Accumulating evidence suggests that spoken word production requires different amounts of top-down control depending on the prevailing circumstances. For example, during Stroop-like tasks, the interference in response time (RT) is typically larger following congruent trials than following incongruent trials. This effect is called the Gratton effect, and has been taken to reflect top-down control adjustments based on the previous trial type. Such control adjustments have been studied extensively in Stroop and Eriksen flanker tasks (mostly using manual responses), but not in the picture–word interference (PWI) task, which is a workhorse of language production research. In one of the few studies of the Gratton effect in PWI, Van Maanen and Van Rijn (2010) examined the effect in picture naming RTs during dual-task performance. Based on PWI effect differences between dual-task conditions, they argued that the functional locus of the PWI effect differs between post-congruent trials (i.e., locus in perceptual and conceptual encoding) and post-incongruent trials (i.e., locus in word planning). However, the dual-task procedure may have contaminated the results. We therefore performed an electroencephalography (EEG) study on the Gratton effect in a regular PWI task. We observed a PWI effect in the RTs, in the N400 component of the event-related brain potentials, and in the midfrontal theta power, regardless of the previous trial type. Moreover, the RTs, N400, and theta power reflected the Gratton effect. These results provide evidence that the PWI effect arises at the word planning stage following both congruent and incongruent trials, while the amount of top-down control changes depending on the previous trial type.
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Droop control is used for power management in DC grids. Based on the level of the DC grid voltage, the amount of power regulated to or from the appliance is regulated such, that power management is possible. The Universal 4 Leg is a laboratory setup for studying the functionality of a grid manager for power management. It has four independent outputs that can be regulated with pulse width modulation to control the power flow between the DC grid and for example, a rechargeable battery, solar panel or any passive load like lighting or heating.
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We examined the effects of age on automatic and voluntary motor adjustments in pointing tasks. To this end, young (20–25 years) and middle-aged adults (48–62 years) were instructed to point at a target that could unexpectedly change its location (to the left or right) or its color (to green or red) during the movement. In the location change conditions, participants were asked to either adjust their pointing movement toward the new location (i.e., normal pointing) or in the opposite direction (i.e., anti-pointing). In the color change conditions, participants were instructed to adjust their movement to the left or right depending on the change in color. The results showed that in a large proportion of the anti-pointing trials, participants made two adjustments: an early initial automatic adjustment in the direction of the target shift followed by a late voluntary adjustment toward the opposite direction. It was found that the late voluntary adjustments were delayed for the middle-aged participants relative to the young participants. There were no age differences for the fast automatic adjustment in normal pointing, but the early adjustment in anti-pointing tended to be later in the middle-aged adults. Finally, the difference in the onset of early and late adjustments in anti-pointing adjustments was greater among the middle-aged adults. Hence, this study is the first to show that aging slows down voluntary goal-directed movement control processes to greater extent than the automatic stimulus-driven processes.
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The application of DC grids is gaining more attention in office applications. Especially since powering an office desk would not require a high power connection to the main AC grid but could be made sustainable using solar power and battery storage. This would result in fewer converters and further advanced grid utilization. In this paper, a sustainable desk power application is described that can be used for powering typical office appliances such as computers, lighting, and telephones. The desk will be powered by a solar panel and has a battery for energy storage. The applied DC grid includes droop control for power management and can either operate stand-alone or connected to other DC-desks to create a meshed-grid system. A dynamic DC nano-grid is made using multiple self-developed half-bridge circuit boards controlled by microcontrollers. This grid is monitored and controlled using a lightweight network protocol, allowing for online integration. Droop control is used to create dynamic power management, allowing automated control for power consumption and production. Digital control is used to regulate the power flow, and drive other applications, including batteries and solar panels. The practical demonstrative setup is a small-sized desktop with applications built into it, such as a lamp, wireless charging pad, and laptop charge point for devices up to 45W. User control is added in the form of an interactive remote wireless touch panel and power consumption is monitored and stored in the cloud. The paper includes a description of technical implementation as well as power consumption measurements.
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The basic level of postural control is functionally active from early infancy onwards: young infants possess a repertoire of direction-specific postural adjustments. Whether or not direction-specific adjustments are used depends on the child's age and the nature of the postural task. The second level of control emerges after 3 months: children start to develop the capacity to adapt postural activity to environmental constraints. But the adult form of postural adaptation first emerges after adolescence. Children with cerebral palsy (CP) in general have the ability to generate direction-specific adjustments, but they show a delayed development in the capacity to recruit direction-specific adjustments in tasks with a mild postural challenge. Children with CP virtually always have difficulties in the adaptation of direction-specific activity. The limited data available on the effect of intervention on postural development suggest that intervention involving active trial and error experience may accelerate postural development in typically developing infants and may improve postural control in children with or at high risk for a developmental motor disorder.
