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Measuring diversity in research works is critical to the promotion of scientific evaluation. Existing approaches usually focus on quantifying the diverse interdisciplinary states of research fields, lacking fine-grained detection and comparative analysis between different diversity calculation schemas at the level of individual scholars. To clearly recognize essential characters of research content and reflect important research diversity characteristics of scholars, we propose to use entitymetrics analysis for the scholar-level diversity measurement. Compared to disciplines or topics, minimal stable knowledge units embedded in scientific papers have advantages in mining knowledge usage and capturing the microscopic differences among contents. In this study, we compare six diversity calculation schemas based on the three primary properties of entity diversity: variety, balance, and disparity. The comparison demonstrates the usefulness of entities in portraying manifold subject categories, detecting content disparity, and characterizing content distribution patterns of research, which reflects research diversity of scholars in a more granular way. It also points out the respective features, scopes, and application scenarios of each schema, which provides further guidance for selections and appropriate usage of schemas, ultimately fostering the accurate scientific assessment of scholar characteristics (e.g., the cross-disciplinary collaboration potentiality, academic aptitude, multi-subject problem-solving skills). [ABSTRACT FROM AUTHOR]

Interdisciplinary research is increasingly recognized as one of the solutions to today's challenging scientific and societal issues. Many studies have aimed to explore the relationship between the interdisciplinarity of research and the attention they receive from the scientific community as well as society. However, the relationship between interdisciplinarity and attention from policy documents remains unclear. In this study, we utilize publications data on the COVID-19 topic to explore such a relationship. Through the analysis and interpretation of empirical datasets, this research finds that there is a positive correlation between the interdisciplinarity of scientific publications and the attention they receive from policy documents in almost all fields. Among the three dimensions (i.e., variety, balance, and disparity) of interdisciplinarity, variety exhibits the most pronounced positive impact on political attention. This study fills a previous research gap and provides insights for researchers and policymakers, highlighting that interdisciplinary research holds greater potential to impact policy formulation and implementation processes. [ABSTRACT FROM AUTHOR]

Interdisciplinary research is a driving force of transformative and innovative science, yet it remains unclear how early-career scientists pursue interdisciplinary research paths. Analyzing data from 675,135 doctoral theses of U.S. Ph.D. graduates who graduated from 1950 to 2016, we study the development of interdisciplinary doctoral theses in the five scientific domains of behavioral sciences, biological sciences, engineering, health and medical sciences, and mathematical and physical sciences. We propose an indicator to measure the degree of interdisciplinarity embedded in the doctoral research by employing co-occurrence matrices of subjects assigned to doctoral theses in the ProQuest Dissertations & Theses Database. This study finds that interdisciplinary doctoral theses have exhibited a growing trend across different scientific domains, and universities of varying research intensity. Since the 1990s, interdisciplinary research has played a dominant role in doctoral theses within the five scientific domains. The results of multivariate regression models suggest persistent gender disparities in the interdisciplinarity level of doctoral theses. Specifically, male-authored doctoral theses demonstrate a higher level of interdisciplinarity than female-authored doctoral theses. In addition, this study suggests that being supervised by female advisors may amplify gender disparities in the interdisciplinarity level of their students' doctoral theses. The findings indicate the potential underrepresentation of female scientists in pursuing interdisciplinary research at the early stages of their careers. Given that funding agencies have promoted interdisciplinary research and its potential benefits, the lower level of interdisciplinarity in the doctoral theses of female students may hinder their career advancement. Furthermore, our findings indicate that offering increased support to female faculty members may not only directly benefit their career development but also hold considerable significance in promoting future generations of female scientists. The findings of this study have important policy implications for advancing the careers of female scientists. [ABSTRACT FROM AUTHOR]

In this era characterized by fast development of urbanization, public transportation problem is one of the main obstacles for people to promote their life satisfaction in China. This paper aims at discussing problems on mass customization public transportation, providing suggestions and consults for its sustainable development and improvement. A mass customization model for public transportation is constructed based on client requirement and cost analysis, and case studies are made to validate route planning results. Results show that mass customization public transportation can make high profit for bus companies and relieve traffic congestion and air contamination. [ABSTRACT FROM AUTHOR]

