Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques. Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty. Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping. Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models. Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.
Abstract: Combined lifestyle interventions (CLI) are focused on guiding clients with weight-related health risks into a healthy lifestyle. CLIs are most often delivered through face-to-face sessions with limited use of eHealth technologies. To integrate eHealth into existing CLIs, it is important to identify how behavior change techniques are being used by health professionals in the online and offline treatment of overweight clients. Therefore, we conducted online semi-structured interviews with providers of online and offline lifestyle interventions. Data were analyzed using an inductive thematic approach. Thirty-eight professionals with (n = 23) and without (n = 15) eHealth experience were interviewed. Professionals indicate that goal setting and action planning, providing feedback and monitoring, facilitating social support, and shaping knowledge are of high value to improve physical activity and eating behaviors. These findings suggest that it may be beneficial to use monitoring devices combined with video consultations to provide just-in-time feedback based on the client’s actual performance. In addition, it can be useful to incorporate specific social support functions allowing CLI clients to interact with each other. Lastly, our results indicate that online modules can be used to enhance knowledge about health consequences of unhealthy behavior in clients with weight-related health risks.
Op 8 januari 2020 verdedigde ik mijn proef - schrift bij de Rijksuniversiteit Groningen. Het proefschrift richt zich op het vergroten van inzicht in de aard en de omvang van potentiële complicaties na het toepassen van manueeltherapeutische handelingen aan de cervicale wervelkolom bij mensen met nekpijn en/of hoofdpijn. Zowel onder leken als onder zorgprofessionals bestaat de veronderstelling dat manueeltherapeutische handelingen die worden toegepast aan de cervicale wervelkolom, kunnen leiden tot complicaties. Er is tot nu toe geen duidelijk causaal verband gevonden tussen de handelingen en ernstige complicaties. Bovendien wordt slechts sporadisch gepubliceerd over casuïstiek met ernstige complicaties die tijdens of na manuele behandelingen van de cervicale wervelkolom ontstaan zijn. De schattingen van het voorkomen van complicaties variëren enorm. Daarnaast is niet duidelijk welke patiënten een hoger of lager risico lopen op dergelijke complicaties.
Designing cities that are socially sustainable has been a significant challenge until today. Lately, European Commission’s research agenda of Industy 5.0 has prioritised a sustainable, human-centric and resilient development over merely pursuing efficiency and productivity in societal transitions. The focus has been on searching for sustainable solutions to societal challenges, engaging part of the design industry. In architecture and urban design, whose common goal is to create a condition for human life, much effort was put into elevating the engineering process of physical space, making it more efficient. However, the natural process of social evolution has not been given priority in urban and architectural research on sustainable design. STEPS stems from the common interest of the project partners in accessible, diverse, and progressive public spaces, which is vital to socially sustainable urban development. The primary challenge lies in how to synthesise the standardised sustainable design techniques with unique social values of public space, propelling a transition from technical sustainability to social sustainability. Although a large number of social-oriented studies in urban design have been published in the academic domain, principles and guidelines that can be applied to practice are large missing. How can we generate operative principles guiding public space analysis and design to explore and achieve the social condition of sustainability, developing transferable ways of utilising research knowledge in design? STEPS will develop a design catalogue with operative principles guiding public space analysis and design. This will help designers apply cross-domain knowledge of social sustainability in practice.
Size measurement plays an essential role for micro-/nanoparticle characterization and property evaluation. Due to high costs, complex operation or resolution limit, conventional characterization techniques cannot satisfy the growing demand of routine size measurements in various industry sectors and research departments, e.g., pharmaceuticals, nanomaterials and food industry etc. Together with start-up SeeNano and other partners, we will develop a portable compact device to measure particle size based on particle-impact electrochemical sensing technology. The main task in this project is to extend the measurement range for particles with diameters ranging from 20 nm to 20 um and to validate this technology with realistic samples from various application areas. In this project a new electrode chip will be designed and fabricated. It will result in a workable prototype including new UMEs (ultra-micro electrode), showing that particle sizing can be achieved on a compact portable device with full measuring range. Following experimental testing with calibrated particles, a reliable calibration model will be built up for full range measurement. In a further step, samples from partners or potential customers will be tested on the device to evaluate the application feasibility. The results will be validated by high-resolution and mainstream sizing techniques such as scanning electron microscopy (SEM), dynamic light scattering (DLS) and Coulter counter.
Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
