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The effectiveness of rhetorical structure is essential to communicate key messages in research articles (RAs). The interdisciplinary nature of library and information science (LIS) has led to unclear patterns and practice of using rhetorical structures. Understanding how RAs are constructed in LIS to facilitate effective scholarly communication is important. Numerous studies investigated the rhetorical structure of RAs in a range of disciplines, but LIS articles have not been well studied.

In this study, the authors encoded rhetorical structures to 2,216 articles in the Journal of the Association for Information Science and Technology covering a period from 2001 to 2018 with the approaches of co-word analysis and visualization. The results show that the predominant rhetorical structures used by LIS researchers follow the sequence of Introduction-Literature Review-Methodology-Result-Discussion-Conclusion (ILMRDC).

The authors' temporal examination reveals the shifts of evolutionary pattern of rhetorical structure in 2008 and 2014. More importantly, the authors' study demonstrates that rhetorical structures have varied greatly across research areas in LIS community. For example, scholarly communication and scientometrics studies tend to exclude literature review in articles.

The present paper offers a first systematic examination of how rhetorical structures are used in a representative sample of a LIS journal, especially from a temporal perspective.

Library Hi Tech is one of the most influential journals that publish leading research in library and information science (LIS). The present study aims to understand the scholarly communication in Library Hi Tech by profiling its historic footprint, emerging trends and knowledge diffusion.

A total of 3,131 bibliographic records between 1995 and 2018 were collected from the Web of Science. Text mining, graph analysis and data visualization were used to analyze subject category assignment, domain-level citation trends, co-occurrence of keywords, keyword bursts, networks of document co-citation and landmark articles.

Findings indicated that published research in the journal was largely influenced by the psychology, education and social domain as a unidisciplinary discipline. Knowledge of the journal has been disseminated into multiple domains such as LIS, computer science and education. Dominant thematic concentrations were also identified: (1) library services in academic libraries and related to digital libraries, (2) adoption of new information technologies and (3) information-seeking behavior in these contexts. Additionally, the journal has exhibited an increased research emphasis on mixed-method user-centered studies and investigations into libraries' use of new media.

This study provides a promising approach to understand scientific trends and the intellectual growth of journals. It also helps Library Hi Tech to become more self-explanatory with a detailed bibliometric profile and to identify future directions in editorship and readership. Finally, researchers in the community can better position their studies within the emerging trends and current challenges of the journal.

Drug repurposing involves the identification of new applications for existing drugs. Owing to the enormous rise in the costs of pharmaceutical R&D, several pharmaceutical companies are leveraging repurposing strategies. Parkinson's disease is the second most common neurodegenerative disorder worldwide, affecting approximately 1–2 percent of the human population older than 65 years. This study proposes a literature-based drug repurposing strategy in Parkinson's disease.

The literature-based drug repurposing strategy proposed herein combined natural language processing, network science and machine learning methods for analyzing unstructured text data and producing actional knowledge for drug repurposing. The approach comprised multiple computational components, including the extraction of biomedical entities and their relationships, knowledge graph construction, knowledge representation learning and machine learning-based prediction.

The proposed strategy was used to mine information pertaining to the mechanisms of disease treatment from known treatment relationships and predict drugs for repurposing against Parkinson's disease. The F1 score of the best-performing method was 0.97, indicating the effectiveness of the proposed approach. The study also presents experimental results obtained by combining the different components of the strategy.

The drug repurposing strategy proposed herein for Parkinson's disease is distinct from those existing in the literature in that the drug repurposing pipeline includes components of natural language processing, knowledge representation and machine learning for analyzing the scientific literature. The results of the study provide important and valuable information to researchers studying different aspects of Parkinson's disease.

Data science is a relatively new field which has gained considerable attention in recent years. This new field requires a wide range of knowledge and skills from different disciplines including mathematics and statistics, computer science and information science. The purpose of this paper is to present the results of the study that explored the field of data science from the library and information science (LIS) perspective.

Analysis of research publications on data science was made on the basis of papers published in the Web of Science database. The following research questions were proposed: What are the main tendencies in publication years, document types, countries of origin, source titles, authors of publications, affiliations of the article authors and the most cited articles related to data science in the field of LIS? What are the main themes discussed in the publications from the LIS perspective?

The highest contribution to data science comes from the computer science research community. The contribution of information science and library science community is quite small. However, there has been continuous increase in articles from the year 2015. The main document types are journal articles, followed by conference proceedings and editorial material. The top three journals that publish data science papers from the LIS perspective are the Journal of the American Medical Informatics Association, the International Journal of Information Management and the Journal of the Association for Information Science and Technology. The top five countries publishing are USA, China, England, Australia and India. The most cited article has got 112 citations. The analysis revealed that the data science field is quite interdisciplinary by nature. In addition to the field of LIS the papers belonged to several other research areas. The reviewed articles belonged to the six broad categories: data science education and training; knowledge and skills of the data professional; the role of libraries and librarians in the data science movement; tools, techniques and applications of data science; data science from the knowledge management perspective; and data science from the perspective of health sciences.

