The Serverless Computing Survey: A Technical Primer for Design Architecture

The development of cloud infrastructures inspires the emergence of cloud-native computing. As the most promising architecture for deploying microservices, serverless computing has recently attracted more and more attention in both industry and academia. Due to its inherent scalability and flexibility, serverless computing becomes attractive and more pervasive for ever-growing Internet services. Despite the momentum in the cloud-native community, the existing challenges and compromises still wait for more advanced research and solutions to further explore the potentials of the serverless computing model. As a contribution to this knowledge, this article surveys and elaborates the research domains in the serverless context by decoupling the architecture into four stack layers: Virtualization, Encapsule, System Orchestration, and System Coordination. Inspired by the security model, we highlight the key implications and limitations of these works in each layer, and make suggestions for potential challenges to the field of future serverless computing.

Conceptualizing the Contextual Dynamics of Safety Climate and Safety Culture Research: A Comparative Scientometric Analysis

Safety climate and safety culture are important research domains in risk and safety science, and various industry and service sectors show significant interest in, and commitment to, applying its concepts, theories, and methods to enhance organizational safety performance. Despite the large body of literature on these topics, there are disagreements about the scope and focus of these concepts, and there is a lack of systematic understanding of their development patterns and the knowledge domains on which these are built. This article presents a comparative analysis of the literature focusing on safety climate and safety culture, using various scientometric analysis approaches and tools. General development patterns are identified, including the publication trends, in terms of temporal and geographical activity, the science domains in which safety culture and safety climate research occurs, and the scientific domains and articles that have primarily influenced their respective development. It is found that the safety culture and safety climate domains show strong similarities, e.g., in dominant application domains and frequently occurring terms. However, safety culture research attracts comparatively more attention from other scientific domains, and the research domains rely on partially different knowledge bases. In particular, while measurement plays a role in both domains, the results suggest that safety climate research focuses comparatively more on the development and validation of questionnaires and surveys in particular organizational contexts, whereas safety culture research appears to relate these measurements to wider organizational features and management mechanisms. Finally, various directions for future research are identified based on the obtained results.

Analyzing the generalizability of the network-based topic emergence identification method

Topic evolution helps the understanding of current research topics and their histories by automatically modeling and detecting the set of shared research fields in academic publications as topics. This paper provides a generalized analysis of the topic evolution method for predicting the emergence of new topics, which can operate on any dataset where the topics are defined as the relationships of their neighborhoods in the past by extrapolating to the future topics. Twenty sample topic networks were built with various fields-of-study keywords as seeds, covering domains such as business, materials, diseases, and computer science from the Microsoft Academic Graph dataset. The binary classifier was trained for each topic network using 15 structural features of emerging and existing topics and consistently resulted in accuracy and F1 over 0.91 for all twenty datasets over the periods of 2000 to 2019. Feature selection showed that the models retained most of the performance with only one-third of the tested features. Incremental learning was tested within the same topic over time and between different topics, which resulted in slight performance improvements in both cases. This indicates there is an underlying pattern to the neighbors of new topics common to research domains, likely beyond the sample topics used in the experiment. The result showed that network-based new topic prediction can be applied to various research domains with different research patterns.

Integration of Data Mining and Business Intelligence in Big Data Analytics

The purpose of this chapter is to analyze and explore the research studies for scholarly publication trends and patterns related to the integration of data mining in particular business intelligence in big data analytics domains published in the period of 2010-2019. Research patterns explore in highly prestigious sources that have high impact factors and citations counted in the ISI Web of Science Core Collection database (indexes included SCI-Exp and SSCI). Bibliometric analysis methods applied for this study under the research limitations. Research questions formed based on bibliometric principles concentrating fields such as descriptive of publication, author productivity, country-regions distribution, keyword analysis with contribution among researchers, citation analysis, co-citation patterns searched. Findings showed strong relations and patterns on these important research domains. Besides this chapter would useful for researchers to obtain an overview of publication trends on research domains to be concerned for further studies and shows the potential gaps in those fields.

A Bibliometric Analysis and Review of Building Information Modelling for Post-Disaster Reconstruction

Post-disaster reconstruction (PDR) is a dynamic, complex system that is chaotic in nature, and represents many challenges and issues. Recently, building information modelling (BIM) has been commonly utilized in the construction industry to solve complex and dynamic challenges. However, BIM has not been thoroughly considered for managing PDR, and there is a lack of comprehensive scientometric analyses that objectively examine the trends in BIM applications in PDR. A literature search was performed considering studies published from 2010 to March 2021 using the Scopus database. A total of 75 relevant studies were found to meet the inclusion criteria. The collected literature was analyzed using VOSviewer through scientific journals, authors, keywords, citations, and countries. This is the first study in its vital significance and originality that aims to investigate the current states of research on BIM applications in PDR and provide suggestions for potential research directions. The findings showed that “Reconstruction” and “Safety Management” have emerged as mainstream research themes in this field and recently attracted scholars’ interest, which could represent the directions of future research. Five major research domains associated with BIM were identified based on the most frequently used keywords, namely “Disasters”, “Earthquakes”, “HBIM”, “Damage Detection”, and “Life Cycle”. Moreover, a proposed conceptual framework of BIM adoption for PDR is provided. Accordingly, the outcomes of this study will help scholars and practitioners gain clear ideas of the present status and identify the directions of future research.

