13197 research outputs found
Sort by
Synthesis and Spectroscopic Properties of Diarylethene-Subporphyrinoid Hybrids
Get PDFTwo novel diarylethene-fused subporphyrinoids were prepared and characterized. A mono diarylethene derivative was obtained via a statistical condensation reaction with 22005eq. of thiophene-disubstituted butenedinitrile. The symmetric triply diarylethene-fused subporphyrazine was synthesized via a cyclotrimerization reaction of the thiophene-disubstituted butenedinitrile derivative. These compounds were characterized by NMR spectroscopy and high-resolution mass spectrometry. The spectroscopic properties have been measured in hexane and in chloroform. The mono diarylethene-fused-type compound showed photochromism at 5802005nm wavelength, accompanied by degradation. According to DFT calculations, photoreactivity likely depends on the contribution of aromatic feature of pyrrole ring bonded to two thiophene rings.journal articl
Functional characterization of the Csm1-like protein TITAN 9 in Arabidopsis thaliana
No full textKinetochores are essential for chromosome segregation in eukaryotes. An important component of kinetochores in opisthokonta is Csm1. However, its function appears to be diversified and, while Csm1 in budding yeast is a component of the monopolin complex mediating mono-orientation of sister kinetochores during meiosis I, the fission yeast homolog Pcs1 prevents merotelic spindle microtubule attachments during mitosis and meiosis II. Here, we have characterized TITAN9 (TTN9), a distantly related Csm1-like protein in the flowering plant Arabidopsis. TTN9 accumulates in mitotic and meiotic tissue and localizes to centromeres throughout the cell cycle. By analyzing proteome-wide TTN9 associated proteins, we identified a substantial subset of the Arabidopsis kinetochore proteome, including DSN1, mirroring known Csm1 interactions in yeast. While homozygous ttn9 mutants are not viable, a meiosis-specific knock-down of TTN9 causes chromosome segregation defects and split centromeres during meiosis I. These findings suggest that Csm1-like proteins contribute to conserved kinetochore functions across eukaryotes.journal articl
Enhancing image reconstruction method in high-frequency electric field visualization systems using a polarized light image sensor
No full textThis paper introduces an image processing method, used to achieve uniform sensitivity across the imaging plane in a high-frequency electric field imaging system, that employs an electro-optical crystal and a polarization image sensor. The polarization pixels have two polarization directions, 0° and 90°, in pairs, and, conventionally, their difference is computed first. In contrast, this study proposes a method to separate each polarization image, perform pixel completion, and subsequently perform intensity correction. The proposed method was demonstrated to improve field distribution images acquired using 36 GHz and 30 GHz input signals for a microstrip line and patch antenna, respectively. From the measurement results of the microstrip line, the application of the proposed method reduced the electric field fluctuations on the line from 3.1 dB to 1.5 dB. This image-processing method can be applied sequentially during image acquisition, making it suitable for the real-time imaging of electric fields.journal articl
Enhanced Estimation of Bone Mineral Content from an X-ray Image Using Diffusion Models to Quantify Prediction Uncertainty for Osteoporosis Diagnosis
Get PDF奈良先端科学技術大学院大学修士（工学）master thesi
Toward Cross-Hospital Deployment of Natural Language Processing Systems: Model Development and Validation of Fine-Tuned Large Language Models for Disease Name Recognition in Japanese
No full textBackground: Disease name recognition is a fundamental task in clinical natural language processing, enabling the extraction of critical patient information from electronic health records. While recent advances in large language models (LLMs) have shown promise, most evaluations have focused on English, and little is known about their robustness in low-resource languages such as Japanese. In particular, whether these models can perform reliably on previously unseen in-hospital data, which differs from training data in writing styles and clinical contexts, has not been thoroughly investigated. Objective: This study evaluated the robustness of fine-tuned LLMs for disease name recognition in Japanese clinical notes, with a particular focus on their performance on in-hospital data that was not included during training. Methods: We used two corpora for this study: (1) a publicly available set of Japanese case reports denoted as CR, and (2) a newly constructed corpus of progress notes, denoted as PN, written by ten physicians to capture stylistic variations of in-hospital clinical notes. To reflect real-world deployment scenarios, we first fine-tuned models on CR. Specifically, we compared a LLM and a baseline-masked language model (MLM). These models were then evaluated under two conditions: (1) on CR, representing the in-domain (ID) setting with the same document type, similar to training, and (2) on PN, representing the out-of-domain (OOD) setting with a different document type. Robustness was assessed by calculating the performance gap (ie, the performance drop from in-domain to out-of-domain settings). Results: The LLM demonstrated greater robustness, with a smaller performance gap in F1-scores (ID–OOD = −8.6) compared to the MLM baseline performance (ID–OOD = −13.9). This indicated more stable performance across ID and OOD settings, highlighting the effectiveness of fine-tuned LLMs for reliable use in diverse clinical settings. Conclusions: Fine-tuned LLMs demonstrate superior robustness for disease name recognition in Japanese clinical notes, with a smaller performance gap. These findings highlight the potential of LLMs as reliable tools for clinical natural language processing in low-resource language settings and support their deployment in real-world health care applications, where diversity in documentation is inevitable.journal articl
Venus flytraps' metabolome analysis discloses the metabolic fate of prey animal foodstock
No full textCarnivorous plants such as the Venus flytrap Dionaea muscipula survive in nutrient-poor habitats by attracting and consuming animals. Upon deflection of the touch-sensitive trigger hairs, the trap closes instantly. Panicking prey repeatedly collides with trigger hairs, which activate the endocrine system: mechano- and chemosensors translate the information on the prey's nature, size, and activity into jasmonate-dependent lytic enzyme secretion. This digestive fluid gradually degrades its exoskeleton and internal tissues. The released substances are absorbed by glands covering the inner trap surface. To understand Dionaea's modification of metabolism upon prey consumption, we compared the metabolic profiles associated with secretion and insect feeding. In favor of digestive enzyme secretion, the abundance of most amino acids decreased after JA-stimulation without prey present. By contrast, insect feeding resulted in an increase in almost all amino acids within the trap. In agreement with the export of prey-derived nitrogen, the abundance of certain amino acids also increased in the petiole. In response to feeding with urea, chitin, nucleic acids, or phospholipids, the amino acid profile remained relatively unchanged. This might indicate that the alterations in the Venus flytrap's metabolism depend both on the type of substance and on its amount.journal articl
Forecasting Road Traffic Volume Using Temporal-Only Time Series Models
No full textPredicting road traffic in road networks is essential for alleviating congestion and enhancing traffic flow efficiency. This study presents a traffic volume prediction model trained using time-series data collected from loop detectors installed at three junctions in Istanbul, Turkey. The detectors record vehicle counts, providing the historical data used to train a residual LSTM model designed to forecast vehicle volumes 15 minutes into the future. The proposed model achieved an average mean absolute error of 0.26 across multiple loop detectors, demonstrating its effectiveness in accurately predicting short-term traffic volumes.conference pape