Healing Effect of Controlled Anti‐Electromigration on Conventional and High‐Tc Superconducting Nanowires

The electromigration process has the potential capability to move atoms one by one when properly controlled. It is therefore an appealing tool to tune the cross section of monoatomic compounds with ultimate resolution or, in the case of polyatomic compounds, to change the stoichiometry with the same atomic precision. As demonstrated here, a combination of electromigration and anti‐electromigration can be used to reversibly displace atoms with a high degree of control. This enables a fine adjustment of the superconducting properties of Al weak links, whereas in Nb the diffusion of atoms leads to a more irreversible process. In a superconductor with a complex unit cell (La_2?x Ce_x CuO₄), the electromigration process acts selectively on the oxygen atoms with no apparent modification of the structure. This allows to adjust the doping of this compound and switch from a superconducting to an insulating state in a nearly reversible fashion. In addition, the conditions needed to replace feedback controlled electromigration by a simpler technique of electropulsing are discussed. These findings have a direct practical application as a method to explore the dependence of the characteristic parameters on the exact oxygen content and pave the way for a reversible control of local properties of nanowires.     

Prediction of indications for valve replacement among asymptomatic or minimally symptomatic patients with chronic aortic regurgitation and normal left ventricular performance

BACKGROUND: Optimal criteria for valve replacement are unclear in asymptomatic/minimally symptomatic patients with aortic regurgitation (AR) and normal left ventricular (LV) performance at rest. Moreover, previous studies have not assessed the prognostic capacity of load-adjusted LV performance ("contractility") variables, which may be fundamentally related to clinical state. Therefore, 18 years ago, we set out to test prospectively the hypothesis that objective noninvasive measures of LV size and performance and, specifically, of load-adjusted variables, assessed at rest and during exercise (ex), could predict the development of currently accepted indications for operation for AR. METHODS AND RESULTS: Clinical variables and measures of LV size, performance, and end-systolic wall stress (ESS) were assessed annually in 104 patients by radionuclide cineangiography at rest and maximal ex and by echocardiography at rest; ESS was derived during ex. During an average 7.3-year follow-up among patients who had not been operated on, 39 of 104 patients either died suddenly (n = 4) or developed operable symptoms only (n = 22) or subnormal LV performance with or without symptoms (n = 13) (progression rate=6.2%/y). By multivariate Cox model analysis, change (delta) in LV ejection fraction (EF) from rest to ex, normalized for deltaESS from rest to ex (deltaLVEF-deltaESS index), was the strongest predictor of progression to any end point or to sudden cardiac death alone. Unadjusted deltaLVEF was almost as efficient. Symptom status modified prediction on the basis of the deltaLVEF-deltaESS index. The population tercile at highest risk by deltaLVEF-deltaESS progressed to end points at a rate of 13.3%/y, and the lowest-risk tercile progressed at 1.8%/y. CONCLUSIONS: Currently accepted symptom and LV performance indications for valve replacement, as well as sudden cardiac death, can be predicted in asymptomatic/minimally symptomatic patients with AR by load-adjusted deltaLVEF-deltaESS index, which includes data obtained during exercise.     

Digital image processing-an object-oriented approach

This paper presents a class library dedicated to digital image processing which provides resources for essential digital image processing operations. Besides its practical value, the class library is used to teach both object-oriented software engineering methodology and digital image processing. The resulting module can be accessed from independent specialized applications through its public interface while its implementation details are perfectly encapsulated. First of all it is used as the inner part of an integrated environment designed for students and researchers in the field of digital image processing. This software component was built aiming for both portability and extendibility. It contains attributes and methods that allow for a wide range of digital image processing algorithms: point and geometric operations; filter, edge detection, segmentation and texture operations; and fast Fourier transforms, discrete cosine transforms, and wavelet and Gabor transformations. All these can be used for image enhancement, restoration, compression, analysis, and synthesis     

Logic programming for combinatorial problems

Combinatorial problems appear in many areas in science, engineering, biomedicine, business, and operations research. This article presents a new intelligent computing approach for solving combinatorial problems, involving permutations and combinations, by incorporating logic programming. An overview of applied combinatorial problems in various domains is given. Such computationally hard and popular combinatorial problems as the traveling salesman problem are discussed to illustrate the usefulness of the logic programming approach. Detailed discussions of implementation of combinatorial problems with time complexity analyses are presented in Prolog, the standard language of logic programming. These programs can be easily integrated into other systems to implement logic programming in combinatorics.     

Coping with information overload in email communication: Evaluation of a training intervention

The present paper introduces three facets of information overload in email communication: A large amount of incoming information, inefficient workflow, and deficient communication quality. In order to cope with these facets of information overload, a training intervention was developed and evaluated. Data were collected from 90 employees on several evaluation levels within a longitudinal evaluation design (one pretest double posttest design). The results reveal that the training contributed to an increase in knowledge and media competencies. We also found evidence for a transfer of training contents to the workplace. Finally, strain diminished on several dimensions. In particular, problems with media usage and work impairment decline significantly, an effect that was stronger for those participants who face a large amount of email at their workplaces.     

Unsupervised classification of dynamic obstacles in urban environments

This paper presents a solution to the problem of unsupervised classification of dynamic obstacles in urban environments. A track‐based model is introduced for the integration of two‐dimensional laser and vision information that provides a robust spatiotemporal synthesis of the sensed moving obstacles and forms the basis for suitable algorithms to perform unsupervised classification by clustering. This work presents various contributions in order to achieve accurate and efficient performance, initially using laser tracks for classification and then incorporating visual tracks to the model. A procedure is proposed for accurate unsupervised classification of dynamic obstacles using a laser stamp representation of the tracks. Laser data are then integrated with visual information through a single‐instance visual stamp representation, which is finally extended using a multiple‐instance framework to robustly deal with challenges associated with perception in real‐world scenarios. The proposed algorithms are extensively validated with a simulated environment. Experiments with a research vehicle in an urban environment demonstrate the performance of the approach with real data. The experimental results reach an accuracy of more than 92% for obstacle classification, finding the clusters that correspond to the main obstacle classes in the data. © 2010 Wiley Periodicals, Inc.     

Pseudo Bond Graph modelling and on-line estimation of unknown kinetics for a wastewater biodegradation process

This paper deals with the problem of modelling and on-line estimation of kinetics for a biomethanation process. This bioprocess is in fact a wastewater biodegradation process with production of methane gas, which takes place inside a Continuous Stirred Tank Bioreactor. The reaction scheme and the analysis of biochemical phenomena inside the bioreactor are used in order to obtain a nonlinear dynamic model of the bioprocess, by means of the pseudo Bond Graph method. Two nonlinear estimation strategies are developed for the identification of unknown kinetics of the bioprocess. First, an estimator is developed by using a state observer based technique. Second, an observer based on high-gain approach is designed and implemented. Several numerical simulations are performed in order to analyse and compare the behaviour and the performance of the proposed estimators.     

Sparse polynomial division using a heap

In 1974, Johnson showed how to multiply and divide sparse polynomials using a binary heap. This paper introduces a new algorithm that uses a heap to divide with the same complexity as multiplication. It is a fraction-free method that also reduces the number of integer operations for divisions of polynomials with integer coefficients over the rationals. Heap-based algorithms use very little memory and do not generate garbage. They can run in the CPU cache and achieve high performance. We compare our C implementation of sparse polynomial multiplication and division with integer coefficients to the routines of the Magma, Maple, Pari, Singular and Trip computer algebra systems.