A recyclable hydrophobic anchor-tagged asymmetric amino thiourea catalyst

A novel recyclable thiourea-based, asymmetric organocatalyst containing a hydrophobic anchor has been developed. The chemical nature of the hydrophobic anchor contributes to the desirable characteristics of the recyclable catalyst. The hydrophobic anchor-tagged thiourea catalyst is highly soluble in less polar solvents compatible to the amino thiourea catalyst-mediated asymmetric reactions, but sparingly soluble in polar solvents used for recycle process. This asymmetric catalyst delivers a catalytic performance comparable to that of a parent catalyst and can be readily recycled from reactions

Spicule Dynamics over Plage Region

We studied spicular jets over a plage area and derived their dynamic characteristics using Hinode Solar Optical Telescope (SOT) high-resolution images. The target plage region was near the west limb of the solar disk. This location permitted us to study the dynamics of spicular jets without the overlapping effect of spicular structures along the line of sight. In this work, to increase the ease with which we can identify spicules on the disk, we applied the image processing method `MadMax' developed by Koutchmy et al. (1989). It enhances fine, slender structures (like jets), over a diffuse background. We identified 169 spicules over the target plage. This sample permits us to derive statistically reliable results regarding spicular dynamics. The properties of plage spicules can be summarized as follows: (1) In a plage area, we clearly identified spicular jet features. (2) They were shorter in length than the quiet region limb spicules, and followed ballistic motion under constant deceleration. (3) The majority (80%) of the plage spicules showed the cycle of rise and retreat, while 10% of them faded out without a complete retreat phase. (4) The deceleration of the spicule was proportional to the velocity of ejection (i.e. the initial velocity).Comment: 12 pages, 9 figures, accepted for publication in PAS

Sea Trials for Benthos Sampling Using Autonomous Underwater Vehicle

For enhancement of oceanic engineering technology and researchers, underwater robot competition has been held since 2016. Seventh competition in this year consists AUV league that university\u27s vehicles automatically cruise at field and junior league that underwater craft is made. The paper reports competition regulations of AUV and junior league and results of the competition held in October 2019.The 2020 International Conference on Artificial Life and Robotics (ICAROB 2020), January 13-16, 2020, B-Con Plaza, Beppu, Oit

Lymphoepithelial Carcinoma in the Lateral Tongue: The Case Report

Lymphoepithelial carcinoma (LEC) of the tongue is a rare subtype of squamous cell carcinoma. Histologically, it is an undifferentiated carcinoma with rich lymphocyte and plasma cell infiltration. The most common location for LEC in the head and neck is the salivary glands, and LEC of the oral cavity is extremely rare. The second case report of LEC in the lateral tongue is presented. In addition, a review of the literature was performed, and the relationship between LEC and Epstein-Barr virus infection was considered

Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques

We present the task description and discussion on the results of the DCASE 2022 Challenge Task 2: ``Unsupervised anomalous sound detection (ASD) for machine condition monitoring applying domain generalization techniques''. Domain shifts are a critical problem for the application of ASD systems. Because domain shifts can change the acoustic characteristics of data, a model trained in a source domain performs poorly for a target domain. In DCASE 2021 Challenge Task 2, we organized an ASD task for handling domain shifts. In this task, it was assumed that the occurrences of domain shifts are known. However, in practice, the domain of each sample may not be given, and the domain shifts can occur implicitly. In 2022 Task 2, we focus on domain generalization techniques that detects anomalies regardless of the domain shifts. Specifically, the domain of each sample is not given in the test data and only one threshold is allowed for all domains. Analysis of 81 submissions from 31 teams revealed two remarkable types of domain generalization techniques: 1) domain-mixing-based approach that obtains generalized representations and 2) domain-classification-based approach that explicitly or implicitly classifies different domains to improve detection performance for each domain.Comment: arXiv admin note: substantial text overlap with arXiv:2106.0449