Measuring interdiffusion at an interface between two elastomers with tapping-mode and contact-resonance atomic force microscopy imaging

Despite the common use of tapping-mode atomic force microscopy to image composites or polymer blends, very few studies have focused on the measurement of the interdiffusion at an interface between two polymers in contact. In this study, we show how to assess the interphase between two polymers with two methods. First, stable and robust tapping conditions are established, and the problem of the phase contrast is discussed. Second, a contact-resonance method is presented: the tip in contact with the sample is electrostatically excited at its resonance frequency by a self-controlled oscillator. The gain and frequency images allow us to measure the interdiffusion width. Both methods (using high and weak mechanical solicitation) give the same assessment of the interdiffusion width. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Lack of effects of lesions of the dorsal noradrenergic bundle on behavioral vigilance

The effects of 6-hydroxydopamine (6-OHDA)-induced lesions of the dorsal noradrenergic bundle (DNB) were assessed in animals trained in a task designed to measure sustained attention, or vigilance. Infusions of 6-OHDA reduced frontal cortical noradrenaline contents but did not significantly affect striatal and hypothalamic noradrenaline contents. The performance of lesioned animals did not differ significantly from sham-lesioned controls. The performance of both the lesioned and sham-lesioned animals was impaired by the presentation of a visual distractor and by a decrease in the probability for a signal. The results from this study largely coincide with the results from previous studies on the effects of noradrenergic lesions on various aspects of attention. In contrast to the attentional functions assessed in this experiment, the ability to detect and select stimuli that are associated with activation of sympathetic functions is hypothesized to be sensitive to the effects of DNB lesions.     

High-Performance Multilayer Capacitor Dielectrics from Chemically Prepared Powders

Advantages of chemically prepared powders for electronic ceramics have been demonstrated for a number of multilayer capacitor (MLC) dielectrics. A cost-efficient precipitation process was developed to produce undoped or doped crystalline barium titanate powder with a narrow particle size distribution close to 0.5 μm. More complex compositions, e.g., barium-neodymium titanate, were amorphous as precipitated but could be crystallized by calcination below 1000°C. Additional compositional modifications, to adjust electrical properties or to lower sintering temperature, were accomplished by doping the surface of the powder particles using a solution coating process. Exceptional fired densities and electrical performance were obtained.     

Design and implementation of a confidentiality and access control solution for publish/subscribe systems

The publish/subscribe model offers a loosely-coupled communication paradigm where applications interact indirectly and asynchronously. Publishers generate events that are sent to interested applications through a network of brokers. Subscribers express their interest by specifying filters that brokers can use for routing the events. Supporting confidentiality of messages being exchanged is still challenging. First of all, it is desirable that any scheme used for protecting the confidentiality of both the events and filters should not require publishers and subscribers to share secret keys. In fact, such a restriction is against the loose-coupling of the model. Moreover, such a scheme should not restrict the expressiveness of filters and should allow the broker to perform event filtering to route the events to the interested parties. Existing solutions do not fully address these issues. In this paper, we provide a novel scheme that supports (i) confidentiality for events and filters; (ii) allows publishers to express further constraints about who can access their events; (iii) filters that can express very complex constraints on events even if brokers are not able to access any information in clear on both events and filters; (iv) and, finally, it does not require publishers and subscribers to share keys. Furthermore, we show how we applied our scheme to a real-world e-health scenario, developed together with a hospital. We also describe the implementation of our solution in Java and the integration with an existing publish/subscribe system.     

Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks

The success of hydraulic simulation models of water distribution networks is associated with the ability of these models to represent real systems accurately. To achieve this, the calibration phase is essential. Current calibration methods are based on minimizing the error between measured and simulated values of pressure and flow. This minimization is based on a search of parameter values to be calibrated, including pipe roughness, nodal demand, and leakage flow. The resulting hydraulic problem contains several variables. In addition, a limited set of known monitored pressure and flow values creates an indeterminate problem with more variables than equations. Seeking to address the lack of monitored data for the calibration of Water Distribution Networks (WDNs), this paper uses a meta-model based on an Artificial Neural Network (ANN) to estimate pressure on all nodes of a network. The calibration of pipe roughness applies a metaheuristic search method called Particle Swarm Optimization (PSO) to minimize the objective function represented by the difference between simulated and forecasted pressure values. The proposed method is evaluated at steady state and over an extended period for a real District Metering Area (DMA), named Campos do Conde II, and the hypothetical network named C-town, which is used as a benchmark for calibration studies.     

Analytical ray tracing system: Introducing art, a C-library designed for seismic applications

Ray tracing technique is an important tool not only to forward but also for inverse problems in Geophysics, which most of the seismic processing steps depend on. However, implementing ray tracing codes can be very time consuming. This article presents a computer library to trace rays in 2.5D media composed by a stack of layers. The velocity profile inside each layer is such that the eikonal equation can be analytically solved. Therefore, the ray tracing within such profile is made fast and accurate. The great advantage of an analytical ray tracing library is the numerical precision of the quantities computed and the fast execution of the implemented codes. Even though ray tracing programs exist for a long time, for example the seis88 package by ?ervený, most of those programs use a numerical approach to compute the ray. Regardless of the fact that numerical methods can solve more general problems, the analytical ones could be part of a more sophisticated simulation process, where the ray tracing time is completely relevant. We demonstrate the feasibility of our codes using several examples (Miqueles et al., 2013)  [1]. The library can also be used for other applications besides seismic, e.g., optics and tomography.     

Fitting polynomial surfaces to triangular meshes with Voronoi squared distance minimization

This paper introduces Voronoi squared distance minimization (VSDM), an algorithm that fits a surface to an input mesh. VSDM minimizes an objective function that corresponds to a Voronoi-based approximation of the overall squared distance function between the surface and the input mesh (SDM). This objective function is a generalization of the one minimized by centroidal Voronoi tessellation, and can be minimized by a quasi-Newton solver. VSDM naturally adapts the orientation of the mesh elements to best approximate the input, without estimating any differential quantities. Therefore, it can be applied to triangle soups or surfaces with degenerate triangles, topological noise and sharp features. Applications of fitting quad meshes and polynomial surfaces to input triangular meshes are demonstrated.     

Gewinnung von Brennstoff für Kraftwerke aus Klärschlamm

Production of a combustible for coal-fired power stations based on sewage sludge . This article describes various means of achieving more extensive mechanical dewatering of sewage sludges. The heat content of the sludge solids can become available for combustion processes. The sludge filter cakes obtained by the “CarboSed” process can be disposed of with minimum energy consumption by fluidized bed combustion or be used after appropriate work-up as a combustible in coal-fired power stations with full exploitation of their heat content for generation of steam and electric current. Partial substitution of primary energy sources such as coal and fuel oil by sludge filter cake is feasible in all cases. The processes thus make a contribution to the saving of energy resources and the disposal of sludge.     

Learning to rank academic experts in the DBLP dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.