Marginal Probability-Based Integer Handling for CMA-ES Tackling Single-and Multi-Objective Mixed-Integer Black-Box Optimization

This study targets the mixed-integer black-box optimization (MI-BBO) problem where continuous and integer variables should be optimized simultaneously. The CMA-ES, our focus in this study, is a population-based stochastic search method that samples solution candidates from a multivariate Gaussian distribution (MGD), which shows excellent performance in continuous BBO. The parameters of MGD, mean and (co)variance, are updated based on the evaluation value of candidate solutions in the CMA-ES. If the CMA-ES is applied to the MI-BBO with straightforward discretization, however, the variance corresponding to the integer variables becomes much smaller than the granularity of the discretization before reaching the optimal solution, which leads to the stagnation of the optimization. In particular, when binary variables are included in the problem, this stagnation more likely occurs because the granularity of the discretization becomes wider, and the existing integer handling for the CMA-ES does not address this stagnation. To overcome these limitations, we propose a simple integer handling for the CMA-ES based on lower-bounding the marginal probabilities associated with the generation of integer variables in the MGD. The numerical experiments on the MI-BBO benchmark problems demonstrate the efficiency and robustness of the proposed method. Furthermore, in order to demonstrate the generality of the idea of the proposed method, in addition to the single-objective optimization case, we incorporate it into multi-objective CMA-ES and verify its performance on bi-objective mixed-integer benchmark problems.Comment: Camera-ready version for ACM Transactions on Evolutionary Learning and Optimization (TELO). This paper is an extended version of the work presented in arXiv:2205.1348

Machine-Learning Optimization of Multiple Measurement Parameters Nonlinearly Affecting the Signal Quality

Determination of optimal measurement parameters is essential for measurement experiments. They can be manually optimized if the linear correlation between them and the corresponding signal quality is known or easily determinable. However, in practice, this correlation is often nonlinear and not known a priori; hence, complicated trial and error procedures are employed for finding optimal parameters while avoiding local optima. In this work, we propose a novel approach based on machine learning for optimizing multiple measurement parameters, which nonlinearly influence the signal quality. Optically detected magnetic resonance measurements of nitrogen-vacancy centers in fluorescent nanodiamonds were used as a proof-of-concept system. We constructed a suitable dataset of optically detected magnetic resonance spectra for predicting the optimal laser and microwave powers that deliver the highest contrast and signal-to-noise ratio values by means of linear regression, neural networks, and random forests. The model developed by the considered neural network turned out to have a coefficient of determination significantly higher than that of the other methods. The proposed method thus provided a novel approach for the rapid setting of measurement parameters that influence the signal quality in a nonlinear way, opening a gate for fields like nuclear magnetic resonance, electron paramagnetic resonance, and fluorescence microscopy to benefit from it

Structural Insights into Methylated DNA Recognition by the Methyl-CpG Binding Domain of MBD6 from Arabidopsis thaliana

Cytosine methylation is an epigenetic modification essential for formation of mature heterochromatin, gene silencing, and genomic stability. In plants, methylation occurs not only at cytosine bases in CpG but also in CpHpG and CpHpH contexts, where H denotes A, T, or C. Methyl-CpG binding domain (MBD) proteins, which recognize symmetrical methyl-CpG dinucleotides and act as gene repressors in mammalian cells, are also present in plant cells, although their structural and functional properties still remain poorly understood. To fill this gap, in this study, we determined the solution structure of the MBD domain of the MBD6 protein from Arabidopsis thaliana and investigated its binding properties to methylated DNA by binding assays and an in-depth NMR spectroscopic analysis. The AtMBD6 MBD domain folds into a canonical MBD structure in line with its binding specificity toward methyl-CpG and possesses a DNA binding interface similar to mammalian MBD domains. Intriguingly, however, the binding affinity of the AtMBD6 MBD domain toward methyl-CpG-containing DNA was found to be much lower than that of known mammalian MBD domains. The main difference arises from the absence of positively charged residues in AtMBD6 that supposedly interact with the DNA backbone as seen in mammalian MBD/methyl-CpG-containing DNA complexes. Taken together, we have established a structural basis for methyl-CpG recognition by AtMBD6 to develop a deeper understanding how MBD proteins work as mediators of epigenetic signals in plant cells

The DNA methyltransferase Dnmt1 directly interacts with the SET and RING finger-associated (SRA) domain of the multifunctional protein Uhrf1 to facilitate accession of the catalytic center to hemi-methylated DNA

