A Coupled Experimental and Statistical Approach for an Assessment of the Airborne Infection Risk in Event Locations

Operators of event locations are particularly affected by a pandemic. Resulting restrictions may cause uneconomical business. With previous models, only an incomplete quantitative risk assessments is possible, whereby no suitable restrictions can be derived. Hence, a mathematical and statistical model has been developed in order to link measurement data of substance dispersion in rooms with epidemiological data like incidences, reproduction numbers, vaccination rates and test qualities. This allows a first time overall assessment of airborne infection risks in large event locations. In these venues displacement ventilation concepts are often implemented. In this case simplified theoretical assumptions fail for the prediction of relevant airflows for infection processes. Thus, with locally resolving trace gas measurements and specific data of infection processes, individual risks can be computed more detailed. Via inclusion of many measurement positions, an assessment of entire event locations is possible. Embedding the overall model in a flexible application, daily updated epidemiological data allow latest calculations of expected new infections and individual risks of single visitors for a certain event. With this model, an instrument has been created that can help policymakers and operators to take appropriate measures and to check restrictions for their effect.

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Piano performance is an art with rich artistic elements and unpredictable performance skills. It is an important carrier for playing beautiful piano sounds. The generation of musical tension and expression of piano performance is a vivid display of piano performance skills. In piano performance, we should pay attention to the cultivation and flexible application of performance skills. In order to ensure the richness and artistry of piano performance, it is fully based on the artistic characteristics of piano performance. Through in-depth analysis of the principle of the hidden Markov model, it is applied to the multimedia recognition process of piano playing music. In the process of obtaining the template, the fundamental frequency of the piano playing music differs greatly, and the piano playing music appears during the performance process. For the problem of low recognition rate, this paper proposes a multimedia recognition method for piano music. Finally, the analysis of experimental results shows that the method proposed in this paper has a 16% higher recognition rate than the traditional method, and it has a certain value in the multimedia recognition of piano music.

The role of supra-professional competencies in the professional development of students

Researchers' attention to the problem of supra-professional competencies is explained by the rapid changes in all spheres of human activity. Changes in the production sphere, changes in the labor market, changes in the economic, political, socio-cultural spheres pose the task of pedagogical science to search for internal resources of the educational process for the training of a new type of specialist. In today's changing conditions, the problem of training professional personnel is relevant all over the world and for all professional fields. One of the ways to solve this problem is the study and development of the theory and practice of supra-professional competencies as an additional resource for the professional development of a labor subject. The article presents the results of a theoretical analysis of various approaches to determining the content of the concept of "supra-professional competencies"; options for classifying these competencies; discusses the results of an empirical study to assess the formation of supra-professional competencies among students. The paper also presents a discussion by various authors on the role and significance of the formation and development of supra-professional competencies during vocational training. The presented work also emphasizes the fact that employers note a sufficiently high theoretical level of graduate training, which increases the share of practical training, but still graduates are not ready for creative and flexible application of the theoretical knowledge and practical skills acquired in the workplace. Drawing conclusions based on the assessment of different opinions, as well as the empirical results obtained, the authors emphasize the exceptional role and great importance of supra-professional competencies in the professional development and formation of a future specialist, which poses new challenges to the higher education system for the development and improvement of this group of competencies.

Using Photographs in Mixed Methods Research: An Illustration Integrating Quantitative and Qualitative Analyses from Consumer Research

Photograph analysis poses a novel methodological challenge for mixed methods researchers. In this paper, we argue that photographs are a valid data source that are not outside of the quantitative–qualitative binary and, hence, can be analyzed and used for integration, applying mixed methods principles. We summarize photograph analysis methods from different scientific fields and contribute to the field of mixed methods by proposing a mixed methods framework for analyzing visual data that allows the flexible application and integration of different quantitative and qualitative photograph analysis methods by focusing on data transformation. We use an illustrative example from consumer research.

Adaptable (Not Adaptive) Automation: The Forefront of Human–Automation Teaming

Objective Identify a critical research gap for the human factors community that has implications for successful human–automation teaming. Background There are a variety of approaches for applying automation in systems. Flexible application of automation such that its level and/or type changes during system operations has been shown to enhance human–automation system performance. Method This mini-review describes flexible automation in which the level of automated support varies across tasks during system operation, rather than remaining fixed. Two types distinguish the locus of authority to change automation level: adaptable automation (the human operator assigns how automation is applied) has been found to aid human’s situation awareness and provide more perceived control versus adaptive automation (the system assigns automation level) that may impose less workload and attentional demands by automatically adjusting levels in response to changes in one or more states of the human, task, environment, and so on. Results In contrast to vast investments in adaptive automation approaches, limited research has been devoted to adaptable automation. Experiments directly comparing adaptable and adaptive automation are particularly scant. These few studies show that adaptable automation was not only preferred over adaptive automation, but it also resulted in improved task performance and, notably, less perceived workload. Conclusion Systematic research examining adaptable automation is overdue, including hybrid approaches with adaptive automation. Specific recommendations for further research are provided. Application Adaptable automation together with effective human-factored interface designs to establish working agreements are key to enabling human–automation teaming in future complex systems.

Severity: a QoS-aware approach to cloud application elasticity

While a multitude of cloud vendors exist today offering flexible application hosting services, the application adaptation capabilities provided in terms of autoscaling are rather limited. In most cases, a static adaptation action is used having a fixed scaling response. In the cases that a dynamic adaptation action is provided, this is based on a single scaling variable. We propose Severity, a novel algorithmic approach aiding the adaptation of cloud applications. Based on the input of the DevOps, our approach detects situations, calculates their Severity and proposes adaptations which can lead to better application performance. Severity can be calculated for any number of application QoS attributes and any type of such attributes, whether bounded or unbounded. Evaluation with four distinct workload types and a variety of monitoring attributes shows that QoS for particular application categories is improved. The feasibility of our approach is demonstrated with a prototype implementation of an application adaptation manager, for which the source code is provided.

Towards the Development of Orally Available Peptide Therapeutics

Peptides have a number of attractive properties that make them an interesting modality for drug development, including their ability to bind challenging targets, their high target specificity, and their non-toxic metabolic products. However, a major limitation of peptides as drugs is their typically poor oral availability, hindering their convenient and flexible application as pills. Of the more than 60 approved peptide drugs, the large majority is not orally applicable. The oral delivery of peptides is hampered by their metabolic instability and/or limited intestinal uptake. In this article, we review the barriers peptides need to overcome after their oral administration to reach disease targets, we highlight two recent successes of pharma companies in developing orally applicable peptide drugs, and we discuss efforts of our laboratory towards the generation of bioavailable cyclic peptides.