Accumulation of Cu(II) cations in poly(3,4-ethylenedioxythiophene) films doped by hexacyanoferrate anions and its application in Cu-selective electrodes with PVC based membranes

Electrochemical properties of poly(3,4-ethylenedioxythiophene) doped with hexacyanoferrate(II,III) ions (PEDOT(HCF)) were studied in the presence of Cu²⁺ ions. Voltammetric and EDAX studies revealed retention of hexacyanoferrate anions in the polymer film and accumulation of Cu(II) cations, as well as formation of solid copper hexacyanoferrate near the polymer surface.Accumulation of Cu²⁺ ions was found to be advantageous from the point of view of PEDOT(HCF) applications as a solid contact (ion-to-electron transducer) in all-solid-state Cu²⁺-selective electrodes with solvent polymeric polyvinyl chloride (PVC) based membrane, containing Cu²⁺-selective ionophore. Binding of Cu²⁺ ions in the conducting polymer layer results in analyte ions flux into the transducer phase. Thus, pronounced enhancement of selectivity of the all-solid-state Cu²⁺-selective electrode or lower detection limit of the potentiometric response range was achieved, reaching under optimised conditions 10⁻⁷ M CuSO₄.     

Detecting Fixed Patterns in Chordal Graphs in Polynomial Time

The Contractibility problem takes as input two graphs G and H, and the task is to decide whether H can be obtained from G by a sequence of edge contractions. The Induced Minor and Induced Topological Minor problems are similar, but the first allows both edge contractions and vertex deletions, whereas the latter allows only vertex deletions and vertex dissolutions. All three problems are NP-complete, even for certain fixed graphs H. We show that these problems can be solved in polynomial time for every fixed H when the input graph G is chordal. Our results can be considered tight, since these problems are known to be W[1]-hard on chordal graphs when parameterized by the size of H. To solve Contractibility and Induced Minor, we define and use a generalization of the classic Disjoint Paths problem, where we require the vertices of each of the k paths to be chosen from a specified set. We prove that this variant is NP-complete even when k=2, but that it is polynomial-time solvable on chordal graphs for every fixed k. Our algorithm for Induced Topological Minor is based on another generalization of Disjoint Paths called Induced Disjoint Paths, where the vertices from different paths may no longer be adjacent. We show that this problem, which is known to be NP-complete when k=2, can be solved in polynomial time on chordal graphs even when k is part of the input. Our results fit into the general framework of graph containment problems, where the aim is to decide whether a graph can be modified into another graph by a sequence of specified graph operations. Allowing combinations of the four well-known operations edge deletion, edge contraction, vertex deletion, and vertex dissolution results in the following ten containment relations: (induced) minor, (induced) topological minor, (induced) subgraph, (induced) spanning subgraph, dissolution, and contraction. Our results, combined with existing results, settle the complexity of each of the ten corresponding containment problems on chordal graphs.     

Experiences with large-scale operational trials of ALTO-enhanced P2P filesharing in an intra-ISP scenario

Application Layer Traffic Optimization (ALTO) has recently gained attention in the research and standardisation community as a way for a network operator to guide the peer selection process of distributed applications by providing network layer topology information. In particular P2P applications are expected to gain from ALTO, due to the many connections peers form among each other, often without taking network layer topology information into account. In this paper, we present results of an extensive intra-ISP trial with an ALTO-enhanced P2P filesharing software. In summary, our results show that—depending on the concrete setting and on the distribution of upload capacity in the network—ALTO enables an ISP to save operational costs significantly while not degrading application layer performance noticeably. In addition, based on our experience we are able to give advice to operators on how to save costs with ALTO while not sacrificing application layer performance at all.     

Deciding k-Colorability of P 5-Free Graphs in Polynomial Time

The problem of computing the chromatic number of a P ₅-free graph (a graph which contains no path on 5 vertices as an induced subgraph) is known to be NP-hard. However, we show that for every fixed integer k, there exists a polynomial-time algorithm determining whether or not a P ₅-free graph admits a k-coloring, and finding one, if it does.     

Is Evolution Algorithmic?

In Darwin’s Dangerous Idea, Daniel Dennett claims that evolution is algorithmic. On Dennett’s analysis, evolutionary processes are trivially algorithmic because he assumes that all natural processes are algorithmic. I will argue that there are more robust ways to understand algorithmic processes that make the claim that evolution is algorithmic empirical and not conceptual. While laws of nature can be seen as compression algorithms of information about the world, it does not follow logically that they are implemented as algorithms by physical processes. For that to be true, the processes have to be part of computational systems. The basic difference between mere simulation and real computing is having proper causal structure. I will show what kind of requirements this poses for natural evolutionary processes if they are to be computational.     

Application of the OBD method for optimization of neural state variable estimators of the two-mass drive system

This paper presents neural estimators of the mechanical state variables of the electrical drive system with elastic joints. The non-measurable state variables, as the torsional torque and the load machine speed are estimated using multilayer feed-forward neural networks. The main stages of the design methodology of these neural estimators are presented. The optimal brain damage method is implemented for the structure optimization of each neural network. Then signals estimated by neural estimators are tested in the electrical drive control structure with additional feedbacks from the estimated shaft torque and the difference between the motor and the load speeds. The simulation results show good accuracy of both presented neural estimators for the wide range of changes of the reference speed and the load torque. The simulation results are then verified by laboratory experiments.     

Randomized mutual exclusion on a multiple access channel

In this paper we consider the mutual exclusion problem on a multiple access channel. Mutual exclusion is one of the fundamental problems in distributed computing. In the classic version of this problem, n processes execute a concurrent program that occasionally triggers some of them to use shared resources, such as memory, communication channel, device, etc. The goal is to design a distributed algorithm to control entries and exits to/from the shared resource (also called a critical section), in such a way that at any time, there is at most one process accessing it. In our considerations, the shared resource is the shared communication channel itself (multiple access channel), and the main challenge arises because the channel is also the only mean of communication between these processes. We consider both the classic and a slightly weaker version of mutual exclusion, called \(\varepsilon \)-mutual-exclusion, where for each period of a process staying in the critical section the probability that there is some other process in the critical section is at most \(\varepsilon \). We show that there are channel settings, where the classic mutual exclusion is not feasible even for randomized algorithms, while the \(\varepsilon \)-mutual-exclusion is. In more relaxed channel settings, we prove an exponential gap between the makespan complexity of the classic mutual exclusion problem and its weaker \(\varepsilon \)-exclusion version. We also show how to guarantee fairness of mutual exclusion algorithms, i.e., that each process that wants to enter the critical section will eventually succeed.