Zugelich: Diss. Frankfurt (Oder), 2008. / Literaturverz.

It is well-known that taxes affect risky investment decisions. Analytical studies indicate that tax rate increases (decreases) can foster (hinder) investment if there is flexibility, in particular when an exit option is available. We design an experiment based on an analytical model with binomial random walk and entry and exit flexibility. Contrasting the underlying model, we find accelerated investment, which is often considered as an increased willingness to invest, on tax rate increases to be independent of the existence of an exit option. However, we observe this investor reaction only for a tax increase, not for a tax decrease. This behavior is driven possibly by tax salience and the mechanisms known from the theory of irreversible choice under uncertainty. Our empirical evidence suggests that the at-first-sight unexpected tax reform effects are more common than is predicted by the theoretical literature. Policy makers should therefore carefully consider the behavioral aspects when anticipating taxpayer reactions. (authors' abstract) / Series: WU International Taxation Research Paper Series

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Today (2014), software is the key ingredient of most products and services. Software generates innovation and progress in many modern industries. Software is an indispensable element of evolution, of quality of life, and of our future. Software development is (slowly) evolving from a craft to an industrial discipline. Software – and the ability to efficiently produce and evolve high-quality software – is the single most important success factor for many highly competitive industries. Software technology, development methods and tools, and applications in more and more areas are rapidly evolving. The impact of software in 2025 in nearly all areas of life, work, relationships, culture, and society is expected to be massive. The question of the future of software is therefore important. However – like all predictions – quite difficult. Some market forces, industrial developments, social needs, and technology trends are visible today. How will they develop and influence the software we will have in 2025?:Impact of Heterogeneous Processor Architectures and Adaptation Technologies on the Software of 2025 (Kay Bierzynski) 9 Facing Future Software Engineering Challenges by Means of Software Product Lines (David Gollasch) 19 Capabilities of Digital Search and Impact on Work and Life in 2025 (Christina Korger) 27 Transparent Components for Software Systems (Paul Peschel) 37 Functionality, Threats and Influence of Ubiquitous Personal Assistants with Regard to the Society (Jonas Rausch) 47 Evolution-driven Changes of Non-Functional Requirements and Their Architecture (Hendrik Schön) 57

Produktivitätsmodelle geben Auskunft darüber, welche Leistung mit einem bestimmten Verfahren unter konkreten Rahmenbedingungen zu erwarten ist. In der Forstwirtschaft sind sie für Planungen und Kalkulationen notwendig. In bisherigen forstlichen Produktivitätsmodellen für den Maschineneinsatz wurde der Faktor Mensch, welcher einen wichtigen, bisher jedoch weitestgehend unbekannten Einfluss auf die Leistung hat, vernachlässigt. Ziel der vorliegenden Untersuchung ist es daher, den menschlichen Einfluss auf die Leistung von Harvestersystemen quantitativ zu erfassen und ihn in Produktivitätsmodelle einzubauen. Die Untersuchungsgrundlage bilden Leistungsmessungen, die mit vier verschiedenen Datenerhebungsverfahren an bis zu 32 Fahrern erfolgten. Neben einer neu entwickelten, sensorgestützten, semiautomatischen Zeitstudienmessung fand die Auswertung von summarischen Bordcomputer-Bestandesdaten über einen Zeitraum von drei Jahren Anwendung. Weiterhin erfolgte die (Weiter-)Entwicklung eines standardisierten Parcourstests, welcher auf einer Freifläche durchgeführt wird sowie eine Beurteilung der Leistung der Harvesterfahrer durch Gutachter. Alle vier Verfahren wurden miteinander verglichen und auf ihre Treffsicherheit und Aussagefähigkeit hin überprüft. Dabei konnten signifikante Korrelationen zwischen allen vier Datenerhebungsverfahren nachgewiesen werden, was eine Umrechnung untereinander grundsätzlich zulässt. Im Rahmen dieser Untersuchungen konnte die Vermutung quantitativ bestätigt werden, dass große, signifikant unterschiedliche Leistungshergaben zwischen den verschiedenen Harvesterfahrern existieren. Dies gilt nicht nur für den Vergleich zwischen so genannten „unerfahrenen“ und „erfahrenen“ Maschinenführern. Auch zwischen schon lange auf den Erntemaschinen arbeitenden Fahrern ist ein Leistungsunterschied von bis zu 80% zu verzeichnen. Somit ist die Beachtung des Parameters „Mensch“ für präzise Produktivitätsmodelle zwingend erforderlich. Der ursprüngliche Lösungsansatz, ein allgemein gültiges Produktivitätsmodell zu entwickeln, in dem der Einfluss des Menschen berücksichtigt wird, wurde aufgrund von Informationsdefiziten sowie zu starken Unterschieden und Komplexität der vorhandenen Modelle verworfen. Mit dem neu gewählten Lösungsansatz, der die Bestimmung eines Leistungswertes für jeden Fahrer vorsieht, ist es nun möglich, ein beliebig erstelltes Produktivitätsmodell linear auf ein Basisniveau zu normieren. Die Multiplikation des normierten Modells mit dem Leistungswert eines Fahrers ermöglicht es, die wahrscheinlich von ihm zu erwartende Produktivität zu berechnen. Dieser Wert kann auf verschiedene Weisen erhoben werden. Als