Techniques to Measure Solar Flux Density Distribution on Large-Scale Receivers

Flux density measurement applied to central receiver ystems delivers the spatial distribution of the concentrated solar radiation on the receiver aperture, measures receiver input power, and monitors and might control heliostat aimpoints. Commercial solar tower plants have much larger aperture surfaces than the receiver prototypes tested in earlier research and development (R&D) projects. Existing methods to measure the solar flux density in the receiver aperture face new challenges regarding the receiver size. Also, the requirements regarding costs, accuracy, spatial resolution, and measuring speed are different. This paper summarizes existent concepts, presents recent research results for techniques that can be applied to large-scale receivers and assesses them against a catalog of requirements. Direct and indirect moving bar techniques offer high measurement accuracy, but also have the disadvantage of large moving parts on a solar tower. In the case of external receivers, measuring directly on receiver surfaces avoids moving parts and allows continuous measurement but may be not as precise. This promising technique requires proper scientific evaluation due to specific reflectance properties of current receiver materials. Measurement-supported simulation techniques can also be applied to cavity receivers without installing moving parts. They have reasonable uncertainties under ideal conditions and require comparatively low effort

Measuring soot particles from automotive exhaust emissions

The European Metrology Research Programme participating countries and the European Union jointly fund a three year project to address the need of the automotive industry for a metrological sound base for exhaust measurements. The collaborative work on particle emissions involves five European National Metrology Institutes, the Tampere University of Technology, the Joint Research Centre for Energy and Transport and the Leibniz Institute for Tropospheric Research. On one hand, a particle number and size standard for soot particles is aimed for. Eventually this will allow the partners to provide accurate and comparable calibrations of measurement instruments for the type approval of Euro 5b and Euro 6 vehicles. Calibration aerosols of combustion particles, silver and graphite proof partially suitable. Yet, a consensus choice together with instrument manufactures is pending as the aerosol choice considerably affects the number concentration measurement. Furthermore, the consortium issued consistent requirements for novel measuring instruments foreseen to replace today’s opacimeters in regulatory periodic emission controls of soot and compared them with European legislative requirements. Four partners are conducting a metrological validation of prototype measurement instruments. The novel instruments base on light scattering, electrical, ionisation chamber and diffusion charging sensors and will be tested at low and high particle concentrations. Results shall allow manufacturers to further improve their instruments to comply with legal requirements

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

© 2017 IOP Publishing Ltd. Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be easily integrated in devising more advanced SC schemes and/or strategies for automatic BCI self-adaptations

Assessing the costs and cost-effectiveness of ICare internet-based interventions (protocol)

Background: Mental health problems are common and place a burden on the individual as well as on societal resources. Despite the existence of evidence-based treatments, access to treatment is often prevented or delayed due to insufficient health care resources. Effective internet-based self-help interventions have the potential to reduce the risk for mental health problems, to successfully bridge waiting time for face-to-face treatment and to address inequities in access. However, little is known about the cost-effectiveness of such interventions. This paper describes the study protocol for the economic evaluation of the studies that form the ICare programme of internet-based interventions for the prevention and treatment of a range of mental health problems. Methods: An overarching work package within the ICare programme was developed to assess the cost-effectiveness of the internet-based interventions alongside the clinical trials. There are two underlying tasks in the ICare economic evaluation. First, to develop schedules that generate equivalent and comparable information on use of services and supports across seven countries taking part in clinical trials of different interventions and second, to estimate unit costs for each service and support used. From these data the cost per person will be estimated by multiplying each participant's use of each service by the unit cost for that service, taking both a public sector and a societal perspective. This individual level of cost data matches the level of outcome data used in the clinical trials. Following the analyses of service use and costs data, joint analysis of costs and outcomes will be undertaken to provide findings on the relative cost-effectiveness of the interventions. These analyses use a well-established framework, the Production of Welfare approach, and standard methods and techniques underpinned by economic theory. Discussion/conclusion: Existing research tends to support the effectiveness of internet-based interventions, but there is little information on their cost-effectiveness compared to ‘treatment as usual’. The economic evaluation of ICare interventions will add considerably to this evidence base

Guided internet-based transdiagnostic individually tailored Cognitive Behavioral Therapy for symptoms of depression and/or anxiety in college students: A randomized controlled trial

Common mental disorders, such as depression and anxiety, often emerge in college students during the transition into early adulthood. Mental health problems can seriously impact students' functioning, interpersonal relationships, and academic achievement. Actively reaching out to college students with mental health problems and offering them internet-based interventions may be a promising way of providing low-threshold access to evidence-based treatment in colleges. This randomized controlled trial aimed to assess the effectiveness of a guided web-based transdiagnostic individually tailored Cognitive Behavioral Therapy (iCBT) in treating college students with depression and/or anxiety symptoms. Through an online survey that screened college students' mental health, we recruited 100 college students aged ≥18 years who reported mild to moderate depression and/or anxiety symptoms and were attending colleges in the Netherlands. Participants were randomly allocated to guided iCBT (n = 48) or treatment as usual (TAU) control (n = 52). Primary outcomes were symptoms of depression and anxiety measured at post-treatment (7 weeks post-randomization). We also measured all outcomes at 6- and 12-months post-randomization. All analyses were based on the intention-to-treat principle and were repeated using the complete-case sample. We found no evidence of a difference between the effects of guided iCBT and TAU in any of the examined outcomes (i.e., symptoms of depression and anxiety, quality of life, educational achievement, and college dropout) across all time points (p > .05). There was no evidence that effects of iCBT were associated with treatment satisfaction and adherence. More research into transdiagnostic individually tailored iCBT is necessary. Further, future studies should recruit larger samples to investigate possible smaller but clinically relevant effects of internet-based interventions for college students with depression and/or anxiety

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource