Abstract: Electronic and electrical waste (e-waste) is growing fast. The purpose of this study is to examine young consumers’ purchase intention of refurbished electronic devices (REDs) such as laptop, tablet, mobile phone and game console. From literature review the factors that influence young consumers’ purchase intention were identified as ‘environmental awareness’, ‘social acceptance’, ‘seller/brand reputation and availability’, and ‘affordability and value’. For each factor a few statements were developed and used as independent variables in a questionnaire. One statement was added about purchase intention as dependent variable. A Pearson correlation coefficient test us showed a clear positive correlation of ‘environmental awareness’ and ‘affordability and value’ with the intention to purchase REDs, but not for the other two factors. This analysis contributes to knowledge on young consumers’ perceptions of refurbished electronic devices and can inform the design of innovative value propositions and new business models for REDs that contribute to a circular economy
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Background: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands. Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error. Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets. Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.
BackgroundPatients undergoing total knee arthroplasty (TKA) often experience strength deficits both pre- and post-operatively. As these deficits may have a direct impact on functional recovery, strength assessment should be performed in this patient population. For these assessments, reliable measurements should be used. This study aimed to determine the inter- and intrarater reliability of hand-held dynamometry (HHD) in measuring isometric knee strength in patients awaiting TKA.MethodsTo determine interrater reliability, 32 patients (81.3% female) were assessed by two examiners. Patients were assessed consecutively by both examiners on the same individual test dates. To determine intrarater reliability, a subgroup (n = 13) was again assessed by the examiners within four weeks of the initial testing procedure. Maximal isometric knee flexor and extensor strength were tested using a modified Citec hand-held dynamometer. Both the affected and unaffected knee were tested. Reliability was assessed using the Intraclass Correlation Coefficient (ICC). In addition, the Standard Error of Measurement (SEM) and the Smallest Detectable Difference (SDD) were used to determine reliability.ResultsIn both the affected and unaffected knee, the inter- and intrarater reliability were good for knee flexors (ICC range 0.76-0.94) and excellent for knee extensors (ICC range 0.92-0.97). However, measurement error was high, displaying SDD ranges between 21.7% and 36.2% for interrater reliability and between 19.0% and 57.5% for intrarater reliability. Overall, measurement error was higher for the knee flexors than for the knee extensors.ConclusionsModified HHD appears to be a reliable strength measure, producing good to excellent ICC values for both inter- and intrarater reliability in a group of TKA patients. High SEM and SDD values, however, indicate high measurement error for individual measures. This study demonstrates that a modified HHD is appropriate to evaluate knee strength changes in TKA patient groups. However, it also demonstrates that modified HHD is not suitable to measure individual strength changes. The use of modified HHD is, therefore, not advised for use in a clinical setting.
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Climate change is one of the most critical global challenges nowadays. Increasing atmospheric CO2 concentration brought by anthropogenic emissions has been recognized as the primary driver of global warming. Therefore, currently, there is a strong demand within the chemical and chemical technology industry for systems that can covert, capture and reuse/recover CO2. Few examples can be seen in the literature: Hamelers et al (2013) presented systems that can use CO2 aqueous solutions to produce energy using electrochemical cells with porous electrodes; Legrand et al (2018) has proven that CDI can be used to capture CO2 without solvents; Shu et al (2020) have used electrochemical systems to desorb (recover) CO2 from an alkaline absorbent with low energy demand. Even though many efforts have been done, there is still demand for efficient and market-ready systems, especially related to solvent-free CO2 capturing systems. This project intends to assess a relatively efficient technology, with low-energy costs which can change the CO2 capturing market. This technology is called whorlpipe. The whorlpipe, developed by Viktor Schauberger, has shown already promising results in reducing the energy and CO2 emissions for water pumping. Recently, studies conducted by Wetsus and NHL Stenden (under submission), in combination with different companies (also members in this proposal) have shown that vortices like systems, like the Schauberger funnel, and thus “whorlpipe”, can be fluid dynamically represented using Taylor-Couette flows. This means that such systems have a strong tendency to form vortices like fluid-patterns close to their air-water interface. Such flow system drastically increase advection. Combined with their higher area to volume ratio, which increases diffusion, these systems can greatly enhance gas capturing (in liquids), and are, thus, a unique opportunity for CO2 uptake from the air, i.e. competing with systems like conventional scrubbers or bubble-based aeration.