In this study, we introduce a new literature-aging conceptual model to study the citation curve and discuss its implications. First, we improve the conceptual model by adding a period to describe the "death" of citations. Second, we offer a feasible operationalization for this conceptual model and implement a set of cross-discipline publications in the Web of Science to test its performance. Furthermore, we propose two measurements according to the new model—"Sleeping Period" and "Recognition Period"—to capture publications' citation curve patterns. For instance, we find that half of the papers in Arts & Humanities published in 1985 receive no or extremely few citations in the first 5 years after their publication; after that, on average, those papers in Arts & Humanities have a 5-year-long period when their citations grow rapidly. In addition, we observe a special phenomenon named "literature revival" as some publications may have multiple citation life-cycles, which has received little attention from current research. Finally, we discuss the implications of our study, especially the application of the Sleeping Period and Recognition Period in improving scientific evaluation and collection development in libraries, and the inspiration of the "literature revival". [ABSTRACT FROM AUTHOR]

Downloads and citations of papers are regarded as significant metrics of the academic level of researchers and the influence of journals. Besides, exploring the association between them helps grease the wheels of the academic evaluation system. In this paper, we select 7552 articles published in The Lancet from January 2007 to October 2017 as the research sample and conduct Granger causal inference to investigate the relationship and directionality between downloads and citations. Furthermore, based on the download-citation patterns of articles, this study stratifies articles to explore the directionality between the downloads and citations of articles with different patterns. The results show that 75.86% of the articles have Granger causality between download and citation counts, suggesting that there is a significant causal relationship between downloads and citations. Specifically, the proportion of articles with bilateral Granger causality between download counts and citation counts is the highest, accounting for 35.51%; the proportion of articles whose download counts affect citation counts unilaterally accounts for 14.3%; and the proportion of articles whose citation counts affect download counts unilaterally accounts for 26.05%; 24.14% of the articles have no Granger causality between downloads and citations. Further, most Lancet articles are downloaded more at the early stage after publication, while the citations mainly appear after a period of time, making the slope trend of downloads and citations inconsistent throughout the citation life cycle. Meanwhile, the Granger causal relationship between downloads and citations is related to the slope of their curves. That is, the metric with a lower slope tends to be influenced by the metric with a higher slope. [ABSTRACT FROM AUTHOR]

Responsible indicators are crucial for research assessment and monitoring. Transparency and accuracy of indicators are required to make research assessment fair and ensure reproducibility. However, sometimes it is difficult to conduct or replicate studies based on indicators due to the lack of transparency in conceptualization and operationalization. In this paper, we review the different variants of the Probabilistic Affinity Index (PAI), considering both the conceptual and empirical underpinnings. We begin with a review of the historical development of the indicator and the different alternatives proposed. To demonstrate the utility of the indicator, we demonstrate the application of PAI to identifying preferred partners in scientific collaboration. A streamlined procedure is provided, to demonstrate the variations and appropriate calculations. We then compare the results of implementation for 5 specific countries involved in international scientific collaboration. Despite the different proposals on its calculation, we do not observe large differences between the PAI variants, particularly with respect to country size. As with any indicator, the selection of a particular variant is dependent on the research question. To facilitate appropriate use, we provide recommendations for the use of the indicator given specific contexts. [ABSTRACT FROM AUTHOR]

This paper proposes keyword-citation-keyword (KCK) network to analyze the knowledge structure of a discipline. Different from traditional co-word network analysis, KCK network highlights the importance of keywords assigned in different articles, as well as the semantic relationship between keywords in various articles. In this study, we select computer science domain as an example to illustrate the proposed method. Meanwhile, the results of network analysis, PageRank analysis, and research topic analysis are compared with those of traditional co-word analysis. A total of 110,360 articles with 164,146 unique keywords and 1,615,030 references collected from ACM digital library have been used for this empirical study. The results demonstrate that KCK network outperforms in detecting indirect links between keywords with higher semantic relationship, identifying important knowledge units, as well as discovering the topics with greater significance. Findings from this study contribute to a new perspective and understanding for elucidating discipline knowledge structures, and provide guidance for applying this method in various disciplines. [ABSTRACT FROM AUTHOR]

PubMed® is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguous, which has significantly hindered knowledge discovery. To address this issue, we constructed a PubMed knowledge graph (PKG) by extracting bio-entities from 29 million PubMed abstracts, disambiguating author names, integrating funding data through the National Institutes of Health (NIH) ExPORTER, collecting affiliation history and educational background of authors from ORCID®, and identifying fine-grained affiliation data from MapAffil. Through the integration of these credible multi-source data, we could create connections among the bio-entities, authors, articles, affiliations, and funding. Data validation revealed that the BioBERT deep learning method of bio-entity extraction significantly outperformed the state-of-the-art models based on the F1 score (by 0.51%), with the author name disambiguation (AND) achieving an F1 score of 98.09%. PKG can trigger broader innovations, not only enabling us to measure scholarly impact, knowledge usage, and knowledge transfer, but also assisting us in profiling authors and organizations based on their connections with bio-entities. Measurement(s) textual entity • author information textual entity • funding source declaration textual entity • abstract • Biologic Entity Classification Technology Type(s) machine learning • computational modeling technique Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12452597 [ABSTRACT FROM AUTHOR]

In recent years, magnetic interference thin films have gained wide attention in optical security devices field by virtue of their gonioapparent and dynamic 3D effects. Based on the color mechanism of metal-dielectric Fabry-Perot structure, a novel seven-layer magnetic thin film structure is proposed by adopting the ultrathin metal layer as a bonding layer and a pure metallic Ni layer as a magnetic layer as well as a reflective layer. Color target optimization optimac method is utilized that realizes the seven-layer metal-dielectric optically variable magnetic thin film structure with green at the normal incidence and purple-red at 60°. The structure effectively solves the delaminate problem and simplifies the multilayer structure. Through different combined magnetic field designs, the magnetic orientation experiment of the prepared magnetic optically variable thin film is carried out, and the 3D anti-counterfeiting with remarkable dynamic color change effect is obtained, which provides a new solution for optical security devices. [ABSTRACT FROM AUTHOR]

Understanding communications across disciplines is critical to the promotion of interdisciplinary innovation. Using research into the psychological concept of joint attention (JA) as an example of shared interest, this paper focuses on studies of JA across three different domains (child psychology, robotics, and human–computer interaction) and analyzes topic evolution in JA in these three domains, as well as lead–lag and topic similarity between domains. Our empirical study has yielded interesting findings. First, the analysis of topic evolution indicates that the three domains have distinctive topic evolution patterns, which reflected in both the topic division and merge phenomena and points of focus. Second, lead–lag clearly exists between different domains, which allowed knowledge diffusion to be viewed from a macroscopic perspective. Third, topic similarity across different domains can be identified with its migrations and changes in content, which helps to improve understanding of the impact of topics between domains and of interdependence within disciplines. This paper provides a foundation for further research that may improve communications across disciplines, thereby facilitating interdisciplinary innovation. [ABSTRACT FROM AUTHOR]

This paper proposes a novel concept of the citing cascade, defined as a network comprising citing relationships between a paper and its citing paper, as well as those among its citing papers. Compared with citation counts using a single number, citing cascades reveal the structural information of citation networks of a scientific publication and thus help us better understand the citation impact of a scientific publication (called the owner of the citing cascade). We then define and elaborate on several basic and advanced properties of citing cascades. By employing computer science publication records in the Microsoft Academic Graph dataset, we found that cascade size, edge count, in-degree, and out-degree all follow typical power law distributions with various exponential parameters (α). In addition, cascade depth is observed to follow an exponential distribution. We also examine the relation between citation count of the owner and some advanced properties that we defined. Many related future studies are also illustrated at the end of this paper. [ABSTRACT FROM AUTHOR]

