ISFET based enzyme sensors

This paper reviews the results that have been reported on ISFET based enzyme sensors. The most important improvement that results from the application of ISFETs instead of glass membrane electrodes is in the method of fabrication. Problems with regard to the pH dependence of the response and the dynamic range as well as the influence of the sample buffer capacity have not been solved. As a possible solution we introduce a coulometric system that compensates for the analyte buffer capacity. If the pH in the immobilized enzyme layer is thus controlled, the resulting pH-static enzyme sensor has an output that is independent of the sample pH and buffer capacity and has an expanded linear range

The pH-static enzyme sensor : An ISFET-based enzyme sensor, insensitive to the buffer capacity of the sample

An ISFET-based urea sensor is combined with a noble-metal electrode which provides continuous coulometric titration of the products of the enzymatic reaction. The sensor thus becomes independent of the buffer capacity of the sample; and because the enzyme is operating at a constant pH, the linear response range is expanded

Evaluation of the sensor properties of the pH-static enzyme sensor

The pH-static enzyme sensor consists of a chemical sensor-actuator system covered with a thin enzyme-entrapping membrane. By the electrochemical generation of protons or hydroxyl ions, pH changes induced by the conversion of a substrate by the enzymatic reaction are compensated. The pH inside the membrane remains at a constant level and the control current is linearly related to the substrate concentration and independent of the buffer capacity of the sample. The sensitivity and linearity of the sensor response are evaluated. Depending on the enzyme load of the membrane, the operation of the sensor is either diffusion controlled or determined by the enzyme kinetics

The pH-static enzyme sensor: Design of the pH control system

The pH-static enzyme sensor offers a solution to the buffer dependency of ISFET-based enzyme sensors. A continuous coulometric titration of the reaction products keeps the pH in the enzymatic membrane at a constant level. This paper presents an automatic system to control the compensating current that is a direct measure for the substrate concentration

Comment on "Large Difference in the Elastic Properties of fcc and hcp Hard-Sphere Crystals"

As is well known, hard-sphere crystals of the fcc and hcp type differ very little in their thermodynamic properties. Nonetheless, recent computer simulations by Pronk and Frenkel indicate that the elastic response to mechanical deformation of the two types of crystal should be quite different. By invoking a geometrical argument put forward by R. Martin some time ago, we suggest that this is largely due to the different symmetries of the fcc and hcp crystal structures. Indeed, we find that elastic constants obtained by means of computer simulations for the fcc hard-sphere crystal can be mapped onto the equivalent ones of the hcp crystal to very high accuracy. The same procedure applied to density functional theoretical predictions for the elastic properties of the fcc hard-sphere crystal also produces remarkably accurate predictions for those of the hcp hard-sphere crystal.Comment: 7 pages, 5 figure

Symmetric separable convex resource allocation problems with structured disjoint interval bound constraints

Motivated by the problem of scheduling electric vehicle (EV) charging with a minimum charging threshold in smart distribution grids, we introduce the resource allocation problem (RAP) with a symmetric separable convex objective function and disjoint interval bound constraints. In this RAP, the aim is to allocate an amount of resource over a set of $n$ activities, where each individual allocation is restricted to a disjoint collection of $m$ intervals. This is a generalization of classical RAPs studied in the literature where in contrast each allocation is only restricted by simple lower and upper bounds, i.e., $m=1$. We propose an exact algorithm that, for four special cases of the problem, returns an optimal solution in $O \left(\binom{n+m-2}{m-2} (n \log n + nF) \right)$ time, where the term $nF$ represents the number of flops required for one evaluation of the separable objective function. In particular, the algorithm runs in polynomial time when the number of intervals $m$ is fixed. Moreover, we show how this algorithm can be adapted to also output an optimal solution to the problem with integer variables without increasing its time complexity. Computational experiments demonstrate the practical efficiency of the algorithm for small values of $m$ and in particular for solving EV charging problems.Comment: 20 pages, 4 figure

Self diffusion of particles in complex fluids: temporary cages and permanent barriers

We study the self diffusion of individual particles in dense (non-)uniform complex fluids within dynamic density functional theory and explicitly account for their coupling to the temporally fluctuating background particles. Applying the formalism to rod-like particles in uniaxial nematic and smectic liquid crystals, we find correlated diffusion in different directions: The temporary cage formed by the neighboring particles competes with permanent barriers in periodic inhomogeneous systems such as the lamellar smectic state and delays self diffusion of particles even in uniform systems. We compare our theory with recent experimental data on the self diffusion of fluorescently labelled filamentous virus particles in aqueous dispersions in the smectic phase and find qualitative agreement. This demonstrates the importance of explicitly dealing with the time-dependent self-consistent molecular field that every particle experiences.Comment: submitte

On a reduction for a class of resource allocation problems

In the resource allocation problem (RAP), the goal is to divide a given amount of resource over a set of activities while minimizing the cost of this allocation and possibly satisfying constraints on allocations to subsets of the activities. Most solution approaches for the RAP and its extensions allow each activity to have its own cost function. However, in many applications, often the structure of the objective function is the same for each activity and the difference between the cost functions lies in different parameter choices such as, e.g., the multiplicative factors. In this article, we introduce a new class of objective functions that captures the majority of the objectives occurring in studied applications. These objectives are characterized by a shared structure of the cost function depending on two input parameters. We show that, given the two input parameters, there exists a solution to the RAP that is optimal for any choice of the shared structure. As a consequence, this problem reduces to the quadratic RAP, making available the vast amount of solution approaches and algorithms for the latter problem. We show the impact of our reduction result on several applications and, in particular, we improve the best known worst-case complexity bound of two important problems in vessel routing and processor scheduling from $O(n^2)$ to $O(n \log n)$

A fast algorithm for quadratic resource allocation problems with nested constraints

We study the quadratic resource allocation problem and its variant with lower and upper constraints on nested sums of variables. This problem occurs in many applications, in particular battery scheduling within decentralized energy management (DEM) for smart grids. We present an algorithm for this problem that runs in $O(n \log n)$ time and, in contrast to existing algorithms for this problem, achieves this time complexity using relatively simple and easy-to-implement subroutines and data structures. This makes our algorithm very attractive for real-life adaptation and implementation. Numerical comparisons of our algorithm with a subroutine for battery scheduling within an existing tool for DEM research indicates that our algorithm significantly reduces the overall execution time of the DEM system, especially when the battery is expected to be completely full or empty multiple times in the optimal schedule. Moreover, computational experiments with synthetic data show that our algorithm outperforms the currently most efficient algorithm by more than one order of magnitude. In particular, our algorithm is able to solves all considered instances with up to one million variables in less than 17 seconds on a personal computer

Quadratic nonseparable resource allocation problems with generalized bound constraints

We study a quadratic nonseparable resource allocation problem that arises in the area of decentralized energy management (DEM), where unbalance in electricity networks has to be minimized. In this problem, the given resource is allocated over a set of activities that is divided into subsets, and a cost is assigned to the overall allocated amount of resources to activities within the same subset. We derive two efficient algorithms with $O(n\log n)$ worst-case time complexity to solve this problem. For the special case where all subsets have the same size, one of these algorithms even runs in linear time given the subset size. Both algorithms are inspired by well-studied breakpoint search methods for separable convex resource allocation problems. Numerical evaluations on both real and synthetic data confirm the theoretical efficiency of both algorithms and demonstrate their suitability for integration in DEM systems