Selective determination of urea using urease immobilized on ZnO nanowires

Well-aligned zinc oxide (ZnO) nanowire arrays were fabricated on gold-coated plastic substrates using a low-temperature aqueous chemical growth (ACG) method. The ZnO nanowire arrays with 50–130 nm diameters and ∼1 μm in lengths were used in an enzyme-based urea sensor through immobilization of the enzyme urease that was found to be sensitive to urea concentrations from 0.1 mM to 100 mM. Two linear sensitivity regions were observed when the electrochemical responses (EMF) of the sensors were plotted vs. the logarithmic concentration range of urea from 0.1 mM to 100 mM. The proposed sensor showed a sensitivity of 52.8 mV/decade for 0.1–40 mM urea and a fast response time less than 4 s was achieved with good selectivity, reproducibility and negligible response to common interferents such as ascorbic acid and uric acid, glucose, K⁺ and Na⁺ ions.     

Modelling of interstitials in the bcc phase

There are several widespread thermodynamic datasets which produce a spurious bcc interstitial solution at high temperature and high X content (X is an interstitally dissolved element). The reason for this is the standard model for bcc interstitial solutions (M(V a,X)₃), which requires careful selection of optimising parameters to minimise spurious appearances of the bcc phase. In this work the model M(V a,X)₁ is suggested as an alternative. This model is much easier to handle and its parameters can be directly compared with those of the fcc phase. The two models are compared for the Fe–C and Nb–N systems. In the Fe–C system almost identical results are achieved. In Nb–N there are some differences for high N content, but there is no experimental data to clearly support any model.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Outflow Boundary Conditions for the Fourier Transformed One-Dimensional Vlasov–Poisson System

In order to facilitate numerical simulations of plasma phenomena where kinetic processes are important, we have studied the technique of Fourier transforming the Vlasov equation analytically in the velocity space, and solving the resulting equation numerically. Special attention has been paid to the boundary conditions of the Fourier transformed system. By using outgoing wave boundary conditions in the Fourier transformed space, small-scale information in velocity space is carried outside the computational domain and is lost. Thereby the so-called recurrence phenomenon is reduced. This method is an alternative to using numerical dissipation or smoothing operators in velocity space. Different high-order methods are used for computing derivatives as well as for the time-stepping, leading to an over-all fourth-order method.     

Competitive exploration of rectilinear polygons

Exploring a polygon with robots when the robots do not have knowledge of the surroundings can be viewed as an online problem. Typical for online problems is that decisions must be made based on past events without complete information about the future. In our case the robots do not have complete information about the environment. Competitive analysis can be used to measure the performance of methods solving online problems. The competitive ratio of such a method is the ratio between the method's performance and the performance of the best method having full knowledge of the future. We prove constant competitive strategies and lower bounds for exploring a simple rectilinear polygon in the _L1$L_1$ metric.     

Thermal conductivity and heat capacity of solid AgCl under pressure

Using the transient hot-wire method, measurements were made for solid AgCl of both the thermal conductivity, , and the heat capacity per unit volume, c _p, where is the mass density. Measurements were made in the temperature range 100 to 400 K, and at pressures up to 2 GPa. c _p(P, T) could be adequately described if the acoustic modes were represented by a Debye model and the optic modes by an Einstein model. Analysis of (T) showed that only the acoustic modes needed to be taken into account up to 300 K, but that the optic modes were increasingly effective in carrying heat at higher temperatures. (P) was adequately described by the Lawson formula, but not by the Leibfried-Schlömann formula, to which it is formally equivalent. Agreement with experiment could be achieved by two different modifications of the Leibfried-Schlömann formula, although neither has a firm theoretical basis.     

New method for selectivity enhancement of SiC field effect gas sensors for quantification of NO x

A silicon carbide based enhancement type metal insulator field effect transistor with porous gate metallization has been investigated as a total NO _x sensor operated in a temperature cycling mode. This operating mode is quite new for gas sensors based on the field effect but promising results have been reported earlier. Based on static investigations we have developed a suitable T-cycle optimized for NO _x detection and quantification in a mixture of typical exhaust gases (CO, C₂H₄, and NH₃). Significant features describing the shape of the sensor response have been extracted and evaluated with multivariate statistics (e.g. linear discriminant analysis) allowing quantification of NO _x . Additional cleaning-cycles every 30?min improve the stability of the sensor further. With this kind of advanced signal processing the influence of sensor drift and cross sensitivity to ambient gases can be reduced effectively. Measurements have proven that different concentrations of NO _x can be detected even in a changing mixture of other typical exhaust gases under dry and humid conditions. In addition to that, unknown concentrations of NO _x can be detected based on a small set of training data. It can be concluded that the performance of GasFETs for NO _x determination can be enhanced considerably with temperature cycling and appropriate signal processing.     

Determination of Inclusion Characteristics in the Asea‐SKF Process using the Modified Spark‐Induced OES Technique as a Complement in Studying the Influence of Top Slag Composition

The spark‐induced modified optical emission spectroscopy (OES) technique developed by Ovako Steel makes it possible to rapidly determine inclusion characteristics in steel samples. In earlier investigations using the modified spark‐induced OES technique for steel samples taken from billets, predicted oxygen contents agreed well with results from conventional melt extraction analyses. In this investigation, samples taken during ladle treatment in an ASEA‐SKF ladle furnace were analysed using the modified OES technique. When comparing the results with inclusion characteristics determined by conventional analysis, similar trends were found. Plant trials were also carried out where three different top slag compositions were used. The purpose was to evaluate if the modified OES technique can be used to study the effect of changes in the refining operation on inclusion characteristics. Results indicated that the modified OES technique could be used to determine the effect of a changed slag composition on the inclusion characteristics in the steel. Since the modified OES method provides rapid feedback of inclusion characteristics, it has the potential of being used for faster optimisation of ladle refining operations.     

Key principles for user-centred systems design

The concept of user-centred systems design (UCSD) has no agreed upon definition. Consequently, there is a great variety in the ways it is applied, which may lead to poor quality and poor usability in the resulting systems, as well as misconceptions about the effectiveness of UCSD. The purpose of this paper is to propose a definition of UCSD. We have identified 12 key principles for the adoption of a user-centred development process, principles that are based on existing theory, as well as research in and experiences from a large number of software development projects. The initial set of principles were applied and evaluated in a case study and modified accordingly. These principles can be used to communicate the nature of UCSD, evaluate a development process or develop systems development processes that support a user-centred approach. We also suggest activity lists and some tools for applying UCSD.     

Some experiences in the use of ADINA in the Swedish Nuclear Industry

This paper presents a number of engineering analysis problems solved from 1990 to 1996 where ADINA was used in the analysis. The problems are in the following areas: natural frequencies, dynamic loading, fatigue, fracture mechanics and natural convection-driven fluid flow. For most of the problems, a comparison between calculations and measurements is also presented. Our experience is that good numerical results can be achieved for static linear problems even when the geometry is complex, but in dynamic analysis it can be difficult to establish models that accurately contain all frequencies, and, of course, in non-linear analysis, the representation of the non-linear material behaviour provides a limit to the modelling accuracy.