Improving accuracy in detecting acoustic onsets.

In current cognitive psychology, naming latencies are commonly measured by electronic voice keys that detect when sound exceeds a certain amplitude threshold. However, recent research (e.g., K. Rastle & M. H. Davis, 2002) has shown that these devices are particularly inaccurate in precisely detecting acoustic onsets. In this article, the authors discuss the various problems and solutions that have been put forward with respect to this issue and show that classical voice keys may trigger several tens of milliseconds later than acoustic onset. The authors argue that a solution to this problem may come from voice keys that use a combination of analogue and digital noise (nonspeech sound) detection. It is shown that the acoustic onsets detected by such a device are only a few milliseconds delayed and correlate highly (up to .99) with reaction time values obtained by visual waveform inspection. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of nitrogen lewis basicity in boronate affinity chromatography of nucleosides

Urinary modified nucleosides have a potential role as cancer biomarkers, and most of the methods used in their study have utilized low-pressure phenylboronate affinity chromatography materials for the purification of the cis-diol-containing nucleosides. In this study, a boronate HPLC column was surprisingly shown not to trap the nucleosides as would be expected from experience with the classic Affigel 601 resin but showed only partial selectivity toward cis-diol groups while other groups exhibited better retention. In aprotic conditions, trapping of nucleosides was possible; however, the selectivity toward cis-diol-containing compounds was lost with the Lewis basicity of available nitrogens being the main determinant of retention. The experimental findings are compared to and confirmed by DFT calculations.     

The Progress of Intestinal Epithelial Models from Cell Lines to Gut-On-Chip

Over the past years, several preclinical in vitro and ex vivo models have been developed that helped to understand some of the critical aspects of intestinal functions in health and disease such as inflammatory bowel disease (IBD). However, the translation to the human in vivo situation remains problematic. The main reason for this is that these approaches fail to fully reflect the multifactorial and complex in vivo environment (e.g., including microbiota, nutrition, and immune response) in the gut system. Although conventional models such as cell lines, Ussing chamber, and the everted sac are still used, increasingly more sophisticated intestinal models have been developed over the past years including organoids, InTESTine™ and microfluidic gut-on-chip. In this review, we gathered the most recent insights on the setup, advantages, limitations, and future perspectives of most frequently used in vitro and ex vivo models to study intestinal physiology and functions in health and disease.     

The Multifaceted Role of Serotonin in Intestinal Homeostasis

The monoamine serotonin, 5-hydroxytryptamine (5-HT), is a remarkable molecule with conserved production in prokaryotes and eukaryotes and a wide range of functions. In the gastrointestinal tract, enterochromaffin cells are the most important source for 5-HT production. Some intestinal bacterial species are also able to produce 5-HT. Besides its role as a neurotransmitter, 5-HT acts on immune cells to regulate their activation. Several lines of evidence indicate that intestinal 5-HT signaling is altered in patients with inflammatory bowel disease. In this review, we discuss the current knowledge on the production, secretion, and signaling of 5-HT in the intestine. We present an inventory of intestinal immune and epithelial cells that respond to 5-HT and describe the effects of these signaling processes on intestinal homeostasis. Further, we detail the mechanisms by which 5-HT could affect inflammatory bowel disease course and describe the effects of interventions that target intestinal 5-HT signaling.     

Modeling of copper sorption onto GFH and design of full-scale GFH adsorbers

During rain events, copper wash-off occurring from copper roofs results in environmental hazards. In this study, columns filled with granulated ferric hydroxide (GFH) were used to treat copper-containing roof runoff. It was shown that copper could be removed to a high extent. A model was developed to describe this removal process. The model was based on the Two Region Model (TRM), extended with an additional diffusion zone. The extended model was able to describe the copper removal in long-term experiments (up to 125 days) with variable flow rates reflecting realistic runoff events. The four parameters of the model were estimated based on data gained with specific column experiments according to maximum sensitivity for each parameter. After model validation, the parameter set was used for the design of full-scale adsorbers. These full-scale adsorbers show high removal rates during extended periods of time.     

Synergy between bio‐based industry and the feed industry through biorefinery

Processing biomass into multi‐functional components can contribute to the increasing demand for raw materials for feed and bio‐based non‐food products. This contribution aims to demonstrate synergy between the bio‐based industry and the feed industry through biorefinery of currently used feed ingredients. Illustrating the biorefinery concept, rapeseed was selected as a low priced feed ingredient based on market prices versus crude protein, crude fat and apparent ileal digestible lysine content. In addition it is already used as an alternative protein source in diets and can be cultivated in European climate zones. Furthermore, inclusion level of rapeseed meal in pig diet is limited because of its nutritionally active factors. A conceptual process was developed to improve rapeseeds nutritional value and producing other bio‐based building blocks simultaneously. Based on the correlation between market prices of feed ingredients and its protein and fat content, the value of refined products was estimated. Finally, a sensitivity analysis, under two profit scenario, shows that the process is economically feasible. This study demonstrates that using biorefinery processes on feed ingredients can improve feed quality. In conjunction, it produces building blocks for a bio‐based industry and creates synergy between bio‐based and feed industry for more efficient use of biomass. © 2015 Society of Chemical Industry     

Increasing robustness against changes in the interferent structure by incorporating prior information in the augmented classical least-squares framework

A class of multivariate calibration methods called augmented classical least squares (ACLS) has been proposed which combines an explicit linear additive model with the predictive power of inverse models, such as principal component regression (PCR) and partial least squares (PLS). Because of its use of the explicit linear additive model, ACLS provides an interesting framework to incorporate different sources of prior information, such as measured pure component spectra, in the model. In this study, the predictive power of ACLS models incorporating different amounts of prior information has been compared to that of PCR and PLS using two examples, a designed experiment and one with biological samples. In both cases, the ACLS models showed predictive power comparable to PLS under idealized validation conditions. When a different interferent structure was present in the validation samples, the predictive power of the inverse models (PCR and PLS) dramatically decreased, with an increase in root-mean-squared error of prediction by a factor of 3.5 for the first example and a factor of 2 in the second example. The incorporation of prior information in the ACLS framework was found to considerably reduce or even completely remove these dramatic effects, especially when the pure component contributions for the interferents were taken into account.     

