Hydrodynamics of Binary Fluid Mixtures - An Augmented Multiparticle Collison Dynamics Approach

The Multiparticle Collision Dynamics technique (MPC) for hydrodynamics simulations is generalized to binary fluid mixtures and multiphase flows, by coupling the particle-based fluid dynamics to a Ginzburg-Landau free-energy functional for phase-separating binary fluids. To describe fluids with a non-ideal equation of state, an additional density-dependent term is introduced. The new approach is verified by applying it to thermodynamics near the critical demixing point, and interface fluctuations of droplets. The interfacial tension obtained from the analysis of the capillary wave spectrum agrees well with the results based on the Laplace-Young equation. Phase-separation dynamics follows the Lifshitz-Slyozov law

Accuracy and uncertainty of single-shot, nonresonant laser-induced thermal acoustics

We study the accuracy and uncertainty of single-shot nonresonant laser-induced thermal acoustics measurements of the speed of sound and the thermal diffusivity in unseeded atmospheric air from electrostrictive gratings as a function of the laser power settings. For low pump energies, the measured speed of sound is too low, which is due to the influence of noise on the numerical data analysis scheme. For pump energies comparable to and higher than the breakdown energy of the gas, the measured speed of sound is too high. This is an effect of leaving the acoustic limit, and instead creating finite-amplitude density perturbations. The measured thermal diffusivity is too large for high noise levels but it decreases below the predicted value for high pump energies. The pump energy where the error is minimal coincides for the speed of sound and for the thermal diffusivity measurements. The errors at this minimum are 0.03% and 1%, respectively. The uncertainties for the speed of sound and the thermal diffusivity decrease monotonically with signal intensity to 0.25% and 5%, respectively

Flupenthixol in relapse prevention in schizophrenics with comorbid alcoholism: Results from an open clinical study

Substance use, especially alcoholism, has been recognized as a significant problem in schizophrenic patients, though only a few studies on the effects of pharmacotherapy in these patients have been conducted so far. The thioxanthene neuroleptic flupenthixol, which can be given intramuscularly (i.m.) for improving compliance, has been studied as a possible anti-craving drug both in animal models of alcoholism and some clinical studies. Pilot studies suggest that comorbid schizophrenics with substance use may benefit from treatment with flupenthixol. Efficacy of flupenthixol (10-60 mg i.m.) in reducing alcohol consumption of dual diagnosis patients was studied in an open 6-month clinical trial in 27 schizophrenics with comorbid alcoholism. Twenty-one patients entered the intention-to-treat analysis. Fourteen subjects were completers, 13 dropped out. Six patients completely abstained from alcohol during treatment. Alcohol consumption was significantly reduced compared to baseline (4 weeks before treatment as measured by timeline follow-back interview). In general, while patients showed a marked improvement concerning alcohol consumption, only a slight improvement in psychopathology was recorded. Overall tolerability was good. These data indicate a probable beneficial effect of flupenthixol in schizophrenic patients with comorbid alcoholism. Although the efficacy of flupenthixol as an anti-craving drug in dual diagnosis patients has to be explored in further studies, the drug may be considered a promising medication for these patients. Copyright (C) 2003 S. Karger AG, Basel

Sovereign Digital Consent through Privacy Impact Quantification and Dynamic Consent

Digitization is becoming more and more important in the medical sector. Through electronic health records and the growing amount of digital data of patients available, big data research finds an increasing amount of use cases. The rising amount of data and the imposing privacy risks can be overwhelming for patients, so they can have the feeling of being out of control of their data. Several previous studies on digital consent have tried to solve this problem and empower the patient. However, there are no complete solution for the arising questions yet. This paper presents the concept of Sovereign Digital Consent by the combination of a consent privacy impact quantification and a technology for proactive sovereign consent. The privacy impact quantification supports the patient to comprehend the potential risk when sharing the data and considers the personal preferences regarding acceptance for a research project. The proactive dynamic consent implementation provides an implementation for fine granular digital consent, using medical data categorization terminology. This gives patients the ability to control their consent decisions dynamically and is research friendly through the automatic enforcement of the patients’ consent decision. Both technologies are evaluated and implemented in a prototypical application. With the combination of those technologies, a promising step towards patient empowerment through Sovereign Digital Consent can be made

Full versus incomplete cross-validation: measuring the impact of imperfect separation between training and test sets in prediction error estimation

In practical applications of supervised statistical learning the separation of the training and test data is often violated through performing one or several analysis steps prior to estimating the prediction error by cross-validation (CV) procedures. We refer to such practices as incomplete CV. For the special case of preliminary variable selection in high-dimensional microarray data the corresponding error estimate is well known to be strongly downwardly biased, resulting in over-optimistic conclusions regarding prediction accuracy of the fitted models. However, while other data preparation steps may also be affected by these types of problems, their impact on error estimation is far less acknowledged in the literature. In this paper we shed light on these issues. We present a new measure quantifying the impact of incomplete CV that is based on the ratio between the errors estimated by incomplete CV and by a formally correct "full CV." The new measure is illustrated through applications to several low- and high-dimensional biomedical data sets and various data preparation steps including preliminary variable selection, choice of tuning parameters, normalization of gene expression microarray data, and imputation of missing values. It may be used in biometrical applications to determine whether specific data preparation steps can be safely performed as preliminary steps before running the CV procedure, or if they should be repeatedly trained in each CV iteration

CRISPaint allows modular base-specific gene tagging using a ligase-4-dependent mechanism

The site-specific insertion of heterologous genetic material into genomes provides a powerful means to study gene function. Here we describe a modular system entitled CRISPaint (CRISPR-assisted insertion tagging) that allows precise and efficient integration of large heterologous DNA cassettes into eukaryotic genomes. CRISPaint makes use of the CRISPR-Cas9 system to introduce a double-strand break (DSB) at a user-defined genomic location. A universal donor DNA, optionally provided as minicircle DNA, is cleaved simultaneously to be integrated at the genomic DSB, while processing the donor plasmid at three possible positions allows flexible reading-frame selection. Applying this system allows to create C-terminal tag fusions of endogenously encoded proteins in human cells with high efficiencies. Knocking out known DSB repair components reveals that site-specific insertion is completely dependent on canonical NHEJ (DNA-PKcs, XLF and ligase-4). A large repertoire of modular donor vectors renders CRISPaint compatible with a wide array of applications