Surface roughness analysis of hardened steel after high-speed milling

The work refers to analysis of various factors affecting surface roughness after end milling of hardened steel in high-speed milling (HSM) conditions. Investigations of milling parameters (cutting speed v(c) , axial depth of cut a(p) ) and the process dynamics that influence machined surface roughness were presented, and a surface roughness model, including cutter displacements, was elaborated. The work also involved analysis of surface profile charts from the point of view of vibrations and cutting force components. The research showed that theoretic surface roughness resulting from the kinematic-geometric projection of cutting edge in the workpiece is significantly different from the reality. The dominant factor in the research was not feed per tooth f(z) (according to the theoretical model) but dynamical phenomena and feed per revolution f.     

The evolution of spatial patterns of residential segregation in Central European Cities: The Łódź Functional Urban Region from mature socialism to mature post-socialism

Two themes dominated the study of socio-spatial change in Central Eastern Europe (CEE) after 1990. One was that the development of urban regions in CEE after the demise of socialism is characterized by suburbanization. The second topic raises the issue of growing residential segregation. Unfortunately, studies on patterns of residential segregation are still scarce in the CEE context, in particular those that employ traditional measures of segregation. Relying on solid empirical materials from the 1988 and 2002 National Censuses, the purpose of this paper is to map and analyze the patterns of residential segregation in the ?ód? Functional Urban Region, an old industrial urban region in Poland undergoing a rapid deconcentration and shrinkage of the core area. This contribution concludes that the first decade of systemic transition resulted in decreasing residential segregation, as gauged by global measures of segregation.     

Analog filter pair design on the basis of a gyrator–capacitor prototype circuit

The paper presents an algorithmic approach to a low‐sensitivity design strategy for analog filter pairs based on a gyrator–capacitor prototype circuit. The general structure of the prototype circuit is proposed. It assumed that the generic structure of the prototype circuit can evolve, with the use of additional gyrators, into a circuit with increased redundancy. It is shown that symbolic analysis of the prototype circuit, used to formulate a set of nonlinear algebraic equations, is necessary to achieve a sufficiently high algorithm operation speed. To find a solution to this specific system of nonlinear algebraic equations, different numerical methods are compared. The modified Hooke and Jeeves algorithm is found to be the most effective. The elaborated algorithms and programs are illustrated with the seventh‐order filter pair example. The obtained filter is better than the filter obtained using LC ladder structures with respect to chip area and power consumption, and these improvements are obtained without loss of sensitivity properties. Copyright © 2010 John Wiley & Sons, Ltd.     

Over rail-to-rail fully differential voltage-to-current converters for nm scale CMOS technology

The converters presented in this paper are based on long channel complementary MOS transistors, instead of the commonly used differential amplifiers or differential transistor pairs which are difficult to implement in low voltage, nm scale CMOS technology. Nonlinearities of drain currents can be cancelled in the fully differential structure. As a result, the low power, nanometre standard digital CMOS technology converters are obtained. Layout examples are designed in 65 nm TSMC technology. Post-layout simulations show that the range of input voltage over rail-to-rail is achieved with very good linearity and reduced harmonic distortion.     

Linear regression for uplift modeling

The purpose of statistical modeling is to select targets for some action, such as a medical treatment or a marketing campaign. Unfortunately, classical machine learning algorithms are not well suited to this task since they predict the results after the action, and not its causal impact. The answer to this problem is uplift modeling, which, in addition to the usual training set containing objects on which the action was taken, uses an additional control group of objects not subjected to it. The predicted true effect of the action on a given individual is modeled as the difference between responses in both groups. This paper analyzes two uplift modeling approaches to linear regression, one based on the use of two separate models and the other based on target variable transformation. Adapting the second estimator to the problem of regression is one of the contributions of the paper. We identify the situations when each model performs best and, contrary to several claims in the literature, show that the double model approach has favorable theoretical properties and often performs well in practice. Finally, based on our analysis we propose a third model which combines the benefits of both approaches and seems to be the model of choice for uplift linear regression. Experimental analysis confirms our theoretical results on both simulated and real data, clearly demonstrating good performance of the double model and the advantages of the proposed approach.     

Nanofabrication of PTCDA molecular chains on rutile TiO(2)(011)-(2 × 1) surfaces

The adsorption of 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) on a rutile TiO(2)(011)-(2 × 1) surface is studied using ultra-high vacuum scanning tunneling microscopy. The self-assembly process is dominated by the fine interplay between the lateral intermolecular interactions and the binding to the substrate. By means of temperature-induced change in the adsorption configuration and the activation of diffusion, the molecules are assembled into one-dimensional chains oriented along the [Formula: see text] crystallographic direction.     

Convergence and stability analysis of the deformable discrete element method

This work investigates numerical properties of the algorithm of the discrete element method (DEM) employing deformable circular disks presented in the authors' earlier publication. The new formulation called the deformable DEM (DDEM) enhances the standard DEM (SDEM) by introducing an additional (global) deformation mode caused by the stresses in the particles induced by the contact forces. An accurate computation of the contact forces would require an iterative solution of the implicit relationship between the contact forces and particle displacements. In order to preserve efficiency of the DEM, the new formulation has been adapted to the explicit time integration. It has been shown that the explicit DDEM algorithm is conditionally stable and there are two restrictions on its stability. Except for the limitation of the time step as in the SDEM, the stability in the DDEM is governed by the convergence criterion of the iterative solution of the contact forces. The convergence and stability limits have been determined analytically and numerically for selected regular and irregular configurations. It has also been found out that the critical time step in DDEM remains unchanged with respect to the SDEM.     

The Folding of Knotted Proteins: Distinguishing the Distinct Behavior of Shallow and Deep Knots

The mechanism of deep knot formation in proteins has been debated for the past two decades, but definitive answers are still lacking. In this review, we first describe knotted proteins from the perspective of shallow and deep knots, taking into account recent experimental and theoretical results. We focus on the folding mechanism, where this difference is most profound. We explain in more details the cotranslational knotting pathway. Then, we additionally show that proteins with extremely deep knots have a distinct mechanism of knotting from proteins with shallow knots. The approach based on treating shallow and deep knots as separate classes of molecules allow to classify them better and introduce a new paradigm of thinking about knotted proteins as such. This may in turn help to avoid ambiguities in further research.     

Photosensitization and photocurrent switching effects in wide band gap semiconductors: CuI and TiO<Subscript>2</Subscript> functionalized with iron and nickel complexes: from semiconductors to logic devices

Materials obtained by immobilization of nickel and iron complexes on the surface of n-type titanium dioxide and p-type copper iodide have interesting photoelectrochemical properties. Fe(NA)Cl₂@TiO₂, Fe(NA)Cl₂@CuI, Ni-rutin@CuI and Ni-rutin@TiO₂ exhibit pronounced photosensitization towards visible light and photoelectrodes prepared from these materials generate photocurrents over a broad light wavelength window. The polarity of the generated photocurrents varies with change of the applied potential. Photocurrent switching phenomena can be described in terms of photoinduced charges transfer involving semiconductor and excited metal complex. Various types of interaction between semiconductor and adsorbed complex reflected in different mechanism of photosensitization. The studied materials has been characterized using various spectroscopic, crystallographic and electrochemical methods. Based on the photochemical measurements and diffuse reflectance spectroscopy the mechanism of photosensitization as well as mechanism of photocurrent generation in various conditions have been suggested. Due to interesting photoelectrochemical properties, studied materials are promising for optoelectronic logic devices such as demultiplexer. Studied materials are particularly attractive due to high stability and photostability.