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Sexual dimorphism in the Chinese endemic species Pachyhynobius shangchengensis Fei, Qu and Wu, 1983 (Urodela: Hynobiidae)

Jianli Xiong, Baowei Zhang, Qiangqiang Liu, Tao Pan, Jianping Gou
2019 PeerJ  
The Shangcheng stout salamander (Pachyhynobius shangchengensis Fei, Qu & Wu, 1983) is an endemic and poorly known Chinese salamander, which is only distributed in the Dabie Mountains of Southeastern China  ...  shihi are aquatic throughout the year (permanently aquatic), the species of Hynobius, S. keyserlingii, Ps. flavomaculatus and O. zhangyapingi are mainly terrestrial, and aquatic only during breeding (Fei  ... 
doi:10.7717/peerj.6408 pmid:30809436 pmcid:PMC6385682 fatcat:rea724e7ljentfzjqnnml54r7m

Voices from Unoccupied China. Liu Naichen , Tsai Chaio , C. K. Chu , J. Heng Liu , Fei Hsiato-t'ung, Wu Ching-Chaio , Chin Yueh-lin , Harley Farnsworth MacNair

Allan B. Cole
1944 The Journal of modern history  
One of the most interesting papers was given by Professor Fei Hsiao-t’ung on ‘Some social problems of free China.”  ...  HENG Liu, Fer Hsrao-t’unNG, Wu Cutnc-CuHatro, and CHIN YUEH-LIN. Edited by HARLEY FARNSWORTH MAcNarr. Chicago: Univer- sity of Chicago Press, 1944. Pp. 99. $1.50.  ... 
doi:10.1086/236842 fatcat:keouinn3ufgmldkr5njwtpxcje

Density alteration in non-physiological cells

Ming Wang, Hai-Cheng Li, Lin-Na Li, Ju-Xiang Li, Yu Liu, Yuan-Chang Zhu, Bin-Bin Wu, Xiao-Hua Wu, Fei-Fei Lan, Jia Fei, Jian-Ge Wei
2011 Nature Precedings  
In present study an important phenomenon of cells was discovered: the change of intracellular density in cell's response to drug and environmental factors. For convenience this phenomenon is named as "density alteration in non-physiological cells" ( DANCE). DANCE was determined by discontinuous sucrose gradient centrifugation (DSGC), in which cells were separated into several bands. The number and position of the bands in DSGC varied with the change of cell culture conditions, drugs, and
more » ... l process, indicating that cell's response to these factors was associated with alteration of intracellular density. Our results showed that the bands of cells were molecularly different from each other, such as the expression of some mRNAs. For most cells tested, intracellular density usually decreased when the cells were in bad conditions, in presence of dugs, or undergoing pathological changes. However, unlike other tissue cells, brain cells showed increased intracellular density in 24 hrs after the animal death. In addition, DANCE was found to be related to drug resistance, with higher drug-resistance in cells of lower intracellular density. Further study found that DANCE also occurred in microorganisms including bacteria and fungus, suggesting that DANCE might be a sensitive and general response of cells to drugs and environmental change. The mechanisms for DANCE are not clear. Based on our study the following causes were hypothesized: change of metabolism mode, change of cell membrane function, and pathological change. DANCE could be important in medical and biological sciences. Study of DANCE might be helpful to the understanding of drug resistance, development of new drugs, separation of new subtypes from a cell population, forensic analysis, and importantly, discovery of new physiological or pathological properties of cells. In a previous study we found that RT-PCR results varied in a significantly great range. The poor repeatability of the RT-PCR results could not be explained by the standard deviation of the method. Even under same experimental conditions cells responded quite differently to a same drug. To find out if there were different cells in a cell line with different sensitivities to a drug, we tried to
doi:10.1038/npre.2011.6541.1 fatcat:5zscpld265hczignakf7m74rjq

Galaxy Learning -- A Position Paper [article]

