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Deep Depth from Focal Stack with Defocus Model for Camera-Setting Invariance
No full textWe propose deep depth from focal stack (DDFS), which takes a focal stack as input of a neural network for estimating scene depth. Defocus blur is a useful cue for depth estimation. However, the size of the blur depends on not only scene depth but also camera settings such as focus distance, focal length, and f-number. Current learning-based methods without any defocus models cannot estimate a correct depth map if camera settings are different at training and test times. Our method takes a plane sweep volume as input for the constraint between scene depth, defocus images, and camera settings, and this intermediate representation enables depth estimation with different camera settings at training and test times. This camera-setting invariance can enhance the applicability of DDFS. The experimental results also indicate that our method is robust against a synthetic-to-real domain gap.journal articl
Impact of crystallinity on thermal conductivity of RF magnetron sputtered MoS2 thin films
No full textThis study investigates the effects of sulfur atomic defects and crystallinity on the thermal conductivity of MoS2 thin films. Utilizing scanning transmission electron microscopy (STEM), X-ray diffraction (XRD), and Raman spectroscopy, we examined MoS2 films, several nanometers thick, deposited on Si/SiO2 substrates. These films were prepared via a combination of RF magnetron sputtering and sulfur vapor annealing (SVA) treatment. Structural analyses, including cross-sectional STEM and in-plane and out-of-plane XRD measurements, revealed an increase in the S/Mo ratio and grain size of the MoS2 films following SVA treatment. Notably, the in-plane thermal conductivity of MoS2 films treated with SVA was found to be at least an order of magnitude higher than that of films without SVA treatment. This research suggests that the in-plane thermal conductivity of MoS2 thin films can be significantly enhanced through crystallinity improvement via SVA treatment.journal articl
Utility analysis and demonstration of real-world clinical texts: A case study on Japanese cancer-related EHRs
No full textReal-world data (RWD) in the medical field, such as electronic health records (EHRs) and medication orders, are receiving increasing attention from researchers and practitioners. While structured data have played a vital role thus far, unstructured data represented by text (e.g., discharge summaries) are not effectively utilized because of the difficulty in extracting medical information. We evaluated the information gained by supplementing structured data with clinical concepts extracted from unstructured text by leveraging natural language processing techniques. Using a machine learning-based pretrained named entity recognition tool, we extracted disease and medication names from real discharge summaries in a Japanese hospital and linked them to medical concepts using medical term dictionaries. By comparing the diseases and medications mentioned in the text with medical codes in tabular diagnosis records, we found that: (1) the text data contained richer information on patient symptoms than tabular diagnosis records, whereas the medication-order table stored more injection data than text. In addition, (2) extractable information regarding specific diseases showed surprisingly small intersections among text, diagnosis records, and medication orders. Text data can thus be a useful supplement for RWD mining, which is further demonstrated by (3) our practical application system for drug safety evaluation, which exhaustively visualizes suspicious adverse drug effects caused by the simultaneous use of anticancer drug pairs. We conclude that proper use of textual information extraction can lead to better outcomes in medical RWD mining.journal articl
La[N(SiMe3)2]3: A highly active catalyst for the ring-opening polymerization of trimethylene carbonate
Get PDFPoly(trimethylene carbonate) (PTMC) has been extensively researched as biomaterials due to its biocompatibility and biodegradability. However, its limited mechanical strength has restricted its application in various commodity materials, necessitating an enhancement through higher molecular weight. A traditional method for synthesizing high molecular weight PTMC mainly involves SnOct2 as a polymerization catalyst, conducting trimethylene carbonate (TMC) polymerization at high temperatures over several days. This approach consumes significant time and energy, making further molecular weight enhancement challenging. In this study, we polymerized TMC using the highly active catalyst La[N(SiMe3)2]3. We have successfully synthesized high molecular weight PTMC (Mn >500,000) within minutes at room temperature. The tensile test results of PTMC molding films demonstrated strain-induced crystallization specific to high molecular weight PTMC.journal articl
Translation arrest cancellation of VemP, a secretion monitor in Vibrio, is regulated by multiple cis and trans factors, including SecY
No full textVemP is a secretory protein in the Vibrio species that monitors cellular protein-transport activity through its translation arrest, allowing expression of the downstream secD2-secF2 genes in the same operon, which encode components of the protein translocation machinery. When cellular protein-transport function is fully active, secD2/F2 expression remains repressed as VemP translation arrest is canceled immediately. The VemP arrest cancellation occurs on the SecY/E/G translocon in a late stage in the translocation process and requires both trans factors, SecD/F and PpiD/YfgM, and a cis element, Arg-85 in VemP; however, the detailed molecular mechanism remains elusive. This study aimed to elucidate how VemP passing through SecY specifically monitors SecD/F function. Genetic and biochemical studies showed that SecY is involved in the VemP arrest cancellation and that the arrested VemP is stably associated with a specific site in the protein-conducting pore of SecY. VemP-Bla reporter analyses revealed that a short hydrophobic segment adjacent to Arg-85 plays a critical role in the regulated arrest cancellation with its hydrophobicity correlating with the stability of the VemP arrest. We identified Gln-65 and Pro-67 in VemP as novel elements important for the regulation. We propose a model for the regulation of the VemP arrest cancellation by multiple cis elements and trans factors with different roles.journal articl
