Quantum effects for the neutrino mixing matrix in the democratic-type model

We investigate the quantum effects for the democratic-type neutrino mass matrix given at the right-handed neutrino mass scale $m_R$ in order to see (i) whether $\theta_{23}=-\pi/4$ predicted by the model is stable to explain the atmospheric neutrino anomaly, (ii) how $\theta_{12}$ and $\theta_{13}$ behave, and (iii) whether the predicted Dirac CP phase $\delta$ keeps maximal size, at the weak scale $m_Z$. We find that, for the (inversely) hierarchical mass spectrum with $m_1\sim m_2$, $\theta_{23}$ and $\theta_{13}$ are stable, while $\theta_{12}$ is not so, which leads to the possibility that the solar neutrino mixing angle can become large at $m_Z$ even if it is taken small at $m_R$. We also show that $\delta$ keeps almost maximal for the above mass spectrum, and our model can give the large CP violation effect in the future neutrino oscillation experiments if the solar neutrino puzzle is explained by the large mixing angle MSW solution.Comment: LaTeX, 21 pages, 2 figures, some mistakes correcte

Ionic Liquid-Induced Unique Structural Transitions of Proteins

The structural transitions of proteins in aqueous solutions of various ionic liquids (ILs) over a wide concentration range (x (mol% IL) = 0–30) were investigated using Fourier-transform infrared and near-UV circular dichroism spectroscopy combined with small-angle X-ray scattering. The proteins in the aqueous IL solutions showed two structural transition patterns: (i) the folded state → unfolded state → partial globular state (α-helical formation disrupted tertiary structure) and (ii) the folded state → unfolded state → aggregation (amyloid-like aggregation or disordered aggregation). We found that the helical formation of proteins in the condensed IL solutions was strongly related to the competition between the low polarity and denaturation effect of ions. Moreover, the amyloid-like aggregate formation correlated with the competition between the size of the confined water assemblies in the IL layer and the IL-amino acid residue interactions. On the basis of these results, we discussed the future applications of ILs, including their use as cryoprotectants for proteins and as agents for the suppression of amyloid formation

Local Positional Encoding for Multi-Layer Perceptrons

A multi-layer perceptron (MLP) is a type of neural networks which has a long history of research and has been studied actively recently in computer vision and graphics fields. One of the well-known problems of an MLP is the capability of expressing high-frequency signals from low-dimensional inputs. There are several studies for input encodings to improve the reconstruction quality of an MLP by applying pre-processing against the input data. This paper proposes a novel input encoding method, local positional encoding, which is an extension of positional and grid encodings. Our proposed method combines these two encoding techniques so that a small MLP learns high-frequency signals by using positional encoding with fewer frequencies under the lower resolution of the grid to consider the local position and scale in each grid cell. We demonstrate the effectiveness of our proposed method by applying it to common 2D and 3D regression tasks where it shows higher-quality results compared to positional and grid encodings, and comparable results to hierarchical variants of grid encoding such as multi-resolution grid encoding with equivalent memory footprint