Chao Wu, Jun Xiao, Gang Huang, Fei Wu
2019 arXiv   pre-print
The recent rapid development of artificial intelligence (AI, mainly driven by machine learning research, especially deep learning) has achieved phenomenal success in various applications. However, to further apply AI technologies in real-world context, several significant issues regarding the AI ecosystem should be addressed. We identify the main issues as data privacy, ownership, and exchange, which are difficult to be solved with the current centralized paradigm of machine learning training
more » ... thodology. As a result, we propose a novel model training paradigm based on blockchain, named Galaxy Learning, which aims to train a model with distributed data and to reserve the data ownership for their owners. In this new paradigm, encrypted models are moved around instead, and are federated once trained. Model training, as well as the communication, is achieved with blockchain and its smart contracts. Pricing of training data is determined by its contribution, and therefore it is not about the exchange of data ownership. In this position paper, we describe the motivation, paradigm, design, and challenges as well as opportunities of Galaxy Learning.
arXiv:1905.00753v1 fatcat:q7wb5gcejnbc3ear5r4jmy6equ

Designing optimal quantum cloning machine for qubit system [article]

Xiaohua Wu, Fei Wu
2010 arXiv   pre-print
Following the work of Niu and Griffiths, in Phys.Rev.A 58, 4377(1998), we shall investigate the problem, how to design the optimal quantum cloning machines (QCMs) for qubit system, with the help of Bloch-sphere representation. In stead of the quality factor there, the Fiurás̆ek's optimal condition, where the optimal cloning machine should maximize a convex mixture of the average fidelity, is used as the optimality criterion in present protocol. Almost all of the known optimal QCMs in previous
more » ... rks, the cloning for states with fixed polar angle, the phase-covariant cloning, the universal QCMs, the cloning for two arbitrary pure states, and the mirror phase-covariant cloning, should be discussed in a systematic way. The known results, the optimal fidelities for various input ensembles according to different optimality criteria, are recovered here. Our present scheme also offers a general way of constructing the unitary transformation to realize the optimal cloning.
arXiv:1004.5210v1 fatcat:ux2ftozvybd6bnkvvr2ra5kgva

Macrophages Promote Coal Tar Pitch Extract-induced Tumorigenesis of BEAS-2B Cells and Tumor Metastasis in Nude Mice Mediated by AP-1

Peng Zhang, Yue-Fei Jin, Qiao Zhang, Yi-Ming Wu, Wei-Dong Wu, Wu Yao, Yong-Jun Wu, Zhi-Tao Li, Yong Zhao, Yu Liu, Fei-Fei Feng
2014 Asian Pacific Journal of Cancer Prevention  
Nude Mice Mediated by AP-1 Peng Zhang 1 , Yue-Fei Jin 2& , Qiao Zhang 3 , Yi-Ming Wu 2 , Wei-Dong Wu 4 , Wu Yao 2 , Yong-Jun Wu 3 , Zhi-Tao Li 2 , Yong Zhao 2 , Yu Liu 2 , Fei-Fei Feng 3 * al., 2012;  ... 
doi:10.7314/apjcp.2014.15.12.4871 fatcat:57xmakctovauzafmmkfbmgdgi4

5-MethylL-glutamate

Yong-Fei Wu, Fen-Fang Li, Long-Fei Jin
2005 Acta Crystallographica Section E  
doi:10.1107/s1600536805032952 fatcat:fvuriqrgkjdqtotmtg7p26fmq4

