Comparison of different measures for quantum discord under non-Markovian noise

Two geometric measures for quantum discord were recently proposed by Modi et al. [Phys. Rev. Lett. 104, 080501 (2010)] and Dakic et al. [Phys. Rev. Lett. 105, 190502 (2010)]. We study the similarities and differences for total quantum correlations of Bell-diagonal states using these two geometry-based quantum discord and the original quantum discord. We show that, under non-Markovian dephasing channels, quantum discord and one of the geometric measures stay constant for a finite amount of time, but not the other geometric measure. However, all the three measures share a common sudden change point. Our study on critical point of sudden transition might be useful for keeping long time total quantum correlations under decoherence.Comment: 10 pages, 3 figures submitted for publicatio

PTEN inhibitor bisperoxovanadium protects oligodendrocytes and myelin and prevents neuronal atrophy in adult rats following cervical hemicontusive spinal cord injury

Cervical spinal cord injury (SCI) damages axons and motor neurons responsible for ipsilateral forelimb function and causes demyelination and oligodendrocyte death. Inhibition of the phosphatase and tensin homologue, PTEN, promotes neural cell survival, neuroprotection and regeneration in vivo and in vitro. PTEN inhibition can also promote oligodendrocyte-mediated myelination of axons in vitro likely through Akt activation. We recently demonstrated that acute treatment with phosphatase PTEN inhibitor, bisperoxovanadium (bpV)-pic reduced tissue damage, neuron death, and promoted functional recovery after cervical hemi-contusion SCI. Evidence suggests bpV can promote myelin stability; however, bpV effects on myelination and oligodendrocytes in contusive SCI models are unclear. We hypothesized that bpV could increase myelin around the injury site through sparing or remyelination, and that bpV treatment may promote increased numbers of oligodendrocytes. Using histological and immunofluorescence labeling, we found that bpV treatment promoted significant spared white matter (30%; p < 0.01) and Luxol Fast Blue (LFB)+ myelin area rostral (Veh: 0.56 ± 0.01 vs. bpV: 0.64 ± 0.02; p < 0.05) and at the epicenter (Veh: 0.4175 ± 0.03 vs. bpV: 0.5400 ± 0.03; p < 0.05). VLF oligodendrocytes were also significantly greater with bpV therapy (109 ± 5.3 vs. Veh: 77 ± 2.7/mm2; p < 0.01). In addition, bpV increased mean motor neuron soma area versus vehicle-treatment (1.0 ± 0.02 vs. Veh: 0.77 ± 0.02) relative to Sham neuron size. This study provides key insight into additional cell and tissue effects that could contribute to bpV-mediated functional recovery observed after contusive cervical SCI

Thermalization of quark-gluon matter by 2-to-2 and 3-to-3 elastic scatterings

Thermalization of quark-gluon matter is studied with a transport equation that includes contributions of 2-to-2 and 3-to-3 elastic scatterings. Thermalization time is related to the squared amplitudes for the elastic scatterings that are calculated in perturbative QCD.Comment: LaTex, 6 pages, 3 figures, talk presented at the 19th international conference on ultra-relativistic nucleus-nucleus collisions, Shanghai, China, Nov. 200

Teaching about Madrid: A Collaborative Agents-Based Distributed Learning Course

Interactive art courses require a huge amount of computational resources to be running on real time. These computational resources are even bigger if the course has been designed as a Virtual Environment with which students can interact. In this paper, we present an initiative that has been develop in a close collaboration between two Spanish Universities: Universidad Politécnica de Madrid and Universidad Rey Juan Carlos with the aim of join two previous research project: a Collaborative Awareness Model for Task-Balancing-Delivery (CAMT) in clusters and the “Teaching about Madrid” course, which provides a cultural interactive background of the capital of Spain

Motion Deblurring in the Wild

The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object. Due to the complexity of the general image model we propose a novel convolutional network architecture which directly generates the sharp image.This network is built in three stages, and exploits the benefits of pyramid schemes often used in blind deconvolution. One of the main difficulties in training such a network is to design a suitable dataset. While useful data can be obtained by synthetically blurring a collection of images, more realistic data must be collected in the wild. To obtain such data we use a high frame rate video camera and keep one frame as the sharp image and frame average as the corresponding blurred image. We show that this realistic dataset is key in achieving state-of-the-art performance and dealing with occlusions