DSpace 集合:
https://scholars.lib.ntu.edu.tw/handle/123456789/61212
2024-03-19T02:31:24ZCoexistence of Oligocene toothed and baleen-assisted mysticetes in the northwestern Pacific
https://scholars.lib.ntu.edu.tw/handle/123456789/640753
標題: Coexistence of Oligocene toothed and baleen-assisted mysticetes in the northwestern Pacific
作者: CHENG-HSIU TSAI; Kimura, Toshiyuki; Hasegawa, Yoshikazu
摘要: Oligocene mysticetes display an unparalleled diversity and morphological disparity in the evolutionary history of Mysticeti. However, their paleoecological aspects, such as the patterns of coexistence of different morphotypes, remain poorly explored. Here we describe an aetiocetid (toothed mysticete) from the Jinnobaru Formation (lower upper Oligocene, about 28 million years ago) of Umashima Island, Kitakyushu, Japan. Our description of a toothed mysticete from the Oligocene of Umashima exemplifies the coexistence of toothed and baleen-assisted mysticetes in the northwestern Pacific. Hopefully, new finds of Oligocene mysticetes will lead to a well-sampled dataset for analyzing this and other related paleoecological traits to understand the demise of “archaic” Oligocene mysticetes and the subsequent rise of the modern-looking baleen-bearing whales in Miocene times.2024-01-11T00:00:00ZFlower colour and size-signals vary with altitude and resulting climate on the tropical-subtropical islands of Taiwan
https://scholars.lib.ntu.edu.tw/handle/123456789/640213
標題: Flower colour and size-signals vary with altitude and resulting climate on the tropical-subtropical islands of Taiwan
作者: Shrestha, Mani; Tai, King-Chun; Dyer, Adrian G; Garcia, Jair E; EN-CHENG YANG; Jentsch, Anke; CHUN-NENG WANG
摘要: The diversity of flower colours in nature provides quantifiable evidence for how visitations by colour sensing insect pollinators can drive the evolution of angiosperm visual signalling. Recent research shows that both biotic and abiotic factors may influence flower signalling, and that harsher climate conditions may also promote salient signalling to entice scarcer pollinators to visit. In parallel, a more sophisticated appreciation of the visual task foragers face reveals that bees have a complex visual system that uses achromatic vision when moving fast, whilst colour vision requires slower, more careful inspection of targets. Spectra of 714 native flowering species across Taiwan from sea level to mountainous regions 3,300 m above sea level (a.s.l.) were measured. We modelled how the visual system of key bee pollinators process signals, including flower size. By using phylogenetically informed analyses, we observed that at lower altitudes including foothills and submontane landscapes, there is a significant relationship between colour contrast and achromatic signals. Overall, the frequency of flowers with high colour contrast increases with altitude, whilst flower size decreases. The evidence that flower colour signaling becomes increasingly salient in higher altitude conditions supports that abiotic factors influence pollinator foraging in a way that directly influences how flowering plants need to advertise.2024-02-01T00:00:00ZMacrophages enhance regeneration of lateral line neuromast derived from interneuromast cells through TGF-β in zebrafish
https://scholars.lib.ntu.edu.tw/handle/123456789/639763
標題: Macrophages enhance regeneration of lateral line neuromast derived from interneuromast cells through TGF-β in zebrafish
作者: Hsu, Wei-Lin; Lin, Yu-Chi; Lin, Meng-Ju; Wang, Yi-Wen; SHYH-JYE LEE
摘要: Macrophages play a pivotal role in the response to injury, contributing significantly to the repair and regrowth of damaged tissues. The external lateral line system in aquatic organisms offers a practical model for studying regeneration, featuring interneuromast cells connecting sensory neuromasts. Under normal conditions, these cells remain dormant, but their transformation into neuromasts occurs when overcoming inhibitory signals from Schwann cells and posterior lateral line nerves. The mechanism enabling interneuromast cells to evade inhibition by Schwann cells remains unclear. Previous observations suggest that macrophages physically interact with neuromasts, nerves, and Schwann cells during regeneration. This interaction leads to the regeneration of neuromasts in a subset of zebrafish with ablated neuromasts. To explore whether macrophages achieve this effect through secreted cytokines, we conducted experiments involving tail amputation in zebrafish larvae and tested the impact of cytokine inhibitors on neuromast regeneration. Most injured larvae remarkably regenerated a neuromast within 4 days post-amputation. Intriguingly, removal of macrophages and inhibition of the anti-inflammatory cytokine transforming growth factor-beta (TGF-β) significantly delayed neuromast regeneration. Conversely, inhibition of the pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) had minor effects on the regeneration process. This study provides insights into how macrophages activate interneuromast cells, elucidating the pathways underlying neuromast regeneration.2024-01-28T00:00:00ZAn Automated Machine Learning System for Generating Myocardial Infarction Location Classifiers Using Lead-I ECG Signal
https://scholars.lib.ntu.edu.tw/handle/123456789/639762
標題: An Automated Machine Learning System for Generating Myocardial Infarction Location Classifiers Using Lead-I ECG Signal
作者: Wang, Shaunna; SU-YI TSAI; Chang, Jui Chih
摘要: This research paper proposes a novel machine learning (ML) system to automate the generation of myocardial infarction (MI) classifiers using lead I electrocardiogram (ECG) signals. The proposed system comprises three primary processes: data preprocessing, automated model generation, and model evaluation. The automated model generation process executes two procedures, namely, model generation and model optimization. In the model generation procedure, the system utilizes ten feature engineering algorithms and nine machine learning models to generate 90 models automatically. The generated models are then fine-tuned by the model optimization procedure through meta learning and hyperparameter optimization algorithms. The proposed system's significant advantage is that users only need to provide the dataset and prediction target of an application, and the embedded machine learning algorithms automatically generate an optimal model. The system is easy to use and an end-to-end modeling solution that can be applied to various fields without requiring machine learning expertise. To validate the system's effectiveness, the Physikalisch-Technische Bundesanstalt (PTB) open electrocardiogram (ECG) dataset is utilized to generate a myocardial infarction (MI) location classifier using the lead I ECG signal of the dataset. Among the 90 models generated, the random forest model with the system-identified parameters achieved the best performance, achieving an accuracy, sensitivity, specificity, F1 score, and classification accuracy of 99.90%, 99.46%, 99.94%, 99.55%, and 99.40%, respectively. The results demonstrate that the proposed automated ML system is an efficient and effective approach for non-ML experts to leverage AI technology to solve their applications in an easy-to-use, end-to-end manner.2023-01-01T00:00:00Z