Superfluid density and collective modes of fermion superfluid in dice lattice

Yu-Rong Wu, Xiao-Fei Zhang, Chao-Fei Liu, Wu-Ming Liu, Yi-Cai Zhang
2021 Scientific Reports  
AbstractThe superfluid properties of attractive Hubbard model in dice lattice are investigated. It is found that three superfluid order parameters increase as the interaction increases. When the filling factor falls into the flat band, due to the infinite large density of states, the resultant superfluid order parameters are proportional to interaction strength, which is in striking contrast with the exponentially small counterparts in usual superfluid (or superconductor). When the interaction
more » ... s weak, and the filling factor is near the bottom of the lowest band (or the top of highest band), the superfluid density is determined by the effective mass of the lowest (or highest) single-particle band. When the interaction is strong and filling factor is small, the superfluid density is inversely proportional to interaction strength, which is related to effective mass of tightly bound pairs. In the strong interaction limit and finite filling, the asymptotic behaviors of superfluid density can be captured by a parabolic function of filling factor. Furthermore, when the filling is in flat band, the superfluid density shows a logarithmic singularity as the interaction approaches zero. In addition, there exist three undamped collective modes for strong interactions. The lowest excitation is gapless phonon, which is characterized by the total density oscillations. The two others are gapped Leggett modes, which correspond relative density fluctuations between sublattices. The collective modes are also reflected in the two-particle spectral functions by sharp peaks. Furthermore, it is found that the two-particle spectral functions satisfy an exact sum-rule, which is directly related to the filling factor (or density of particle). The sum-rule of the spectral functions may be useful to distinguish between the hole-doped and particle-doped superfluid (superconductor) in experiments.
doi:10.1038/s41598-021-93007-z pmid:34193952 pmcid:PMC8245560 fatcat:a32jn5acbzevbk46ysd2q442yu

Metallogenic Mechanism of Typical Carbonate-Hosted Uranium Deposits in Guizhou (China)

Lin-Fei Qiu, Yu Wu, Qiong Wang, Lin-Feng Wu, Zhong-Bo He, Song Peng, Yun-Fei Fan
2022 Minerals  
Research on topics such as geological–tectonic evolution, metallogenic models of deposits (gold, mercury, lead, zinc, etc.), and ore-forming fluids' evolution has been conducted in Guizhou. However, few studies have been conducted on uranium (U) deposits (especially carbonate-hosted U deposits). Moreover, the relationship between hydrocarbon fluids and U-mineralization has not been addressed at all. Typical carbonate-hosted U deposits (including some ore spots) in Guizhou Province have been
more » ... stigated through close field work, petrography, mineralogical, micro-spectroscopy, organic geochemical and C isotope studies. The central part of the U-ore body is often black (the black alternation zone) at the outcrop, and its sides are gray and gray-brown (the gray alternation zone); the color gradually becomes lighter (black to gray) from the center of the ore body out to the sides. Petrographic observations, microscopic laser Raman spectroscopy, and infrared spectroscopic and scanning electron microscope analyses have indicated that U-minerals (pitchblende and coffinite), pyrite and "black" organic matter (OM) are closely co-dependent, with the OM having the typical characteristics of bitumen. Large light oil fluid inclusions were found in gray alternation rocks (besides the U-ore body) with strong light blue fluorescence properties, indicating that hydrocarbon fluids and U-minerals may came from the same U-bearing hydrocarbon fluids. The values of the 13C isotope value, a biomarker of OM and trace elements, REEs in U-ores, were found to be similar here to those in the local paleo-petroleum reservoir, indicating that the bitumen may originate from the deeply intruding paleo-petroleum reservoir. The precipitation of U is related to the cracking differentiation of hydrocarbon fluids. As result, the carbonate-hosted U-mineralization in Guizhou is neither of a sedimentary diagenesis type, nor of a sedimentary diagenesis superimposed leaching hydrothermal transformation type, as have been described by previous scholars. To be exact, the U deposit is controlled by fault and hydrocarbon fluids, and so it can be defined as a structural hydrocarbon–carbonate-type U deposit. A new U-mineralization model was proposed in this study. Here, U, molybdenum, and other metals were mainly found in the black rocks in the lower stratum (presumably Niutitang Formation), having migrated together with hydrocarbon fluids in the form of tiny mineral inclusions. The hydrocarbon fluids (containing some brine) caused cracking and differentiation upon entering the fracture zone, at which point the ore-forming materials (U, pyrite, and other metals) were released and precipitated.
doi:10.3390/min12050585 fatcat:yfgwslgn6rb3fps4kqqlb2gr7m

Federated Graph Learning – A Position Paper [article]

Huanding Zhang, Tao Shen, Fei Wu, Mingyang Yin, Hongxia Yang, Chao Wu
2021 arXiv   pre-print
[Wu et al., 2021] designs a federated GNN framework for privacy preserving recommendation.  ...  Therefore, discovering latent edges among local subgraphs of clients is a crucial challenge in horizontal intra-graph FL, there are some researches who have mentioned it, [Wu et al., 2021] proposes a  ... 
arXiv:2105.11099v1 fatcat:6bhzsfiwwvgndizffwokpuiaym

Outcome-based student assessment enhances academic performance in basic medical laboratory course

Kai-Feng Li, Bo-Zhi Liu, Fei-Fei Wu, Xia-Cheng Sun, Fei Tian, You-Sheng Wu, Le-Le Ji, Nan-Nan Liu, Hai-Feng Zhang, Ya-Yun Wang
2021 Advances in Physiology Education  
Basic medical laboratory courses (BMLCs) play an important role in medical educational courses helping the student acquire three important skills of surgical operating, collaborative learning, and problem solving. The outcome-based student assessment (OBSA) is a learning evaluation method that establishes specific evaluation points based on performance of students in three aspects: surgical operating, collaborative learning, and problem solving in the BMLC curriculum practices. The purpose of
more » ... e present randomized controlled trial study is to explore the efficiency of OBSA program in BMLCs. The 233 students attending BMLCs were randomly divided into 2 groups, 118 in the OBSA group and 115 in the control group. We conducted multiple-choice examination questions (MCQs) test and two questionnaires with the method of two-sample t test for statistics. The results of MCQs in total eight BMLC blocks showed that the academic performance of the OBSA group was significantly better than that of the control group (P < 0.05). In addition, the average scores of direct observation of procedural skills (DOPS) and mini-experimental evaluation exercise in OBSA group were significantly higher than those in control group (P < 0.05). The majority of the medical students preferred the OBSA and considered OBSA could effectively improve their surgical operating skills (83.9%), collaborative learning skills (92.1%), and problem-solving skills (91.1%). From the above, OBSA is an effective evaluation method for the implementation of the BMLC curriculum.
doi:10.1152/advan.00157.2020 pmid:33825525 fatcat:ukea4putpnbxdenjyxpveosyeu

A mode-locked external-cavity quantum-dot laser with a variable repetition rate

Jian Wu, Peng Jin, Xin-Kun Li, Heng Wei, Yan-Hua Wu, Fei-Fei Wang, Hong-Mei Chen, Ju Wu, Zhan-Guo Wang
2013 Chinese Physics B  
A mode-locked external-cavity laser emitting at 1.17-µm wavelength using an InAs/GaAs quantum-dot gain medium and a discrete semiconductor saturable absorber mirror is demonstrated. By changing the external-cavity length, repetition rates of 854, 912, and 969 MHz are achieved respectively. The narrowest −3-dB radio-frequency linewidth obtained is 38 kHz, indicating that the laser is under stable mode-locking operation.
doi:10.1088/1674-1056/22/10/104206 fatcat:go3fqtil6vh4hhvbu7aprj7a6a

Memory Regulation and Alignment toward Generalizer RGB-Infrared Person [article]