Ergebnis dieser Arbeit kann dafür der entwickelte, schnell und einfach durchzuführende Parcourstest empfohlen werden. Er erreicht eine ungefähre Treffgenauigkeit von ±10%. Die Untersuchungen wiesen des Weiteren aus, dass beim Harvestereinsatz unter einfachen Umwelt- und Geländebedingungen der Fahrereinfluss auf die Produktivität bei 37% liegt. Er stellt somit nach Baumvolumen des ausscheidenden Bestandes (46%) den zweitwichtigsten Einflussfaktor dar. Die Leistungshergabe des einzelnen Harvesterfahrers ist nicht immer gleich, sondern verändert sich über der Zeit (Lernkurve). Die gemessenen Lerngeschwindigkeiten variieren dabei zwischen den Harvesterfahrern sehr stark. Das Anlernen eines unerfahrenen Harvesterfahrers dauerte bei den untersuchten Probanden im Mittel neun Monate, was einer Minderleistung von ca. 24% über diesen Zeitraum entspricht. Die bisherigen angenommenen Modelle der Lernkurve konnten bestätigt werden. Darüber hinaus zeigten sich Tendenzen, dass die Leistung der Fahrer nach der Lernphase ein konstantes Leistungsniveau erreicht, allerdings bei einer hohen Fehlerabweichung. Durch die Beurteilung und Berücksichtigung der Leistungen der Fahrer steht der Forstwirtschaft ein Werkzeug zur Verfügung, mit dem man in Zukunft die erstellten Produktivitätsmodelle für den Harvestereinsatz genauer auf die jeweiligen individuellen Gegebenheiten des eigenen Betriebes anpassen kann. Die Übertragung des gewählten Lösungsansatzes auf weitere Forstmaschinen, die von Menschen bedient werden, sollte geprüft werden. / Productivity models provide information about the expected performance of a given procedure under specific conditions. In forestry, they are essential to planning and cost estimation. In hitherto existing productivity models of forest machinery, however, the human being as an important yet mostly unknown factor influencing productivity has been disregarded. Therefore, the objectives of this study are the quantification of the human impact on the performance of forest harvesting systems and its integration into productivity models. The study is based on performance measurements collected using four different methods of data acquisition to monitor up to 32 machine operators: (i) a newly developed sensor-based semi-automatic time study, (ii) the extraction of on-board computer data accumulated over a 3-year period, (iii) an improved standardized machinery test course conducted in an open area, and (iv) the expert evaluation of operator performance. The four data acquisition methods were compared and tested for data accuracy and informational value. All correlations between data yielded by each of the four methods were significant, thus in principle allowing for data conversion between data rendered by different acquisition methods. The results of this study quantitatively corroborate the presumption of major, significantly different performances between harvester operators. This holds true not only for the comparison of so-called ‘inexperienced’ and ‘experienced’ machine operators, but also when exclusively comparing experienced operators with each other. A performance difference of up to 80% has been observed between individuals featuring long-term experience in operating harvesting machinery. The integration of the parameter ‘human being’ is thus an imperative for precise productivity models. The original aim of developing a general productivity model accounting for human influence had to be abandoned due to an information deficit, substantial differences between the existing models as well as their inherent complexity. Instead, the new approach of determining a performance indicator for each individual machine operator now allows for the linear standardisation of any productivity model. By multiplying the standardised model with the performance indicator of a particular operator the probable performance to be expected of this operator can be calculated. This value can be determined in various ways. Based on this study, the test course value can be recommended, which was explicitly developed for fast and simple assessment of operator performance and achieves an accuracy of ±10%. The study results show that under favourable environmental conditions and on easy terrain the influence of the machine operator on overall performance amounts to 37%. The human factor is thus second only to the average volume of harvested trees (46%) with respect to influencing performance. The performance of an individual harvester operator is not constant, but changes over time (learning curve). The measured rate of learning largely differed between operators. The initial training of an inexperienced harvester operator took on average nine months, which corresponds to a performance deficiency of approx. 24% throughout this time period. Hitherto developed models of learning curves were corroborated by the study results. Performance levels following the initial training period tended to remain constant over time, but were characterised by large error margins. The evaluation and consideration of operator performance presents a forest management tool which allows for future customization of existing productivity models of harvesting machinery to the specific conditions and economics of any individual forest enterprise. The extrapolation of the presented approach towards quantification and integration of machine operator performance to other human-operated forest machinery needs to be investigated in subsequent studies.