Understanding the formation of interdisciplinary research (IDF) is critically important for the promotion of interdisciplinary development. In this paper, we adopt extracted keywords to investigate the features of interdisciplinarity development, as well as the distinct roles that different participating domains play in various periods, and detect potential barriers among domains. We take joint attention (JA) as the study domain, since it has undergone a development process from a topic of one domain to interdisciplinary research (IDR). Our empirical study has yielded interesting findings. First, we detect the phenomenon of knowledge diffusion as it evolved through three domains of JA. It enabled us to observe the shift of roles the domains played during the process of IDF, as well as the existence of potential barriers among these domains. Second, according to the diffusion and development process of JA among domains, three phases that an IDR field in general goes through were identified: a latent phase, an embryo phase, and a mature phase. Third, domains may play different roles in distinct periods, with the formation of IDR. Four roles are identified: knowledge origin, knowledge receiver, knowledge respondent, and interdisciplinary participant. This paper showcases how to detect the evolution of IDR by analyzing keyword evolution. By giving the profiles of IDR fields and descriptions of keyword evolution, it would be valuable for policy makers and regulators to promote IDR development. [ABSTRACT FROM AUTHOR]

Citation is regarded as one of the “norms of science” (Merton in Am Sociol Rev 22(6):635-659, 1957) and is deeply researched by the field of scientometrics. The motivations authors have for citing one another are considered significant and have been the subject of extensive qualitative research such as content analysis, questionnaires, and interviews of citing authors. However, the existing qualitative studies have covered a limited number of samples. To expand the dataset, this paper proposes a quantitative method applied to detecting citation reasons from the angle of citation networks and the attributes of cited authors, including their publication count (the number of single-authored publications, collaborative and first-authored publications as well as collaborative but non-first-authored publications, and number of whole publications), citation count, research topic interests, and gender. By applying the Exponential Random Graph Models (ERGMs), the current study revealed that authors in the field of information retrieval tend to cite those with more single-authored, collaborative and first-authored, and collaborative but not first-authored publications. Besides, in this field, the number of publications, similar topical domains, and same gender are proven to be significantly favorable in selecting references in our experiment. [ABSTRACT FROM AUTHOR]

As a frequently used method of depicting scientific intellectual structures, author co-citation analysis (ACA) has been applied to many domains. However, only count-based information is involved as the input of ACA, which is not sufficiently informative for knowledge representations. This article catches several metadata in full text of citing papers but not aims at content-level information, which increases the amount of information input to ACA without increasing computational complexity a lot. We propose a new method by involving information including the number of mentioned times in a citing paper and the number of context words in a citing sentence. We combine these pieces of information into the traditional ACA and compare the results between ACA and the proposed approach by using factor analysis, network analysis, and MDS-measurement. The result of our empirical study indicates that compared with the traditional ACA, the proposed method shows a better clustering performance in visualizations and reveals more details in displaying intellectual structures. [ABSTRACT FROM AUTHOR]

This study explores the international profiles in collaboration and mobility of countries included in the so-called “travel bans” implemented by US President Trump as executive order in 2017. The objective of this research is to analyze the exchange of knowledge between countries and the relative importance of specific countries in order to inform evidence-based science policy. The work serves as a proof-of-concept of the utility of asymmetry and affinity indexes for collaboration and mobility. Comparative analyses of these indicators can be useful for informing immigration policies and motivating collaboration and mobility relationships—emphasizing the importance of geographic and cultural similarities. Egocentric and relational perspectives are analyzed to provide various lenses on the importance of countries. Our analysis suggests that comparisons of collaboration and mobility from an affinity perspective can identify discrepancies between levels of collaboration and mobility. This approach can inform international immigration policies and, if extended, demonstrate potential partnerships at several levels of analysis (e.g., institutional, sectoral, state/province). [ABSTRACT FROM AUTHOR]

