Clustering of illustrations by atmosphere using a combination of supervised and unsupervised learning

The distribution of illustrations on social media, such as Twitter and Pixiv has increased with the growing popularity of animation, games, and animated movies. The "atmosphere" of illustrations plays an important role in user preferences. Classifying illustrations by atmosphere can be helpful for recommendations and searches. However, assigning clear labels to the elusive "atmosphere" and conventional supervised classification is not always practical. Furthermore, even images with similar colors, edges, and low-level features may not have similar atmospheres, making classification based on low-level features challenging. In this paper, this problem is solved using both supervised and unsupervised learning with pseudo-labels. The feature vectors are obtained using the supervised method with pseudo-labels that contribute to an ambiguous atmosphere. Further, clustering is performed based on these feature vectors. Experimental analyses show that our method outperforms conventional methods in human-like clustering on datasets manually classified by humans.Comment: 5 pages, 2 figure

Atomic-level structural change in Ni-Ti alloys under martensite and amorphous transformations

The Ni-Ti alloys have been used widely as functional materials, especially for the purpose of superelastic behavior or shape memory effect. It has been believed that martensitic transformation (MT) between crystals plays a major role in the phase transition behavior, but recent experimental observation shows that there also exists stable amorphous structure. Detailed information of the atomic-level change, that is microscopic crystalline rearrangement of Ni-Ti alloys in applied shear deformation is needed. Our study aims at clarifying those atomic mechanisms by using molecular dynamics (MD) simulations. For Ni-Ti alloys, we assess the possibility of the modified version of EAM (MEAM) with parameters for Ni-Ti. We construct MD models to investigate both MT and amorphization in Ni-Ti alloys. We devise a method based on so-called common neighbor analysis (CNA) to effectively detects amorphous atoms, by finding clusters with five-folded symmetry (pentagonal bipyramids). In comparing models with different crystal orientation, when crystalline slip is not easy due to small resolved shear stress, the atoms in initial B2 or B19’ structure tend to be rearranged with rotational motion and transform to amorphous atoms. Besides, there are ”pre-amorphous” structures as a symptom of major and later increase of amorphous atoms

Treatment effects on neurometabolite levels in schizophrenia: A meta-analysis dataset of proton magnetic resonance spectroscopy

This article describes a dataset for a meta-analysis that aimed to investigate the effects of treatment on the neurometabolite status in patients with schizophrenia (DOI of original article: https://doi.org/10.1016/j.schres.2020.03.069 [1]). The data search was performed with MEDLINE, Embase, and PsycINFO. The neurometabolites investigated include glutamate, glutamine, glutamate + glutamine, gamma-aminobutyric acid, N-acetylaspartate, and myo-inositol, and the regions of interest (ROIs) include the frontal cortex, temporal cortex, parieto-occipital cortex, thalamus, basal ganglia, and hippocampus. The meta-analysis was conducted with a random-effects model, and the use of the standardized mean difference method between pre- and post-treatment of subjects for neurometabolites in each ROI of three patient groups or more. The dataset covers raw data of 39 patient groups (773 patients with schizophrenia at follow-up) with neurometabolite levels measured by magnetic resonance spectroscopy both before and after treatment. Furthermore, it contains details of clinical characteristics and treatment types for each group. Therefore, the data would be useful for a reinvestigation of treatment effects on the neurometabolite status from diverse points of view, as well as for the development of future treatment strategies for psychiatric diseases

Neuroendocrine Carcinoma of the Stomach: A Case Study

Gastric neuroendocrine carcinomas are rare and have a poor prognosis, and the diagnostic criteria for this disease have recently changed. We herein report a case of sporadic gastric neuroendocrine carcinoma. A 75-year-old man was referred to our hospital with epigastric pain. Endoscopic examination revealed a localized ulcerative lesion (diameter, 4 cm) at the upper stomach. The diagnosis on biopsy was neuroendocrine carcinoma. Total gastrectomy with D2 lymphadenectomy, splenectomy, and cholecystectomy was performed. Pathologically, the tumor infiltrated the subserosal layer, and 6/49 lymph nodes were involved. The tumor was uniform in shape and arranged in a rosette-like structure to form solid nests, with medium-sized, round-to-cuboid-shaped tumor cells and intense mitosis 46/10 HPF. It was positive for synaptophysin and chromogranin A, and the Ki-67 labeling index was 70–80%. The diagnosis of neuroendocrine carcinoma was made according to the WHO 2010 criteria. The patient was followed up for three years without recurrence

A guiding role of the Arabidopsis circadian clock in cell differentiation revealed by time-series single-cell RNA sequencing

Circadian rhythms and progression of cell differentiation are closely coupled in multicellular organisms. However, whether establishment of circadian rhythms regulates cell differentiation or vice versa has not been elucidated due to technical limitations. Here, we exploit high cell fate plasticity of plant cells to perform single-cell RNA sequencing during the entire process of cell differentiation. By analyzing reconstructed actual time series of the differentiation processes at single-cell resolution using a method we developed (PeakMatch), we find that the expression profile of clock genes is changed prior to cell differentiation, including induction of the clock gene LUX ARRYTHMO (LUX). ChIP sequencing analysis reveals that LUX induction in early differentiating cells directly targets genes involved in cell-cycle progression to regulate cell differentiation. Taken together, these results not only reveal a guiding role of the plant circadian clock in cell differentiation but also provide an approach for time-series analysis at single-cell resolution