The Sub-Surface Structure of a Large Sample of Active Regions

We employ ring-diagram analysis to study the sub-surface thermal structure of active regions. We present results using a large number of active regions over the course of Solar Cycle 23. We present both traditional inversions of ring-diagram frequency differences, with a total sample size of 264, and a statistical study using Principal Component Analysis. We confirm earlier results on smaller samples that sound speed and adiabatic index are changed below regions of strong magnetic field. We find that sound speed is decreased in the region between approximately r=0.99R_sun and r=0.995R_sun (depths of 3Mm to 7Mm), and increased in the region between r=0.97R_sun and r=0.985R_sun (depths of 11Mm to 21Mm). The adiabatic index is enhanced in the same deeper layers that sound-speed enhancement is seen. A weak decrease in adiabatic index is seen in the shallower layers in many active regions. We find that the magnitudes of these perturbations depend on the strength of the surface magnetic field, but we find a great deal of scatter in this relation, implying other factors may be relevant.Comment: 16 pages, 11 figures, accepted for publication in Solar Physic

Closed timelike curves via post-selection: theory and experimental demonstration

Closed timelike curves (CTCs) are trajectories in spacetime that effectively travel backwards in time: a test particle following a CTC can in principle interact with its former self in the past. CTCs appear in many solutions of Einstein's field equations and any future quantum version of general relativity will have to reconcile them with the requirements of quantum mechanics and of quantum field theory. A widely accepted quantum theory of CTCs was proposed by Deutsch. Here we explore an alternative quantum formulation of CTCs and show that it is physically inequivalent to Deutsch's. Because it is based on combining quantum teleportation with post-selection, the predictions/retrodictions of our theory are experimentally testable: we report the results of an experiment demonstrating our theory's resolution of the well-known `grandfather paradox.Comment: 5 pages, 4 figure

EFL GTPase in Cryptomonads and the Distribution of EFL and EF-1a in Chromalveolates

EFL (EF-like protein) is a member of the GTPase superfamily that includes several translation factors. Because it has only been found in a few eukaryotic lineages and its presence correlates with the absence of the related core translation factor EF-1a, its distribution is hypothesized to be the result of lateral gene transfer and replacement of EF-1a. In one supergroup of eukaryotes, the chromalveolates, two major lineages were found to contain EFL (dinoflagellates and haptophytes), while the others encode EF-1a (apicomplexans, ciliates, heterokonts and cryptomonads). For each of these groups, this distribution was deduced from whole genome sequence or expressed sequence tag (EST) data from several species, with the exception of cryptomonads from which only a single EF-1a PCR product from one species was known. By sequencing ESTs from two cryptomonads, Guillardia theta and Rhodomonas salina, and searching for all GTPase translation factors, we revealed that EFL is present in both species, but, contrary to expectations, we found EF-1a in neither. On balance, we suggest the previously reported EF-1a from Rhodomonas salina is likely an artefact of contamination. We also identified EFL in EST data from two members of the dinoflagellate lineage, Karlodinium micrum and Oxyrrhis marina, and from an ongoing genomic sequence project from a third, Perkinsus marinus. Karlodinium micrum is a symbiotic pairing of two lineages that would have both had EFL (a dinoflagellate and a haptophyte), but only the dinoflagellate gene remains. Oxyrrhis marina and Perkinsus marinus are early diverging sister-groups to dinoflagellates, and together show that EFL originated early in this lineage. Phylogenetic analysis confirmed that these genes are all EFL homologues, and showed that cryptomonad genes are not detectably related to EFL from other chromalveolates, which collectively form several distinct groups. The known distribution of EFL now includes a third group of chromalveolates, cryptomonads. Of the six major subgroups of chromalveolates, EFL is found in half and EF-1a in the other half, and none as yet unambiguously possess both genes. Phylogenetic analysis indicates EFL likely arose early within each subgroup where it is found, but suggests it may have originated multiple times within chromalveolates as a whole

Methods for Analysis of Matrix Metalloproteinase Regulation of Neutrophil-Endothelial Cell Adhesion

