Nanocomposite Ag–LSM solid oxide fuel cell electrodes

Advances in infiltration technology have enabled the creation of innovative electrode architectures that are key to highly effective SOFC anodes and cathodes. In this work, an Ag-infiltrated electrode has been created using a pre-sintered porous scandia-stabilized zirconia (SSZ) electrode backbone. The well-sintered SSZ provides a highly connected ion-conducting pathway throughout the electrode, while the nanometer thickness of the Ag particle layer minimizes the oxygen transport resistance that otherwise limits reaction rates in typical Ag composite electrodes. The new Ag composite electrode had minimal activation polarization by 750 °C.     

Method matters: Systematic effects of testing procedure on visual working memory sensitivity.

Visual working memory (WM) is traditionally considered a robust form of visual representation that survives changes in object motion, observer's position, and other visual transients. This article presents data that are inconsistent with the traditional view. We show that memory sensitivity is dramatically influenced by small variations in the testing procedure, supporting the idea that representations in visual WM are susceptible to interference from testing. In the study, participants were shown an array of colors to remember. After a short retention interval, memory for one of the items was tested with either a same–different task or a 2-alternative-forced-choice (2AFC) task. Memory sensitivity was much lower in the 2AFC task than in the same–different task. This difference was found regardless of encoding similarity or of whether visual WM required a fine or coarse memory resolution. The 2AFC disadvantage was reduced when participants were informed shortly before testing which item would be probed. The 2AFC disadvantage diminished in perceptual tasks and was not found in tasks probing visual long-term memory. These results support memory models that acknowledge the labile nature of visual WM and have implications for the format of visual WM and its assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Basing cryptographic protocols on tamper-evident seals

In this article, we attempt to formally study two very intuitive physical models: sealed envelopes and locked boxes, often used as illustrations for common cryptographic operations. We relax the security properties usually required from locked boxes [such as in bit-commitment (BC) protocols] and require only that a broken lock or torn envelope be identifiable to the original sender. Unlike the completely impregnable locked box, this functionality may be achievable in real life, where containers having this property are called “tamper-evident seals”. Another physical object with this property is the “scratch-off card”, often used in lottery tickets. We consider three variations of tamper-evident seals, and show that under some conditions they can be used to implement oblivious transfer, BC and coin flipping (CF). We also show a separation between the three models. One of our results is a strongly fair CF protocol with bias bounded by O(1/r) (where r is the number of rounds); this was a stepping stone towards achieving such a protocol in the standard model (in subsequent work).     

“Designer” scaffolds for tissue engineering and regeneration

Tissue engineering entails the in vitro or in vivo generation of replacement tissues from cells with the aid of supporting scaffolds and stimulating biomolecules, in order to provide biological substitutes for restoration and maintenance of human tissue functions. In this review, we summarize the main classes of degradable polymeric scaffolds, natural and synthetic ones, and the evolution made in this field from adaptation of materials in clinical use to the fabrication of “designer” scaffolds.     

Advanced Technologies for Engineering Tissue Mimetics

Micro- and nanotechnologies have become central to fields ranging from tissue and cellular biophysics to regenerative medicine toward the creation of more complex and progressive tissues. In this article, we overview some of the new technological concepts in this field for recapitulating the native extracellular matrix, designing dynamic microenvironments, and the incorporation of small-scale devices for actuating and monitoring engineered tissue performances.     

Enantiomeric Control of Intrinsically Chiral Nanocrystals

The chiral aspect of inorganic crystals that crystallize in chiral space groups has been largely ignored until recently, partly due to difficulties in characterizing the chiroptical properties of bulk crystals, and also due to the difficulty in separating (sub)micrometer-scale chiral crystal enantiomers. In recent years, the colloidal synthesis of intrinsically chiral nanocrystals (NCs) of several chiral inorganic compounds with significant enantiomeric excess has been demonstrated. This is achieved through the use of chiral molecular ligands, which bind to the atomic/ionic components of the crystals, preferentially forming one crystal enantiomorph. Here, recent progress on several aspects of these NCs is described, including the connection between ligand structure and its ability to direct NC handedness, chiral amplification in the synthesis leading to enantiopure NC samples, spontaneous symmetry breaking, the formation of NCs with chiral shapes, the connection between lattice and shape chirality and mixed contributions of atomic-scale and shape chirality to the chiroptical properties.     

Anytime similarity measures for faster alignment

Image alignment refers to finding the best transformation from a fixed reference image to a new image of a scene. This process is often optimizing a similarity measure between images, computed based on the image data. However, in time-critical applications state-of-the-art methods for computing similarity are too slow. Instead of using all the image data to compute similarity, one could use only a subset of pixels to improve the speed, but often this comes at the cost of reduced accuracy. These kinds of tradeoffs between the amount of computation and the accuracy of the result have been addressed in the field of real-time artificial intelligence as deliberation control problems. We propose that the optimization of a similarity measure is a natural application domain for deliberation control using the anytime algorithm framework. In this paper, we present anytime versions for the computation of two common image similarity measures: mean squared difference and mutual information. Off-line, we learn a performance profile specific to each measure, which is then used on-line to select the appropriate amount of pixels to process at each optimization step. When tested against existing techniques, our method achieves comparable quality and robustness with significantly less computation.