Application of mid-infrared spectroscopy: measuring hydrogen peroxide concentrations in bleaching baths

The presented work applies mid-infrared attenuated total reflection (ATR) spectroscopy to the measurment of hydrogen peroxide in aqueous matrices. The performance of different ATR crystals mounted in flow cells was investigated in the presence of aqueous hydrogen peroxide solutions. Quantitative determination has been achieved by evaluation of specific OH stretching and deformation vibrations with linear correlation between peak areas or peak heights and hydrogen peroxide concentration in the range of 1-10% (weight in water). Important aspects such as chemical stability of the waveguide material and influences of pH and ionic strength on the performance are discussed. Feasibility for the investigation of real world samples is demonstrated by measuring industrial bleaching solutions with known concentrations of hydrogen peroxide fitting well with calibration graphs established with neat hydrogen peroxide solutions. The presented sensor system is capable of determining hydrogen peroxide within complex matrices and clearly corroborates the potential of providing an in situ measurement concept for on-line hydrogen peroxide detection.     

Solvent-free derivatization of pristine multi-walled carbon nanotubes with amines

We performed direct solvent-free amination of multi-walled carbon nanotubes (MWCNTs) with nonylamine, dodecylamine, octadecylamine, 4-phenylbutylamine and 1,8-ocanediamine at a temperature of 150-170 degrees C and reduced pressure. Thermogravimetric analysis and temperature-programmed desorption-mass spectrometry revealed that a major amine fraction decomposes in a temperature interval of 250-500 degrees C, thus existing on multi-walled carbon nanotubes as chemically bonded species; a minor amine fraction was found in physisorbed form. The new derivatization technique combines simplicity in implementation and attractive features of "green" chemistry. It requires no additional chemical activation, but thermal activation instead; it is relatively fast since it can be completed in about 2 h; the high temperature allows one to spontaneously remove excess amine from the nanotube and minimize the possibility of physical adsorption; there is no need to use an (organic) solvent medium. In the case of diamines (represented in this study by 1,8-ocanediamine), the functional groups introduced can be potentially used as chemical linkers for anchoring metal complexes and nanoparticles to multi-walled carbon nanotubes, for adsorption and concentration of trace metal ions.     

Microstructure and mechanical properties of Mg-5Li-1Al sheets prepared by accumulative roll bonding

Ultrafine-grain and high-strength Mg-5Li-1Al sheets were prepared by accumulative roll bonding (ARB) process. Evolution of microstructure and mechanical properties of ARB-processed Mg-5Li-1Al sheets was investigated.Results show that, during ARB process, the evolution of deformation mechanism of t Mg-5Li-1Al alloy is as follows: twinning deformation, shear deformation, forming macro shear zone, and finally dynamic recrystallization (DRX). The grain refining mechanism changes from twin DRX to rotation DRX. With the increase in ARB cycles, strength of the Mg-5Li-1Al sheets is enhanced, whilst elongation varies slightly. With the increase in rolling cycles, anisotropy of mechanical properties decreases. It is conclusive that strain hardening and grain refinement dominate the strengthening mechanism of Mg-5Li-1Al alloy.     

Mathematical model of an industrial robot with articulated configuration and six degrees of freedom

This paper analyses the load influence on a d.c. drive motor servo system for all six degrees of freedom of industrial robots with an articulated configuration. Through the analyses, the analytical equations of total inertia and gravitation moments of an industrial robot servo system for external coordinate function were obtained. A mathematical model of an electro-mechanical industrial robot system was also developed.     

Using Ideas of Kolmogorov Complexity for Studying Biological Texts

Kolmogorov complexity furnishes many useful tools for studying different natural processes that can be expressed using sequences of symbols from a finite alphabet (texts), such as genetic texts, literary and music texts, animal communications, etc. Although Kolmogorov complexity is not algorithmically computable, in a certain sense it can be estimated by means of data compressors. Here we suggest a method of analysis of sequences based on ideas of Kolmogorov complexity and mathematical statistics, and apply this method to biological (ethological) ??texts.?? A distinction of the suggested method from other approaches to the analysis of sequential data by means of Kolmogorov complexity is that it belongs to the framework of mathematical statistics, more specifically, that of hypothesis testing. This makes it a promising candidate for being included in the toolbox of standard biological methods of analysis of different natural texts, from DNA sequences to animal behavioural patterns (ethological ??texts??). Two examples of analysis of ethological texts are considered in this paper. Theses examples show that the proposed method is a useful tool for distinguishing between stereotyped and flexible behaviours, which is important for behavioural and evolutionary studies.     

