The Kinetics of the Thermal Decomposition of Thermoplastic Polyurethane Elastomers under Thermoplastic Processing Conditions

A theoretical approach to the kinetics of the thermal decomposition of molten thermoplastic polyurethane elastomers, under conditions of thermoplastic processing, is described. On the basis of these considerations, the thermal decomposition in different instruments (melt index analyser and measuring extruder) can be described quantitatively and the various results can be compared. As a result, identical conditions of decomposition of the melt can be defined accurately, thus opening up the possibility of combining experimental values from different instruments. The fundamental kinetic equation obtained for the kinetics of the thermal decomposition of thermoplastic polyurethanes describes the decomposition reaction and the reverse reaction (formation reaction) – which is dependent on the system of measurement and processing – as a function of the molar mass (end‐group concentration) of the original product, determined from the velocity constants for the decomposition reaction and back reaction. The consideration of the limiting value for t → ∞ is in agreement with the equilibrium constant. Consequently, the development of physical characteristic functions of thermoplastic polyurethane elastomers – independent of the system of measurement – is possible.

Experimental values and calculated curves for the thermal decomposition of PUR‐Et in a melt index analyser.     

Kinetics of Solid-State Reactions in Heterogeneous Catalysis from Time-Resolved X-Ray Absorption Spectroscopy

The potentials of X-ray absorption spectroscopy (XAS) (quantitative phase composition and average valence together with a short-range order structure analysis) combined with a time-resolution in the second range make time-resolved (TR-) XAS a powerful tool for investigating the reactivity of solids in catalysis and solid-state chemistry. General aspects of TR-XAS investigations are discussed (i.e., instrumentation, data analysis). In addition, some experiments illustrate how the kinetics of solid-state reactions in heterogeneous catalysis can be elucidated from TR-XAS studies.     

Applications of Two-Dimensional 1H NMR Methods to Photo-Chemically Induced Dynamic Nuclear Polarisation Spectroscopy

Photo-CIDNP is a useful technique to identify surface residues in proteins and to assign resonances in their ¹H NMR spectra by the spectral simplification that is obtained. In spite of this simplification, conventional photo-CIDNP spectra can be quite complex due to spectral overlap. For this reason two-dimensional (2D) methods are welcome. We present combinations of photo-CIDNP with 2D J-correlated spectroscopy (CIDNP-COSY) and with 2D NOE spectroscopy (CIDNP-NOESY). In these experiments we insert a saturation pulse sequence and a short laser-irradiation period at the beginning of the preparation period to generate CIDNP, leaving the remaining of the pulse scheme essentially unaltered. The CIDNP-COSY and CIDNP-NOESY spectra of a hen egg-white (HEW) lysozyme are presented. The CIDNP-NOESY spectrum of lysozyme is compared with the results from 1D cross-polarisation experiments on the same protein. CIDNP-NOESY spectra of lysozyme with and without inhibitor NAG are compared.     

Living dispersion polymerization of styrene in the presence of polystyrene-block-poly(4-trimethylsilylstyrene)

Summary Living polystyrene microparticles with average particle diameters varying between 0.5 and 3.8 m were obtained via sec-butyl lithium-initated anionic polymerization of styrene in n-hexane diluent when polystyrene-block-poly(4-trimethyl-silylstyrene) was added as dispersing agent. The influence of block copolymer molecular architecture and concentration as well as polymerization temperature, monomer concentration and THF addition on polystyrene particle size, molecular weight and molecular weight distribution were investigated. In comparison to anionic styrene polymerization in cyclohexane solution, the anionic styrene dispersion polymerization in n-hexane was markedly slower.     

On the effect of peroxisomal β-oxidation and carnitine palmitoyltransferase activity by eicosapentaenoic acid in liver and heart from rats

Repeated administration of highly purified eicosapentaenoic acid (as ethyl ester) resulted in a decrease in plasma triglycerides and high density lipoprotein (HDL) cholesterol. This was accompanied by a stimulation in the activities of carnitine palmitoyltransferase, fatty acyl-CoA oxidase and peroxisomal β-oxidation in the liver. The results suggest that the triglyceride-lowering effect observed with eicosapentaenoic acid may be due to a reduced supply of fatty acids for hepatic triglyceride synthesis because of increased fatty acid oxidation. Eicosapentaenoic acid feeding marginally affected the triglyceride content of heart and mitochondrial and peroxisomal enzyme activities.     

A New Research Infrastructure for Investigating Flow Hydraulics and Process Equipment at Critical Fluid Properties

An optimized equipment design for natural gas processing and liquefaction plants becomes increasingly difficult with changing process conditions: Particularly low values of surface tension create rising challenges on the design of phase separators and column internals. The TERESA test rig at HZDR was designed to allow the investigation of multiphase thermohydraulics and phase separator performance under critical fluid properties in industrial dimensions. A versatile pipe test section is available in DN200 and equipment internals may be tested in a sectional DN300/DN500 test separator. The applied test fluid shows a high vapor-liquid density difference between 1470 and 940 kg m⁻³, viscosity as low as 0.12 mm²s⁻¹, and surface tension down to 1.3 mN m⁻¹. Volumetric liquid and vapor flow rates may be varied up to 9 and 530 m³h⁻¹ in the test rig, respectively.     

Toward Self‐Motivated,Cognitive, Continually Planning Agents

We present a flexible initial framework for defining self‐motivated, self‐aware agents in simulated worlds, planning continuously so as to maximize long‐term rewards. While such agents employ reasoned exploration of feasible sequences of actions and corresponding states, they also behave opportunistically and recover from failure, thanks to their continual plan updates and quest for rewards. Our framework allows for both specific and general (quantified) knowledge and for epistemic predicates such as knowing‐that and knowing‐whether. Because realistic agents have only partial knowledge of their world, the reasoning of the proposed agents uses a weakened closed‐world assumption; this has consequences for epistemic reasoning, in particular introspection. The planning operators allow for quantitative, gradual change and side effects such as the passage of time, changes in distances and rewards, and language production, using a uniform procedural attachment method. Question answering (involving introspection) and experimental runs are shown for our particular agent ME in a simple world, demonstrating the value of continual deliberate, reward‐driven planning. Though the primary merit of agents definable in our framework is that they combine all of the aforementioned features, they can also be configured as single or multiple goal‐seeking agents and as such perform comparably with some recent experimental agents.     

Forming an intention to act on recommendations given via online social networks

Online social networks (OSN) are technology-enabled relationship tools in which a user creates a profile, connects to other individuals, and shares user-generated content with them. One of the many features OSN offer is the ability to post messages in the form of product and service recommendations. Although word-of-mouth research has examined this type of personal communication to intentionally influence consumer decisions, limited understanding exists regarding when a user acts upon a recommendation received from one of their contacts. In this study, we draw on relationship theories and research on trust to analyze the impact relationship characteristics and behaviors of the OSN contacts have on trust in the recommendation that subsequently leads a user to act on this OSN contact’s recommendation. The results of a survey of 116 OSN users showed that closeness, excessive posting behavior, and past recommendation experience have a positive impact on trust and intention to act on the recommendation. One characteristic of the relationships, that is, similarity, however, does not affect recommendation trust in the context of OSN. The findings enhance our understanding of relationships and their defining characteristics in OSN. The results also provide insights into how companies might leverage OSN in their marketing efforts.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.