Fluorine speciation analysis using reverse phase liquid chromatography coupled off-line to continuum source molecular absorption spectrometry (CS-MAS): identification and quantification of novel fluorinated organic compounds in environmental and biological samples

Driven by increasing demand for the monitoring of industrial perfluorinated compounds (PFCs), the identification of novel fluorine containing compounds (FOCs) and the tracking of organofluorine drugs and their degradation products, there is a clear need for sensitive, fluorine-specific detection of unknown FOCs. Here we report the first ever direct fluorine-specific (speciation) method; capable of individually detecting untargeted FOCs in environmental and biological samples through the application of continuum source molecular absorption spectrometry (CS-MAS) using a commercial CS-AAS. Two model FOCs (2,4,6, trifluorobenzoic acid (TFBA) and 5-fluoroindol-5-carboxylic acid (FICA)) were used, achieving fluorine-specific detection across a range of 0.1 to 300 ng/mL fluorine, corresponding to a limit of detection of 4 pg F and 5.26 nM for both compounds. Both TFBA and FICA showed a similar response to CS-MAS detection, potentially enabling the quantification of fluorine content in novel FOCs without having molecular standards available. This paper also reports the use of reverse-phase high performance liquid chromatography (RP-HPLC) coupled off-line with CS-MAS for the identification of single organofluorines in a mixture of FOCs via fraction collection. The linear range of both FOCs was determined to be from 1 to 500 ng/mL. The limits of detection of those species were just above 1 ng/mL (100 pg) and can therefore compete with targeted analytical methods such as ESI-MS. Finally, as a proof of principle the analysis of a fluoride-containing groundwater sample from Ghana demonstrated that this method can be used in the detection of novel FOCs, with identification achieved through parallel ESI-MS. Coupled HPLC-CS-MAS/ESI-MS is the first analytical methodology capable of selectively detecting and identifying novel FOCs, making possible the quantification of all fluorine containing compounds in one sample. This is the necessary analytical requirement to perform fluoronomics.     

Nanostructured β-phase Ti–31.0Fe–9.0Sn and sub-μm structured Ti–39.3Nb–13.3Zr–10.7Ta alloys for biomedical applications: Microstructure benefits on the mechanical and corrosion performances

Nanostructured Ti–31.0Fe–9.0Sn and sub-micrometer structured Ti–39.3Nb–13.3Zr–10.7Ta (wt.%) β-type alloys, exhibiting different microstructures and dissimilar mechanical properties, have been prepared by copper mold casting. The microstructure, mechanical behavior and corrosion resistance, in simulated body fluid, of both alloys have been investigated and compared to those of commercial Ti–6Al–4V. Nanoindentation experiments reveal that the Ti–31.0Fe–9.0Sn rods exhibit very large hardness (H ≈ 9 GPa) and high Young's modulus. Conversely, the Ti–39.3Nb–13.3Zr–10.7Ta alloy is mechanically softer but it is interesting for biomedical application because of its rather low Young's modulus (E ≈ 71 GPa). Concerning the corrosion performance, Ti–35Nb–7Zr–5Ta shows a corrosion behavior comparable to Ti–Al6–V4, with no potential breakdown up to 0.4 V vs. Ag|AgCl. On the contrary, the Ti–31.0Fe–9.0Sn alloy exhibits a more anodic corrosion potential, but the value is still less negative than for pure elemental Fe and Ti. From all these properties and because of the absence of toxic elements in the compositions, the Ti–39.3Nb–13.3Zr–10.7Ta and Ti–31.0Fe–9.0Sn alloys are attractive for use as metallic biomaterials.     

A neural network approach for the prediction of the refractive index based on experimental data

This article presents a systematic approach for correlating the refractive index of different material kinds and forms with experimentally measured inputs like wavelength, temperature, and concentration. The correlation is accomplished using neural network models, which can deal effectively with the nonlinear nature of the problem without requiring a predefined form of equation, while taking into account all the parameters affecting the refractive index. The proposed methodology employs the powerful radial basis function network architecture and the neural network training procedure is accomplished using an innovative algorithm, which provides results with increased prediction accuracy. The methodology is applied to two cases, involving the estimation of the refractive index of semiconductor material crystals and an ethanol–water mixture and the results show that the refractive index predictions are accurate approximately to the same number of decimal places as the real measurements. Comparisons with other neural network training methods, but also with empirical forms like the Sellmeier equation, highlight the superiority of the proposed approach.     

Ist ein Therapieverzicht gegen den Willen des Patienten ethisch begründbar?

Definition of the problem Decisions to limit life-prolonging treatment (DLT) precede the majority of non-sudden deaths in European countries. While existing studies focus on patient refusal of treatment, no data exists about patient consent to DLT, especially in situations where patients are not prepared to accept limitations of treatment. In a study on patient involvement in DLT we could show that one third of terminally-ill patients wish to extend their lifetime. In these patients treatment limitations are often decided without involving the patient. These data raise the question, whether doctors are allowed to limit treatment in patients who prefer “everything to be done”. Or should they rather follow the patient’s wish for intensive therapy even if they deem it futile. Arguments Neither the concept of futility nor that of patient autonomy or shared decision making are apt to guide decision making in situations where patients ask for treatment that physicians consider as futile. Using a principled approach we arrive at four criteria that should be factored in the decision and communication about limiting life-prolonging treatment: effectiveness of the intervention, the patient’s capability for autonomous decision-making based on his level of information and coping with the disease, burden of the intervention as perceived by the patient and an explicit mention of extensive treatment costs. Conclusion These criteria help to decide whether it is justifiable for the physician to limit care without consent of the patient. They also help to identify cases where continuing life-prolonging treatment on the request of the patient is justifiable even if their physicians find it inappropriate.     