The limitations of this research are that this study only analyzed research papers in the Web of Science database and therefore only covers a certain amount of scientific papers published in the field of LIS. In addition, only publications with the term “data science” in the topic area of the Web of Science database were analyzed. Therefore, several relevant studies are not discussed in this paper that are not reflected in the Web of Science database or were related to other keywords such as “e-science,” “e-research,” “data service,” “data curation” or “research data management.”

The field of data science has not been explored using bibliographic analysis of publications from the perspective of the LIS. This paper helps to better understand the field of data science and the perspectives for information professionals.

The purpose of this paper is to analyze the ability of turbulence models to model the flow field in the runner of a Francis turbine. Although the complex flow in the turbine can be simulated by CFD models, the prediction accuracy still needs to be improved. The choice of the turbulence model is one key tool that affects the prediction accuracy of numerical simulations.

This study used the SST k-w and RNG k-e turbulence models, which can both accurately predict complex flow fields in numerical simulations, to simulate the flow in the entire flow passage of a Francis turbine with the results compared against experimental data for the performance and blade pressure distribution in the turbine to evaluate the applicability of the turbulence models.

The results show that the SST k-w turbulence model more accurately predicts the turbine performance than the RNG turbulence model. However, the blade surface pressures predicted by the SST k-w turbulence model were basically identical to those predicted by the RNG k-e turbulence model, with both accurately predicting the experimental data.

Due to the lack of space, the method used to measure the blade surface pressure distributions is not introduced in this paper.

Turbine performance and flow field pressure in the runner, which are the basis of turbine preliminary performance judgment and optimization through CFD, can be used to judge the rationality of the turbine runner design. The paper provides an evidence for the turbulence selection in numerical simulation to predict turbine performance and flow field pressure in the runner and improves the CFD prediction accuracy.

This paper fulfils a test of the flow field pressure in the runner, which provide an evidence for judge the adaptability of turbulence model on the flow field in runner. And this paper also provides important evaluations of two turbulence models for modeling the flow field pressure distribution in the runner of a Francis turbine to improve the accuracy of CFD models for predicting turbine performance.

This study aims to perform flow simulations inside the acinus with fine alveolar pores (Kohn pores) using hexagonal cells and bottom-up geometric modeling, which enabled the elimination of invalid voids using previous top-bottom methods and spherical or circular cells.

Regular hexagonal cells were used to construct alveoli with no gaps via tessellation. Some hexagonal cells were fused to eliminate the inner boundaries to represent the structure of the bronchial tree. For the remaining hexagonal cells, the side lengths of the shared walls were adjusted to construct alveolar pores. Periodic moving boundaries with the same phase were set for all walls to describe synchronous contraction and expansion of the bronchi and alveoli.

More realistic flow characteristics in the distal lung were obtained. The effects of pore size and the mechanism of auxiliary ventilation of alveolar pores were revealed.

To the best of the authors’ knowledge, this is the first numerical simulation study on the function of multiple alveolar pores at the level of pulmonary acini, which will be helpful for simulating the dynamic process of cough and sputum excretion in the future.

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

First, the contributions of spatial characteristics to microclimate were analyzed. And the results from mobile measurements were compared to those from fixed measurements to examine accuracy of mobile method. Air temperature and physiologically equivalent temperature (PET) profiles were plotted to explore the impacts of the spatial characteristics of that urban square and local street.

This research investigates the effects of urban canyons and landscape on air temperature and outdoor thermal comfort in an open square in Seoul, Korea, a city of diverse thermal environments. Mobile field measurements were carried out to obtain local meteorological data based on higher spatial resolution.

On a day in October under clear sky, air temperature and PET differences of up to 1.77 °C and 9.6 °C were observed at 2 p.m. and 3 p.m., respectively. These were mainly from the impact of shading effects caused by surrounding obstacles. The current layout and volume of vegetation in the square seemed not effective for reducing air temperature and improving thermal comfort, which needs further study.

The authors tested a way to investigate time delay when using mobile measurements by correcting measured local data using adjacent meteorological observatory data. The findings of and limitations on mobile station-based field measurement and analysis are discussed herein.

The purpose of this paper is to study the mechanism of efficient sputum excretion from the distal lung by using a tessellationally distal lung model with alveolar pores.

First, a two-dimensional tessellational composite structure of the bronchus, alveoli and alveolar pores (Kohn pore) is constructed with the tessellational splitting and fusion of regular hexagonal elements. Then, the level set method is used to study the effects of alveolar pores and their sizes, expiratory cycles and respiratory intensity.

The existence of alveolar pores is the prerequisite for sputum excretion, and there is an optimal size of alveolar pores for sputum excretion. Strong asymmetric respiration can break the reversibility of the flow at a low Reynolds number and causes significant net displacement of sputum. The expiratory cycle is negatively correlated with the net displacement of sputum. The respiratory intensity is positively correlated with the net displacement of sputum.

This research is helpful for understanding the complex sputum excretion process in diseases, such as pneumonia, and developing corresponding adjuvant therapy.