12,136 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDFWe 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
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
sj-docx-1-ajs-10.1177_03635465221125936 – Supplemental material for Microfracture Augmentation With Direct In Situ Radial Shockwave Stimulation With Appropriate Energy Has Comparable Repair Performance With Tissue Engineering in the Porcine Osteochondral Defect Model
No full textSupplemental material, sj-docx-1-ajs-10.1177_03635465221125936 for Microfracture Augmentation With Direct In Situ Radial Shockwave Stimulation With Appropriate Energy Has Comparable Repair Performance With Tissue Engineering in the Porcine Osteochondral Defect Model by Zhidong Zhao, Ji Li, Xiaowei Bai, Yuxing Wang, Qi Wang, Ningyu Lv, Huayi Gao, Zheng Guo, Heng Zhu, Quanyi Guo and Zhongli Li in The American Journal of Sports Medicine</p
Enhanced particle self-ordering in a double-layer channel
No full textIn this work, a novel double-layer microfluidic device for enhancing particle focusing was presented. The double-layer device consists of a channel with expansion-contraction array and periodical slanted grooves. The secondary flows induced by the grooves modulate the flow patterns in the expansion-contraction-array (ECA) channel, further affecting the particle migration. Compared with the single ECA channel, the double-layer channel can focus the particles over a wider range of flow rate. Due to the differentiation of lateral migration, the double-layer channel is able to distinguish the particles with different sizes. Furthermore, the equilibrium positions could be modulated by the orientation of grooves. This work demonstrates the possibility to enhance and adjust the inertial focusing in an ECA channel with the assistance of grooves, which may provide a simple and portable platform for downstream filtration, separation, and detection
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
Codon usage bias analysis of the spike protein of human coronavirus 229E and its host adaptability
No full textHuman coronavirus 229E (HCoV-229E) represents one of the known coronaviruses capable of infecting humans and causes mild respiratory symptoms. It is also considered to have a zoonotic source, originating from animals and being transmitted the humans. In this study, a comprehensive phylogenetic and codon usage analysis of the spike (S) gene of HCoV-229E was conducted. Utilizing phylogenetic analysis and principal component analysis, HCoV-229E was categorized into four distinct clusters, each demonstrating unique host affiliations. Furthermore, it was observed that the codon usage bias within the S gene of HCoV-229E is relatively low, primarily influenced by natural selection patterns, with contributions from mutation pressure and dinucleotide abundance. Comparative analysis involving Codon Adaptation Index (CAI) and Relative Codon Deoptimization Index (RCDI) revealed that the codon usage pattern of HCoV-229E mirrors more closely that of camels, as opposed to alpacas and humans. The elucidation of the codon usage pattern within HCoV-229E, which we have meticulously examined, offers valuable insights for a more comprehensive comprehension of viral features, history, and evolutionary trajectory
Liquid metal-based amalgamation-assisted lithography for fabrication of complex channels with diverse structures and configurations
No full textNumerous lab-on-a-chip applications benefit from channels with complex structures and configurations in the areas of tissue engineering and clinical diagnostics. The current fabrication approaches require time-consuming, complicated processes and bulky, expensive facilities. In this work, we propose a novel method for the fabrication of complex channels with the assistance of amalgamation of liquid metal with copper tape. This new technique enables the rapid fabrication of liquid metal molds with various dimensions and diverse structures. Two proof-of-concept experiments were conducted to verify the utilization of this method. First, the channel replicated from the liquid metal mold is used to enhance the mixing performance of liquids flowing through the channel. Second, a channel with a semicircular cross-section is fabricated to achieve 3D focusing in a simple way. This proposed technique can be readily used for fabricating complex channels for a wide range of applications.Full Tex
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
Modeling nitrogen nutrient loss and ammonia emissions from animal farms
Get PDFAuthor institution (Zhao): Department of Food, Agricultural, and Biological Engineering, The Ohio State Universit
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