Toward Self-Assembled Ferroelectric Random Access Memories: Hard-Wired Switching Capacitor Arrays with Almost Tb/in.2 Densities

We report on the successful fabrication of arrays of switchable nanocapacitors made by harnessing the self-assembly of materials. The structures are composed of arrays of 20-40 nm diameter Pt nanowires, spaced 50-100 nm apart, electrodeposited through nanoporous alumina onto a thin film lower electrode on a silicon wafer. A thin film ferroelectric (both barium titanate (BTO) and lead zirconium titanate (PZT)) has been deposited on top of the nanowire array, followed by the deposition of thin film upper electrodes. The PZT nanocapacitors exhibit hysteresis loops with substantial remnant polarizations, while although the switching performance was inferior, the low-field characteristics of the BTO nanocapacitors show dielectric behavior comparable to conventional thin film heterostructures. While registration is not sufficient for commercial RAM production, this is nevertheless an embryonic form of the highest density hard-wired FRAM capacitor array reported to date and compares favorably with atomic force microscopy read-write densities.

Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random-Effects Models

This paper reports the findings from a discrete-choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness-to-pay values for every individual in the sample. This departs from customary approaches in which the willingness-to-pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random-effects models for panel data are subsequently used to identify the determinants of the individual-specific willingness-to-pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete-choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.

Random walk of magnetic field lines for different values of the energy range spectral index

An analytical nonlinear description of field-line wandering in partially statistically magnetic systems was proposed recently. In this article the influence of the wave spectrum in the energy range onto field-line random walk is investigated by applying this formulation. It is demonstrated that in all considered cases we clearly obtain a superdiffusive behavior of the field-lines. If the energy range spectral index exceeds unity a free-streaming behavior of the field-lines can be found for all relevant length-scales of turbulence. Since the superdiffusive results obtained for the slab model are exact, it seems that superdiffusion is the normal behavior of field-line wandering.

Numerical analysis of surface and fossil pollen spectra from northern Fennoscandia

Aim Determination of the main directions of variance in an extensive data base of annual pollen deposition, and the relationship between pollen data from modified Tauber traps and palaeoecological data. Location Northern Finland and Norway. Methods Pollen analysis of annual samples from pollen traps and contiguous high-resolution samples from a peat sequence. Numerical analysis (principal components analysis) of the resulting data. Results The main direction of variation in the trap data is due to the vegetation region in which each trap is located. A secondary direction of variation is due to the annual variability of pollen production of some of the tree taxa, especially Betula and Pinus. This annual variability is more conspicuous in ‘absolute’ data than it is in percentage data which, at this annual resolution, becomes more random. There are systematic differences, with respect to peat-forming taxa, between pollen data from traps and pollen data from a peat profile collected over the same period of time. Main conclusions Annual variability in pollen production is rarely visible in fossil pollen samples because these cannot be sampled at precisely a 12-month resolution. At near-annual resolution sampling, it results in erratic percentage values which do not reflect changes in vegetation. Profiles sampled at near annual resolution are better analysed in terms of pollen accumulation rates with the realization that even these do not record changes in plant abundance but changes in pollen abundance. However, at the coarser temporal resolution common in most fossil samples it does not mask the origin of the pollen in terms of its vegetation region. Climate change may not be recognizable from pollen assemblages until the change has persisted in the same direction sufficiently long enough to alter the flowering (pollen production) pattern of the dominant trees.

Genetic variation of the razor clam Ensis siliqua (Jeffreys, 1875) along the European coast based on random amplified polymorphic DNA markers

Ensis siliqua is regarded as an increasingly valuable fishery resource with potential for commercial aquaculture in many European countries. The genetic variation of this razor clam was analysed by randomly amplified polymorphic DNA (RAPD) in six populations from Spain, Portugal and Ireland. Out of the 40 primers tested, five were chosen to assess genetic variation. A total of 61 RAPD loci were developed ranging in size from 400 to 2000 bp. The percentages of polymorphic loci, the allele effective number and the genetic diversity were comparable among populations, and demonstrated a high level of genetic variability. The values of Nei's genetic distance were small among the Spanish and Portuguese populations (0.051-0.065), and high between these and the Irish populations. Cluster and principal coordinate analyses supported these findings. A mantel test performed between geographic and genetic distance matrices showed a significant correlation (r=0.84, P

