Fate of nonylphenol ethoxylates and their metabolites in two Dutch estuaries: evidence of biodegradation in the field

The environmental behavior of nonylphenol ethoxylates (A9PEO) and their metabolites was investigated in field studies in the two Dutch estuaries Western Scheldt and the Rhine estuary. Using liquid chromatography-electrospray mass spectrometry (LC-ES-MS) analysis after solid-phase extraction, A9PEO, nonylphenol (NP), and the carboxylated metabolites (A9PEC) were determined in surface water and sediments. Maximum dissolved concentrations of 2.3, 0.9, and 8.1 microg L(-1), respectively, were found. In sediments, maximum concentrations of 242 and 1080 ng g(-1) for A9PEO and NP were observed. In almost half of the sediment samples, concentrations of A9PEC in sediments were below the detection limit. Occasionally relatively high values were observed, with a maximum of 239 ng g(-1). Metabolites of the carboxy alkylphenoxy ethoxy acetic acids (CAPEC) type could not be detected in any of the sediment or water samples. In the Scheldt estuary, dissolved concentration profiles showed nonconservative behaviorfor all detected compound groups. While A9PEO and NP concentrations strongly decreased along the salinity gradient, this decrease was weaker for the A9PEC metabolites. The increasing concentration ratio of A9PEC/A9PEO clearly illustratesthe important role that aerobic biodegradation plays in the estuarine fate of these compounds. It is concluded that the oxidative hydrolytic degradation pathway is the main degradation route in this nonstratified estuary. At high salinities, where concentrations drop to background levels of around 50 ng L(-1), this ratio decreases to about unity. Simple model calculations show that this can be explained if continuous diffuse discharges (e.g. from the intensive shipping in the estuary) are assumed. For the stratified Rhine estuary the water concentration profiles are less pronounced, possibly due to more complicated and turbulent water flows and point sources from the Rotterdam harbors.     

Mechanism of thaumasite formation in concrete slabs on grade in Southern California

Thaumasite formation has been observed in residential concrete slabs on grade in Southern California. The concrete examined did not contain any carbonate bearing aggregates or fillers. Microstructural analyses showed a carbonated layer with calcite and gypsum at the bottom of the concrete. Above the carbonation layer, deposits of intermixed gypsum and thaumasite were observed. Further into the concrete towards the upper surface, deposits of thaumasite alone or in combination with ettringite were observed. Most of the thaumasite deposits were observed in air voids. SEM–EDS analysis showed deposits of ettringite, thaumasite and intermediate phases within the same air voids. The formation of thaumasite, ettringite and gypsum was caused by ingress of sulfate and carbonate ions from ground water. The presence of thaumasite, ettringite and intermediate phases in the same air void indicates that ettringite is first formed followed by thaumasite with a series of solid solutions. In this reaction process the pH of the local environment and the balance between sulfate, silicate and carbonate ions are important parameters.     

Carbon nanotube electron sources and applications

In this review we give an overview of the present status of research on carbon nanotube (CNT) field emitters and their applications. Several different construction principles of field-emission devices with CNTs are summarized. The emission mechanism is introduced and a detailed overview is given of the measured emission properties and related topics of CNT electron sources. We give also several examples of field-emission devices with CNT electron emitters that are presently being investigated in the academic world as well as in industry. Carbon nanotube electron sources clearly have interesting properties, such as low voltage operation, good stability, long lifetime and high brightness. The most promising applications are the field-emission display and high-resolution electron-beam instruments. But several hurdles remain, such as the manufacture of an electron source or an array of electron sources with exactly the desired properties in a reproducible manner.     

Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.     

A Multicast-Enabled Delivery Framework for QoE Assurance of Over-The-Top Services in Multimedia Access Networks

Over-The-Top (OTT) video services are becoming more and more important in today’s broadband access networks. While original OTT services only offered short duration medium quality videos, more recently, premium content such as high definition full feature movies and live video are offered as well. For operators, who see the potential in providing Quality of Experience (QoE) assurance for an increased revenue, this introduces important new network management challenges. Traditional network management paradigms are often not suited for ensuring QoE guarantees as the provider does not have any control on the content’s origin. In this article, we focus on the management of an OTT-based video service. We present a loosely coupled architecture that can be seamlessly integrated into an existing OTT-based video delivery architecture. The framework has the goal of resolving the network bottleneck that might occur from high peaks in the requests for OTT video services. The proposed approach groups the existing Hypertext Transfer Protocol (HTTP) based video connections to be multicasted over an access network’s bottleneck and then splits them again to reconstruct the original HTTP connections. A prototype of this architecture is presented, which includes the caching of videos and incorporates retransmission schemes to ensure robust transmission. Furthermore, an autonomic algorithm is presented that allows to intelligently select which OTT videos need to be multicasted by making a remote assessment of the cache state to predict the future availability of content. The approach was evaluated through both simulation and large scale emulation and shows a significant gain in scalability of the prototype compared to a traditional video delivery architecture.     

