Forcibly driven coherent soft phonons in GeTe with intense THz-rate pump fields

We propose an experimental technique to generate large amplitude coherent phonons with irradiation of THz-rate pump pulses and to study the dynamics of phase transition in GeTe ferroelectrics. When a single pump pulse irradiates the sample at various pump power densities, the frequency of the soft phonon decreases sub-linearly and saturates at higher pump powers. By contrast, when THz-rate pump pulse sequence irradiates the sample at matched time intervals to forcibly drive the oscillation, a large red-shift of the phonon frequency is observed without saturation effects. After excitation with a four pump pulse sequence, the coherent soft phonon becomes strongly damped leading to a near critical damping condition. This condition indicates that the lattice is driven to a precursor state of the phase transition.Comment: 4 pages, 3 figure

The effect of varying sound velocity on primordial curvature perturbations

We study the effects of sudden change in the sound velocity on primordial curvature perturbation spectrum in inflationary cosmology, assuming that the background evolution satisfies the slow-roll condition throughout. It is found that the power spectrum acquires oscillating features which are determined by the ratio of the sound speed before and after the transition and the wavenumeber which crosses the sound horizon at the transition, and their analytic expression is given. In some values of those parameters, the oscillating primordial power spectrum can better fit the observed Cosmic Microwave Background temperature anisotropy power spectrum than the simple power-law power spectrum, although introduction of such a new degree of freedom is not justified in the context of Akaike's Information Criterion.Comment: 12 pages, 3 figures; references added; appendix modifie

Antitumor Immunity Produced by the Liver Kupffer Cells, NK Cells, NKT Cells, and CD8+ CD122+ T Cells

Mouse and human livers contain innate immune leukocytes, NK cells, NKT cells, and macrophage-lineage Kupffer cells. Various bacterial components, including Toll-like receptor (TLR) ligands and an NKT cell ligand (α-galactocylceramide), activate liver Kupffer cells, which produce IL-1, IL-6, IL-12, and TNF. IL-12 activates hepatic NK cells and NKT cells to produce IFN-γ, which further activates hepatic T cells, in turn activating phagocytosis and cytokine production by Kupffer cells in a positive feedback loop. These immunological events are essentially evoked to protect the host from bacterial and viral infections; however, these events also contribute to antitumor and antimetastatic immunity in the liver by activated liver NK cells and NKT cells. Bystander CD8+CD122+ T cells, and tumor-specific memory CD8+T cells, are also induced in the liver by α-galactocylceramide. Furthermore, adoptive transfer experiments have revealed that activated liver lymphocytes may migrate to other organs to inhibit tumor growth, such as the lungs and kidneys. The immunological mechanism underlying the development of hepatocellular carcinoma in cirrhotic livers in hepatitis C patients and liver innate immunity as a double-edged sword (hepatocyte injury/regeneration, septic shock, autoimmune disease, etc.) are also discussed

Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks

Last year, IEEE 802.11 Extremely High Throughput Study Group (EHT Study Group) was established to initiate discussions on new IEEE 802.11 features. Coordinated control methods of the access points (APs) in the wireless local area networks (WLANs) are discussed in EHT Study Group. The present study proposes a deep reinforcement learning-based channel allocation scheme using graph convolutional networks (GCNs). As a deep reinforcement learning method, we use a well-known method double deep Q-network. In densely deployed WLANs, the number of the available topologies of APs is extremely high, and thus we extract the features of the topological structures based on GCNs. We apply GCNs to a contention graph where APs within their carrier sensing ranges are connected to extract the features of carrier sensing relationships. Additionally, to improve the learning speed especially in an early stage of learning, we employ a game theory-based method to collect the training data independently of the neural network model. The simulation results indicate that the proposed method can appropriately control the channels when compared to extant methods

Evaluating damage extent of fractured beams in steel moment-resisting frames using dynamic strain responses

Delays in the postearthquake safety estimations of important buildings significantly increase unnecessary disorder in economic and social recovery following devastating earthquakes. Providing promptness and objectivity in evaluation procedures, damage detection through a structural health monitoring system using sensors attracts attention from building owners and other stakeholders. Nonetheless, local damage on individual structural elements is not easily identifiable, as such damage weakly relates to the global vibrational characteristics of buildings. The primary objectives of this research are to present and verify a method that quantifies the amount of local damage (i.e., fractures near beam-column connections) for the health monitoring of steel moment-resisting frames that have undergone a strong earthquake ground motion. In this paper, a novel damage index based on the monitoring of dynamic strain responses of steel beams under ambient vibration before and after earthquakes is firstly presented. Then, the relation between the amount of local damage and the presented damage index is derived numerically with a parametric study using a nine-story steel moment-resisting frame model. Finally, the effectiveness of the damage index and an associated wireless strain-sensing system are examined with a series of vibration tests using a five-story steel frame test bed

Steel slit shear walls with double-tapered links capable of condition assessment

The concept of using a hysteretic damper as a condition assessment device that functions immediately after a damaging earthquake is realized by making use of the residual out-of-plane deformation of links that are arranged in slit shear walls. According to the proposed inspection procedure, the maximum drift ratio experienced by the slit wall is estimated based on the number of torsionally deformed links whose dimensions are determined so that the links would exhibit notable torsional deformation at the target deformations. The adoption of a double-tapered shape for the links enables us to significantly increase the amount of out-of-plane deformation. The relationship between the dimensions and the torsional deformation of the links is established using numerical simulations. The effectiveness of the proposed condition assessment scenario is verified by using a series of cyclic loading tests for individual links and groups of links. As a hysteretic damper, the strength and stiffness of the links predicted by design equations matched well with test results