Expedited Solid-Phase Synthesis of Fluorescently Labeled and Biotinylated Aminoalkane Diphenyl Phosphonate Affinity Probes for Chymotrypsin- and Elastase-Like Serine Proteases

In this study, we report on a novel, expedited solid-phase approach for the synthesis of biotinylated and fluorescently tagged irreversible affinity based probes for the chymotrypsin and elastase-like serine proteases. The novel solid-phase biotinylation or fluorescent labeling of the aminoalkane diphenyl phosphonate warhead using commercially available Biotin-PEG-NovaTag or EDANS NovaTag resin permits rapid, facile synthesis of these reagents. We demonstrate the kinetic evaluation and utilization of a number of these irreversible inactivators for chymotrypsin-like (chymotrypsin/human cathepsin G) and elastase-like serine proteases. Encouragingly, these compounds display comparable potency against their target proteases as their N-benzyloxycarbonyl (Cbz)-protected parent compounds, from which they were derived, and function as efficient active site-directed inactivators of their target proteases. We subsequently applied the biotinylated reagents for the sensitive detection of protease species via Western blot, showing that the inactivation of the protease was specifically mediated through the active site serine. Furthermore, we also demonstrate the successful detection of serine protease species with the fluorescently labeled derivatives “in-gel”, thus avoiding the need for downstream Western blotting. Finally, we also show the utility of biotinylated and pegylated affinity probes for the isolation/enrichment of serine protease species, via capture with immobilized streptavidin, and their subsequent identification via de novo sequencing. Given their selectivity of action against the serine proteases, we believe that these reagents can be exploited for the direct, rapid, and selective identification of these enzymes from biological milieu containing multiple protease subclasses.

Joined Spectral Trees for Scalable SPIHT-Based Multispectral Image Compression

In this paper, the compression of multispectral images is addressed. Such 3-D data are characterized by a high correlation across the spectral components. The efficiency of the state-of-the-art wavelet-based coder 3-D SPIHT is considered. Although the 3-D SPIHT algorithm provides the obvious way to process a multispectral image as a volumetric block and, consequently, maintain the attractive properties exhibited in 2-D (excellent performance, low complexity, and embeddedness of the bit-stream), its 3-D trees structure is shown to be not adequately suited for 3-D wavelet transformed (DWT) multispectral images. The fact that each parent has eight children in the 3-D structure considerably increases the list of insignificant sets (LIS) and the list of insignificant pixels (LIP) since the partitioning of any set produces eight subsets which will be processed similarly during the sorting pass. Thus, a significant portion from the overall bit-budget is wastedly spent to sort insignificant information. Through an investigation based on results analysis, we demonstrate that a straightforward 2-D SPIHT technique, when suitably adjusted to maintain the rate scalability and carried out in the 3-D DWT domain, overcomes this weakness. In addition, a new SPIHT-based scalable multispectral image compression algorithm is used in the initial iterations to exploit the redundancies within each group of two consecutive spectral bands. Numerical experiments on a number of multispectral images have shown that the proposed scheme provides significant improvements over related works.

Hidden Conditional Random Fields for Visual Speech Recognition

In this paper we present the application of Hidden Conditional Random Fields (HCRFs) to modelling speech for visual speech recognition. HCRFs may be easily adapted to model long range dependencies across an observation sequence. As a result visual word recognition performance can be improved as the model is able to take more of a contextual approach to generating state sequences. Results are presented from a speaker-dependent, isolated digit, visual speech recognition task using comparisons with a baseline HMM system. We firstly illustrate that word recognition rates on clean video using HCRFs can be improved by increasing the number of past and future observations being taken into account by each state. Secondly we compare model performances using various levels of video compression on the test set. As far as we are aware this is the first attempted use of HCRFs for visual speech recognition.