Polarization of skylight in the O(2)A band: effects of aerosol properties

Motivated by several observations of the degree of linear polarization of skylight in the oxygen A (O(2)A) band that do not yet have a quantitative explanation, we analyze the influence of aerosol altitude, microphysics, and optical thickness on the degree of linear polarization of the zenith skylight in the spectral region of the O(2)A band, between 755 to 775 nm. It is shown that the degree of linear polarization inside the O(2)A band is particularly sensitive to aerosol altitude. The sensitivity is strongest for aerosols within the troposphere and depends also on their microphysical properties and optical thickness. The polarization of the O(2)A band can be larger than the polarization of the continuum, which typically occurs for strongly polarizing aerosols in an elevated layer, or smaller, which typically occurs for depolarizing aerosols or cirrus clouds in an elevated layer. We show that in the case of a single aerosol layer in the atmosphere a determination of the aerosol layer altitude may be obtained. Furthermore, we show limitations of the aerosol layer altitude determination in case of multiple aerosol layers. To perform these simulations we developed a fast method for multiple scattering radiative transfer calculations in gaseous absorption bands including polarization. The method is a combination of doubling-adding and k-binning methods. We present an error estimation of this method by comparing with accurate line-by-line radiative transfer simulations. For the Motivated by several observations of the degree of linear polarization of skylight in the oxygen A (O(2)A) band that do not yet have a quantitative explanation, we analyze the influence of aerosol altitude, microphysics, and optical thickness on the degree of linear polarization of the zenith skylight in the spectral region of the O(2)A band, between 755 to 775 nm. It is shown that the degree of linear polarization inside the O(2)A band is particularly sensitive to aerosol altitude. The sensitivity is strongest for aerosols within the troposphere and depends also on their microphysical properties and optical thickness. The polarization of the O(2)A band can be larger than the polarization of the continuum, which typically occurs for strongly polarizing aerosols in an elevated layer, or smaller, which typically occurs for depolarizing aerosols or cirrus clouds in an elevated layer. We show that in the case of a single aerosol layer in the atmosphere a determination of the aerosol layer altitude may be obtained. Furthermore, we show limitations of the aerosol layer altitude determination in case of multiple aerosol layers. To perform these simulations we developed a fast method for multiple scattering radiative transfer calculations in gaseous absorption bands including polarization. The method is a combination of doubling-adding and k-binning methods. We present an error estimation of this method by comparing with accurate line-by-line radiative transfer simulations. For the O(2)A band, the errors in the degree of linear polarization are less than 0.11% for transmitted light, and less than 0.31% for reflected light. band, the errors in the degree of linear polarization are less than 0.11% for transmitted light, and less than 0.31% for reflected light.     

Web-based environmental simulation: bridging the gap between scientific modeling and decision-making

Data availability in environmental sciences is growing rapidly. Conventional monitoring systems are collecting data at increasing spatial and temporal resolutions; satellites provide a constant stream of global observations, and citizen scientist generate local data with electronic gadgets and cheap devices. There is a need to process this stream of heterogeneous data into useful information, both for science and for decision-making. Advances in networking and computer technologies increasingly enable accessing, combining, processing, and visualizing these data. This Feature reflects upon the role of environmental models in this process. We consider models as the primary tool for data processing, pattern identification, and scenario analysis. As such, they are an essential element of science-based decision-making. The new technologies analyzed here have the potential to turn the typical top-down flow of information from scientists to users into a much more direct, interactive approach. This may accelerate the dissemination of environmental information to a larger community of users. It may also facilitate harvesting feedback, and evaluating simulations and predictions from different perspectives. However, the evolution poses challenges, not only to model development but also to the communication of model results and their assumptions, shortcomings, and errors.     

Removal of two polycyclic musks in sewage treatment plants: freely dissolved and total concentrations

In the current study, the removal of slowly degradable hydrophobic chemicals in sewage treatment plants (STPs) has been evaluated with emphasis on the combination of free and total concentration data. Free and total concentrations of two polycyclic musks were determined in each compartment of four STPs. The free concentration of the polycyclic musks remains virtually constant throughout all the compartments of the STPs with values between 0.21 and 0.57 microg/L for AHTN and between 0.79 and 2.0 microg/L for HHCB. Total concentrations of these fragrances are highly dependent on the volatile solids in a given compartment resulting in much more variation with values between 0.42 and 92 microg/L for AHTN and between 1.25 and 258 microg/L for HHCB. It is concluded that free concentrations of these hydrophobic chemicals in the compartments of STPs are mostly biodegradation mediated, while total concentrations are mediated by the concentration of solids. The combination of measurements of free and total concentrations can improve estimations regarding removal efficiency and removal pathways.