Accurate Mode-Coupling Characterization of Low-Crosstalk Ring-Core Fibers using Integral Calculation based Swept-Wavelength Interferometry Measurement

In this paper, to accurately characterize the low inter-mode coupling of the weakly-coupled few mode fibers (FMFs), we propose a modified inter-mode coupling characterization method based on swept-wavelength interferometry measurement, in which an integral calculation approach is used to eliminate significant sources of error that may lead to underestimation of the power coupling coefficient. Using the proposed characterization method, a low-crosstalk ring-core fiber (RCF) with low mode dependent loss (MDL) and with single span length up to 100 km is experimentally measured to have low power coupling coefficients between high-order orbital angular momentum (OAM) mode groups of below -30 dB/km over C band. The measured low coupling coefficients based on the proposed method are verified by the direct system power measurements, proving the feasibility and reliability of the proposed inter-mode coupling characterization method

AIDA directly connects sympathetic innervation to adaptive thermogenesis by UCP1

AIDA最早是由林圣彩教授团队首先鉴定和命名的。2007年林圣彩教授团队与孟安明院士团队合作发现AIDA在斑马鱼体轴发育中的功能(Rui, 2007)。2018年，林圣彩教授团队首次发现了AIDA在哺乳动物中的功能，即AIDA介导的内质网降解途径通过降解脂肪合成途径中的关键酶，而限制膳食脂肪在肠道的吸收这一内在抵御肥胖(Luo, 2018)。而本次成果揭示了AIDA在棕色脂肪组织中特定的功能。这些工作将AIDA引入了脂质应激代谢的重要环节，包括脂质吸收和依赖于脂质的产热过程。该论文的共同第一作者为生命科学学院博士生史猛和硕士生黄晓羽，林圣彩教授和林舒勇教授则为共同通讯作者。【Abstract】The sympathetic nervous system–catecholamine–uncoupling protein 1 (UCP1) axis plays an essential role in non-shivering adaptive thermogenesis. However, whether there exists a direct effector that physically connects catecholamine signalling to UCP1 in response to acute cold is unknown. Here we report that outer mitochondrial membrane-located AIDA is phosphorylated at S161 by the catecholamine-activated protein kinase A (PKA). Phosphorylated AIDA translocates to the intermembrane space, where it binds to and activates the uncoupling activity of UCP1 by promoting cysteine oxidation of UCP1.Adipocyte-specific depletion of AIDA abrogates UCP1-dependent thermogenesis, resulting in hypothermia during acute cold exposure. Re-expression of S161A-AIDA, unlike wild-type AIDA, fails to restore the acute cold response in Aida-knockout mice.The PKA–AIDA–UCP1 axis is highly conserved in mammals, including hibernators. Denervation of the sympathetic postganglionic fibres abolishes cold-induced AIDA-dependent thermogenesis. These findings uncover a direct mechanistic link between sympathetic input and UCP1-mediated adaptive thermogenesis.We thank Y. Li, E. Gnaiger, T. Kuwaki, J. R. B. Lighton, E. T. Chouchani and D. Jiang for technical instruction; X. Li and X.-D. Jiang (Core Facility of Biomedical, Xiamen University) for raising the p-S161-AIDA antibody; the Xiamen University Laboratory Animal Center for the mouse in vitro fertilization service and all the other members of S.C.L. laboratory for their technical assistance. This work was supported by grants from the National Key Research and Development Project of China (grant no. 2016YFA0502001) and the National Natural Science Foundation of China (grant nos 31822027, 31871168, 31690101, 91854208 and 82088102), the Fundamental Research Funds for the Central Universities (grant nos 20720190084 and 20720200069), Project ‘111’ sponsored by the State Bureau of Foreign Experts and Ministry of Education of China (grant no. BP2018017), the Youth Innovation Fund of Xiamen (grant no. 3502Z20206028), the Natural Science Foundation of Fujian Province of China (grant no. 2017J01364) and XMU Training Program of Innovation and Entrepreneurship for Undergraduates (grant no. 2019×0666). 该工作得到了厦门大学实验动物中心和生物医学学部仪器平台的重要协助和国家重点研究和发展项目，国家自然科学基金，厦门大学校长基金等的支持

Hypergraph based semi-supervised symmetric nonnegative matrix factorization for image clustering

Semi-supervised symmetric nonnegative matrix factorization (SNMF) has been shown to be a significant method for both linear and nonlinear data clustering applications. Nevertheless, existing SNMF-based methods only adopt a simple graph to construct the similarity matrix, and cannot fully use the limited supervised information for the construction of the similarity matrix. To overcome the drawbacks of previous SNMF-based methods, a new semi-supervised SNMF-based method called hypergraph based semi-supervised SNMF (HSSNMF), is proposed in this paper for image clustering. Specifically, HSSNMF adopts a predefined hypergraph to build a similarity matrix for capturing the high-order relationships of samples. By exploiting a new hypergraph based pairwise constraints propagation (HPCP) algorithm, HSSNMF propagates the pairwise constraints of the limited data points to the entire data points, which can make full use of the limited supervised information and construct a more informative similarity matrix. Using the multiplicative updating algorithm, a discriminative assignment matrix can then be obtained by solving the optimization problem of HSSNMF. Moreover, analyses of the convergence, supervisory information, and computational complexity of HSSNMF are presented. Finally, extensive clustering experiments have been conducted on six real-world image datasets, and the experimental results have demonstrated the superiority of HSSNMF while compared with several state-of-the-art methods.This work is supported in part by the National Nature Science Foundation of China (no. U21A20485, 61976175), the Guangdong Basic and Applied Basic Research Foundation (no. 2021A1515011341), Guangzhou Science and Technology Plan Project (no. 202002030386), and Guangdong Provincial Key Laboratory of Intellectual Property and Big Data under Grant (no. 2018B030322016)

Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors

Abstract Conventional machine learning (ML) and deep learning (DL) play a key role in the selectivity prediction of kinase inhibitors. A number of models based on available datasets can be used to predict the kinase profile of compounds, but there is still controversy about the advantages and disadvantages of ML and DL for such tasks. In this study, we constructed a comprehensive benchmark dataset of kinase inhibitors, involving in 141,086 unique compounds and 216,823 well-defined bioassay data points for 354 kinases. We then systematically compared the performance of 12 ML and DL methods on the kinase profiling prediction task. Extensive experimental results reveal that (1) Descriptor-based ML models generally slightly outperform fingerprint-based ML models in terms of predictive performance. RF as an ensemble learning approach displays the overall best predictive performance. (2) Single-task graph-based DL models are generally inferior to conventional descriptor- and fingerprint-based ML models, however, the corresponding multi-task models generally improves the average accuracy of kinase profile prediction. For example, the multi-task FP-GNN model outperforms the conventional descriptor- and fingerprint-based ML models with an average AUC of 0.807. (3) Fusion models based on voting and stacking methods can further improve the performance of the kinase profiling prediction task, specifically, RF::AtomPairs + FP2 + RDKitDes fusion model performs best with the highest average AUC value of 0.825 on the test sets. These findings provide useful information for guiding choices of the ML and DL methods for the kinase profiling prediction tasks. Finally, an online platform called KIPP ( https://kipp.idruglab.cn ) and python software are developed based on the best models to support the kinase profiling prediction, as well as various kinase inhibitor identification tasks including virtual screening, compound repositioning and target fishing

Mid-Miocene uplift of the northern Qilian Shan as a result of the northward growth of the northern Tibetan Plateau

The northern Tibetan Plateau, north of the Qaidam Basin and south of the Hexi Corridor (China), consists of a series of WNW- to NW-trending elongated mountain ranges. Deciphering the time-space deformation pattern of these ranges is central to understanding the mechanism of plateau formation and to the controversial issue of whether Tibet has undergone progressive northward growth or synchronous growth since the India-Eurasia collision. Here, we report new constraints on the timing of accelerated uplift of the Tuolai Shan, one of the elongated mountain ranges in the northern Tibetan Plateau. New apatite fission-track data from an elevation transect in the Tuolai Shan provide a definitive tie to rapid cooling that began at 17-15 Ma. We attribute this rapid cooling to accelerated exhumation resulting from thrusting in the hanging wall of the Haiyuan fault in response to progressive northward growth of the plateau. Combining these fission-track data and the published geologic, sedimentological, and thermochronologic data from the northern Qilian Shan and Hexi Corridor, we propose a progressively north-northeastward growth model for the northernmost part of Tibet, suggesting that deformation in the inner Qilian Shan occurred synchronously in the middle Miocene, and subsequently, increasingly further north

Gold Nanostar@Polyaniline Theranostic Agent with High Photothermal Conversion Efficiency for Photoacoustic Imaging-Guided Anticancer Phototherapy at a Low Dosage

10.1021/acsami.2c05679ACS Applied Materials & Interfaces142528570-2858

Miocene Range Growth Along the Altyn Tagh Fault: Insights From Apatite Fission Track and (U-Th)/He Thermochronometry in the Western Danghenan Shan, China

The left‐lateral strike‐slip Altyn Tagh fault that defines the northern margin of the Tibetan Plateau plays a crucial role in accommodating the Cenozoic deformation related to the growth of plateau. However, the slip history along the fault remains highly debated. Here we report new 14–16 Ma apatite fission track (AFT) and 9–11 Ma apatite (U‐Th)/He (AHe) data in the western Danghenan Shan, north Tibet. Age‐elevation relationships and AFT/AHe age differences suggest a period of rapid exhumation with an average rate of 0.1–0.3 km/Ma from 16 to 9 Ma for this area. Thermal history modeling indicates that this was preceded by accelerated exhumation between the late Oligocene and middle Miocene (~15 Ma). A northward increase in AFT ages and asymmetric topography across the western Danghenan Shan indicate that the uplift and exhumation are mainly controlled by the thrust fault along the southern flank of the western Danghenan Shan. As the thrust fault is a branch of the Altyn Tagh fault, the rapid exhumation probably represents onset of the transition along the Altyn Tagh fault from left‐slip motion to crustal shortening in the Dangnenan Shan region. Our findings show that the middle Miocene deformation is not only recorded in the middle and northern Qilian Shan but also in the southwestern portion of the Qilian Shan, which favors a synchronous middle‐Miocene deformation model for the entire Qilian Shan

Expression of salt-responsive gene families.

<p>Expression of salt-responsive gene families.</p

Summary of read statistics from RNA-sequencing of <i>Crossostephium chinensis</i>.

<p>Summary of read statistics from RNA-sequencing of <i>Crossostephium chinensis</i>.</p