A new method for manufacturing nanostructured electrodes on glass substrates

The present paper describes a new method for manufacturing a nanostructured porous layer of TiO₂ on a conducting glass substrate for use in a dye-sensitized photoelectrochemical cell. The method involves deposition of a layer of semiconductor particles onto a conducting substrate and compression of the particle layer to form a mechanically stable, electrically conducting, and porous nanostructured film at room temperature. Photoelectrochemical characteristics and morphology of the resulting nanostructured films are presented. The potential use of the new manufacturing method in the future applications of nanostructured systems is discussed.     

A probabilistic model for cleavage fracture with a length scale--parameter estimation and predictions of stationary crack experiments

This study presents a large experimental investigation in the transition temperature region on a modified A508 steel. Tests were carried out on single-edge-notch-bend specimens with three different crack depth over specimen width ratios to capture the strong constraint effect on fracture toughness. Three test temperatures were considered, covering a range of 85 °C. All specimens failed by cleavage fracture prior to ductile tearing. A recently proposed probabilistic model for the cumulative failure by cleavage was applied to the comprehensive sets of experimental data. This modified weakest link model incorporates a length scale, which together with a threshold stress reduce the scatter in predicted toughness distributions as well as introduces a fracture toughness threshold value. Model parameters were estimated by a robust procedure, which is crucial in applications of probabilistic models to real structures. The conformity between predicted and experimental toughness distributions, respectively, were notable at all the test temperatures.     

Ab<Emphasis Type="Italic"> initio</Emphasis> investigation of boron diffusion paths in germanium

Boron is observed to diffuse very slowly in germanium, as opposed to its behaviour in silicon where it exhibits Transient Enhanced Diffusion effects in implanted samples. As a result of this slow diffusion, boron is a very stable dopant, allowing devices to be created with very well-defined doping regions. To understand this superior performance, calculations were performed on a variety of boron diffusion paths, within vacancy and interstitial mediated methods. It was found that the vacancy mediated diffusion which is associated with the fast diffusion of many other species in germanium exhibits a total barrier of 5.8 eV. Interstitial-mediated diffusion had a total barrier for migration of 3.4 eV in the neutral and singly negative charge states, 3.2 eV for the positive charge state, but a formation barrier of 4.1 eV. Thus the barrier for interstitial-mediated diffusion is dominated by the formation energy of the self-interstitial.     

Crystallographic electron microscopy

We present a family of techniques for the transmission electron microscope that generate surface zone-axis patterns. These patterns display the variation of the diffracted-beam intensity as a function of the angle of the incident electrons. The conditions of the experiments are those of reflection high-energy electron diffraction at near grazing incidence. The techniques are: surface convergent-beam diffraction, a surface analogue of the Tanaka method and a modified double-rocking scheme. Experimental results are presented for diffraction from surfaces of MgO and MoS₂. We anticipate that surface zone-axis patterns (surface ZAPs) will become established as an important tool for surface characterization, especially when used in conjunction with high-resolution surface imaging and surface energy loss spectroscopy; surface ZAPs may be expected to play, in surface analysis, a role analogous to that played by convergent-beam diffraction in normal transmission electron microscopy.     

Putting it all together – Formal verification of the VAMP

In the verified architecture microprocessor (VAMP) project we have designed, functionally verified, and synthesized a processor with full DLX instruction set, delayed branch, Tomasulo scheduler, maskable nested precise interrupts, pipelined fully IEEE compatible dual precision floating point unit with variable latency, and separate instruction and data caches. The verification has been carried out in the theorem proving system PVS. The processor has been implemented on a Xilinx FPGA. A shorter version of this article with the title “Instantiating uninterpreted functional units and memory system: functional verification of the VAMP” appeared in [8]. The work reported here was done while all the authors were with Saarland University.     

Distinction between artefactually shrunken and truly degenerated 'dark' neurons by in situ fixation with microwave irradiation

Dark, shrunken neurons frequently occur as artefacts in immersion fixed tissue. Perfusion fixation will prevent artefacts of this type. However, morphologically identical neurons have been described as truly degenerated cells in perfusion fixed brains in various pathological conditions. Since adequate perfusion is difficult to obtain in some pathological conditions, the question still remains whether the dark neurons found in some of these situations are true in vivo phenomena or artefacts caused by inadequate fixation. In the present study rat brains with cryogenic lesions were fixed in situ by microwave irradiation. With this method no artefactually changed dark neurons were observed in the normal parts of the brains. In the cryogenic lesions, however, a narrow rim of dark, shrunken neurons occurred adjacent to the normal cortex. This zone was identical to that observed in perfusion fixed tissue. Since inadequate fixation due to uneven perfusion of the damaged tissue is prevented with this method, we suggest that the neuronal changes represent true in vivo phenomena. Fixation with microwave irradiation can thus be used to differentiate between artefactually changed and truly degenerated dark neurons in various pathological conditions.     

Psychometric considerations in the dimensional analysis of subjective picture quality

A discussion of the factors involved in the subjective perception of television picture quality is presented. Much of the work in this field is cited, and it is concluded that future work needs to consider a broader range of variables than has been looked at so far.     

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.