Multi-objective optimisation of batch separation processes

This paper considers for the first time the simultaneous multi-objective optimisation of design and operation of batch distillation as well as of batch hybrid distillation/pervaporation processes. The overall problem is formulated as a multi-objective mixed integer dynamic optimisation (MO-MIDO) problem. The optimisation strategy comprises of different ranking procedures that allow the determination of the Pareto optimal set. A case study for the separation of a homogeneous tangent-pinch (acetone–water) mixture is presented for a dual-criteria optimisation case of minimising capital investment while at the same time minimising the energy consumption rate during the batch. It is found that the proposed distance ranking procedure yields the best Pareto optimal set when compared to other non-dominated sorting procedures. Furthermore, the distance ranking procedure was found to be further improved when used with an elitism operator.     

First–Order Representations of Discrete Linear Multidimensional Systems

The classical localstate–space models for discrete multidimensional linearsystems, as proposed by Roesser or Fornasini and Marchesini,require causality of the resulting transfer matrices. We considera generalization comprising non-causal systems, based on Willems'state-space behaviors. A vector of manifest and a vector of latentvariables are supposed to be linked via a first–order dynamicequation and a static equation. Any system of linear constant–coefficientpartial difference equations gives rise to such an ``output–nulling'(ON) representation. Controllable systems possess driving–variablerepresentations, which are the dual counterpart of ON repsin many aspects. We study these representations with respectto their minimality, observability and controllability, and wederive conditions for their reducibility to the standard input–state–outputsetting.     

Integrating explicit path planning with reactive control of mobile robots using Trulla

This article describes and investigates a method of interleaving explicit path planning with reactive control. The Trulla all-paths planner computes an a priori set of optimal paths. Minor reactions to obstacles and terrain changes serve to switch the robot from the precomputed path to a new precomputed path, eliminating subgoal obsession. Major deviations suggest that the a priori map is significantly wrong; explicit replanning should be triggered to ensure continued progress of the robot. The dot product is used as the intrinsic measure of a major deviation. This methodology is particularly well-suited for computationally bound robots such as planetary rovers and robots operating in indoor environments with a large number of minor unmodeled obstacles.

The article describes the Trulla and dot product algorithms, and reports on experimental data collected from a mobile robot under representative scenarios. The method is compared to continuous and fixed frequency replanning under differing environments and robot velocities. The results show that the deferred replanning with the Trulla/dot product methodology produced actual paths similar to more frequent replanning in distance and time but with up to 100 times less computation. The reduced computation led to a 8.75% increase in distance traveled and 24% increase in travel time. In the presence of faulty sensor data, Trulla outperformed the other methods which radically changed the path back and forth due to spurious sensor readings.     

Skateboarders exploring urban public space: Ollies, obstacles and conflicts

This paper reports on an explorative study about skateboarding practices in Amsterdam. One indoor spot and nine street locations for skateboarding were observed and over thirty skaters were interviewed. The research questions concern the identity of the people involved, the group interactions, and the use of urban space and routes. The majority of the observed skateboarders are male middle-class youngsters. In this respect, the skateboarding scene is not very different from other forms of urban public play where men predominate. At the same time, however, skateboarding can be seen as a way of experimenting with new forms of masculinity. Since hanging about by adolescents is mainly a lower-class phenomenon, the middle-class status of the skateboarding youth is surprising. Notwithstanding their individual skateboarding acts, youngsters involved in skateboarding negotiate their claim on specific spaces in groups. The colonizing of public spaces for skateboarding does not remain free of conflict. Groups of skaters are continuously putting public spaces into and out of use. In a sense, skateboarders can be considered the nomads of the city. Their `traveling in packs' results in a map of skate locations which is constantly changing. To understand the phenomenon of skateboarding, further research is needed, not only in Amsterdam but also in other cities and the suburbs.     

Maternal intrusive support in the academic context: Transactional socialization processes.

Although transactional models of socialization have received support, there has been little investigation of the processes involved. The goal of this research was to move in this direction in the context of the socialization of achievement. Mothers and their elementary school children (N?=?166) took part in an 18-month longitudinal study including a 2-week daily checklist. The results suggested that children's low achievement elicits intrusive support from mothers through 2 mechanisms. Mothers worried over their children's performance, and this was associated with heightened intrusive support. Children's low achievement manifested itself in uncertainty, which was linked to heightened intrusive support. The achievement of children whose mothers frequently used intrusive support improved over time but did not exceed that of children whose mothers infrequently used intrusive support. Day-to-day analyses suggested that although intrusive support promotes success, it also fosters failure for low-achieving children. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Functional Networks: A New Network-Based Methodology

In this article we give a general methodology to build and work with functional networks, a network-based alternative to the neural networks paradigm. In functional networks, neural functions are allowed to be not only multivariate but also truly multiargument and different for all neurons. Thus neural functions instead of weights are learned. In addition, outputs coming from different neurons can be connected, that is, forced to output the same values. The topology and neuron functions of functional networks can be selected based on data, domain knowledge, or a combination of the two. Functional equations play an important role in functional networks, since the preceding types of connections lead to functional equations that impose a substantial reduction in the degrees of freedom of the initial neural functions. Some methods are given to obtain equivalent functional and differential equations, and they are applied to approximating the solutions of differential equations problems. The examples of an associative operator, a cantilever beam, and a mass supported by two springs and a viscous damper are given to illustrate the methods and show their power.