Cognitive and affective processes for learning science in immersive virtual reality

As immersive virtual reality (IVR) systems proliferate in classrooms, it is important to understand how they affect learning outcomes and the underlying affective and cognitive processes that may cause these outcomes. Proponents argue that IVR could improve learning by increasing positive affective and cognitive processing, thereby supporting improved performance on tests of learning outcome, whereas opponents of IVR contend that it could hurt learning by increasing distraction, thereby disrupting cognitive learning processes and leading to poorer learning outcomes. In a media comparison study, students viewed a biology lesson either as an interactive animated journey in IVR or as a slideshow on a desktop monitor. Those who viewed the IVR lesson performed significantly worse on transfer tests, reported higher emotional arousal, reported more extraneous cognitive load and showed less engagement based on EEG measures than those who viewed the slideshow lesson, with or without practice questions added to the lessons. Mediational analyses showed that the lower retention scores for the IVR lesson were related to an increase in self-reported extraneous cognitive load and emotional arousal. These results support the notion that immersive environments create high affective and cognitive distraction, which leads to poorer learning outcomes than desktop environments.     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

数字花卉植物的全息可视化与交互实现

花卉植物形态、结构与生长过程的数字化和可视化是现代林业科研的重要研究内 容，数字花卉植物在科普、教育、展示等方面都有着广泛的应用与需求。全息影像技术是一种 新兴的前沿技术，其原理源自佩珀尔幻象，通常用于生成立体感强的影像，实现数字幻象与真 实世界的融合，拥有良好的观赏性，用户接受度较高。将全息影像技术与数字花卉植物相关研 究进行结合，可以加强数字花卉植物的可视化效果，从而实现更好的科普、教育、展示效果。 因此在现有的研究基础之上，考虑实现数字花卉植物的全息可视化，并在可视基础上增加了用 户交互实现，设计出一套兼具展示性和交互性的流程，力求总结出一种具有完整可行性的方案， 从而对数字花卉植物的新型表现形式进行深入研究，以期对数字植物研究与应用的进一步发展 提供参考。     

Soft Matter Technology at KIT: Chemical Perspective from Nanoarchitectures to Microstructures

Bioinspiration has emerged as an important design principle in the rapidly growing field of materials science and especially its subarea, soft matter science. For example, biological cells form hierarchically organized tissues that not only are optimized and designed for durability, but also have to adapt to their external environment, undergo self‐repair, and perform many highly complex functions. Being able to create artificial soft materials that mimic those highly complex functions will enable future materials applications. Herein, soft matter technologies that are used to realize bioinspired material structures are described, and potential pathways to integrate these into a comprehensive soft matter research environment are addressed. Solutions become available because soft matter technologies are benefitting from the synergies between organic synthesis, polymer chemistry, and materials science.     

Misconceptions of human factors concepts

Abstract

Like many scientific topics, Human Factors, and Ergonomics concepts are susceptible to being misunderstood by people unfamiliar with the subject matter. Most of the time these misunderstandings are harmless, like when a safety poster within a work setting encourages employees to 'overcome complacency'. This misunderstanding of complacency suggests it is a motivational aspect of human behaviour correctable with encouragement, whereas the human factors approach to overcoming complacency would be to evaluate how task design could diminish the destructive consequences of unexpected changes within a routine setting. No harm comes from the message within the safety poster, other than some wasted ink and paper, but misconceptions among particular audiences can eventually result in dire consequences for the human operator. This paper presents recent evidence that the concepts are being misapplied by casual consumers of human factors, particularly in the aftermath of accidents within complex systems, in ways detrimental to the core mission of improving the well-being of the human operator. Later, because this special issue presents new ways to demonstrate value via return on investment, practical efforts we can take to overcome such misconceptions are suggested.     

Prediction methods and applications in the science of science: A survey

Science of science has become a popular topic that attracts great attentions from the research community. The development of data analytics technologies and the readily available scholarly data enable the exploration of data-driven prediction, which plays a pivotal role in finding the trend of scientific impact. In this paper, we analyse methods and applications in data-driven prediction in the science of science, and discuss their significance. First, we introduce the background and review the current state of the science of science. Second, we review data-driven prediction based on paper citation count, and investigate research issues in this area. Then, we discuss methods to predict scholar impact, and we analyse different approaches to promote the scholarly collaboration in the collaboration network. This paper also discusses open issues and existing challenges, and suggests potential research directions.     

Leveraging industrial statistics in the data revolution: The Youden Memorial Address at the 63rd Annual Fall Technical Conference

We are in the midst of a “Data Revolution” that is transforming our economy. This revolution is as large and profound as other major economic shifts from the introduction of the printing press to the Industrial Revolution. In this article, we compare the development of the field of Industrial Statistics as an outgrowth of the Machine Age to the development of the field of Data Science as an outgrowth of the Information Age. It is shown how the knowledge, skills, and abilities required for “Data Scientists” have evolved to support companies as they try to differentiate themselves in the Information Age. It is discussed how the unique skills that Industrial Statisticians possess can provide a transformative advantage to Data Scientists working in the Information Age. Advice is given on how to leverage Industrial Statistics in the midst of the Data Revolution so that we ethically and responsibly implement the tools of Data Science, address important problems, and inclusively educate future generations.     

Toward a model of socializing project team members: An integrative approach

Project work is becoming more and more important in everyday business, as is staffing the right newcomers for the project. Recognizing that not all new project team workers possess equally important specific knowledge, skills and abilities for the success of projects, we draw on project management, human resource management, and organizational socialization literature to develop a framework on how new project team members might be socialized, depending on their strategic value for the project. We specifically draw on the socialization tactics literature and propose how four categories of new employees – Internal specialists, External specialists, External generalists and Internal generalists; based on two dimensions – work task complexity and employment mode, can be socialized more effectively. Implications for theory and practice are discussed as well.     

Factors affecting detection of a bimodal sour-savory mixture and inter-individual umami taste perception

While basic taste interactions have been the subject of many research studies, there is one combination where data is limited in the literature: sour and umami. This combination is universal in culinary preparations and of key interest to the food industry. Therefore, the primary goal of the present study is to assess how increasing concentrations of acidity (citric acid) affect, if at all, the intensity of a constant concentration of umami (monosodium glutamate, MSG). The secondary goal is to investigate other possible factors in umami taste perception. Here, a crowdsourced cohort of 734 individuals (age range 8–81) tasted and rated the intensity of 50 mM MSG alone, and in combination with citric acid at varying concentrations (1.25 mM, 6.25 mM, 31.25 mM). Participants were also genotyped for the single nucleotide polymorphism rs34160967 in the TAS1R1 gene. The results show a significant decrease in the intensity perception of umami as sour concentration increases (low: p = 0.005, medium: p < 0.001, high: p < 0.001). Situational factors such as participant hunger level and time since last eating also have a significant effect on umami intensity perception. Neither the biological factors of sex, age, and ancestry appear to play a role in umami perception, nor does variation in gene TAS1R1 at rs34160967. These new data contribute to the growing field of taste and sensory interaction by giving evidence that sour suppresses umami taste perception in bi-model samples.