Feng Chen, Fei Wu, Qi Wu, Zhiguo Wan
2021 arXiv   pre-print
The domain shift, coming from unneglectable modality gap and non-overlapped identity classes between training and test sets, is a major issue of RGB-Infrared person re-identification. A key to tackle the inherent issue – domain shift – is to enforce the data distributions of the two domains to be similar. However, RGB-IR ReID always demands discriminative features, leading to over-rely feature sensitivity of seen classes, e.g., via attention-based feature alignment or metric learning.
more » ... predicting the unseen query category from predefined training classes may not be accurate and leads to a sub-optimal adversarial gradient. In this paper, we uncover it in a more explainable way and propose a novel multi-granularity memory regulation and alignment module (MG-MRA) to solve this issue. By explicitly incorporating a latent variable attribute, from fine-grained to coarse semantic granularity, into intermediate features, our method could alleviate the over-confidence of the model about discriminative features of seen classes. Moreover, instead of matching discriminative features by traversing nearest neighbor, sparse attributes, i.e., global structural pattern, are recollected with respect to features and assigned to measure pair-wise image similarity in hashing. Extensive experiments on RegDB and SYSU-MM01 show the superiority of the proposed method that outperforms existing state-of-the-art methods. Our code is available in https://github.com/Chenfeng1271/MGMRA.
arXiv:2109.08843v1 fatcat:7cupwlsuonccxe4akw4la5hfhu

Learning Decomposed Representation for Counterfactual Inference [article]

Anpeng Wu, Kun Kuang, Junkun Yuan, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu
2021 arXiv   pre-print
The fundamental problem in treatment effect estimation from observational data is confounder identification and balancing. Most of the previous methods realized confounder balancing by treating all observed pre-treatment variables as confounders, ignoring further identifying confounders and non-confounders. In general, not all the observed pre-treatment variables are confounders that refer to the common causes of the treatment and the outcome, some variables only contribute to the treatment and
more » ... some only contribute to the outcome. Balancing those non-confounders, including instrumental variables and adjustment variables, would generate additional bias for treatment effect estimation. By modeling the different causal relations among observed pre-treatment variables, treatment and outcome, we propose a synergistic learning framework to 1) identify confounders by learning decomposed representations of both confounders and non-confounders, 2) balance confounder with sample re-weighting technique, and simultaneously 3) estimate the treatment effect in observational studies via counterfactual inference. Empirical results on synthetic and real-world datasets demonstrate that the proposed method can precisely decompose confounders and achieve a more precise estimation of treatment effect than baselines.
arXiv:2006.07040v2 fatcat:mw4twlenybevxgc6bflzzsqj5y

Semantic Exploration of Traffic Dynamics [article]

Fei Wu, Hongjian Wang, Zhenhui Li
2018 arXiv   pre-print
Given a large collection of urban datasets, how can we find their hidden correlations? For example, New York City (NYC) provides open access to taxi data from year 2012 to 2015 with about half million taxi trips generated per day. In the meantime, we have a rich set of urban data in NYC including points-of-interest (POIs), geo-tagged tweets, weather, vehicle collisions, etc. Is it possible that these ubiquitous datasets can be used to explain the city traffic? Understanding the hidden
more » ... n between external data and traffic data would allow us to answer many important questions in urban computing such as: If we observe a high traffic volume at Madison Square Garden (MSG) in NYC, is it because of the regular peak hour or a big event being held at MSG? If a disaster weather such as a hurricane or a snow storm hits the city, how would the traffic be affected? While existing studies may utilize external datasets for prediction task, they do not explicitly seek for direct explanations from the external datasets. In this paper, we present our results in attempts to understand taxi traffic dynamics in NYC from multiple external data sources. We use four real-world ubiquitous urban datasets, including POI, weather, geo-tagged tweet, and collision records. To address the heterogeneity of ubiquitous urban data, we present carefully-designed feature representations for various datasets. Extensive experiments on real data demonstrate the explanatory power on taxi traffic by using external datasets. More specifically, our analysis suggests that POIs can well describe the regular traffic patterns. At the same time, geo-tagged tweets can explain irregular traffic caused by big events and weather can explain the abnormal traffic drop.
arXiv:1804.04165v1 fatcat:7wbcz5x4bjbtrc4qtzlfzb7tui
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