Rotating black hole in extended Chern-Simons modified gravity

We investigate a slowly rotating black hole in four-dimensional extended Chern-Simons modified gravity. We obtain an approximate solution that reduces to the Kerr solution when a coupling constant vanishes. The Chern-Simons correction effectively reduces the frame-dragging effect around a black hole in comparison with that of the Kerr solution.Comment: 9 pages, 1 figure, to appear in Progress of Theoretical Physics, typos correcte

Does a black hole rotate in Chern-Simons modified gravity?

Rotating black hole solutions in the (3+1)-dimensional Chern-Simons modified gravity theory are discussed by taking account of perturbation around the Schwarzschild solution. The zenith-angle dependence of a metric function related to the frame-dragging effect is determined from a constraint equation independently of a choice of the embedding coordinate. We find that at least within the framework of the first-order perturbation method, the black hole cannot rotate for finite black hole mass if the embedding coordinate is taken to be a timelike vector. However, the rotation can be permitted in the limit of $M/r \to 0$ (where $M$ is the black hole mass and $r$ is the radius). For a spacelike vector, the rotation can also be permitted for any value of the black hole mass.Comment: 4 pages, Accepted for publication in Phys. Rev.

Dehydration of main-chain amides in the final folding step of single-chain monellin revealed by time-resolved infrared spectroscopy

Kinetic IR spectroscopy was used to reveal β-sheet formation and water expulsion in the folding of single-chain monellin (SMN) composed of a five-stranded β-sheet and an α-helix. The time-resolved IR spectra between 100 μs and 10 s were analyzed based on two consecutive intermediates, I1 and I2, appearing within 100 μs and with a time constant of ≈100 ms, respectively. The initial unfolded state showed broad amide I′ corresponded to a fluctuating conformation. In contrast, I1 possessed a feature at 1,636 cm−1 for solvated helix and weak features assignable to turns, demonstrating the rapid formation of helix and turns. I2 possessed a line for solvated helix at 1,637 cm−1 and major and minor lines for β-sheet at 1,625 and 1,680 cm−1, respectively. The splitting of the major and minor lines is smaller than that of the native state, implying an incomplete formation of the β-sheet. Furthermore, both major and minor lines demonstrated a low-frequency shift compared to those of the native state, which was interpreted to be caused by hydration of the C=O group in the β-sheet. Together with the identification of solvated helix, the core domain of I2 was interpreted as being hydrated. Finally, slow conversion of the water-penetrated core of I2 to the dehydrated core of the native state was observed. We propose that both the expulsion of water, hydrogen-bonded to main-chain amides, and the completion of the secondary structure formation contribute to the energetic barrier of the rate-limiting step in SMN folding

Three-dimensional imaging of dislocations in a Ti-35mass%Nb alloy by electron tomography

We have studied three-dimensional (3D) configurations of dislocations in the β phase of a Ti-35mass%Nb alloy by means of single-axis tilt tomography using bright-field scanning transmission electron microscopy (BF-STEM). To visualize dislocations, the hh0 systematic reflections were excited throughout tilt-series acquisition with the maximum tilt angle of 70°. Dislocations in the β grains were clearly reconstructed by the weighted back-projection algorithm. The slip planes of the dislocations were deduced by rotating the reconstructed volumes with the aid of selected area electron diffraction patterns. It was found that BF-STEM images with relatively low contrasts, taken along low-order zone axes, are capable to reproduce and preserve the quality of reconstructed image of dislocations. We also found that tilt angles as low as 40° are practically acceptable to visualize 3D configurations of dislocations, while there exists limitation in resolution due to the existence of a large missing wedge.Sato K, Semboshi S, Konno TJ. Three-Dimensional Imaging of Dislocations in a Ti–35mass%Nb Alloy by Electron Tomography. Materials. 2015; 8(4):1924-1933. https://doi.org/10.3390/ma8041924

Flat rotation curves in Chern-Simons modified gravity

We investigate the spacetime of a slowly rotating black hole in the Chern-Simons modified gravity. The long range feature of frame-dragging effect under the Chern-Simon gravity well explains the flat rotation curves of galaxies which is a central evidence of dark matter. Our solution provides a different scenario of rotating space from Goedel's solution.Comment: 4 pages, Accepted for publication in Phys. Rev.

Important comments on KERMA factors and DPA cross-section data in ACE files of JENDL-4.0, JEFF-3.2 and ENDF/B-VII.1

We have studied reasons of differences of KERMA factors and DPA cross-section data among nuclear data libraries. Here the KERMA factors and DPA cross-section data included in the official ACE files of JENDL-4.0, ENDF/B-VII.1 and JEFF-3.2 are examined in more detail. As a result, it is newly found out that the KERMA factors and DPA cross-section data of a lot of nuclei are different among JENDL-4.0, ENDF/B-VII.1 and JEFF-3.2 and reasons of the differences are the followings: 1) large secondary particle production yield, 2) no secondary gamma data, 3) secondary gamma data in files12–15 mt = 3, 4) mt = 103–107 data without mt = 600 s–800 s data in file6. The issue 1) is considered to be due to nuclear data, while the issues 2)-4) seem to be due to NJOY. The ACE files of JENDL-4.0, ENDF/B-VII.1 and JEFF-3.2 with these problems should be revised after correcting wrong nuclear data and NJOY problems

Biological neurons act as generalization filters in reservoir computing

Reservoir computing is a machine learning paradigm that transforms the transient dynamics of high-dimensional nonlinear systems for processing time-series data. Although reservoir computing was initially proposed to model information processing in the mammalian cortex, it remains unclear how the non-random network architecture, such as the modular architecture, in the cortex integrates with the biophysics of living neurons to characterize the function of biological neuronal networks (BNNs). Here, we used optogenetics and fluorescent calcium imaging to record the multicellular responses of cultured BNNs and employed the reservoir computing framework to decode their computational capabilities. Micropatterned substrates were used to embed the modular architecture in the BNNs. We first show that modular BNNs can be used to classify static input patterns with a linear decoder and that the modularity of the BNNs positively correlates with the classification accuracy. We then used a timer task to verify that BNNs possess a short-term memory of ~1 s and finally show that this property can be exploited for spoken digit classification. Interestingly, BNN-based reservoirs allow transfer learning, wherein a network trained on one dataset can be used to classify separate datasets of the same category. Such classification was not possible when the input patterns were directly decoded by a linear decoder, suggesting that BNNs act as a generalization filter to improve reservoir computing performance. Our findings pave the way toward a mechanistic understanding of information processing within BNNs and, simultaneously, build future expectations toward the realization of physical reservoir computing systems based on BNNs.Comment: 31 pages, 5 figures, 3 supplementary figure

Design and Development of a Legged Robot Research Platform JROB-1

Proceedings of the 1998 IEEE International Conference on Robotics & Automation, Leuven, Belgium, May 199