Poly-instanton axion inflation

We investigate the axion inflation model derived by poly-instanton effects in type II superstring theories. Poly-instanton effects are instanton effects corrected by another instanton and it can generate the modulus-axion potential with the double exponential function. Although the axion has a period of small value, this potential can have a flat region because its derivatives are exponentially suppressed by non-perturbative effects. From the view point of the cosmic inflation, such potential is interesting. In this paper, we numerically study the possibilities for realizing the cosmic inflation. We also study their spectral index and other cosmological observables, numerically.Comment: 13 pages, 2 figure

F-term Moduli Stabilization and Uplifting

We study K\"ahler moduli stabilization in IIB superstring theory. We propose a new moduli stabilization mechanism by the supersymmetry-braking chiral superfield which is coupled to K\"ahler moduli in K\"ahler potential. We also study uplifting of the Large Volume Scenario (LVS) by it. In both cases, the form of superpotential is crucial for moduli stabilization. We confirm that our uplifting mechanism does not destabilize the vacuum of the LVS drastically.Comment: 22 pages, 2 figure

Survey of the stray dog population and the health education program on the prevention of dog bites and dog-acquired infections: a comparative study in Nepal and Okayama Prefecture, Japan.

We estimated the number of stray dogs in Kathmandu, Nepal, where human rabies cases still occur, and in Shimotsui, Okayama Prefecture, Japan. In Kathmandu, the stray dog density was 2,930 stray dogs/km2, and the ratio of stray dogs to humans was 1:4.7. In Shimotsui, the density was 225 stray dogs/km2, and the ratio was 1:5.2. Since the stray dog population in Nepal is very large, one of the measures used to prevent dog bites and dog-acquired infections such as rabies is an effort to capture stray dogs. Another such measure is an effort to decrease the availability of food for stray dogs. We also organized health education programs in both Nepal and Okayama Prefecture, Japan, which involved a course on the prevention of dog bites and subsequent infections. After each course, a questionnaire survey was conducted. The results suggest that the course participants understood these important preventive methods. In addition to the measures mentioned above and the routine vaccination of dogs, this health education course is recommended as a long-term preventive program</p

Open Set Domain Adaptation by Backpropagation

Numerous algorithms have been proposed for transferring knowledge from a label-rich domain (source) to a label-scarce domain (target). Almost all of them are proposed for a closed-set scenario, where the source and the target domain completely share the class of their samples. We call the shared class the \doublequote{known class.} However, in practice, when samples in target domain are not labeled, we cannot know whether the domains share the class. A target domain can contain samples of classes that are not shared by the source domain. We call such classes the \doublequote{unknown class} and algorithms that work well in the open set situation are very practical. However, most existing distribution matching methods for domain adaptation do not work well in this setting because unknown target samples should not be aligned with the source. In this paper, we propose a method for an open set domain adaptation scenario which utilizes adversarial training. A classifier is trained to make a boundary between the source and the target samples whereas a generator is trained to make target samples far from the boundary. Thus, we assign two options to the feature generator: aligning them with source known samples or rejecting them as unknown target samples. This approach allows extracting features that separate unknown target samples from known target samples. Our method was extensively evaluated in domain adaptation setting and outperformed other methods with a large margin in most settings.Comment: Accepted by ECCV201

Effect of the surface geology on strong ground motions due to the 2016 Central Tottori Earthquake, Japan

On October 21, 2016, an earthquake with Japan Meteorological Agency (JMA) magnitude 6.6 hit the central part of Tottori Prefecture, Japan. This paper demonstrates two notable effects of the surface geology on strong ground motions due to the earthquake. One is a predominant period issue observed over a large area. A seismic intensity of 6 lower on the JMA scale was registered at three sites in the disaster area. However, the peak ground acceleration ranged from 0.3 to 1.4 G at the three sites because of the varying peak periods of observed strong ground motions. The spectral properties of the observations also reflect the damage around the sites. Three-component microtremors were observed in the area; the predominant ground period distributions based on horizontal to vertical spectral ratios were provided by the authors. The peak periods of the strong motion records agree well with predominant periods estimated from microtremor observations at a rather hard site; however, the predominant periods of the microtremors are slightly shorter than those of the main shock at the other two soft sites. We checked the nonlinear effect at the sites by comparing the site responses to small events and the main shock. The peak periods of the main shock were longer than those of the weak motions at the sites. This phenomenon indicates a nonlinear site effect due to large ground motions caused by the main shock. A horizontal component of the accelerogram showed rather pulsating swings that indicate cyclic mobility behavior, especially at a site close to a pond shore; ground subsidence of ~20 cm was observed around the site. The peak periods of weak motions agree well with those of the microtremor observations. This implies an important issue that the predominant periods estimated by microtremors are not sufficient to estimate the effect of surface geology for disaster mitigation. We have to estimate the predominant periods under large ground motions considering the nonlinear site response of soft sediment sites