The increasing number of open-access full-text scientific documents promotes the transformation from metadata- to content-based studies, which is more detailed and semantic. Along with the benefits of ample data, the confused internal structure introduces great difficulties to data organization and analysis. Each unit in scientific documents has its own function in expressing authors’ research ideas, such as introducing motivations, describing methods, stating related work, and drawing conclusions; these could be used to identify functional structure of scientific documents. This paper firstly proposes a clustering method to generate domain-specific structures based on high-frequency section headers in scientific documents of a domain. To automatically identify the structure of scientific documents, we categorize scientific documents into three types: (1) strong-structure documents; (2) weak-structure documents; and (3) no-structure documents. We further divide the identification into three levels—section header-based identification, section content-based identification, and paragraph-based identification—corresponding to the three types of documents. Our experiments on documents in the field of computer science show that: (1) section header-based identification is the most direct and simplest method, but its accuracy is limited by unknown words in section headers; (2) section content-based identification is more stable and obtains good performance; and (3) paragraph-based identification is promising in identifying functions of no-structure documents. Additionally, we apply our methods to two tasks: academic search and keyword extraction. Both tasks demonstrate the effectiveness of functional structure. [ABSTRACT FROM AUTHOR]

Stability has long been regarded as an important characteristic of many natural and social processes. In regards to scientific collaborations, we define stability to reflect the consistent investment of a certain amount of effort into a relationship. In this paper, we provide an explicit definition of a new indicator of stability, based on the year-to-year publication output of collaborations. We conduct a large-scale analysis of stability among collaborations between authors publishing in the field of computer science. Collaborations with medium–high degree of stability tend to occur most frequently, and on average, have the highest average scientific impact. We explore other “circumstances”, reflecting the composition of collaborators, that may interact with the relationship between stability and impact, and show that (1) Transdisciplinary collaborations with low stability leads to high impact publications; (2) Stable collaboration with the collaborative author pairs showing greater difference in scientific age or career impact can produce high impact publications; and (3) Highly-cited collaborators whose publications have a large number of co-authors do not keep stable collaborations. We also demonstrate how our indicator for stability can be used alongside other similar indicators, such as persistence, to better understand the nature of scientific collaboration, and outline a new taxonomy of collaborations. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a hybrid satellite-terrestrial cooperative relay system, where both of the source-relay and source-destination links experience independent non-identical shadowed-Rician fading while the relay-destination link undergoes uncorrelated Rayleigh fading. By employing maximal-ratio-combining at the destination to combine the signals from the direct link and the fixed-gain relay links, we first obtain the analytical expression for the moment generating function (MGF) of the output signal-to-noise ratio (SNR). Then, with the help of the obtained MGF, we derive the theoretical formulas for the ergodic capacity and average symbol error rate of the considered system. Moreover, the asymptotic analysis at high SNR is also presented to reveal the diversity order and array gain of the system. Finally, the effectiveness of the analytical results is verified through comparison with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Author co-citation analysis (ACA) is a well-known and frequently-used method to exhibit the academic researchers and the professional field sketch according to co-citation relationships between authors in an article set. However, visualizing subtle examination is limited because only author co-citation information is required in ACA. The proposed method, called modified author co-citation analysis (MACA), exploits author co-citation relationship, citations published time, citations published carriers, and citations keywords, to construct MACA-based co-citation matrices. According to the results of our experiments: (1) MACA shows a good clustering result with more delicacy and more clearness; (2) more information involved in co-citation analysis performs good visual acuity; (3) in visualization of co-citation network produced by MACA, the points in different categories have far more distance, and the points indicating authors in the same category are closer together. As a result, the proposed MACA is found that more detailed and subtle information of a knowledge domain analyzed can be obtained, compared to ACA. [ABSTRACT FROM AUTHOR]

Sucrose and molasses are attractive raw materials for industrial fermentation. Although Corynebacterium glutamicum shows sucrose-utilizing activity, sucrose or molasses is only a fraction of carbon source used in the fermentation medium in most works. An engineered C. glutamicum strain was constructed for producing L-ornithine with sucrose or molasses as a sole carbon source by transferring Mannheimia succiniciproducens β-fructofuranosidase gene ( sacC). The engineered strain, C. glutamicum ΔAPE6937R42 (pEC-sacC), produced 22.0 g/L of L-ornithine with sucrose as the sole carbon source, which is on par with that obtained by the parent strain C. glutamicum ΔAPE6937R42 with glucose as the sole carbon. The resulting strain C. glutamicum ΔAPE6937R42 (pEC-sacC) produced 27.0 g/L of L-ornithine with molasses as the sole carbon source, which is higher than that obtained by the parent strain C. glutamicum ΔAPE6937R42 with glucose as the sole carbon. This strategy can be applied for developing sucrose- or molasses-utilizing industrial strains. [ABSTRACT FROM AUTHOR]

