[Inter- and Transdisciplinarity as a Normative Dynamic: Challenges and Opportunities for Political Science]. / Inter- und Transdisziplinarität als normative Dynamik: Herausforderungen und Chancen für die Politikwissenschaft.

Inter- and transdisciplinarity (ITD) has been part of political science for quite some time now, but although political science regularly deals with its self-understanding, the consequences for research and researchers of ITD have not yet been systematically considered. To stimulate this debate, we conceptualize ITD as a spectrum of knowledge integration, application, and participation. We use International Relations norm research as a theoretical framework to describe, analyze, and reflect on ITD as a normative dynamic. Autoethnographically and through participatory observation, we examine ITD as a normative dynamic, with insights from three research projects in the field of sustainability. Specifically, we ask what implications ITD has for researchers and research in political science. As a result, we find that ITD offers both opportunities and challenges. In the context of knowledge integration, we discuss the importance of the participation of political science in major societal issues in contrast to ITD's preferences for a particular understanding of knowledge and research. We reflect on ITD's application bias in terms of problem-solving opportunities and output orientation. In addition, we consider the participation postulate of ITD and weigh potential democratizing effects against the conditions under which these might be realized. Finally, we address where further research seems useful to continue reflection on ITD.

Reconstruction of the respiratory signal through ECG and wrist accelerometer data.

Respiratory rate and changes in respiratory activity provide important markers of health and fitness. Assessing the breathing signal without direct respiratory sensors can be very helpful in large cohort studies and for screening purposes. In this paper, we demonstrate that long-term nocturnal acceleration measurements from the wrist yield significantly better respiration proxies than four standard approaches of ECG (electrocardiogram) derived respiration. We validate our approach by comparison with flow-derived respiration as standard reference signal, studying the full-night data of 223 subjects in a clinical sleep laboratory. Specifically, we find that phase synchronization indices between respiration proxies and the flow signal are large for five suggested acceleration-derived proxies with [Formula: see text] for males and [Formula: see text] for females (means ± standard deviations), while ECG-derived proxies yield only [Formula: see text] for males and [Formula: see text] for females. Similarly, respiratory rates can be determined more precisely by wrist-worn acceleration devices compared with a derivation from the ECG. As limitation we must mention that acceleration-derived respiration proxies are only available during episodes of non-physical activity (especially during sleep).

Responsibility, rationality, and acceptance: How future users of autonomous driving are constructed in stakeholders' sociotechnical imaginaries.

Although autonomous driving is expected to provide a solution for various mobility-related issues, ideas on how the technology will actually unfold are vague. Nevertheless, stakeholders in the field hold expectations about the technology and the future users. With very few exceptions, so far research does not focus on these expectations as social constructions of individuals and publics. In addition, these perceptions play only a minor role in the technology-centered debate. Thus, to bring these perceptions to light and to analyze their implications, we draw on the sociotechnical imaginaries approach to reconstruct stakeholders' views of future users and publics. We perform a qualitative content analysis and show that imaginaries unfold along the themes of responsibility for the process of driving, rationality in decision-making, and acceptance for emerging technologies. We discuss how the themes relate to each other, what role science plays, and what implications follow from the respective stakeholders' views.

Detection and analysis of pulse waves during sleep via wrist-worn actigraphy.

The high temporal and intensity resolution of modern accelerometers gives the opportunity of detecting even tiny body movements via motion-based sensors. In this paper, we demonstrate and evaluate an approach to identify pulse waves and heartbeats from acceleration data of the human wrist during sleep. Specifically, we have recorded simultaneously full-night polysomnography and 3d wrist actigraphy data of 363 subjects during one night in a clinical sleep laboratory. The acceleration data was segmented and cleaned, excluding body movements and separating episodes with different sleep positions. Then, we applied a bandpass filter and a Hilbert transform to uncover the pulse wave signal, which worked well for an average duration of 1.7 h per subject. We found that 81 percent of the detected pulse wave intervals could be correctly associated with the R peak intervals from independently recorded ECGs and obtained a median Pearson cross-correlation of 0.94. While the low-frequency components of both signals were practically identical, the high-frequency component of the pulse wave interval time series was increased, indicating a respiratory modulation of pulse transit times, probably as an additional contribution to respiratory sinus arrhythmia. Our approach could be used to obtain long-term nocturnal heartbeat interval time series and pulse wave signals from wrist-worn accelerometers without the need of recording ECG or photoplethysmography. This is particularly useful for an ambulatory monitoring of high-risk cardiac patients as well as for assessing cardiac dynamics in large cohort studies solely with accelerometer devices that are already used for activity tracking and sleep pattern analysis.