NICE h : a higher-order explicit numerical scheme for integration of constitutive models in plasticity

The article introduces, as a result of further development of the first-order scheme NICE, a simple and efficient higher-order explicit numerical scheme for the integration of a system of ordinary differential equations which is constrained by an algebraic condition (DAE). The scheme is based on the truncated Taylor expansion of the constraint equation with order h of the scheme being determined by the highest exponent in the truncated Taylor series. The integration scheme thus conceived will be named NICE ^h , considering both principal premises of its construction. In conjunction with a direct solution technique used to solve the boundary value problem, the NICE ^h scheme is very convenient for integrating constitutive models in plasticity. The plasticity models are defined mostly by a system of algebraic and differential equations in which the yield criterion represents the constraint condition. To study the properties of the new integration scheme, which, like the forward-Euler scheme, is characterised by its implementation simplicity due to the explicitness of its formulations, a damage constitutive model (Gurson–Tvergaard–Needleman model) is considered. The general opinion that the implicit backward-Euler scheme is much more accurate than the thus-far known explicit schemes is challenged by the introduction of the NICE ^h scheme. The accuracy of the higher-order explicit scheme in the studied cases is significantly higher than the accuracy of the classical backward-Euler scheme, if we compare them under the condition of a similar CPU time consumption.     

Patterns of self-stabilization in database consistency maintenance

A substantial portion of the database programming efforts are invested in integrity constraints enforcement. Traditionally, both the constraint semantics and their enforcement were embedded inside application programs. In recent years several studies have dealt with specifying integrity constraints as separate entities (e.g. rules), and relating the database consistency requirements to these rules. In this paper we deal with the complementary issue of stabilizing the database when update exceptions occur. While a simplistic approach is to abort any transaction that inflicts consistency violations, this is not always the desired action. We take advantage of the empirical observation that most of the exception-handling policies follow a small number of behavior patterns. Unlike some previous approaches that base their repair solution on syntactic analysis of the constraints and performance issues, we base our approach on the application semantics as reflected in these behavioral patterns. We describe a model that uses high-level abstractions called stabilizer types denoting these behavior patterns for consistency restorations, whose exact semantics is case dependent. It follows the fault tolerance's self-stabilization approach. An inference mechanism translates these abstractions into executable active rules. This approach provides high-level language to the exception handling portion of the application and substantially reduces the required programming.     

Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...     

Odometry-Based Viterbi Localization with Artificial Neural Networks and Laser Range Finders for Mobile Robots

This paper proposes an approach that solves the Robot Localization problem by using a conditional state-transition Hidden Markov Model (HMM). Through the use of Self Organized Maps (SOMs) a Tolerant Observation Model (TOM) is built, while odometer-dependent transition probabilities are used for building an Odometer-Dependent Motion Model (ODMM). By using the Viterbi Algorithm and establishing a trigger value when evaluating the state-transition updates, the presented approach can easily take care of Position Tracking (PT), Global Localization (GL) and Robot Kidnapping (RK) with an ease of implementation difficult to achieve in most of the state-of-the-art localization algorithms. Also, an optimization is presented to allow the algorithm to run in standard microprocessors in real time, without the need of huge probability gridmaps.     

Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices

An additive spectral method for fuzzy clustering is proposed. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which makes the spectral approach quite natural. The iterative extraction of clusters, also, allows us to draw several stopping rules to the procedure. This applies to several relational data types differently normalized: network structure data (the first eigenvector subtracted), affinity between multidimensional vectors (the pseudo-inverse Laplacian transformation), and conventional relational data including in-house data of similarity between research topics according to working of a research center. The method is experimentally compared with several classic and recent techniques and shown to be competitive.