High Figure of Merit (FOM) of Bragg Modes in Au‐Coated Nanodisk Arrays for Plasmonic Sensing

Gold‐coated nanodisk arrays of nearly micron periodicity are reported that have high figure of merit (FOM) and sensitivity necessary for plasmonic refractometric sensing, with the added benefit of suitability for surface‐enhanced Raman scattering (SERS), large‐scale microfabrication using standard photolithographic techniques and a simple instrumental setup. Gold nanodisk arrays are covered with a gold layer to excite the Bragg modes (BM), which are the propagative surface plasmons localized by the diffraction from the disk array. This generates surface‐guided modes, localized as standing waves, leading to highly confined fields confirmed by a mapping of the SERS intensity and numerical simulations with 3D finite element method. The optimal gold‐coated nanodisk arrays are applied for refractometric sensing in transmission spectroscopy with better performance than nanohole arrays and they are integrated to a 96‐well plate reader for detection of IgY proteins in the nanometer range in PBS. The potential for sensing in biofluids is assessed with IgG detection in 1:1 diluted urine. The structure exhibits a high FOM of up to 46, exceeding the FOM of structures supporting surface plasmon polaritons and comparable to more complex nanostructures, demonstrating that subwavelength features are not necessary for high‐performance plasmonic sensing.     

A monotone nonlinear finite volume method for approximating diffusion operators on general meshes

The basic principles of the discrete duality and nonlinear monotone finite volume methods are combined in order to obtain a new monotone nonlinear finite volume method for the approximation of diffusion operators on general meshes. Numerical results highlight both the second‐order accuracy of this method on general meshes and its capability to deal with challenging anisotropic diffusion problems on various computational domains. Copyright © 2016 John Wiley & Sons, Ltd.     

An Overview and Future Perspectives of Aluminum Batteries

A critical overview of the latest developments in the aluminum battery technologies is reported. The substitution of lithium with alternative metal anodes characterized by lower cost and higher abundance is nowadays one of the most widely explored paths to reduce the cost of electrochemical storage systems and enable long‐term sustainability. Aluminum based secondary batteries could be a viable alternative to the present Li‐ion technology because of their high volumetric capacity (8040 mAh cm^?3 for Al vs 2046 mAh cm^?3 for Li). Additionally, the low cost aluminum makes these batteries appealing for large‐scale electrical energy storage. Here, we describe the evolution of the various aluminum systems, starting from those based on aqueous electrolytes to, in more details, those based on non‐aqueous electrolytes. Particular attention has been dedicated to the latest development of electrolytic media characterized by low reactivity towards other cell components. The attention is then focused on electrode materials enabling the reversible aluminum intercalation‐deintercalation process. Finally, we touch on the topic of high‐capacity aluminum‐sulfur batteries, attempting to forecast their chances to reach the status of practical energy storage systems.     

Threshold Fluence Measurement for Laser Liftoff of InP Thin Films by Selective Absorption

We explore conditions for achieving laser liftoff in epitaxially grown heterojunctions, in which single crystal thin films can be separated from their growth substrates using a selectively absorbing buried intermediate layer. Because this highly non‐linear process is subject to a variety of process instabilities, it is essential to accurately characterize the parameters resulting in liftoff. Here, we present an InP/InGaAs/InP heterojunction as a model system for such characterization. We show separation of InP thin films from single crystal InP growth substrates, wherein a ≈10 ns, Nd:YAG laser pulse selectively heats a coherently strained, buried InGaAs layer. We develop a technique to measure liftoff threshold fluences within an inhomogeneous laser spatial profile, and apply this technique to determine threshold fluences of the order 0.5 J cm^?2 for our specimens. We find that the fluence at the InGaAs layer is limited by non‐linear absorption and InP surface damage at high powers, and measure the energy transmission in an InP substrate from 0 to 8 J cm^?2. Characterization of the ejected thin films shows crack‐free, single crystal InP. Finally, we present evidence that the hot InGaAs initiates a liquid phase front that travels into the InP substrate during liftoff.

     

Thin and thick YBCO films grown by MOCVD processes. Study of the angular magnetic field dependence of current transport properties

Thin and thick YBCO Films have been grown by Aerosol Assisted as well as by thermal MOCVD. The Aerosol Assisted MOCVD technique allows the growth of YBCO films from a single liquid source at deposition rates of up to 10m/h.Transport measurements (I-V) on etched microbridges using a single pulse technique have been performed. The angular magnetic field dependence J_c() of the critical current density from T_c down to 50 K has been measured. Transport properties are reported and discussed with respect to the microstructural features as determined by X-ray diffraction and electron microscopy.     

Removing web spam links from search engine results

Web spam denotes the manipulation of web pages with the sole intent to raise their position in search engine rankings. Since a better position in the rankings directly and positively affects the number of visits to a site, attackers use different techniques to boost their pages to higher ranks. In the best case, web spam pages are a nuisance that provide undeserved advertisement revenues to the page owners. In the worst case, these pages pose a threat to Internet users by hosting malicious content and launching drive-by attacks against unsuspecting victims. When successful, these drive-by attacks then install malware on the victims’ machines. In this paper, we introduce an approach to detect web spam pages in the list of results that are returned by a search engine. In a first step, we determine the importance of different page features to the ranking in search engine results. Based on this information, we develop a classification technique that uses important features to successfully distinguish spam sites from legitimate entries. By removing spam sites from the results, more slots are available to links that point to pages with useful content. Additionally, and more importantly, the threat posed by malicious web sites can be mitigated, reducing the risk for users to get infected by malicious code that spreads via drive-by attacks.     

Koordination in Service Value Networks

The fundamental paradigm shift from traditional value chains to agile service value networks implies new economic and organizational challenges. As coordination mechanisms, auctions have proven to perform quite well in situations where intangible and heterogeneous goods are traded. Nevertheless, traditional approaches in the area of multidimensional combinatorial auctions are not quite suitable to enable the trade of composite services. A flawless service execution and therefore the requester’s valuation highly depends on the accurate sequence of the functional parts of the composition, meaning that in contrary to service bundles, composite services only generate value through a valid order of their components. The authors present an abstract model as a formalization of service value networks. The model comprehends a graph-based mechanism implementation to allocate multidimensional service offers within the network, to impose penalties for non-performance and to determine prices for complex services. The mechanism and the bidding language support various types of QoS attributes and their (semantic) aggregation. It is analytically shown that this variant is incentive compatible with respect to all dimensions of the service offer (quality and price). Based on these results, the authors numerically analyze strategic behavior of participating service providers regarding possible collusion strategies.     

Localization of shapes using statistical models and stochastic optimization

In this paper, we present a new model for deformations of shapes. A pseudo-likelihood is based on the statistical distribution of the gradient vector field of the gray level. The prior distribution is based on the Probabilistic Principal Component Analysis (PPCA). We also propose a new model based on mixtures of PPCA that is useful in the case of greater variability in the shape. A criterion of global or local object specificity based on a preliminary color segmentation of the image, is included into the model. The localization of a shape in an image is then viewed as minimizing the corresponding Gibbs field. We use the Exploration/Selection (E/S) stochastic algorithm in order to find the optimal deformation. This yields a new unsupervised statistical method for localization of shapes. In order to estimate the statistical parameters for the gradient vector field of the gray level, we use an Iterative Conditional Estimation (ICE) procedure. The color segmentation of the image can be computed with an Exploration/Selection/Estimation (ESE) procedure.     

Real-time scheduling for energy harvesting sensor nodes

Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First scheduling.