Background & aims: Sarcopenia is defined as the age-related loss in muscle quantity and quality which is associated with physical disability. The assessment of muscle quantity plays a role in the diagnosis of sarcopenia. However, the methods used for this assessment have many disadvantages in daily practice and research, like high costs, exposure to radiation, not being portable, or doubtful reliability. Ultrasound has been suggested for the estimation of muscle quantity by estimating muscle mass, using a prediction equation based on muscle thickness. In this systematic review, we aimed to summarize the available evidence on existing prediction equations to estimate muscle mass and to assess whether these are applicable in various adult populations. Methods: The databases PubMed, PsycINFO, and Web of Science were used to search for studies predicting total or appendicular muscle mass using ultrasound. The methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies, version 2 (QUADAS-2) and the quality assessment checklist (QA) designed by Pretorius and Keating (2008). Results: Twelve studies were included in this systematic review. The participants were between 18 and 79 years old. Magnetic Resonance Imaging and dual-energy X-ray absorptiometry were used as reference methods. The studies generally had low risk of bias and there were low concerns regarding the applicability (QUADAS-2). Nine out of eleven studies reached high quality on the QA. All equations were developed in healthy adults. Conclusions: The ultrasound-derived equations in the included articles are valid and applicable in a healthy population. For a Caucasian population we recommend to use the equation of Abe et al., 2015. While for an Asian population, we recommend to use the equation of Abe et al., 2018, for the South American population, the use of the equation of Barbosa-Silva et al., 2021 is the most appropriate.
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The COVID-19 pandemic led to an accelerated implementation of digital solutions, such as online proctoring. In this paper we discuss how the use of an ethical matrix may influence the way in which digital solutions are applied. To initiate an ethical discussion, we conducted an online workshop with educators, examiners, controllers, and students to identify risks and opportunities of online proctoring for various stakeholders. We used the Ethical Matrix to structure the meeting. We compared the outcome of the workshop with the outcomes of a proctoring software pilot by examiners. We found that the two approaches led to complementary implementation criteria. The ethical session was less focused on making things work and more on transparency about conditions, processes, and rights. The ethical session also concentrated more on the values of all involved rather than on fraud detection effectiveness
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The integration of renewable energy resources, controllable devices and energy storage into electricity distribution grids requires Decentralized Energy Management to ensure a stable distribution process. This demands the full integration of information and communication technology into the control of distribution grids. Supervisory Control and Data Acquisition (SCADA) is used to communicate measurements and commands between individual components and the control server. In the future this control is especially needed at medium voltage and probably also at the low voltage. This leads to an increased connectivity and thereby makes the system more vulnerable to cyber-attacks. According to the research agenda NCSRA III, the energy domain is becoming a prime target for cyber-attacks, e.g., abusing control protocol vulnerabilities. Detection of such attacks in SCADA networks is challenging when only relying on existing network Intrusion Detection Systems (IDSs). Although these systems were designed specifically for SCADA, they do not necessarily detect malicious control commands sent in legitimate format. However, analyzing each command in the context of the physical system has the potential to reveal certain inconsistencies. We propose to use dedicated intrusion detection mechanisms, which are fundamentally different from existing techniques used in the Internet. Up to now distribution grids are monitored and controlled centrally, whereby measurements are taken at field stations and send to the control room, which then issues commands back to actuators. In future smart grids, communication with and remote control of field stations is required. Attackers, who gain access to the corresponding communication links to substations can intercept and even exchange commands, which would not be detected by central security mechanisms. We argue that centralized SCADA systems should be enhanced by a distributed intrusion-detection approach to meet the new security challenges. Recently, as a first step a process-aware monitoring approach has been proposed as an additional layer that can be applied directly at Remote Terminal Units (RTUs). However, this allows purely local consistency checks. Instead, we propose a distributed and integrated approach for process-aware monitoring, which includes knowledge about the grid topology and measurements from neighboring RTUs to detect malicious incoming commands. The proposed approach requires a near real-time model of the relevant physical process, direct and secure communication between adjacent RTUs, and synchronized sensor measurements in trustable real-time, labeled with accurate global time-stamps. We investigate, to which extend the grid topology can be integrated into the IDS, while maintaining near real-time performance. Based on topology information and efficient solving of power flow equation we aim to detect e.g. non-consistent voltage drops or the occurrence of over/under-voltage and -current. By this, centrally requested switching commands and transformer tap change commands can be checked on consistency and safety based on the current state of the physical system. The developed concepts are not only relevant to increase the security of the distribution grids but are also crucial to deal with future developments like e.g. the safe integration of microgrids in the distribution networks or the operation of decentralized heat or biogas networks.
Thermal batteries, which store and release energy by hydrating and dehydrating salt crystals, hold great promise for domestic heating. Such batteries can be charged from waste heat from industrial processes, and discharged to provide neighbourhood heating. Unlike hot water storage systems, the energy is stored at room temperature, so the thermal losses are very low, making a salt battery highly efficient. However, the electrochemical change of the salt due to hydration and dehydration is very small, making it difficult to measure how much energy is stored in a battery. One promising technique is to measure the absolute humidity of the inlet and outlet air flow. The difference in humidity, combined with a rate equation model allows the total mass of water stored in the battery to be calculated, which can then be used to calculate the energy storage and battery power flow. However, there are several uncertainties in this approach. Commercially available sensors age over time, sometimes quite suddenly. It is not yet known if software can be used to compensate for sensor aging, or if a different sensor type is required. In addition to aging, each measurement is subject to random noise, which will be integrated into the model used to calculate the charge of the battery. It is not yet known how the noise will influence charge estimates. On the other hand, the sensor system must be as durable as domestic heating systems (decades). Hence, it is required to understand sensor aging in order to validate the sensor system for its intended use.
