Waseda University

About: Waseda University is a education organization based out in Tokyo, Japan. It is known for research contribution in the topics: Catalysis & Large Hadron Collider. The organization has 24220 authors who have published 46859 publications receiving 837855 citations. The organization is also known as: Waseda daigaku & Sōdai.

A Circadian Clock Gene, Rev-erbα, Modulates the Inflammatory Function of Macrophages through the Negative Regulation of Ccl2 Expression

Abstract: Disruption of the circadian rhythm is a contributory factor to clinical and pathophysiological conditions, including cancer, the metabolic syndrome, and inflammation. Chronic and systemic inflammation are a potential trigger of type 2 diabetes and cardiovascular disease and are caused by the infiltration of large numbers of inflammatory macrophages into tissue. Although recent studies identified the circadian clock gene Rev-erbα, a member of the orphan nuclear receptors, as a key mediator between clockwork and inflammation, the molecular mechanism remains unknown. In this study, we demonstrate that Rev-erbα modulates the inflammatory function of macrophages through the direct regulation of Ccl2 expression. Clinical conditions associated with chronic and systemic inflammation, such as aging or obesity, dampened Rev-erbα gene expression in peritoneal macrophages from C57BL/6J mice. Rev-erbα agonists or overexpression of Rev-erbα in the murine macrophage cell line RAW264 suppressed the induction of Ccl2 following an LPS endotoxin challenge. We discovered that Rev-erbα represses Ccl2 expression directly through a Rev-erbα-binding motif in the Ccl2 promoter region. Rev-erbα also suppressed CCL2-activated signals, ERK and p38, which was recovered by the addition of exogenous CCL2. Further, Rev-erbα impaired cell adhesion and migration, which are inflammatory responses activated through the ERK- and p38-signaling pathways, respectively. Peritoneal macrophages from mice lacking Rev-erbα display increases in Ccl2 expression. These data suggest that Rev-erbα regulates the inflammatory infiltration of macrophages through the suppression of Ccl2 expression. Therefore, Rev-erbα may be a key link between aging- or obesity-associated impairment of clockwork and inflammation.

Early Fermi Gamma-ray Space Telescope Observations of the Quasar 3C 454.3

Abstract: This is the first report of Fermi Gamma-ray Space Telescope observations of the quasar 3C 454.3, which has been undergoing pronounced long-term outbursts since 2000. The data from the Large Area Telescope (LAT), covering 2008 July 7 - October 6, indicate strong, highly variable gamma-ray emission with an average flux of ~3 x 10^{-6} photons cm^{-2} s^{-1}, for energies above 100 MeV. The gamma-ray flux is variable, with strong, distinct, symmetrically-shaped flares for which the flux increases by a factor of several on a time scale of about three days. This variability indicates a compact emission region, and the requirement that the source is optically thin to pair-production implies relativistic beaming with Doppler factor delta > 8, consistent with the values inferred from VLBI observations of superluminal expansion (delta ~ 25). The observed gamma-ray spectrum is not consistent with a simple power-law, but instead steepens strongly above ~2 GeV, and is well described by a broken power-law with photon indices of ~2.3 and ~3.5 below and above the break, respectively. This is the first direct observation of a break in the spectrum of a high luminosity blazar above 100 MeV, and it is likely direct evidence for an intrinsic break in the energy distribution of the radiating particles. Alternatively, the spectral softening above 2 GeV could be due to gamma-ray absorption via photon-photon pair production on the soft X-ray photon field of the host AGN, but such an interpretation would require the dissipation region to be located very close (less than 100 gravitational radii) to the black hole, which would be inconsistent with the X-ray spectrum of the source.

Fermi LAT Observations of LS I +61 303: First Detection of an Orbital Modulation in GeV Gamma Rays

Abstract: This Letter presents the first results from the observations of LS I +61°303 using Large Area Telescope data from the Fermi Gamma-Ray Space Telescope between 2008 August and 2009 March. Our results indicate variability that is consistent with the binary period, with the emission being modulated at 26.6 ± 0.5 days. This constitutes the first detection of orbital periodicity in high-energy gamma rays (20 MeV-100 GeV, HE). The light curve is characterized by a broad peak after periastron, as well as a smaller peak just before apastron. The spectrum is best represented by a power law with an exponential cutoff, yielding an overall flux above 100 MeV of 0.82 ± 0.03(stat) ± 0.07(syst) 10–6 ph cm–2 s–1, with a cutoff at 6.3 ± 1.1(stat) ± 0.4(syst) GeV and photon index Γ = 2.21 ± 0.04(stat) ± 0.06(syst). There is no significant spectral change with orbital phase. The phase of maximum emission, close to periastron, hints at inverse Compton scattering as the main radiation mechanism. However, previous very high-energy gamma ray (>100 GeV, VHE) observations by MAGIC and VERITAS show peak emission close to apastron. This and the energy cutoff seen with Fermi suggest that the link between HE and VHE gamma rays is nontrivial.

Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning

Abstract: We propose a practical state-of-the-art method to develop a machine-learning-based humanoid robot that can work as a production line worker. The proposed approach provides an intuitive way to collect data and exhibits the following characteristics: task performing capability, task reiteration ability, generalizability, and easy applicability. The proposed approach utilizes a real-time user interface with a monitor and provides a first-person perspective using a head-mounted display. Through this interface, teleoperation is used for collecting task operating data, especially for tasks that are difficult to be applied with a conventional method. A two-phase deep learning model is also utilized in the proposed approach. A deep convolutional autoencoder extracts images features and reconstructs images, and a fully connected deep time delay neural network learns the dynamics of a robot task process from the extracted image features and motion angle signals. The “Nextage Open” humanoid robot is used as an experimental platform to evaluate the proposed model. The object folding task utilizing with 35 trained and 5 untrained sensory motor sequences for test. Testing the trained model with online generation demonstrates a 77.8% success rate for the object folding task.

Space–Time and ALE-VMS Techniques for Patient-Specific Cardiovascular Fluid–Structure Interaction Modeling

Abstract: This is an extensive overview of the core and special space–time and Arbitrary Lagrangian–Eulerian (ALE) techniques developed by the authors’ research teams for patient-specific cardiovascular fluid–structure interaction (FSI) modeling. The core techniques are the ALE-based variational multiscale (ALE-VMS) method, the Deforming-Spatial-Domain/Stabilized Space–Time formulation, and the stabilized space–time FSI technique. The special techniques include methods for calculating an estimated zero-pressure arterial geometry, prestressing of the blood vessel wall, a special mapping technique for specifying the velocity profile at an inflow boundary with non-circular shape, techniques for using variable arterial wall thickness, mesh generation techniques for building layers of refined fluid mechanics mesh near the arterial walls, a recipe for pre-FSI computations that improve the convergence of the FSI computations, the Sequentially-Coupled Arterial FSI technique and its multiscale versions, techniques for the projection of fluid–structure interface stresses, calculation of the wall shear stress and oscillatory shear index, arterial-surface extraction and boundary condition techniques, and a scaling technique for specifying a more realistic volumetric flow rate. With results from earlier computations, we show how these core and special FSI techniques work in patient-specific cardiovascular simulations.