Grants

Thomsen & Andreasen (2019) demonstrated that The Egtved Girl & The Skrydstrup Woman likely came from the areas in which they were later buried, in contrast to previous studies that proposed they came from far away (Frei et al. 2015, Frei et al 2017). These studies did not take into account the influence of modern agriculture on the Sr method, which shows that although the method is a promising one for showing whether a prehistoric person originally came from the area in which she was later buried, & whether she moved around or lived her whole life in one place, the method was used prematurely. This project will address the two main outstanding issues surrounding the Sr method: 1) Can drops of sea spray change the Sr signature of the environment inland or are unexpected Sr values due to the effect of agriculture? 2) How is Sr transferred from soils to waters & further up the food chain? in order to determine how the Sr method can best be used in the future.

The main aim of this project is to create a wearable seizure alarm which can detect epileptic seizures. In recent studies we have shown that heart rate variability analysis measured with electrocardiogram (ECG) can detect seizures for patients with epilepsy. Therefore, this project will develop an online detection of epileptic seizures by means of small, wearable and wireless ECG-devices. In 100 patients we will assess detection of seizures using a wearable ECG-patch, which sends ECG-data to a smartphone with implemented real-time seizure detection, during long-term video-EEG monitoring. Additional 20 patients will be monitored with a subcutaneously implanted wearable ECG-device for 6 months home monitoring. We will also measure EMG and accelerometry to test if multimodal seizure detection algorithms can increase seizure detection sensitivity. The wearable seizure alarm will be a vital asset for patients enabling caregivers and family to take necessary precautions during seizures.

The field of treatment research is in need of an increased understanding of how psychological treatment works in order to optimize existing treatments. The common approach is to embed mechanism studies in Randomized Controlled Trials (RCTs) with the aim of elucidating change processes during therapy. Yet mechanism studies do not provide information about how change was brought about, i.e., which treatment components that lead to change. To overcome the current challenge of the field, we put forward an innovative and alternative methodological approach, namely the Multiphase Optimization Strategy (MOST), which is designed specifically to identify potent treatment components. Thus, this project aims to optimize psychological treatment for pain using MOST. It focuses on pain after breast cancer as studies suggest a need for optimization for this population. If successful, the method could be applied to optimization of other multicomponent interventions.

Moving Data-Moving People examines the role of the forthcoming Social Credit System (SCS) in reshaping relations of trust for China’s many mobile people. Due to be launched in 2020 across mainland China, the SCS has the potential, through a social credit score, create a more uniform governance of both the mobility of people and data about them. In Western contexts, the SCS is often described as a case of big data totalitarianism. According to the Chinese State Council (2014), however, the purpose of the SCS is to create a more "trustworthy" society. We see this large scale state digitalization project as having the potential to fundamentally alter previous ways of negotiating trusting relations, particularly for China's mobile population. Through locally embedded ethnographic fieldwork and document analysis, our project will provide early insights into the implementation of the SCS and what it means for relationships of trust between mobile people, local governments and local citizens