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This paper investigates how management accounting and control systems (operationalized by using Simons’ (1995a) levers of control framework) can be used as devices to support public value creation and as such it contributes to the literature on public value accounting. Using a mixed methods case study approach, including documentary analysis and semi-structured interviews, we found diverging uses of control systems in the Dutch university of applied sciences we investigated. While belief and interactive control systems are used intensively for strategy change and implementation, diagnostic controls were used mainly at the decentral level and seen as devices to make sure that operational and financial boundaries were not crossed. Therefore, belief and interactive control systems lay the foundation for the implementation of a new strategy, in which concepts of public value play a large role, using diagnostic controls to constrain actions at the operational level. We also found that whereas the institution wanted to have interaction with the external stakeholders, in daily practice this takes place only at the phase of strategy formulation, but not in the phase of intermediate strategy evaluation.
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The aim of this study was to examine differences in the performance of children with probable Developmental Coordination Disorder (p-DCD) and balance problems (BP) and typical developing children (TD) on a Wii Fit task and to measure the effect on balance skills after a Wii Fit intervention. Twenty-eight children with BP and 20 TD-children participated in the study. Motor performance was assessed with the Movement Assessment Battery for Children (MABC2), three subtests of the Bruininks Oseretsky Test (BOT2): Bilateral Coordination, Balance and Running Speed & Agility, and a Wii Fit ski slalom test. The TD children and half of the children in the BP group were tested before and after a 6 weeks non-intervention period. All children with BP received 6 weeks of Wii Fit intervention (with games other than the ski game) and were tested before and afterwards. Children with BP were less proficient than TD children in playing the Wii Fit ski slalom game. Training with the Wii Fit improved their motor performance. The improvement was significantly larger after intervention than after a period of non-intervention. Therefore the change cannot solely be attributed to spontaneous development or test-retest effect. Nearly all children enjoyed participation during the 6 weeks of intervention. Our study shows that Wii Fit intervention is effective and is potentially a method to support treatment of (dynamic) balance control problems in children.
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AIMS: To assess the influence of peer alcohol use during adolescence on young adults' alcohol use and abuse, and to assess to what extent parents' perception of their adolescent child's friends and adolescent's self-control modify this influence.METHODS: We analyzed data from the first, third, and fourth wave of a population-based prospective cohort study of 2230 adolescents conducted between 2001 and 2010 (mean ages: 11.1, 16.3, and 19.1, respectively). Alcohol use and abuse were measured at T4 by self-report questionnaires and by the Composite International Diagnostics Interview (CIDI), respectively. Peer alcohol use, self-control, and parents' perception of their adolescent child's friends were measured at T3. We adjusted for gender, age, socioeconomic-status, parental alcohol use, and adolescent baseline alcohol use.RESULTS: Peer alcohol use during adolescence was related to young adults' alcohol use and abuse [odds ratio (95% confidence interval): 1.31 (1.11-1.54) and 1.50 (1.20-1.87), respectively]. Neither parents' perception of their adolescent child's friends nor self-control modified this relationship. Alcohol abusers were more likely to have low self-control than alcohol users. No differences were found between alcohol users and abusers regarding their parents' perception of their friends and peer alcohol use.CONCLUSIONS: Peer alcohol use during adolescence affects young adults' alcohol use and abuse. We found that self-control was only related to alcohol abuse. Peer influence was not modified by parents' perception of peers or by self-control. Peer alcohol use and self-control should thus be separate targets in the prevention of alcohol use/abuse.
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Optimal postural control is an essential capacity in daily life and can be highly variable. The purpose of this study was to investigate if young people have the ability to choose the optimal postural control strategy according to the postural condition and to investigate if non-specific low back pain (NSLBP) influences the variability in proprioceptive postural control strategies. Young individuals with NSLBP (n = 106) and healthy controls (n = 50) were tested on a force plate in different postural conditions (i.e., sitting, stable support standing and unstable support standing). The role of proprioception in postural control was directly examined by means of muscle vibration on triceps surae and lumbar multifidus muscles. Root mean square and mean displacements of the center of pressure were recorded during the different trials. To appraise the proprioceptive postural control strategy, the relative proprioceptive weighting (RPW, ratio of ankle muscles proprioceptive inputs vs. back muscles proprioceptive inputs) was calculated. Postural robustness was significantly less in individuals with NSLBP during the more complex postural conditions (p < 0.05). Significantly higher RPW values were observed in the NSLBP group in all postural conditions (p < 0.05), suggesting less ability to rely on back muscle proprioceptive inputs for postural control. Therefore, healthy controls seem to have the ability to choose a more optimal postural control strategy according to the postural condition. In contrast, young people with NSLBP showed a reduced capacity to switch to a more multi-segmental postural control strategy during complex postural conditions, which leads to decreased postural robustness.
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The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
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