In der Studie wurde untersucht, wie relevant eine durch hohe Milchleistung bedingte höhere Stress- bzw. Stoffwechselbelastung für das Ausbleiben der Fruchtbarkeit bei ansonsten klinisch gesunden Milchkühen ist und inwieweit eine längere freiwillige Wartezeit die Bereitschaft der Kühe für eine wiederholte Trächtigkeit verbessern kann. Die Kühe mit einer freiwilligen Wartezeit von 120 Tagen konnten alle innerhalb von 60 Tagen nach Beendigung der freiwilligen Wartezeit besamt werden, während es in der Vergleichsgruppe nur 92 % waren. Die Trächtigkeitsrate nach der ersten Besamung lag bei 120-tägiger Wartezeit mit 40,7 % um 10,3 % höher als in der Vergleichsgruppe. In der spät besamten Gruppe traten keine embryonalen Fruchtverluste auf, während dieses in der Vergleichsgruppe 8,9 % der Trächtigkeiten betraf. Redaktionsschluss: 26.03.2020

There is an increasing interest in nanostructured and nanocomposite surface finishings for automotive and aerospace applications. The widespread applicability of these novel materials is based on their unique mechanical, physical, and chemical properties. An advantageous production method is the electrocodeposition (ECD) process from metal plating baths containing dispersed nanoparticles. By using this technique, a broad range of substrate sizes and shapes can be coated cost-effectively. However, the prediction of the amount as well the distribution of nanoparticles within the metal film fails frequently. There is no complete understanding of the particle incorporation mechanism. The goal of this research was to improve the fundamental understanding of the ECD mechanism. In order to identify the forces affecting the codeposition behavior of nanoparticles in a metal matrix, the effects of a variety of interrelated process parameters on the composite film formation have been investigated systematically. Nanocomposites containing metal and metal oxide nanoparticles in a nickel matrix have been prepared by means of ECD from two different types of nickel plating baths, an acidic sulfamate (pH 4.3) and an alkaline pyrophosphate bath (pH 9.5). The effect of deposition conditions on the ECD process was investigated utilizing two electrode configurations, viz. a parallel plate electrode (PPE) and impinging jet electrode (IJE) and different deposition techniques, viz. direct current (DC) deposition, both pulse plating (PP) and pulse-reverse plating (PRP). The surface charge and sedimentation behavior of the nanoparticles in these electrolytes were characterized by zeta potential and stability measurements. The surface charge, hydrodynamic diameter and colloidal stability of the nanoparticles in the nickel electrolytes were mainly affected by the composition and pH of the bath. The particles tend to form agglomerates in both nickel baths. Smaller agglomerates and an improved colloidal stability occurred in the case of the alkaline bath. Composites with a maximum particle content of either ~3.6 vol-% of 13 nm Al2O3 or ~10.4 vol-% of 21 nm TiO2 were obtained using a parallel plate electrode and DC deposition conditions. Both jet plating as well as pulse plating resulted in a distinct increase of the particle codeposition. A maximum incorporation of ~12 vol-% of 50 nm Al2O3 particles in a nickel matrix was achieved using an unsubmerged IJE system, while PP and PRP resulted in composites with particle contents up to 11 vol-% of 13 nm Al2O3. The particle incorporation increased with the particle content of the electrolyte for all deposition conditions studied. A beneficial effect on the amount of codeposited particles was found with decreasing average current density. The Al2O3 and TiO2 particles were found to be negatively charged in the alkaline pyrophosphate bath, and positively charged in the acidic sulfamate bath. It could be shown that negatively charged particles codeposited preferentially within the nickel matrix. The effect of PP and PRP conditions, e.g. pulse frequency, duty cycle and value of the peak current density, on the ECD of Ni-Al2O3 composites was studied using rectangular current pulses in the order of milliseconds. In general, low duty cycles and high pulse frequencies resulted in an enhanced particle codeposition. Using the unsubmerged IJE system, the effects of jet flow rate, particle loading and current density on the particle incorporation were studied. Referring to the experimental results from the ECD of 50 nm alumina with nickel using an IJE system, a kinetic model was developed. Therefore, the particle flux to the electrode was derived from an analysis of the total force acting on the particle in front of the electrode. The model took into account the convective diffusion of particles to the electrode surface, and the effect of gravitational and buoyancy forces on the particle flux. The gravitational force was found to be important for the ECD of 300 nm particles, but not for 50 nm particles. The effect of an external magnetic field on the ECD of Co or Fe3O4 nanoparticles in a nickel matrix has been studied for different current densities, particle contents of the electrolyte and magnetic flux density. The particle incorporation showed a distinct dependency on the orientation of an externally applied magnetic field. While the particle incorporation increased in a perpendicular field (perpendicular with regard to the electrode surface), it decreased in a parallel orientation. The influence of the magnetic field on the ECD of magnetic nanoparticles with nickel was explained by the interplay of Lorentz force and magnetophoretic force. The structure and the properties of the nickel matrix were significantly altered due to the codeposition of nanoparticles. The pure nickel deposits from the sulfamate bath exhibited a strong <100> texture, and those from the pyrophosphate bath a strong <110> preferred orientation. With increasing plating current density and particle incorporation, a variation in the crystallite size and a loss of texture was observed. High resolution TEM imaging proved a complete embedding of nanoparticles by the nickel matrix without any voids. In the case of both nickel baths, the Vickers microhardness showed a tendency to increase with the amount of particle incorporation. The enhanced hardness of the composite films was associated with modifications in the microstructure of the nickel matrix as well as with the nanoparticle incorporation. The wear resistance as examined by linear abrasion test increased with decreasing current density and due to the particle incorporation. Furthermore, the incorporation of magnetic nanoparticles resulted in a distinct increase of the magnetic hardness of the nickel matrix.

