Physical activity awareness and preferences in rheumatic diseases: a qualitative study

Background: Physical inactivity is the fourth leading cause of death (1) and a risk factor for cardiovascular disease (CVD). Patients with rheumatic diseases (RDs), especially rheumatoid arthritis (RA), report low cardiorespiratory fitness levels (2), placing them at an increased risk of premature mortality and CVD.Published versio

Harmonizing and improving European education in prescribing: An overview of digital educational resources used in clinical pharmacology and therapeutics

Aim: Improvement and harmonization of European clinical pharmacology and therapeutics (CPT) education is urgently required. Because digital educational resources can be easily shared, adapted to local situations and re-used widely across a variety of educational systems, they may be ideally suited for this purpose. Methods: With a cross-sectional survey among principal CPT teachers in 279 out of 304 European medical schools, an overview and classification of digital resources was compiled. Results: Teachers from 95 (34%) medical schools in 26 of 28 EU countries responded, 66 (70%) of whom used digital educational resources in their CPT curriculum. A total of 89 of such resources were described in detail, including e-learning (24%), simulators to teach pharmacokinetics and/or pharmacodynamics (10%), virtual patients (8%), and serious games (5%). Together, these resources covered 235 knowledge-based learning objectives, 88 skills, and 13 attitudes. Only one third (27) of the resources were in-part or totally free and only two were licensed open educational resources (free to use, distribute and adapt). A narrative overview of the largest, free and most novel resources is given. Conclusion: Digital educational resources, ranging from e-learning to virtual patients and games, are widely used for CPT education in EU medical schools. Learning objectives are based largely on knowledge rather than skills or attitudes. This may be improved by including more real-life clinical case scenarios. Moreover, the majority of resources are neither free nor open. Therefore, with a view to harmonizing international CPT education, more needs to be learned about why CPT teachers are not currently sharing their educational materials

EurOP2E – the European Open Platform for Prescribing Education, a consensus study among clinical pharmacology and therapeutics teachers

Purpose Sharing and developing digital educational resources and open educational resources has been proposed as a way to harmonize and improve clinical pharmacology and therapeutics (CPT) education in European medical schools. Previous research, however, has shown that there are barriers to the adoption and implementation of open educational resources. The aim of this study was to determine perceived opportunities and barriers to the use and creation of open educational resources among European CPT teachers and possible solutions for these barriers. Methods CPT teachers of British and EU medical schools completed an online survey. Opportunities and challenges were identified by thematic analyses and subsequently discussed in an international consensus meeting. Results Data from 99 CPT teachers from 95 medical schools were analysed. Thirty teachers (30.3%) shared or collaboratively produced digital educational resources. All teachers foresaw opportunities in the more active use of open educational resources, including improving the quality of their teaching. The challenges reported were language barriers, local differences, lack of time, technological issues, difficulties with quality management, and copyright restrictions. Practical solutions for these challenges were discussed and include a peer review system, clear indexing, and use of copyright licenses that permit adaptation of resources. Conclusion Key challenges to making greater use of CPT open educational resources are a limited applicability of such resources due to language and local differences and quality concerns. These challenges may be resolved by relatively simple measures, such as allowing adaptation and translation of resources and a peer review system

Towards Ubiquitous and Efficient LoRaWAN: MAC-Layer Protocols and APP-Layer Coding Mechanisms for Scalable and Energy-Efficient Long-Range Wide-Area Networks (LoRaWAN)

Embedded System

Energy Allocation Strategies for Micro-Grids

The advances of the information and communication technology (ICT) brought changes in the energy distribution domain, introducing the Smart Grid (SG). In SG, generators, distributors, and consumers communicate in a bidirectional way. SGs are envisaged to include micro-grids (MG) consisting of distributed control networks of consumers, prosumers, and the power grid. Two-way communication in MGs allows allocating the produced energy inside a community of consumers, to decentralize the energy flow. However, challenges arise regarding energy sharing, namely: (i) how to balance the demand and supply inside communities; (ii) are there policies that prioritize among the consumers while distributing the producers’ excess of energy; and (iii) how to balance the economic benefit –under a policy– for everyone who participates. In this thesis, we propose energy allocation strategies (EAS) for MG communities consisting of households that use renewable sources of energy (RSEs). Our objective is to maximize the energy usage and the cost reduction, under certain priority policies. Through an in-depth analysis of energy and socioeconomic data of the community, we form groups of households that share similar characteristics, and we channelize the energy flow at will. We present seven, simple and optimized, EASs and several consumer priority policies (CPPs). Our EASs and CPPs are scalable and can meet the specific needs of an MG community. We evaluate our algorithms and techniques using real data, acquired from a community of 443 households over a year. We show that the groups of households that we prioritize cover their needs of energy, sometimes completely, in periods of high energy production. We compare on economic basis trading energy within the MG and requesting energy form the grid (classic way). The expenses for prioritized groups of consumers under our EASs are decreased, up to 50% in certain cases. Further, it is shown that even the non-prioritized consumers are benefited economically by allocating the excess of energy.Electrical Engineering, Mathematics and Computer ScienceSoftware TechnologyEmbedded Softwar

