116 research outputs found

    Working surface science model for the Phillips ethylene polymerization catalyst:preparation and testing

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    A surface science model for the Phillips ethylene polymerization catalyst has been prepared, by impregnating aqueous CrO3 on a flat silicium (100) substrate covered by amorphous silica. Impregnating in a spin-coating technique offers control over the chromium loading, which was varied between 0.4 and 4.0 Cr/nm2. After impregnation chromium is dispersed molecularly at loadings smaller than 2 Cr/nm2. Upon calcination chromium is anchored to the support over Cr - O - Si ester bonds, although a fraction is lost from the surface due to volatilization, as could be established with X-ray photoelectron spectroscopy. The model catalyst polymerizes ethylene at 160 °C and atmospheric pressure after being activated in 80/20 He/O2 at 650 °C, confirming its validity as a model for the industrial catalyst.</p

    Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches

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    The ubiquity of smartphones have opened up the possibility of widespread use of the Experience Sampling Method (ESM). The method is used to collect longitudinal data of participants' daily life experiences and is ideal to capture fluctuations in emotions (momentary mental states) as an indicator for later mental ill-health. In this study, ESM data of patients with psychosis spectrum disorder and controls were used to examine daily life emotions and higher order patterns thereof. We attempted to determine whether aggregated ESM data, in which statistical measures represent the distribution and dynamics of the original data, were able to distinguish patients from controls in a predictive modelling framework. Variable importance, recursive feature elimination, and ReliefF methods were used for feature selection. Model training, tuning, and testing were performed in nested cross-validation, based on algorithms such as Random Forests, Support Vector Machines, Gaussian Processes, Logistic Regression and Neural Networks. ROC analysis was used to post-process these models. Stability of model performance was studied using Monte Carlo simulations. The results provide evidence that patterns in emotion changes can be captured by applying a combination of these techniques. Acceleration in the variables anxious and insecure was particularly successful in adding further predictive power to the models. The best results were achieved by Support Vector Machines with radial kernel (accuracy=82% and sensitivity=82%). This proof-of-concept work demonstrates that synergistic machine learning and statistical modeling may be used to harness the power of ESM data in the future

    Outcome of Insertable Cardiac Monitors in Symptomatic Patients with Brugada Syndrome at Low Risk of Sudden Cardiac Death

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    Introduction: There is limited data on the experience with insertable cardiac monitors (ICMs) in patients with Brugada syndrome. Objective: To evaluate the outcome of ICM in symptomatic patients with Brugada syndrome who are at suspected low risk of sudden cardiac death (SCD). Methods: We conducted a prospective single-center cohort study including all symptomatic patients with Brugada syndrome who received an ICM (Reveal LINQ) between July 2014 and October 2019. The main indication for monitoring was to exclude ventricular arrhythmias as the cause of symptoms and to establish a symptom-rhythm relationship. Results: A total of 20 patients (mean age, 39 ± 12 years; 55% male) received an ICM during the study period. Nine patients (45%) had a history of syncope (presumed nonarrhythmogenic), and 5 patients had a recent syncope (<6 months). During a median follow-up of 32 months (interquartile range, 11-36 months), 3 patients (15%) experienced an episode of nonsustained ventricular arrhythmia. No patient died suddenly or experienced a sustained ventricular arrhythmia, and no

    Olivine Weathering in Soil, and Its Effects on Growth and Nutrient Uptake in Ryegrass (lolium perenne L.): A Pot Experiment

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    Mineral carbonation of basic silicate minerals regulates atmospheric CO2 on geological time scales by locking up carbon. Mining and spreading onto the earth's surface of fast-weathering silicates, such as olivine, has been proposed to speed up this natur

    Klimaatverandering en de functies van het landelijk gebied : resultaten van vier jaar klimaatonderzoek

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    Vier thema's komen in deze brochure aan bod: koolstofvastlegging in bos en landbouw; emissies van lachgas en methaan uit de landbouw; landgebruik als actor en reactor in het klimaatsysteem; klimaatverandering en het landelijk gebied: een integrale kijk. Uitleg over een actueel onderwerp, aan de hand van 31 vrage

    Expert consensus recommendations on the cardiogenetic care for patients with thoracic aortic disease and their first-degree

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    Background: Thoracic aortic aneurysm (TAA) is a potentially life-threatening disorder with a strong genetic component. The number of genes implicated in TAA has increased exponentially over the last decade. Approximately 20% of patients with TAA have a positive family history. As most TAA remain asymptomatic for a long time, screening of at risk relatives is warranted to prevent complications. Existing international guidelines lack detailed instructions regarding genetic evaluation and family screening of TAA patients. We aimed to develop a consensus document to provide medical guidance for all health care professionals involved in the recognition, diagnosis and treatment of patients with thoracic aortic disease and their relatives. Methods: A multidisciplinary panel of experts including cardiologists, cardiothoracic surgeons, clinical geneticists and general practitioners, convened to review and discuss the current literature, guidelines and clinical practice on genetic testing and family screening in TAA. Results: There is a lack of high-quality evidence in the literature. This consensus statement, based on the available literature and expert opinions, summarizes our recommendations in order to standardize and optimize the cardiogenetic care for patients and families with thoracic aortic disease. In particular, we provide criteria to identify those patients most likely to have a genetic predisposition, and discuss the preferred modality and frequency of screening in their relatives. Conclusions: Age, family history, aortic size and syndromic features determine who is advised to have genetic testing as well as screening of first-degree relatives. There is a need for more prospective multicenter studies to optimize current recommendations
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