Quickscan vraag en aanbod scholing voor multifunctionele ondernemers

Het doel van het onderzoek is inzicht te verkrijgen in het aanbod en de vraag naar scholing voor de multifunctionele ondernemersnetwerken. Daarnaast is er gekeken of er mogelijkheden zijn in vormen van samenwerking tussen de aanbieders van scholing en de ondernemersnetwerke

Orientational order in dipolar fluids consisting of nonspherical hard particles

We investigate fluids of dipolar hard particles by a certain variant of density-functional theory. The proper treatment of the long range of the dipolar interactions yields a contribution to the free energy which favors ferromagnetic order. This corrects previous theoretical analyses. We determine phase diagrams for dipolar ellipsoids and spherocylinders as a function of the aspect ratio of the particles and their dipole moment. In the nonpolar limit the results for the phase boundary between the isotropic and nematic phase agree well with simulation data. Adding a longitudinal dipole moment favors the nematic phase. For oblate or slightly elongated particles we find a ferromagnetic liquid phase, which has also been detected in computer simulations of fluids consisting of spherical dipolar particles. The detailed structure of the phase diagram and its evolution upon changing the aspect ratio are discussed in detail.Comment: 35 pages LaTeX with epsf style, 11 figures in eps format, submitted to Phys. Rev.

Developing mHealth Apps with researchers: multi-stakeholder design considerations

The authors have been involved with developing a number of mHealth smartphone Apps for use in health or wellness research in collaboration with researchers, clinicians and patient groups for clinical areas including Sickle Cell Disease, Attention Deficit Hyperactivity Disorder, asthma and infertility treatment. In these types of applications, end-users self-report their symptoms and quality of life or conduct psychometric tests. Physiological data may also be captured using sensors that are internal or external to the device. Following a discussion of the multiple stakeholders that are typically involved in small scale research projects involving end-user data collection, four Apps are used as case studies to explore the issue of non-functional requirements

Explainable haemoglobin deferral predictions using machine learning models: interpretation and consequences for the blood supply

BACKGROUND AND OBJECTIVES\nMATERIALS AND METHODS\nRESULTS\nCONCLUSION\nAccurate predictions of haemoglobin (Hb) deferral for whole-blood donors could aid blood banks in reducing deferral rates and increasing efficiency and donor motivation. Complex models are needed to make accurate predictions, but predictions must also be explainable. Before the implementation of a prediction model, its impact on the blood supply should be estimated to avoid shortages.\nDonation visits between October 2017 and December 2021 were selected from Sanquin's database system. The following variables were available for each visit: donor sex, age, donation start time, month, number of donations in the last 24 months, most recent ferritin level, days since last ferritin measurement, Hb at nth previous visit (n between 1 and 5), days since the nth previous visit. Outcome Hb deferral has two classes: deferred and not deferred. Support vector machines were used as prediction models, and SHapley Additive exPlanations values were used to quantify the contribution of each variable to the model predictions. Performance was assessed using precision and recall. The potential impact on blood supply was estimated by predicting deferral at earlier or later donation dates.\nWe present a model that predicts Hb deferral in an explainable way. If used in practice, 64% of non-deferred donors would be invited on or before their original donation date, while 80% of deferred donors would be invited later.\nBy using this model to invite donors, the number of blood bank visits would increase by 15%, while deferral rates would decrease by 60% (currently 3% for women and 1% for men).Algorithms and the Foundations of Software technolog

Influence of enzalutamide on cabazitaxel pharmacokinetics: A Drug–Drug interaction study in metastatic castration-resistant prostate cancer (mCRPC) patients

Purpose: In ongoing clinical research on metastatic castration-resistant prostate cancer (mCRPC) treatment, the potential enhanced efficacy of the combination of taxanes with AR-targeted agents, that is, enzalutamide and abiraterone, is currently being explored. Because enzalutamide induces the CYP3A4 enzyme and taxanes are metabolized by this enzyme, a potential drug–drug interaction needs to be investigated. Experimental Design: Therefore, we performed a pharmacokinetic cross-over study in mCRPC patients who were scheduled for treatment with cabazitaxel Q3W (25 mg/m2). Patients were studied for three consecutive cabazitaxel cycles. Enzalutamide (160 mg once daily) was administered concomitantly after the first cabazitaxel cycle, during 6 weeks. Primary endpoint was the difference in mean area under the curve (AUC) between the first (cabazitaxel monotherapy) and third cabazitaxel cycle, when enzalutamide was added. Results: A potential clinically relevant 22% (95% CI, 9%–34%; P ¼ 0.005) reduction in cabazitaxel exposure was found with concomitant enzalutamide use. The geometric mean AUC0–24h of cabazitaxel was 181 ngh/mL (95% CI, 150–219 ngh/mL) in cycle 3 and 234 ngh/mL (95% CI, 209–261 ngh/mL) in cycle 1. This combination did not result in excessive toxicity, whereas PSA response was promising. Conclusions: We found a significant decrease in cabazitaxel exposure when combined with enzalutamide. In an era of clinical trials on combination strategies for mCRPC, it is important to be aware of clinically relevant drug–drug interactions. Because recent study results support the use of a lower standard cabazitaxel dose of 20 mg/m2, the clinical relevance of this interaction may be substantial, because the addition of enzalutamide may result in subtherapeutic cabazitaxel exposure

Evaluating privacy of individuals in medical data

Algorithms and the Foundations of Software technolog

Evaluating cluster-based synthetic data generation for blood-transfusion analysis

Algorithms and the Foundations of Software technolog

First results of a ferritin‐based blood donor deferral policy in the Netherlands

Algorithms and the Foundations of Software technolog

The added value of ferritin levels and genetic markers for the prediction of haemoglobin deferral

Algorithms and the Foundations of Software technolog