditional crowdsourced micro-tasks are not suitable for video annotation and instead demonstrate that deploying time-consuming macro-tasks on MTurk is effective. Finally, we show that by extracting pixel-based features from manually labeled key frames, we are able to leverage more sophisticated interpolation strategies to maximize performance given a fixed budget.

We validate the power of our framework on difficult, real-world data sets and we demonstrate an inherent trade-off between the mix of human and cloud computing used vs.

Appreciation to IJCV Reviewers

We further introduce a novel, cost-based evaluation criteria that compares vision algorithms by the budget required to achieve an acceptable performance. We hope our findings will spur innovation in the creation of massive labeled video data sets and enable novel data-driven computer vision applications.

Efficiently scaling up crowdsourced video annotation - a set of best practices for high quality, economical video labeling. International Journal of Computer Vision1 —, The following are the papers to my knowledge being cited the most in Computer Vision. A threshold selection method from gray-level histograms.

Snakes: Active contour models. Eigenfaces for Recognition. Determining optical flow. Scale-space and edge detection using anisotropic diffusion. Rapid object detection using a boosted cascade of simple features. Computer Vision and Pattern Recognition, CVPR Proceedings of the …. Active contours without edges.

An iterative image registration technique with an application to stereo vision. Lucas and T. KanadeAn iterative image registration technique with an application to stereo vision. Proceedings of Imaging Understanding Workshop, pages — Normalized cuts and image segmentation.

Histograms of oriented gradients for human detection. N Dalal… — … Performance of optical flow techniques. A performance evaluation of local descriptors.Gabriel M. Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States.

Goel, James Davis, Michael Bernstein. Lawrence Zitnick, Ross Girshick. Greene, Diane M. Beck, Li Fei-Fei.

Alliance for Integrity Kick-Off Conference, India 2013

Marie E. Berg, Li Fei-Fei.

ijcv 2013 article

Berg and Li Fei-Fei. Action Recognition with Exemplar Based 2. Distributed cosegmentation vis submodular optimization on anisotropic diffusion. Simple line drawings suffice for functional MRI decoding of natural scene categories. What does classifying more than 10, image categories tell us? What, Where and Who?

To err is human: investigating neural function by correlating error patterns with human behavior. Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories. Neural mechanisms of rapid natural scene categorization in human visual cortex. Natural scene categories revealed in distributed patterns of activity in the human brain. Towards scalable dataset construction: An active learning approach.

ijcv 2013 article

View synthesis for recognizing unseen poses of object classes. Unsupervised learning of human action categories using spatial-temporal words. Spatial-temporal correlations for unsupervised action classification. What, where and who? Classifying event by scene and object recognition.The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images.

The challenge has been run annually from to present, attracting participation from more than fifty institutions.

This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field of large-scale image classification and object detection, and compare the state-of-the-art computer vision accuracy with human accuracy.

This is a preview of subscription content, log in to check access. Rent this article via DeepDyve. In this paper, we will be using the term object recognition broadly to encompass both image classification a task requiring an algorithm to determine what object classes are present in the image as well as object detection a task requiring an algorithm to localize all objects present in the image. Inthe test annotations were later released publicly; since then the test annotation have been kept hidden.

We chose not to provide this level of detail in favor of annotating more images and more object instances. This is done for simplicity and is justified since the ordering of teams by mean average precision was always the same as the ordering by object categories won. For rigid versus deformable objects, the average scale in each bin is For texture, the average scale in each of the four bins is Natural object detection classes are removed from this analysis because there are only 3 and 13 natural untextured and low-textured classes respectively, and none remain after scale normalization.

All other bins contain at least 9 object classes after scale normalization. Ahonen, T. Face description with local binary patterns: Application to face recognition. Pattern Analysis and Machine Intelligence28 14— Alexe, B.

Measuring the objectness of image windows. Arandjelovic, R. Three things everyone should know to improve object retrieval. In CVPR. Multiscale combinatorial grouping. In Computer vision and pattern recognition. Arbelaez, P. Contour detection and hierarchical image segmentation. Batra, D. Cloudcv: Large-scale distributed computer vision as a cloud service. Bell, S. OpenSurfaces: A richly annotated catalog of surface appearance.