Randomly accessible, multilayered optical memory with a Bi(12)SiO(20) crystal

A read-and-write, randomly accessible, multilayered optical memory with a Bi(12) SiO(20) crystal as the medium is demonstrated. Data are recorded in the crystal as an absorption change that is due to the photochromic effect. These data are successfully recorded, read, and selectively erased in five layers in the crystal. The axial-separation distance between neighboring layers is 30 μm, and the lateral distance between bits is 5 μm. Selective bit erasure of the data is accomplished by illumination of the recorded bit datum with He-Ne laser light. To our knowledge, this is the first successful demonstration of the selective optical erasure of the photochromic effect in a BSO crystal.     

Visual comparability of 3D regular sampling and reconstruction

The Body-Centered Cubic (BCC) and Face-Centered Cubic (FCC) lattices have been analytically shown to be more efficient sampling lattices than the traditional Cartesian Cubic (CC) lattice, but there has been no estimate of their visual comparability. Two perceptual studies (each with N = 12 participants) compared the visual quality of images rendered from BCC and FCC lattices to images rendered from the CC lattice. Images were generated from two signals: the commonly used Marschner-Lobb synthetic function and a computed tomography scan of a fish tail. Observers found that BCC and FCC could produce images of comparable visual quality to CC, using 30-35 percent fewer samples. For the images used in our studies, the L(2) error metric shows high correlation with the judgement of human observers. Using the L(2) metric as a proxy, the results of the experiments appear to extend across a wide range of images and parameter choices.     

The role of latent and active failures in workplace slips, trips and falls: an information processing approach

The vast majority of the published workplace slips, trips and falls (STF) literature is exceedingly narrow in its focus and often ignores wider systems issues in workplace STF aetiology. There is little recognition within the published literature of the importance of latent failures or the upstream organisational and cultural contexts within which workplace STF occur. This is unfortunate, as a systems approach to workplace STF analysis, that is inclusive of latent design and work organisation factors that often shape worker behaviour patterns related to STF risk (e.g. rushing, risk taking), is fundamental to the development of effective prevention measures. The aims of this paper are to provide an understanding of workplace STF causation that is cognisant of the potential role of both active and latent failures in STF causation. The paper presents an ergonomics model for workplace STF analysis that highlights information processing in STF aetiology, the STF incident process and the interaction between latent and active failures in STF causation. The paper draws upon ergonomics research conducted in a range of occupational contexts to illustrate the key features of the model as it applies to workplace STF. Implications of the model for analysis and prevention of STF are discussed.     

A well-based reverse-phase protein array applicable to extracts from formalin-fixed paraffin-embedded tissue

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue offers significant diagnostic utility but is complicated due to the high level of covalently crosslinked proteins arising from formalin fixation. To address these challenges, we developed a reliable protein extraction method for FFPE tissue, based on heat-induced antigen retrieval within a pressure cooker. The protein extraction yield from archival FFPE tissue section is approximately 90% of that recovered from frozen tissue. This method demonstrates preservation of immunoreactivity and recovery of full-length proteins by Western blotting. Additionally, we developed a well-based RP protein array platform utilizing an electrochemiluminescence detection system. Protein samples derived from FFPE tissue by means of laser capture dissection, with as few as 500 shots demonstrate measurable signal differences for different proteins. The lysates coated to the array plate, remain stable over 1?month at room temperature. Theses data suggest that this new protein-profiling platform coupled with the protein extraction method can be used for molecular profiling analysis in FFPE tissue, and contribute to the validation and development of biomarkers in clinical studies.     