Recent evidence indicates novel role for matrix metalloproteinases (MMPs), in particular gelatinase A (MMP-2), in the regulation of vascular biology that are unrelated to their well-known proteolytic breakdown of matrix proteins. We have previously reported that MMP-2 can modulate vascular reactivity by cleavage of the Gly32-Leu33 bound in big endothelin-1 (ET-1) yielding a novel vasoactive peptide ET-1[1-32]. These studies were conducted to investigate whether gelatinolytic MMPs could affect neutrophil-endothelial cell attachment. ET-1[1-32] produced by MMP-2 up-regulated CD11b/CD18 expression on human neutrophils, thereby promoted their adhesion to cultured endothelial cells. ET-1[1-32] evoked release of gelatinase B (MMP-9), which in turn cleaved big ET-1 to yield ET-1[1-32], thus revealing a self-amplifying loop for ET-1[1-32] generation. ET-1[1-32] was rather resistant to cleavage by neutrophil proteases and further metabolism of ET-1[1-32] was not a prerequisite for its biological actions on neutrophils. The neutrophil responses to ET-1[1-32] were mediated via activation of ET(A)receptors through activation of the Ras/Raf-1/MEK/ERK signaling pathway. These results suggest a novel role for gelatinase A and B in the regulation of neutrophil functions and their interactions with endothelial cells. Here we describe the methods in detail as they relate to our previously published work

Китайські джерела щодо центральноазійського виміру політики КНР у галузі регіональній безпеки в постбіполярний період

We propose a method for detecting dyadic interactions: fine-grained, coordinated interactions between two people. Our model is capable of recognizing interactions such as a hand shake or a high five, and locating them in time and space. At the core of our method is a pictorial structures model that additionally takes into account the fine-grained movements around the joints of interest during the interaction. Compared to a bag-of-words approach, our method not only allows us to detect the specific type of actions more accurately, but it also provides the specific location of the interaction. The model is trained with both video data and body joint estimates obtained from Kinect. During testing, only video data is required. To demonstrate the efficacy of our approach, we introduce the ShakeFive dataset that consists of videos and Kinect data of hand shake and high five interactions. On this dataset, we obtain a mean average precision of 49.56%, outperforming a bag-of-words approach by 23.32%. We further demonstrate that the model can be learned from just a few interactions

Electromagnetic channel capacity for practical purposes

We give analytic upper bounds to the channel capacity C for transmission of classical information in electromagnetic channels (bosonic channels with thermal noise). In the practically relevant regimes of high noise and low transmissivity, by comparison with know lower bounds on C, our inequalities determine the value of the capacity up to corrections which are irrelevant for all practical purposes. Examples of such channels are radio communication, infrared or visible-wavelength free space channels. We also provide bounds to active channels that include amplification.Comment: 6 pages, 3 figures. NB: the capacity bounds are constructed by generalizing to the multi-mode case the minimum-output entropy bounds of arXiv:quant-ph/0404005 [Phys. Rev. A 70, 032315 (2004)

Interpreting Helioseismic Structure Inversion Results of Solar Active Regions

Helioseismic techniques such as ring-diagram analysis have often been used to determine the subsurface structural differences between solar active and quiet regions. Results obtained by inverting the frequency differences between the regions are usually interpreted as the sound-speed differences between them. These in turn are used as a measure of temperature and magnetic-field strength differences between the two regions. In this paper we first show that the "sound-speed" difference obtained from inversions is actually a combination of sound-speed difference and a magnetic component. Hence, the inversion result is not directly related to the thermal structure. Next, using solar models that include magnetic fields, we develop a formulation to use the inversion results to infer the differences in the magnetic and thermal structures between active and quiet regions. We then apply our technique to existing structure inversion results for different pairs of active and quiet regions. We find that the effect of magnetic fields is strongest in a shallow region above 0.985R_sun and that the strengths of magnetic-field effects at the surface and in the deeper (r < 0.98R_sun) layers are inversely related, i.e., the stronger the surface magnetic field the smaller the magnetic effects in the deeper layers, and vice versa. We also find that the magnetic effects in the deeper layers are the strongest in the quiet regions, consistent with the fact that these are basically regions with weakest magnetic fields at the surface. Because the quiet regions were selected to precede or follow their companion active regions, the results could have implications about the evolution of magnetic fields under active regions.Comment: Accepted for publication in Solar Physic

Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition

Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a breakthrough for Image classification and showing promise for videos, has still not clearly superseded action recognition methods using hand-crafted features, even when training on massive datasets. In this paper, we introduce hybrid video classification architectures based on carefully designed unsupervised representations of hand-crafted spatio-temporal features classified by supervised deep networks. As we show in our experiments on five popular benchmarks for action recognition, our hybrid model combines the best of both worlds: it is data efficient (trained on 150 to 10000 short clips) and yet improves significantly on the state of the art, including recent deep models trained on millions of manually labelled images and videos

Elevated Peripheral Neutrophils and Matrix Metalloproteinase 9 as Biomarkers of Functional Outcome Following Subarachnoid Hemorrhage

There is growing evidence supporting the role of inflammation in early brain injury and cerebral vasospasm following subarachnoid hemorrhage (SAH). Matrix metalloproteinases (MMPs) are released by inflammatory cells and can mediate early brain injury via disruption of the extracellular matrix and mediate vasospasm by cleaving endothelin-1 into vasoactive fragments. We hypothesize that inflammation marked by neutrophil elevation and MMP-9 release in human SAH is associated with vasospasm and with poor clinical outcome. We enrolled consecutive SAH subjects (N = 55), banked serial blood and cerebrospinal fluid (CSF) samples, and evaluated their 3-month modified Rankin scores (mRS). Vasospasm was defined as >50% vessel caliber reduction on angiography 6–8 days post-SAH. A poor outcome was defined as mRS > 2. We compared blood leukocyte and neutrophil counts during post-SAH days 0–14 with respect to vasospasm and 3-month outcome. In a subset of SAH subjects (N = 35), we compared blood and CSF MMP-9 by enzyme-linked immunosorbent assay (ELISA) on post-SAH days 0–1, 2–3, 4–5, 6–8, and 10–14 with respect to vasospasm and to 3-month outcome. Persistent elevation of blood leukocyte (p = 0.0003) and neutrophil (p = 0.0002) counts during post-SAH days 0–14 are independently associated with vasospasm after adjustment for major confounders. In the same time period, blood neutrophil count (post-SAH days 2–3, p = 0.018), blood MMP-9 (post-SAH days 4–5, p = 0.045), and CSF MMP-9 (post-SAH days 2–3, p = 0.05) are associated with poor 3-month SAH clinical outcome. Neutrophil count correlates with blood MMP-9 (post-SAH days 6–8, R = 0.39; p = 0.055; post-SAH days 10–14, R = 0.79; p < 0.0001), and blood MMP-9 correlates with CSF MMP-9 (post-SAH days 4–5, R = 0.72; p = 0.0002). Elevation of CSF MMP-9 during post-SAH days 0–14 is associated with poor 3-month outcome (p = 0.0078). Neither CSF nor blood MMP-9 correlates with vasospasm. Early rise in blood neutrophil count and blood and CSF MMP-9 are associated with poor 3-month SAH clinical outcome. In blood, neutrophil count correlates with MMP-9 levels, suggesting that neutrophils may be an important source of blood MMP-9 early in SAH. Similarly, CSF and blood MMP-9 correlate positively early in the course of SAH, suggesting that blood may be an important source of CSF MMP-9. Blood and CSF MMP-9 are associated with clinical outcome but not with vasospasm, suggesting that MMP-9 may mediate brain injury independent of vasospasm in SAH. Future in vitro studies are needed to investigate the role of MMP-9 in SAH-related brain injury. Larger clinical studies are needed to validate blood and CSF MMP-9 as potential biomarkers for SAH outcome