Voltage‐Induced Coercivity Reduction in Nanoporous Alloy Films: A Boost toward Energy‐Efficient Magnetic Actuation

Magnetic data storage and magnetically actuated devices are conventionally controlled by magnetic fields generated using electric currents. This involves significant power dissipation by Joule heating effect. To optimize energy efficiency, manipulation of magnetic information with lower magnetic fields (i.e., lower electric currents) is desirable. This can be accomplished by reducing the coercivity of the actuated material. Here, a drastic reduction of coercivity is observed at room temperature in thick (≈600 nm), nanoporous, electrodeposited Cu–Ni films by simply subjecting them to the action of an electric field. The effect is due to voltage‐induced changes in the magnetic anisotropy. The large surface‐area‐to‐volume ratio and the ultranarrow pore walls of the system allow the whole film, and not only the topmost surface, to effectively contribute to the observed magnetoelectric effect. This waives the stringent “ultrathin‐film requirement” from previous studies, where small voltage‐driven coercivity variations were reported. This observation expands the already wide range of applications of nanoporous materials (hitherto in areas like energy storage or catalysis) and it opens new paradigms in the fields of spintronics, computation, and magnetic actuation in general.     

Highly Anisotropic Suspended Planar‐Array Chips with Multidimensional Sub‐Micrometric Biomolecular Patterns

Suspended planar‐array (SPA) chips embody millions of individual miniaturized arrays to work in extremely small volumes. Here, the basis of a robust methodology for the fabrication of SPA silicon chips with on‐demand physical and chemical anisotropies is demonstrated. Specifically, physical traits are defined during the fabrication process with special focus on the aspect ratio, branching, faceting, and size gradient of the final chips. Additionally, the chemical attributes augment the functionality of the chips with the inclusion of complete coverage or patterns of selected biomolecules on the surface of the chips with contact printing techniques, offering an extremely high versatility, not only with the choice of the pattern shape and distribution but also in the choice of biomolecular inks to pattern. This approach increases the miniaturization of printed arrays in 3D structures by two orders of magnitude compared to those previously demonstrated. Finally, functional micrometric and sub‐micrometric patterned features are demonstrated with an antibody binding assay with the recognition of the printed spots with labeled antibodies from solution. The selective addition of physical and chemical attributes on the suspended chips represents the basis for future biomedical assays performed within extremely small volumes.     

Modified ferrous oxidation‐xylenol orange method to determine lipid hydroperoxides in fried snacks

A modified ferrous oxidation‐xylenol orange (FOX) method was adapted to measure lipid hydroperoxides (LHP) in lipid extracts from snack foods fried in vegetable oils. First, a methanol‐based FOX reaction medium was assayed, but this became turbid upon addition of the lipid extracts dissolved in ethanol. To avoid the precipitation of lipids, the polarity of the reaction medium was reduced by lowering its water content and by replacing the methanol as the basis of the medium for less polar solvents. Some of the solvents used instead of methanol yielded a lower FOX reaction response. Of the reaction media assayed, the one based on dichloromethane/ethanol (3:2, vol/vol) was not turbid at high lipid extract concentrations (assayed at up to 25 mg of lipid extract/mL reaction medium) and provided the same response level as the methanol‐based medium. Thus, this FOX method shows high sensitivity and is particularly useful for lipid extracts with low LHP content. This method was also successfully applied to edible oils. Solvents such as 2‐propanol, ethyl acetate and butanol were discarded, because they easily produce hydroperoxides, which interfere in the FOX reaction. Xylenol orange preparations from a number of suppliers were tested, and some differences affecting the sensitivity of the reaction were observed.     

Microstructure and crystallization of melt‐mixed poly(ethylene terephthalate)/poly(ethylene isophthalate) blends

Physical blends of poly(ethylene terephthalate) (PET) and poly(ethylene isophthalate) (PEI), abbreviated PET/PEI (80/20) blends, and of PET and a random poly(ethylene terephthalate‐co‐isophthalate) copolymer containing 40% ethylene isophthalate (PET₆₀I₄₀), abbreviated PET/PET₆₀I₄₀ (50/50) blends, were melt‐mixed at 270°C for different reactive blending times to give a series of copolymers containing 20 mol % of ethylene isophthalic units with different degrees of randomness. ¹³C‐NMR spectroscopy precisely determined the microstructure of the blends. The thermal and mechanical properties of the blends were evaluated by DSC and tensile assays, and the obtained results were compared with those obtained for PET and a statistically random PETI copolymer with the same composition. The microstructure of the blends gradually changed from a physical blend into a block copolymer, and finally into a random copolymer with the advance of transreaction time. The melting temperature and enthalpy of the blends decreased with the progress of melt‐mixing. Isothermal crystallization studies carried out on molten samples revealed the same trend for the crystallization rate. The effect of reaction time on crystallizability was more pronounced in the case of the PET/PET₆₀I₄₀ (50/50) blends. The Young's modulus of the melt‐mixed blends was comparable to that of PET, whereas the maximum tensile stress decreased with respect to that of PET. All blend samples showed a noticeable brittleness. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 3076–3086, 2003     