Hierarchical control for large-scale urban road traffic networks

In the current work we focus on the development of hierarchical control structures to tackle the problem of signal control for large-scale urban networks. A recently developed perimeter control regulator, which integrates model-based optimal control and online data-driven learning/adaptation, is utilized for the upper-level layer. Another lower-level control layer utilizes the max-pressure regulator, which has been also proposed recently and constitutes a local feedback control law, applied in coupled intersections, in a distributed systems-of-systems (SoS) concept. Different approaches are discussed about the design of the hierarchical structure of SoS, i.e. mutual interactions between the two control layers, activation/deactivation of each layer, mutually related objectives of the regulators, online versus offline selection of critical intersection for the lower-level control layer. A hierarchical control approach that combines local and network level characteristics is expected to treat better uncertainties in demand and behavioural characteristics of drivers moving towards a more reliable performance of all users in the system

Efficient Allocation of Harvested Energy at the Edge by Building a Tangible Micro-Grid - The Texas Case

The electricity grid, using Information and Communication Technology, is transformed into Smart Grid (SG), which is highly efficient and responsive, promoting two-way energy and information flow between energy-distributors and consumers. Many consumers are becoming prosumers by also harvesting energy. The trend is to form small communities of consumers/prosumers, leading to Micro-grids (MG) to manage energy locally. MGs are parts of SG that decentralize the energy flow, allocating the excess of harvested energy within the community. Energy allocation amongst them must solve certain issues viz., 1) balancing supply/demand within MGs; 2) how allocating energy to a user affects his/her community; and 3) what are the economic benefits for users. To address these issues, we propose six Energy Allocation Strategies (EASs) for MGs - ranging from simple to optimal and their combinations. We maximize the usage of harvested energy within the MG. We form household-groups sharing similar characteristics to apply EASs by analyzing energy and socioeconomic data thoroughly. We propose four evaluation metrics and evaluate our EASs on data acquired from 443 households over a year. By prioritizing specific households, we increase the number of fully served households to 81% compared to random sharing. By combining EASs, we boost the social welfare parameter by 49%. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Embedded and Networked System

Divide and Code: Efficient and Real-time Data Recovery from Corrupted LoRa Frames

Due to power limitations and coexistence in ISM bands, up to 50% of the Long Range (LoRa)-frames are corrupted at low signal strengths (≈ -115dBm) and the built-in redundancy schemes in LoRa-Wide Area Network (LoRaWAN) cannot correct the corrupted bytes. To address this, higher Spreading Factors (SF) are used resulting in wasted energy, increased traffic load, and highly compromised effective data rate. Our on-field experiments showed a high correlation in the corruption of close-by frames. We propose a novel Divide &amp; Code (DC) scheme for LoRaWANs as an alternative to using higher SF. DC pre-encodes LoRa payloads using lightweight and memoryless encoding. After receiving a corrupted frame, DC uses a combination of most probable patterns of errors, Time Thresholds (TT), and splitting of payloads into subgroups for batch processing to recover frames effectively and maintain low complexity and timely operation. By implementing DC on our LoRa-testbed, we show it outperforms vanilla-LoRaWAN and Reed-Solomon codes in decoding and energy consumption. Our schemes decode up to 80.5% of corrupted payloads on SF10 by trying only 0.03% of all patterns of error combinations. TT keeps processing times below 2 ms with only minor reductions in the decoding ratio of corrupted payloads. Finally, we showcase that introducing 30% redundancy with DC results in minimum energy consumption and high decoding ratio at low SNRs. </p