Recording and interpretation/analysis of tilt signals with five ASKANIA borehole tiltmeters at the KTB

In June 2003, a large scale injection experiment started at the Continental Deep Drilling site (KTB) in Germany. A tiltmeter array was installed which consisted of five high resolution borehole tiltmeters of the ASKANIA type, also equipped with three dimensional seismometers. For the next 11 months, 86 000 m(3) were injected into the KTB pilot borehole 4000 m deep. The average injection rate was approximately 200 l/min. The research objective was to observe and to analyze deformation caused by the injection into the upper crust at the kilometer range. A new data acquisition system was developed by Geo-Research Center Potsdam (GFZ) to master the expected huge amount of seismic and tilt data. Furthermore, it was necessary to develop a new preprocessing software called PREANALYSE for long-period time series. This software includes different useful functions, such as step and spike correction, interpolation, filtering, and spectral analysis. This worldwide unique installation offers the excellent opportunity of the separation of signals due to injection and due to environment by correlation of the data of the five stations with the ground water table and meteorological data.     

Solid state reaction in sandwich-type Al/Cu thin films

Al/Cu/Al and Cu/Al/Cu triple layers with approximately 10 nm single layer thickness deposited on tungsten substrates were analyzed in the early stages of reactive interdiffusion by means of atom probe tomography. The first reaction product is found after 5 min thermal treatment at 110 degrees C and identified by direct chemical analysis to be Al2Cu. Surprisingly, we found a significant asymmetry in the reaction rate of the new phase with the stacking sequence: the thickness of the product grown at the interfaces, at which Cu is deposited on top of the Al layer, is approximately 1.5-2 times thicker than the other one at the interfaces at which Al is deposited onto a Cu layer. On the other hand, at both interfaces the thickness of the product layer depends parabolically on time. No precursory interdiffusion and no distinct nucleation process of the product are observed.     

Discriminant subspace analysis: a Fukunaga-Koontz approach

The Fisher Linear Discriminant (FLD) is commonly used in pattern recognition. It finds a linear subspace that maximally separates class patterns according to the Fisher Criterion. Several methods of computing the FLD have been proposed in the literature, most of which require the calculation of the so-called scatter matrices. In this paper, we bring a fresh perspective to FLD via the Fukunaga-Koontz Transform (FKT). We do this by decomposing the whole data space into four subspaces with different discriminability, as measured by eigenvalue ratios. By connecting the eigenvalue ratio with the generalized eigenvalue, we show where the Fisher Criterion is maximally satisfied. We prove the relationship between FLD and FKT analytically, and propose a unified framework to understanding some existing work. Furthermore, we extend our our theory to Multiple Discriminant Analysis (MDA). This is done by transforming the data into intra- and extra-class spaces, followed by maximizing the Bhattacharyya distance. Based on our FKT analysis, we identify the discriminant subspaces of MDA/FKT, and propose an efficient algorithm, which works even when the scatter matrices are singular, or too large to be formed. Our method is general and may be applied to different pattern recognition problems. We validate our method by experimenting on synthetic and real data.     

Deformation models for image recognition

We present the application of different nonlinear image deformation models to the task of image recognition. The deformation models are especially suited for local changes as they often occur in the presence of image object variability. We show that, among the discussed models, there is one approach that combines simplicity of implementation, low-computational complexity, and highly competitive performance across various real-world image recognition tasks. We show experimentally that the model performs very well for four different handwritten digit recognition tasks and for the classification of medical images, thus showing high generalization capacity. In particular, an error rate of 0.54 percent on the MNIST benchmark is achieved, as well as the lowest reported error rate, specifically 12.6 percent, in the 2005 international ImageCLEF evaluation of medical image specifically categorization.     

Quantum chemical studies on protonation of some substituted thiazole derivatives

The acidity constants, pK(a) values for protonation of some substituted thiazole derivatives were calculated by using AM1 and PM3 basis sets of semi-empirical methods and B3LYP/6-31G(d) basis sets of density functional theory (DFT) calculated physical and thermodynamic parameters. Correlation search among the experimental and calculated acidity constants, pK(a) values, revealed that the best correlation exist between the experimental and ab initio calculated pK(a) values with a regression of R(2)=0.98.