Optical security devices play an essential role in the fight against counterfeiting. In this paper, we study and design a pair of metal-dielectric optical filters based on metameric effect, which offer a hidden image effect by the color shift at a specific angle of observation. Compared with all-dielectric multilayer system, the metal-dielectric multilayer structure has larger color shift with varying incident angle, higher color saturation and fewer layers. Finally, the stacks with 5 layers and 7 layers are achieved, and the color difference index is only 0.71, which shows good metameric matching effect. Simultaneously, the sensitivity of filters to deposition errors is analyzed when the thickness deviation is ±2%, and the results show that the two filters have good manufacturability. [ABSTRACT FROM AUTHOR]

We report the deposition of NbO films on unheated BK-7 glass substrates using remote plasma sputtering system. The remote plasma geometry allows pseudo separation of plasma and target bias parameters, which offers complete deposition rate control. Using appropriate oxygen flow rates, high-density and low-loss NbO films are deposited with rates up to 0.49 nm/s. Lower deposition rates (∼0.026 nm/s) can also be obtained by working at low target current and voltage and at low pressure. NbO films deposited at different rates have the refractive index of about 2.3 and the extinction coefficient as low as 6.9×10. [ABSTRACT FROM AUTHOR]

Sputtering deposition coatings offer significant advantages on electron beam (EB) deposition, including high packing density, environmental stability and extremely low losses. But the inherent high compressive stress affects its application in high power laser system. This paper describes the technical feasibility of high damage threshold laser mirrors deposited by a novel remote plasma sputtering technique. This technique is based on generating intensive plasma remotely from the target and then magnetically steering the plasma to the target to realize the full uniform sputtering. The pseudo-independence between target voltage and target current provides us very flexible parameters tuning, especially for the films stress control. Deposition conditions are optimized to yield fully oxidized and low compressive stress single layer HfO and SiO. The high damage threshold of 43.8 J/cm for HfO/SiO laser mirrors at 1064 nm is obtained. For the first time the remote plasma sputtering is successfully applied in depositing laser mirrors with high performance. [ABSTRACT FROM AUTHOR]

The performance of broadband polarizing beam splitters (PBSs) is sensitive to the incident angle. By taking account of the spectrum of the laser source and using the needle optimization method, a large acceptance angle PBS for laser-based displays is designed. The average degrees of polarization in transmission and reflection can reach 0.989 and 0.980 for an acceptance angle of 13.6° in air using two materials, while better results of 0.993 and 0.989 for an acceptance angle of 14.8° in air are attained when three common materials are used. Both designs consist of 40 layers. [ABSTRACT FROM AUTHOR]

This paper describes a new method to design a laser mirror with high reflectivity, wide reflection bandwidth and high laserinduced damage threshold. The mirror is constructed by three materials of HfO/TiO/SiO based on electric field and temperature field distribution characteristics of all-dielectric laser high reflector. TiO/SiO stacks act as the high reflector (HR) and broaden the reflection bandwidth, while HfO/SiO stacks are used for increasing the laser resistance. The HfO/TiO/SiO laser mirror with 34 layers is fabricated by a novel remote plasma sputtering deposition. The damage threshold of zero damage probability for the new mirror is up to 39.6 J/cm (1064 nm, 12 ns). The possible laser damage mechanism of the mirror is discussed. [ABSTRACT FROM AUTHOR]

A design of diode-pumped Nd: YAG laser with a single crystal that generates simultaneous laser action at the wavelengths of 1064 nm and 1319 nm was presented and continuous-wave (CW) of 588.9 nm was obtained for the first time by use of type-I critical phase-matching LBO crystal intracavity sumfrequency mixing. The maximum output power of 62 mW is achieved with an incident pump power of 1.8 W. The optical-to-optical conversion efficiency is up to 3.4%, and the power instability in 24 h is better than ±2.7%. [ABSTRACT FROM AUTHOR]