Automatic detection and correction of context-dependent dt-mistakes using neural networks

We introduce a novel approach to correcting context-dependent dt-mistakes, one of the most frequent spelling errors in the Dutch language. We show that by using a neural network to estimate the probability distribution of a verb's suffix conditioned jointly on its stem and context, we obtain large improvements over state-of-the-art spell checkers on three different benchmarking datasets, achieving a perfect score on a verb spelling test from \emph{de Standaard}, a Flemish newspaper. The method is unsupervised and only relies on basic preprocessing tools to tokenize the text and identify verbs, which enables training on millions of sentences. Furthermore, we propose a method to determine which words in a sentence cause the system to make corrections, which is valuable for providing feedback to the user

Guidelines for morpholino use in zebrafish

The zebrafish (Danio rerio) has emerged as a powerful model to study vertebrate development and disease. Its short generation time makes it amenable to genetic manipulation and analysis, and its small size and high fecundity make it especially well suited for large-scale forward genetic and chemical screens. Fast-developing zebrafish embryos are transparent, facilitating live imaging of a variety of developmental processes in wild-type and mutant animals. ... This brief document provides an updated set of guidelines regarding morpholino use in zebrafish that we anticipate will be of value for experimentalists as well as journal and grant reviewers, and decision makers

Blood/gas partition coefficients of halothane, isoflurane and sevoflurane in horse blood

Background. Blood/gas partition coefficients (λb/g) for volatile agents in horse blood are reported for halothane but not for isoflurane and sevoflurane. We measured the λb/g of halothane, isoflurane and sevoflurane in the blood of fasted horses. The correlation with age, weight and some haematological and biochemical variables was studied. The temperature correction factor for isoflurane solubility was calculated. Methods. Twenty‐four horses were randomly allocated to halothane (n=8), isoflurane (n=8) or sevoflurane (n=8). Blood samples were taken after 10 h' fasting. Calculation of λb/g was based on the measurement of anaesthetic partial pressures in blood at 37 °C, which was achieved with tonometer equilibration and headspace gas chromatography. Results. Mean λb/g was 1.66 (sd 0.06) for halothane, 0.92 (0.04) for isoflurane, and 0.47 (0.03) for sevoflurane. The λb/g values were all significantly lower than in humans (P<0.001). No correlation was found between λb/g and weight, age, haematocrit, plasma triglycerides, cholesterol or total bilirubin. The change in isoflurane solubility per 1 °C temperature increase was -2.63 (0.13)%. Conclusion. The λb/g values of halothane, isoflurane and sevoflurane in fasted horses are significantly lower than those reported in humans. The λb/g for halothane in this study agrees with values reported in the literature but a positive correlation with plasma triglycerides could not be confirmed. Knowledge of λb/g can refine models of anaesthetic uptake. Br J Anaesth 2003; 91: 276-

Fatty Acid Methyl Esters as Biosolvents of Epoxy Resins: A Physicochemical Study

The C8 to C18 fatty acid methyl esters (FAME) have been compared as solvents for two epoxy resin pre-polymers, bisphenol A diglycidyl ether (DGEBA) and triglycidyl paminophenol ether (TGPA). It was found that the solubilization limits vary according to the ester and that methyl caprylate is the best solvent of both resins. To explain these solubility performances, physical and chemical properties of FAME were studied, such as the Hansen parameters, viscosity, binary diffusion coefficient and vaporization enthalpy. Determination of the physicochemical parameters of FAME was carried out by laboratory experimentations and by calculation from bibliographic data. The Hansen parameters of FAME and epoxy resins pre-polymers were theoretically and experimentally determined. The FAME chain length showed a long dependence on the binary diffusion parameters and kinematic viscosity, which are mass and momentum transport properties. Moreover, the vaporization enthalpy of these compounds was directly correlated with the solubilization limits

The inner centromere is a biomolecular condensate scaffolded by the chromosomal passenger complex.

The inner centromere is a region on every mitotic chromosome that enables specific biochemical reactions that underlie properties, such as the maintenance of cohesion, the regulation of kinetochores and the assembly of specialized chromatin, that can resist microtubule pulling forces. The chromosomal passenger complex (CPC) is abundantly localized to the inner centromeres and it is unclear whether it is involved in non-kinase activities that contribute to the generation of these unique chromatin properties. We find that the borealin subunit of the CPC drives phase separation of the CPC in vitro at concentrations that are below those found on the inner centromere. We also provide strong evidence that the CPC exists in a phase-separated state at the inner centromere. CPC phase separation is required for its inner-centromere localization and function during mitosis. We suggest that the CPC combines phase separation, kinase and histone code-reading activities to enable the formation of a chromatin body with unique biochemical activities at the inner centromere

Assessment of distribution of ventilation by electrical impedance tomography in standing horses

The aim was to evaluate the feasibility of using electrical impedance tomography (EIT) in horses. Thoracic EIT was used in nine horses. Thoracic and abdominal circumference changes were also measured with respiratory ultrasound plethysmography (RUP). Data were recorded during baseline, rebreathing of CO2 and sedation. Three breaths were selected for analysis from each recording. During baseline breathing, horses regularly took single large breaths (sighs), which were also analysed. Functional EIT images were created using standard deviations (SD) of pixel signals and correlation coefficients (R) of each pixel signal with a reference respiratory signal. Left-to-right ratio, centre-of-ventilation and global-inhomogeneity-index were calculated. RMANOVA and Bonferroni tests were used (P<0.05). Distribution of ventilation shifted towards right during sighs and towards dependent regions during sighs, rebreathing and sedation. Globalinhomogeneity- index did not change for SD but increased for R images during sedation. The sum of SDs for the respiratory EIT signals correlated well with thoracic (r2 = 0.78) and abdominal (r2 = 0.82) tidal circumferential changes. Inverse respiratory signals were identified on the images at sternal location and based on reviewing CT images, seemed to correspond to location of gas filled intestines. Application of EIT in standing non-sedated horses is feasible. EIT images may provide physiologically useful information even in situations, such as sighs, that cannot easily be tested by other methods

A multivariate interval approach for inverse uncertainty quantification with limited experimental data

© 2018 Elsevier Ltd This paper introduces an improved version of a novel inverse approach for the quantification of multivariate interval uncertainty for high dimensional models under scarce data availability. Furthermore, a conceptual and practical comparison of the method with the well-established probabilistic framework of Bayesian model updating via Transitional Markov Chain Monte Carlo is presented in the context of the DLR-AIRMOD test structure. First, it is shown that the proposed improvements of the inverse method alleviate the curse of dimensionality of the method with a factor up to 105. Furthermore, the comparison with the Bayesian results revealed that the selection ofthe most appropriate method depends largely on the desired information and availability of data. In case large amounts of data are available, and/or the analyst desires full (joint)-probabilistic descriptors of the model parameter uncertainty, the Bayesian method is shown to be the most performing. On the other hand however, when such descriptors are not needed (e.g., for worst-case analysis), and only scarce data are available, the interval method is shown to deliver more objective and robust bounds on the uncertain parameters. Finally, also suggestions to aid the analyst in selecting the most appropriate method for inverse uncertainty quantification are given