Ionic Liquid-Based Gels for Applications in Electrochemical Energy Storage and Conversion Devices: A Review of Recent Progress and Future Prospects

Ionic liquids (ILs) are molten salts that are entirely composed of ions and have melting temperatures below 100 °C. When immobilized in polymeric matrices by sol–gel or chemical polymerization, they generate gels known as ion gels, ionogels, ionic gels, and so on, which may be used for a variety of electrochemical applications. One of the most significant research domains for IL-based gels is the energy industry, notably for energy storage and conversion devices, due to rising demand for clean, sustainable, and greener energy. Due to characteristics such as nonvolatility, high thermal stability, and strong ionic conductivity, IL-based gels appear to meet the stringent demands/criteria of these diverse application domains. This article focuses on the synthesis pathways of IL-based gel polymer electrolytes/organic gel electrolytes and their applications in batteries (Li-ion and beyond), fuel cells, and supercapacitors. Furthermore, the limitations and future possibilities of IL-based gels in the aforementioned application domains are discussed to support the speedy evolution of these materials in the appropriate applicable sectors.

Testing Antigens, Antibodies, and Immune Cells in COVID-19 as a Public Health Topic—Experience and Outlines

The current COVID-19 pandemic has triggered an accelerated pace in all research domains, including reliable diagnostics methodology. Molecular diagnostics of the virus and its presence in biological samples relies on the RT-PCR method, the most used and validated worldwide. Nonconventional tests with improved parameters that are in the development stages will be presented, such as droplet digital PCR or CRISPR-based assays. These molecular tests were followed by rapid antigen testing along with the development of antibody tests, whether based on ELISA platform or on a chemiluminescent microparticle immunoassay. Less-conventional methods of testing antibodies (e.g., lateral flow immunoassay) are presented as well. Left somewhere in the backstage of COVID-19 research, immune cells and, furthermore, immune memory cells, are gaining the spotlight, more so in the vaccination context. Recently, methodologies using flow-cytometry evaluate circulating immune cells in infected/recovered patients. The appearance of new virus variants has triggered a surge for tests improvement. As the pandemic has entered an ongoing or postvaccination era, all methodologies that are used to monitor public health focus on diagnostic strategies and this review points out where gaps should be filled in both clinical and research settings.

Creation and validation of the Picture-Set of Young Children’s Affective Facial Expressions (PSYCAFE)

The immediate detection and correct processing of affective facial expressions are one of the most important competences in social interaction and thus a main subject in emotion and affect research. Generally, studies in these research domains, use pictures of adults who display affective facial expressions as experimental stimuli. However, for studies investigating developmental psychology and attachment behaviour it is necessary to use age-matched stimuli, where it is children that display affective expressions. PSYCAFE represents a newly developed picture-set of children’s faces. It includes reference portraits of girls and boys aged 4 to 6 years averaged digitally from different individual pictures, that were categorized to six basic affects (fear, disgust, happiness, sadness, anger and surprise) plus a neutral facial expression by cluster analysis. This procedure led to deindividualized and affect prototypical portraits. Individual affect expressive portraits of adults from an already validated picture-set (KDEF) were used in a similar way to create affect prototypical images also of adults. The stimulus set has been validated on human observers and entail emotion recognition accuracy rates and scores for intensity, authenticity and likeability ratings of the specific affect displayed. Moreover, the stimuli have also been characterized by the iMotions Facial Expression Analysis Module, providing additional data on probability values representing the likelihood that the stimuli depict the expected affect. Finally, the validation data from human observers and iMotions are compared to data on facial mimicry of healthy adults in response to these portraits, measured by facial EMG (m. zygomaticus major and m. corrugator supercilii).

Beyond Diffusion: A Systematic Literature Review of Innovation Scaling

Innovation is essential for our ability to overcome global issues such as climate change, natural resource depletion, and inequality. A central aspect of innovation is the scaling process. While an abundance of studies on innovation scaling exist in many different disciplines, there is a lack of shared understanding of what scaling means and how it can be successfully achieved. This systematic literature review addresses both these issues by reviewing 147 articles on “innovation scaling” making several contributions to research on innovations and innovation scaling. First, in outlining the ontological differences between “diffusion” and “scaling”, clear conceptual boundaries are established, which provide clarity and support cross-disciplinary consilience. Second, based on the analysis of articles, eleven common modal contextual factors that influence the outcomes of innovation scaling across contexts and disciplines are presented. Third, an initial theoretical framework of the innovation scaling process is developed, outlining four theoretical propositions. As a fourth contribution, the article establishes a research agenda for the future development of innovation scaling research across many research domains.

Older Adults as Co-Creators in the Research Process: An Overview of Concepts, Methods, and Approaches

Participatory approaches have a long-standing tradition in the social sciences and approaches have diversified across multiple research domains. Also in ageing, there is a growing interest in involving older adults, particularly in fields like gerontechnology development, environmental gerontology or patient involvement. In this contribution, ask what participatory approaches and co-creation means in the context of ageing research. What are the benefits and challenges of involving older adults in different research domains, stages of the research process and deploying various participatory methods and approaches? To approach this question, we present preliminary results of a comprehensive scoping review of the literature and provide examples of how older adults can be involved in developing research questions together with researchers, collecting and analysing the data, as well as validating and disseminating study results.