The composition,active components and bacteriostatic activity of propolis in dietetics

The composition and bacteriostatic activities of fifteen propolis samples from various botanic and geographic origins were determined. Twenty-six phenolic components were identified by high-performance liquid chromatography with array photodiode detector. Acacetin and apigenin were most abundant. Pinocembrin, quercetin, rutin and vanillin were present in lesser quantities. Variance analysis shows significant differences (P≤0.05) in the contents of phenols, flavonoids and active components. The minimum inhibitory concentration of propolis is about 53 times higher than that reported for tetracycline againstBacillus subtilis andStaphylococcus aureus, and about 400 times higher againstEscherichia coli.     

Model reference adaptive control of discrete‐time piecewise linear systems

This article presents a switched model reference adaptive controller for discrete‐time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed‐loop error system is obtained, recasting its dynamics as a feedback system and showing the feedforward and the feedback paths are both passive. The challenge is that both paths can be piecewise linear. Numerical results show excellent performance of the proposed controller even in the face of sudden variations of the plant parameters. Copyright © 2012 John Wiley & Sons, Ltd.     

A cross-layer communication module for the Internet of Things

The Internet of Things (IoT) is a novel networking paradigm which allows the communication among all sorts of physical objects over the Internet. The IoT defines a world-wide cyber-physical system with a plethora of applications in the fields of domotics, e-health, goods monitoring and logistics, among others. The use of cross-layer communication schemes to provide adaptive solutions for the IoT is motivated by the high heterogeneity in the hardware capabilities and the communication requirements among things. In this paper, a novel cross-layer module for the IoT is proposed to accurately capture both the high heterogeneity of the IoT and the impact of the Internet as part of the network architecture. The fundamental part of the module is a mathematical framework, which is developed to obtain the optimal routing paths and the communication parameters among things, by exploiting the interrelations among different layer functionalities in the IoT. Moreover, a cross-layer communication protocol is presented to implement this optimization framework in practical scenarios. The results show that the proposed solution can achieve a global communication optimum and outperforms existing layered solutions. The novel cross-layer module is a primary step towards providing efficient and reliable end-to-end communication in the IoT.     

Stable inversion of Abel equations: Application to tracking control in DC–DC nonminimum phase boost converters

Stable inversion plays a key role in the solution of the exact tracking control problem in nonminimum phase systems. However, the general methods developed so far for the computation of stable inverses require backwards time numeric integration of the internal dynamics equation, which yields high sensitivity to external disturbances and/or structured uncertainties. This article introduces an iterative technique that provides periodic, closed-form analytic expressions uniformly convergent to the exact periodic solution of a certain class of Abel ODE written in the normal form. The method is then applied to the output voltage tracking of periodic references in DC–DC boost power converters through a state feedback indirect control scheme. The procedure lies on a number of assumptions for which sufficient conditions involving system parameters and reference candidates are derived. It also allows one to attenuate the effect of bounded, piecewise constant load disturbances using dynamic compensation. Simulation results validate the proposed algorithm.     

Concept-based learning of human behavior for customer relationship management

In this paper, we apply concept learning techniques to solve a number of problems in the customer relationship management (CRM) domain. We present a concept learning technique to tackle common scenarios of interaction between conflicting human agents (such as customers and customer support representatives). Scenarios are represented by directed graphs with labeled vertices (for communicative actions) and arcs (for temporal and causal relationships between these actions and their parameters). The classification of a scenario is performed by comparing a partial matching of its graph with graphs of positive and negative examples. We illustrate machine learning of graph structures using the Nearest Neighbor approach and then proceed to JSM-based concept learning, which minimizes the number of false negatives and takes advantage of a more accurate way of matching sequences of communicative actions. Scenario representation and comparative analysis techniques developed herein are applied to the classification of textual customer complaints as a CRM component. In order to estimate complaint validity, we take advantage of the observation [19] that analyzing the structure of communicative actions without context information is frequently sufficient to judge how humans explain their behavior, in a plausible way or not. This paper demonstrates the superiority of concept learning in tackling human attitudes. Therefore, because human attitudes are domain-independent, the proposed concept learning approach is a good compliment to a wide range of CRM technologies where a formal treatment of inter-human interactions is required.