大きな対寸法変位を有するムービングマグネット及びムービングコイル型3軸電磁MEMSアクチュエータ

要約のみTohoku University田中秀治課

Betula mcallisteri sp. nov. (sect. Acuminatae, Betulaceae), a new diploid species overlooked in the wild and in cultivation, and its relation to the widespread B. luminifera

Taxa are traditionally identified using morphological proxies for groups of evolutionarily isolated populations. These proxies are common characters deemed by taxonomists as significant. However, there is no general rule on which character or sets of characters are appropriate to circumscribe taxa, leading to discussions and uncertainty. Birch species are notoriously hard to identify due to strong morphological variability and factors such as hybridization and the existence of several ploidy levels. Here, we present evidence for an evolutionarily isolated line of birches from China that are not distinguishable by traditionally assumed taxon recognition proxies, such as fruit or leaf characters. We have discovered that some wild material in China and some cultivated in the Royal Botanic Gardens Edinburgh, formerly recognized as Betula luminifera, differ from other individuals by having a peeling bark and a lack of cambial fragrance. We use restriction site-associated DNA sequencing and flow cytometry to study the evolutionary status of the unidentified Betula samples to assess the extent of hybridization between the unidentified Betula samples and typical B. luminifera in natural populations. Molecular analyses show the unidentified Betula samples as a distinct lineage and reveal very little genetic admixture between the unidentified samples and B. luminifera. This may also be facilitated by the finding that B. luminifera is tetraploid, while the unidentified samples turned out to be diploid. We therefore conclude that the samples represent a yet unrecognized species, which is here described as Betula mcallisteri.Copyright © 2023 Zhang, Ding, Holstein and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. The attached file is the published version of the article.NHM Repositor

Past anthropogenic land use change caused a regime shift of the fluvial response to Holocene climate change in the Chinese Loess Plateau

The Wei River catchment in the southern part of the Chinese Loess Plateau (CLP) is one of the centers of the agricultural revolution in China. The area has experienced intense land use changes since ∼6000 BCE, which makes it an ideal place to study the response of fluvial systems to past anthropogenic land cover change (ALCC). We apply a numerical landscape evolution model that combines the Landlab landscape evolution model with an evapotranspiration model to investigate the direct and indirect effects of ALCC on hydrological and morphological processes in the Wei River catchment since the mid-Holocene. The results show that ALCC has not only led to changes in discharge and sediment load in the catchment but also affected their sensitivity to climate change. When the proportion of agricultural land area exceeded 50 % (around 1000 BCE), the sensitivity of discharge and sediment yield to climate change increased abruptly indicating a regime change in the fluvial catchment. This was associated with a large sediment pulse in the lower reaches. The model simulation results also show a link between human settlement, ALCC and floodplain development: changes in agricultural land use led to downstream sediment accumulation and floodplain development, which in turn resulted in further spatial expansion of agriculture and human settlement.</p

Rare Disease Identification from Clinical Notes with Ontologies and Weak Supervision

The identification of rare diseases from clinical notes with Natural Language Processing (NLP) is challenging due to the few cases available for machine learning and the need of data annotation from clinical experts. We propose a method using ontologies and weak supervision. The approach includes two steps: (i) Text-to-UMLS, linking text mentions to concepts in Unified Medical Language System (UMLS), with a named entity linking tool (e.g. SemEHR) and weak supervision based on customised rules and Bidirectional Encoder Representations from Transformers (BERT) based contextual representations, and (ii) UMLS-to-ORDO, matching UMLS concepts to rare diseases in Orphanet Rare Disease Ontology (ORDO). Using MIMIC-III US intensive care discharge summaries as a case study, we show that the Text-to-UMLS process can be greatly improved with weak supervision, without any annotated data from domain experts. Our analysis shows that the overall pipeline processing discharge summaries can surface rare disease cases, which are mostly uncaptured in manual ICD codes of the hospital admissions.Comment: 5 pages, 3 figures, accepted for IEEE EMBC 202

Transcriptome and comparative gene expression analysis of Phyllostachys edulis in response to high light

The values of gene expression in Calvin cycle and photorespiratory metabolism. (XLSX 12 kb

A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction

The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithms mostly rely on the availability of pixel-level annotations, which are often expensive, tedious, and laborious. To alleviate this burden, the past years have witnessed an increasing attention in building label-efficient, deep-learning-based image segmentation algorithms. This paper offers a comprehensive review on label-efficient image segmentation methods. To this end, we first develop a taxonomy to organize these methods according to the supervision provided by different types of weak labels (including no supervision, inexact supervision, incomplete supervision and inaccurate supervision) and supplemented by the types of segmentation problems (including semantic segmentation, instance segmentation and panoptic segmentation). Next, we summarize the existing label-efficient image segmentation methods from a unified perspective that discusses an important question: how to bridge the gap between weak supervision and dense prediction -- the current methods are mostly based on heuristic priors, such as cross-pixel similarity, cross-label constraint, cross-view consistency, and cross-image relation. Finally, we share our opinions about the future research directions for label-efficient deep image segmentation.Comment: Accepted to IEEE TPAM

Late Quaternary aggradation and incision in the headwaters of the Yangtze River, eastern Tibetan Plateau, China

River aggradation or incision at different spatial-temporal scales are governed by tectonics, climate change, and surface processes which all adjust the ratio of sediment load to transport capacity of a channel. But how the river responds to differential tectonic and extreme climate events in a catchment is still poorly understood. Here, we address this issue by reconstructing the distribution, ages, and sedimentary process of fluvial terraces in a tectonically active area and monsoonal environment in the headwaters of the Yangtze River in the eastern Tibetan Plateau, China. Field observations, topographic analyses, and optically stimulated luminescence dating reveal a remarkable fluvial aggradation, followed by terrace formations at elevations of 55-62 m (T7), 42-46 m (T6), 38 m (T5), 22-36 m (T4), 18 m (T3), 12-16 m (T2), and 2-6 m (T1) above the present floodplain. Gravelly fluvial accumulation more than 62 m thick has been dated prior to 24-19 ka. It is regarded as a response to cold climate during the last glacial maximum. Subsequently, the strong monsoon precipitation contributed to cycles of rapid incision and lateral erosion, expressed as cut-in-fill terraces. The correlation of terraces suggests that specific tectonic activity controls the spatial scale and geomorphic characteristics of the terraces, while climate fluctuations determine the valley filling, river incision and terrace formation. Debris and colluvial sediments are frequently interbedded in fluvial sediment sequences, illustrating the episodic, short-timescale blocking of the channel ca. 20 ka. This indicates the potential impact of extreme events on geomorphic evolution in rugged terrain