This research was originally published in Journal of Biological Chemistry. Ahmet Can Berkyurek, Isao Suetake, Kyohei Arita, Kohei Takeshita, Atsushi Nakagawa, Masahiro Shirakawa and Shoji Tajima. The DNA methyltransferase Dnmt1 directly interacts with the SET and RING finger-associated (SRA) domain of the multifunctional protein Uhrf1 to facilitate accession of the catalytic center to hemi-methylated DNA. Journal of Biological Chemistry. 2014; 289, 379-386. © the American Society for Biochemistry and Molecular Biology

High-Sensitivity Rheo-NMR Spectroscopy for Protein Studies

Shear stress can induce structural deformation of proteins, which might result in aggregate formation. Rheo-NMR spectroscopy has the potential to monitor structural changes in proteins under shear stress at the atomic level; however, existing Rheo-NMR methodologies have insufficient sensitivity to probe protein structure and dynamics. Here we present a simple and versatile approach to Rheo-NMR, which maximizes sensitivity by using a spectrometer equipped with a cryogenic probe. As a result, the sensitivity of the instrument ranks highest among the Rheo-NMR spectrometers reported so far. We demonstrate that the newly developed Rheo-NMR instrument can acquire high-quality relaxation data for a protein under shear stress and can trace structural changes in a protein during fibril formation in real time. The described approach will facilitate rheological studies on protein structural deformation, thereby aiding a physical understanding of shear-induced amyloid fibril formation

A novel magnetic resonance-based method to measure gene expression in living cells

In unicellular and multicellular eukaryotes, elaborate gene regulatory mechanisms facilitate a broad range of biological processes from cell division to morphological differentiation. In order to fully understand the gene regulatory networks involved in these biological processes, the spatial and temporal patterns of expression of many thousands of genes will need to be determined in real time in living organisms. Currently available techniques are not sufficient to achieve this goal; however, novel methods based on magnetic resonance (MR) imaging may be particularly useful for sensitive detection of gene expression in opaque tissues. This report describes a novel reporter gene system that monitors gene expression dynamically and quantitatively, in yeast cells, by measuring the accumulation of inorganic polyphosphate (polyP) using MR spectroscopy (MRS) or MR spectroscopic imaging (MRI). Because this system is completely non-invasive and does not require exogenous substrates, it is a powerful tool for studying gene expression in multicellular organisms, as well

Transformation of the Higher Education Policy-making Process in the 2010s: From Ministry-led to Executive-led Higher Education Policy

This book is composed of the results of the Higher Education Policy Research Project of the Japanese Association of Higher Education Research, which was proposed by the President of the Association, Masayuki Kobayashi, and was carried out by a group of researchers within the association under the leadership of board member Takashi HATA. Research on higher education policy-making has been one of the major topics of interest since the establishment of the Association. Indeed, the association’s mission statement declares, “the establishment of an academic society is becoming an ever more critical issue for promoting cooperation and exchanges among the researchers from different study fields, strengthening the theoretical and methodological basis of research, seeking further deepened and developed research, dissemination of the outcomes of this research and contribution to the solution of practical and policy-related challenges.” This research project aims to study the process of policy-making for higher education in Japan, which has changed rapidly in recent years. This change is occurring not only in Japan but also in Europe and the United States. In order to study from a global perspective, the research project was carried out with the participation of experts studying higher education in the United States, France, and the United Kingdom, and new research results were produced through comparative higher education policy analysis. In the Higher Education Policy Project, members interviewed officials from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), and have been energetically studying the policy-making process, especially the relationship between the official residence and the MEXT. At the same time, they have analyzed the decision-making process of higher education policies in each country. We believe that research that examines the decision-making process of higher education policies in so many countries is unparalleled and offers an unprecedented contribution to higher education research.はじめに… 小林雅之 1 序章　高等教育政策決定過程の変容を探求する－研究の課題… 羽田貴史 3 第1章　2010年代高等教育政策決定過程の変容… 羽田貴史 9 第2章　高等教育政策にかかわる会議体とアクター… 丸山和昭 33 第3章　「高等教育の修学支援新制度」の形成過程－政治と官邸主導による新制度創設… 白川優治 51 第4章　高大接続改革への疑義… 荒井克弘 65 第5章　アメリカの高等教育政策決定過程と大統領府… 塙武郎 83 第6章　フランスの高等教育政策決定過程… 大場淳 97 第7章　イギリスの高等教育政策決定過程と首相官邸－証拠に基づく政策形成（EBPM）の仕組み… 田中正弘 109 おわりに… 羽田貴史 12

Distance measurements between 5 nanometer diamonds – single particle magnetic resonance or optical super-resolution imaging?

5 nanometer sized detonation nanodiamonds (DNDs) are studied as potential single-particle labels for distance measurements in biomolecules