13,447 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Comparative genomic and transcriptomic analysis revealed genetic characteristics related to solvent formation and xylose utilization in <it>Clostridium acetobutylicum </it>EA 2018
No full textAbstract Background Clostridium acetobutylicum, a gram-positive and spore-forming anaerobe, is a major strain for the fermentative production of acetone, butanol and ethanol. But a previously isolated hyper-butanol producing strain C. acetobutylicum EA 2018 does not produce spores and has greater capability of solvent production, especially for butanol, than the type strain C. acetobutylicum ATCC 824. Results Complete genome of C. acetobutylicum EA 2018 was sequenced using Roche 454 pyrosequencing. Genomic comparison with ATCC 824 identified many variations which may contribute to the hyper-butanol producing characteristics in the EA 2018 strain, including a total of 46 deletion sites and 26 insertion sites. In addition, transcriptomic profiling of gene expression in EA 2018 relative to that of ATCC824 revealed expression-level changes of several key genes related to solvent formation. For example, spo0A and adhEII have higher expression level, and most of the acid formation related genes have lower expression level in EA 2018. Interestingly, the results also showed that the variation in CEA_G2622 (CAC2613 in ATCC 824), a putative transcriptional regulator involved in xylose utilization, might accelerate utilization of substrate xylose. Conclusions Comparative analysis of C. acetobutylicum hyper-butanol producing strain EA 2018 and type strain ATCC 824 at both genomic and transcriptomic levels, for the first time, provides molecular-level understanding of non-sporulation, higher solvent production and enhanced xylose utilization in the mutant EA 2018. The information could be valuable for further genetic modification of C. acetobutylicum for more effective butanol production.</p
Supplemental Material - Low-dose metformin suppresses hepatocellular carcinoma metastasis via the AMPK/JNK/IL-8 pathway
No full textSupplemental Material for Low-dose metformin suppresses hepatocellular carcinoma metastasis via the AMPK/JNK/IL-8 pathway by Chengwen Zhao, Lu Zheng, Yuting Ma, Yue Zhang, Chanjuan Yue, Feng Gu, Guoping Niu, and Yongqiang Chen in International Journal of Immunopathology and Pharmacology</p
Supplemental Material - Characterizing the inherent activity of urinary bladder matrix for adhesion, migration, and activation of fibroblasts as compared with collagen-based synthetic scaffold
No full textSupplemental Material for Characterizing the inherent activity of urinary bladder matrix for adhesion, migration, and activation of fibroblasts as compared with collagen-based synthetic scaffold by Xiaoyu Tang, Fengbo Yang, Guoping Chu, Xiaoxiao Li, Qiuyan Fu, Mingli Zou, Peng Zhao, and Guozhong Lu in Journal of Biomaterials Applications</p
sj-docx-1-tan-10.1177_17562864221114355 – Supplemental material for Characteristics and trends of globally registered glioma clinical trials in the past 16 years
No full textSupplemental material, sj-docx-1-tan-10.1177_17562864221114355 for Characteristics and trends of globally registered glioma clinical trials in the past 16 years by Xiaofang He, Wenbin Zhao, Jianwen Huang, Jia Xu, Shaoqing Niu, Qun Zhang, Nu Zhang, Huawei Jin and Guoping Shen in Therapeutic Advances in Neurological Disorders</p
Raw data of Zhao et al., 2022, Geoderma
No full textRaw data associated with Zhao et al., 2022, Geoderma. Any use of the data set should be approved by the corresponding author Kai Yue at "[email protected]".</p
Dynamics of magnetic skyrmion clusters driven by spin-polarized current with a spatially varied polarization
No full textMagnetic skyrmions are promising candidates for future information technology. Here, we present a micromagnetic study of isolated skyrmions and skyrmion clusters in ferromagnetic nanodisks driven by the spin-polarized current with spatially varied polarization. The current-driven skyrmion clusters can be either dynamic steady or static, depending on the spatially varied polarization profile. For the dynamic steady state, the skyrmion cluster moves in a circle in the nanodisk, while for the static state, the skyrmion cluster is static. The frequency of the circular motion of skyrmion is also studied. Furthermore, the dependence of the skyrmion cluster dynamics on the magnetic anisotropy and Dzyaloshinskii-Moriya interaction is investigated. Our results may provide a pathway to realize magnetic skyrmion cluster based devices.</p
Chao Yuen Ren (1892–1982)
No full textY. R. Chao is easily the most famous linguist to have come out of China. Born before the end of the last dynasty in China, he received a traditional Confucian education, but was also one of the first Chinese people to be sent to the West for training in modern Western science (under the Boxer Indemnity Fund). The remarkable breadth and scope of his studies included physics, mathematics, linguistics, musical and literary composition, and translation, and he was a pioneer in many of these fields
Gated relational stacked denoising autoencoder with localized author embedding for global citation recommendation
No full textCitation recommendation is an effective and efficient way to facilitate authors finding desired references. This paper presents a novel neural network based model, called gated relational probabilistic stacked denoising autoencoder with localized author (GRSLA) embedding, for global citation recommendation task. Our model is comprised of two modules with different neural network architecture. For each citing and cited papers, we use a gated paper embedding module, which is extended from probabilistic stacked denoising autoencoder (PSDAE) by adding gated units, to obtain their paper vectors. The added gated units are able to utilize text information of cited paper to refine the vector representation of citing paper in multiple semantic levels. For an author in papers, we first apply topic model to obtain his/her semantic neighbors, and then use a localized author embedding (LAE) module to excavate author vector representation from semantic and explicit neighbors. Unlike most graph convolutional network (GCN) based methods, the LAE module is able to avoid computing global Laplacian in whole graph by taking limited neighbors. Moreover, the LAE module can also be stacked to absorb more neighbors, which makes our model have high extendibility. Based on the generation process of GRSLA, we also derive a learning algorithm of our model by maximum a posteriori (MAP) estimation. We conduct experiments on the AAN, DBLP and CORD-19 datasets, and the results show that GRSLA model works well than previous global citation recommendation methods
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