A transition of today’s energy system towards renewableresources, requires solutions to match renewable energy generationwith demand over time. These solutions include smartgrids, demand-side management and energy storage. Energycan be stored during moments of overproduction of renewableenergy and used from the storage during moments ofinsufficient production. Allocation in real time of generatedenergy towards controlled appliances or storage chargers, isdone by a smart control system which makes decisions basedon predictions (of upcoming generation and demand) andinformation of the actual condition of storages.
Purpose: The primary aim of this study was to investigate the concurrent validity of the PAM AM400 accelerometer for measuring physical activity in usual care in hospitalized patients by comparing it with the ActiGraph wGT3X-BT accelerometer. Materials and methods: This was a prospective single centre observational study performed at the University Medical Centre Utrecht in The Netherlands. Patients admitted to different clinical wards were included. Intraclass Correlation Coefficients (ICCs) were computed using a two-way mixed model with random subjects. Additionally, Bland-Altman plots were made to visualize the level of agreement of the PAM with the ActiGraph. To test for proportional bias, a regression analysis was performed. Results: In total 17 patients from different clinical wards were included in the analyses. The level of agreement between the PAM and ActiGraph was found strong with an ICC of 0.955. The Bland-Altman analyses showed a mean difference of 1.12min between the two accelerometers and no proportional bias (p¼0.511). Conclusions: The PAM is a suitable movement sensor to validly measure the active minutes of hospitalized patients. Implementation of this device in daily care might be helpful to change the immobility culture in hospitals.
Background: In Turkey, nursing care in hospitals has gradually included more older patients, resulting in a need for knowledgeable geriatric nurses. It is unknown, however, whether the nursing workforce is ready for this increase. Therefore, the aim of this study is to validate the Knowledge about Older Patients Quiz (KOPQ) in the Turkish language and culture, to describe Turkish hospital nurses’ knowledge about older patients, and to compare levels of knowledge between Turkish and Dutch hospital nurses. Conclusions: The KOPQ-TR is promising for use in Turkey, although psychometric validation should be repeated using a better targeted sample with a larger ability variance to adequately assess the Person Separation Index and Person Reliability. Currently, education regarding care for older patients is not sufficiently represented in Turkish nursing curricula. However, the need to do so is evident, as the results demonstrate that knowledge deficits and an increase in older patients admitted to the hospital will eventually occur. International comparison and cooperation provides an opportunity to learn from other countries that currently face the challenge of an aging (hospital) population.
Horticulture crops and plants use only a limited part of the solar spectrum for their growth, the photosynthetically active radiation (PAR); even within PAR, different spectral regions have different functionality for plant growth, and so different light spectra are used to influence different properties of the plant, such as leaves, fruiting, longer stems and other plant properties. Artificial lighting, typically with LEDs, has been used to provide these specified spectra per plant, defined by their light recipe. This light is called steering light. While the natural sunlight provides a much more sustainable and abundant form of energy, however, the solar spectrum is not tuned towards specific plant needs. In this project, we capitalize on recent breakthroughs in nanoscience to optimally shape the solar spectrum, and produce a spectrally selective steering light, i.e. convert the energy of the entire solar spectrum into a spectrum most useful for agriculture and plant growth to utilize the sustainable solar energy to its fullest, and save on artificial lighting and electricity. We will take advantage of the developed light recipes and create a sustainable alternative to LED steering light, using nanomaterials to optimally shape the natural sunlight spectrum, while maintaining the increased yields. As a proof of concept, we are targeting the compactness of ornamental plants and seek to steer the plants’ growth to reduce leaf extension and thus be more valuable. To realize this project the Peter Schall group at the UvA leads this effort together with the university spinout, SolarFoil, whose expertise lies in the development of spectral conversion layers for horticulture. Renolit - a plastic manufacturer and Chemtrix, expert in flow synthesis, provide expertise and technical support to scale the foil, while Ludvig-Svensson, a pioneer in greenhouse climate screens, provides the desired light specifications and tests the foil in a controlled setting.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
Eggshell particles as bio-ceramic in sustainable bioplastic engineering – ESP-BIOPACK Plastics make our lives easier in many ways. However, if they are not properly disposed of, they end up in the environment. Recently, biodegradable biopolymers, such as polylactic acid (PLA) and polyhydroxy alkanoates (PHAs), have moved towards alternatives for applications such as sustainable packaging. The major limitations of these biopolymers are the high cost, which is due to the high cost of the starting materials and the small volumes, and the poor thermal and mechanical properties such as limited processability and low impact resistance. Attempts to modify PHAs have been researched in many ways, such as blending various biodegradable polymers or mixing inorganic mineral fillers. Eggshell (10 million tons per year by 2030) is a natural bio-ceramic mineral with a unique chemical composition of calcium carbonate (>95% calcite). So far it has been regarded as a zero-value waste product, but it could be a great opportunity as raw material to reduce the cost of biopolymers and to improve properties, including the decomposition process at the end-of-life. In this project, we aim to develop eggshell particles that serve as bio-fillers in biopolymers to lower the cost of the product, to improve mechanical properties and to facilitate the validation of end-of-life routes, therefore, economically enhance the wide applications of such. The developed bioplastic packaging materials will be applied in SME partner EGGXPERT’s cosmetics line but also in other packaging applications, such as e.g. biodegradable coffee capsules. To be able to realize the proposed idea, the partnership between Chemelot Innovation and Learning Labs (CHILL), EGGXPERT B.V. and the Research Centre Material Sciences of Zuyd University of Applied Sciences is needed to research the physical, mechanical and end-of-life influences of eggshell particles (ESP) in biopolymers such as PLA and PHA and optimize their performance.
