In spectroscopic experiments, data acquisition in multi-dimensional phase space may require long acquisition time, owing to the large phase space volume to be covered. In such a case, the limited time available for data acquisition can be a serious constraint for experiments in which multidimensional spectral data are acquired. Here, taking angle-resolved photoemission spectroscopy (ARPES) as an example, we demonstrate a denoising method that utilizes deep learning as an intelligent way to overcome the constraint. With readily available ARPES data and random generation of training datasets, we successfully trained the denoising neural network without overfitting. The denoising neural network can remove the noise in the data while preserving its intrinsic information. We show that the denoising neural network allows us to perform a similar level of second-derivative and line shape analysis on data taken with two orders of magnitude less acquisition time. The importance of our method lies in its applicability to any multidimensional spectral data that are susceptible to statistical noise.

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We explore a new mechanism for switching magnetism and superconductivity in a magnetically frustrated iron-based superconductor using spin-polarized scanning tunneling microscopy (SPSTM). Our SPSTM study on single-crystal Sr_{2}VO_{3}FeAs shows that a spin-polarized tunneling current can switch the Fe-layer magnetism into a nontrivial C_{4} (2×2) order, which cannot be achieved by thermal excitation with an unpolarized current. Our tunneling spectroscopy study shows that the induced C_{4} (2×2) order has characteristics of plaquette antiferromagnetic order in the Fe layer and strongly suppresses superconductivity. Also, thermal agitation beyond the bulk Fe spin ordering temperature erases the C_{4} state. These results suggest a new possibility of switching local superconductivity by changing the symmetry of magnetic order with spin-polarized and unpolarized tunneling currents in iron-based superconductors.

Soybean (Glycine max L.) is one of the most important crop plants in the Republic of Korea. Here, we conducted a soybean virome study. We harvested a total of 172 soybean leaf samples showing disease symptoms from major soybean-growing regions in the Republic of Korea. Individual samples were examined for virus infection by RT-PCR. Moreover, we generated eight libraries representing eight provinces by pooling samples and four libraries from single samples. RNA-seq followed by bioinformatics analyses revealed 10 different RNA viruses infecting soybean. The proportion of viral reads in each transcriptome ranged from 0.2 to 31.7%. Coinfection of different viruses in soybean plants was very common. There was a single dominant virus in each province, and this geographical difference might be related to the soybean seeds that transmit viruses. In this study, 32 viral genome sequences were assembled and successfully used to analyze the phylogenetic relationships and quasispecies nature of the identified RNA viruses. Moreover, RT-PCR with newly developed primers confirmed infection of the identified viruses in each library. Taken together, our soybean virome study provides a comprehensive overview of viruses infecting soybean in eight geographical regions in the Republic of Korea and four single soybean plants in detail.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT A novel allele of the putative soybean raffinose synthase gene, RS2, was discovered in PI200508 that is associated with the low raffinose and stachyose content. Soybean line PI200508 was identified as expressing reduced levels of raffinose and stachyose as well as elevated levels of sucrose. The RS2 mutant gene shows three base pairs InDel with the normal gene. Based on InDel region we developed novel co-dominant and dominant marker. The aim of this study was to develop Korean soybean cultivars, Daewon, Cheongja, and Danmiput, containing low levels of raffinose and stachyose. A specific markers assay for the PI200508 RS2 allele was developed to allow direct selection of the low raffinose and stachyose phenotype. Our findings highlight the efficiency of allele-specific markers in selection, which is evident in the matching genotype and results of the HPLC in the F2 generations of Daewon×PI200508 population.