The aim of this work was to investigate the effects that a magnetic field can induce during the electrodeposition of Ni and Ni-Fe alloys. Special regard was given to mass transport controlled effects. Magnetic field effects on the nucleation and growth of ferromagnetic layers and on the properties of electrodeposited layers (like grain size, texture, morphology or roughness) were investigated. The influence of a magnetic field on the magnetic properties of Ni layers and on the composition of Ni-Fe alloys was also studied. Nucleation and growth of thin Ni layers on gold electrodes under a superimposed magnetic field were analysed in-situ with the Electrochemical Quartz Crystal Microbalance technique. Three theoretical models were chosen for characterizing the Ni nucleation: Scharifker-Hills (SH), Scharifker-Mostany (SM) and Heerman-Tarallo (HT). The AFM images proved that more nuclei appear in a magnetic field in the case that the Lorentz force and the natural convection act in the same direction. From all the models, the HT model gave the best agreement with the AFM results. When the Lorentz force and the natural convection act in the same direction, an increase of the Ni partial current with the magnetic field was obtained. When they act in opposite directions, the Ni current was influenced just at the beginning of deposition (first 10 seconds). At longer times, the magnetic field has no effect on the Ni current. However, the total current (jNi+jHER) decreases with the magnetic field. In the absence of a macroscopic MHD convection, the Ni current decreases with the magnetic field the first 10-15 seconds of deposition. On longer time scales no influence of the magnetic field could be noticed for this configuration. When the magnetic field was applied perpendicular to the electric current, an increase of the hydrogen evolution reaction (HER) with the magnetic flux density was noticed. Hydrogen reduction is mass transport controlled. Therefore, the magnetic field will increase the limiting current of the HER. Optical microscopy images showed that the hydrogen bubbles were circular in the absence of the MHD convection and that they presented a tail when a Lorentz force was present. The direction of the tail depends on the net force induced by the natural and MHD convections. The interplay between the natural and MHD convections proved to be important during Ni-Fe alloy deposition, too. When the Lorentz force and the natural convection act in the same direction, an increase of the Fe content of the alloys with the magnetic field was observed. When the Lorentz force was perpendicular to the natural convection, no significant changes were observed in the composition of the layers. The alloy composition did not change with the magnetic field when the electric current was parallel to the magnetic field lines. Two surfactants were used in the case that Ni was electrodeposited from a sulfamate bath: SDS and sulfirol 8. The Ni layers obtained from a sulfamate bath with sulfirol 8 presented larger grains compared to the layers deposited from a bath free of surfactants. This increase of the grain size was attributed to the incorporation of the surfactant in the deposit. Coarser layers were obtained in a magnetic field (applied perpendicular to the electric current) when the electrodeposition was done from an electrolyte with surfactants. The number of grains increased with the magnetic field for the Ni layers electrodeposited from a bath free of surfactants and for a bath with SDS. As a consequence, the grain size decreased. In the case of the electrolyte with sulfirol 8, the number of grains decreased with the magnetic field, and their size increased. For the Ni-Fe alloys, which contained less than 10 at% Fe, the preferred crystalline orientation changes from (220), in the absence of a magnetic field, to (111), (when the magnetic field was applied perpendicular to the electric current). When the magnetic field lines were parallel to the electric current, both the (111) and (220) textures were preferred in almost the same proportion. As a general conclusion of this work it can be said that by choosing the right experimental condition, one can improve the morphology and the properties of the deposited layers by applying a magnetic field. At the same time, the mass transport processes can be influenced by a magnetic field.