Variational Segmentation of Image Sequences Using Region-Based Active Contours and Deformable Shape Priors

In this paper we address the problem of segmentation in image sequences using region-based active contours and level set methods. We propose a novel method for variational segmentation of image sequences containing nonrigid, moving objects. The method is based on the classical Chan-Vese model augmented with a novel frame-to-frame interaction term, which allow us to update the segmentation result from one image frame to the next using the previous segmentation result as a shape prior. The interaction term is constructed to be pose-invariant and to allow moderate deformations in shape. It is expected to handle the appearance of occlusions which otherwise can make segmentation fail. The performance of the model is illustrated with experiments on synthetic and real image sequences.     

Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces

Concept classes can canonically be represented by matrices with entries 1 and –1. We use the singular value decomposition of this matrix to determine the optimal margins of embeddings of the concept classes of singletons and of half intervals in homogeneous Euclidean half spaces. For these concept classes the singular value decomposition can be used to construct optimal embeddings and also to prove the corresponding best possible upper bounds on the margin. We show that the optimal margin for embedding n singletons is and that the optimal margin for half intervals over {1,...,n} is . For the upper bounds on the margins we generalize a bound by Forster (2001). We also determine the optimal margin of some concept classes defined by circulant matrices up to a small constant factor, and we discuss the concept classes of monomials to point out limitations of our approach.     

Fast and accurate 4‐node quadrilateral

An accurate and variationally consistent 4‐node quadrilateral element is introduced where high coarse mesh accuracy and low mesh distortion sensitivity are characteristic qualities, even when incompressibility is approached for plane strain. One‐point quadrature integration procedure is adopted and a new improved stabilization technique is developed. Orthogonality conditions are utilized so that the patch test is satisfied for arbitrary quadrilaterals. Several numerical examples including a convergence rate study are presented which confirm the excellent performance of this element. Copyright © 2004 John Wiley & Sons, Ltd.     

Interactive topology optimization on hand-held devices

This paper presents an interactive topology optimization application designed for hand-held devices running iOS or Android. The TopOpt app solves the 2D minimum compliance problem with interactive control of load and support positions as well as volume fraction. Thus, it is possible to change the problem settings on the fly and watch the design evolve to a new optimum in real time. The use of an interactive app makes it extremely simple to learn and understand the influence of load-directions, support conditions and volume fraction. The topology optimization kernel is written in C# and the graphical user interface is developed using the game engine Unity3D. The underlying code is inspired by the publicly available 88 and 99 line Matlab codes for topology optimization but does not utilize any low-level linear algebra routines such as BLAS or LAPACK. The TopOpt App can be downloaded on iOS devices from the Apple App Store, at Google Play for the Android platform, and a web-version can be run from www.topopt.dtu.dk.     

An integrated qualitative and quantitative modeling framework for computer‐assisted HAZOP studies

The article proposes a novel practical framework for computer‐assisted hazard and operability (HAZOP) that integrates qualitative reasoning about system function with quantitative dynamic simulation in order to facilitate detailed specific HAZOP analysis. The practical framework is demonstrated and validated on a case study concerning a three‐phase separation process. The multilevel flow modeling (MFM) methodology is used to represent the plant goals and functions. First, means‐end analysis is used to identify and formulate the intention of the process design in terms of components, functions, objectives, and goals on different abstraction levels. Based on this abstraction, qualitative functional models are constructed for the process. Next MFM‐specified causal rules are extended with systems specific features to enable proper reasoning. Finally, systematic HAZOP analysis is performed to identify safety critical operations, its causes and consequences. The outcome is a qualitative hazard analysis of selected process deviations from normal operations and their consequences as input to a traditional HAZOP table. The list of unacceptable high risk deviations identified by the qualitative HAZOP analysis is used as input for rigorous analysis and evaluation by the quantitative analysis part of the framework. To this end, dynamic first‐principles modeling is used to simulate the system behavior and thereby complement the results of the qualitative analysis part. The practical framework for computer‐assisted HAZOP studies introduced in this article allows the HAZOP team to devote more attention to high consequence hazards. © 2014 American Institute of Chemical Engineers AIChE J 60: 4150–4173, 2014