Investigating the Efficacy of Pain Relief Through a Robot's Stroking with Speech
Get PDF“Stroking” is generally recognized to contribute to pain relief. Recent research indicates that combining “stroking with speech” by a robot generates greater positive emotions in individuals than either “speech” or “stroking” only. It has also been known that positive emotions can mitigate the perception of pain. This study aimed to verify whether the action of “stroking with speech” by a robot can reduce pain. We established two hypotheses: 1. Based on the gate control theory, the action of “stroking” with tactile stimulation and “stroking with speech” have pain-relieving efects. 2. The action of “stroking with speech,” which has a greater psychological impact than “stroking,” has a more signifcant pain-relieving efect. Through experiments with 37 subjects, these two hypotheses were supported.conference pape
Electricity Theft Detection for Smart Homes: Harnessing the Power of Machine Learning with Real and Synthetic Attacks
No full textElectricity theft is a pervasive issue with economic implications that necessitate innovative approaches for its detection, given the critical challenge of limited labeled data. However, connecting smart home devices introduces numerous vectors for electricity theft. Therefore, this study introduces an innovative approach to detecting electricity theft in smart homes, leveraging knowledge-based, fine-grained, time-series appliance benign and anomalous consumption patterns. We simulated five attack classes and extended our model’s detection capabilities to unknown anomalies across residential settings by segmenting the anonymized data into three different home categories. We validated our experiment using simulated and real building attack data. Extreme Gradient Boost (XGB), Random Forest, and Multilayer Perceptron (MLP) outperform the legacy unsupervised model (LUM), which included MLP-Autoencoder (AE), 1D-CONV-AE, and Isolation Forest (RF). XGB had the highest average AUC scores of 98.69% and 98.74% for simulated and real attack detection, respectively, followed by RF at 96.76% and 97.07%, respectively, across all homes, indicating the robustness of our model in detecting benign and anomalous appliance consumption patterns. This study contributes to the academic discourse in the field and offers practical solutions to energy providers and stakeholders in the smart home industry.journal articl
ROS アプリケーション ニ オケル トピック ツウシン ノ キジュツ パターン オ モチイタ データフロー カシカ シュホウ
Get PDF本研究では，ソースコード中のトピック 通信の記述パターンに基づいて ROS アプリケーショ ン内部のデータフロー情報を可視化する手法を構築し た．Autoware.universe の二つのシミュレーションを対 象として，実行時に起きる可能性のある通信をソース コードをもとに可視化し，その結果が有用であること を開発者へのインタビューで確認した．journal articl
QA-based Event Start-Points Ordering for Clinical Temporal Relation Annotation
No full textTemporal relation annotation in the clinical domain is crucial yet challenging due to its workload and the medical expertise required. In this paper, we propose a novel annotation method that integrates event start-points ordering and question-answering (QA) as the annotation format. By focusing only on two points on a timeline, start-points ordering reduces ambiguity and simplifies the relation set to be considered during annotation. QA as annotation recasts temporal relation annotation into a reading comprehension task, allowing annotators to use natural language instead of the formalisms commonly adopted in temporal relation annotation. Based on our method, most of the relations in a document are inferable from a significantly smaller number of explicitly annotated relations, showing the efficiency of our proposed method. Using these inferred relations, we develop a temporal relation classification model that achieves a 0.72 F1 score. Also, by decomposing the annotation process into QA generation and QA validation, our method enables collaboration among medical experts and non-experts. We obtained high inter-annotator agreement (IAA) scores, which indicate the positive prospect of such collaboration in the annotation process. Our annotated corpus, annotation tool, and trained model are publicly available: https://github.com/seiji-shimizu/qa-start-ordering.conference pape
Bis(corannulenyl)ethene as an efficient photochromic material
No full textWe herein report photochromic 1,2-bis(2-methoxy-corannulenyl)perfluorocyclopentene (1) possessing two corannulene moieties as the side aryl units of diarylethene. One enantiomer and the other enantiomer of one chiral atropisomer of 1 respectively forming columnar structures in the crystal were revealed via single-crystal X-ray analysis. Compound 1 exhibited an efficient photochromic behaviour with a large molar absorption coefficient of 5.0 × 104 M22121, and significantly high photochemical quantum yields of 0.64 and 0.49 were demonstrated for photocyclization and photocycloreversion reactions, respectively. This high efficiency was rationalized by the changed abundance ratios of atropisomers between the open- and closed-isomers and the shortened distance between reactive carbons with the help of the curved structure. In addition, the application possibility of 1 as a photochromic material was demonstrated in a poly(methyl methacrylate) film.journal articl