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Determinants of earnings forecast error, earnings forecast revision and earnings forecast accuracy
(2012)
Earnings forecasts are ubiquitous in today’s financial markets. They are essential indicators of future firm performance and a starting point for firm valuation. Extremely inaccurate and overoptimistic forecasts during the most recent financial crisis have raised serious doubts regarding the reliability of such forecasts. This thesis therefore investigates new determinants of forecast errors and accuracy. In addition, new determinants of forecast revisions are examined. More specifically, the thesis answers the following questions: 1) How do analyst incentives lead to forecast errors? 2) How do changes in analyst incentives lead to forecast revisions?, and 3) What factors drive differences in forecast accuracy?
Due to the interfering effects of acetic acid in many fermentation processes, a gas-diffusion technique was developed for the online determination of acetic acid. The measurements were accomplished with a flow diffusion analysis (FDA) unit from the TRACE Analytics GmbH, Braunschweig, Germany. The diffusion analysis is based on the UV-absorbance of acetic acid at 205 nm. The measurement was achieved by the separation of an acceptor and a carrier stream (acidified fermentation broth) using a gas permeable polytetrafluoroethylene (PTFE) membrane, whereby broth constituents that would otherwise disturb the UV-measurement of acetic acid, are held back efficiently. Merely, the fermentation by-products, e.g. formic acid, is capable of diffusing through the membrane. While formic acid can disturb the measurement, carbon dioxide does not absorb at 205 nm. The method operates with time-dependent sample enrichment. During the analysis, a small volume of the acceptor stream is stopped for a defined time interval in the acceptor chamber. During this period, the gaseous acetic acid diffuses through the membrane and is enriched in the acceptor chamber. Subsequently after the enrichment, the acceptor stream flows through a UV-detector. The intensity of the signal is proportional to the acetic acid concentration. Online measurements in bioreactors via a sterile filtration probe have been accomplished. A linear calibration in the range of 0.5–5.0 g/L acetic acid with a relative standard deviation of <5 % was obtained. A sampling rate of 8 samples per hour was possible. The system was applied for the determination of acetic acid in E. coli fermentation broth. The instrument is easy to clean, very user-friendly and does not require any toxic or expensive reagents.
On-line monitoring of the metabolic activity of microorganisms involved in intermediate stages of biogas production plays an important role to avoid undesirable “down times” during the biogas production. In order to control this process, an on-chip differential measuring system based on the light-addressable potentiometric sensor (LAPS) principle combined with a 3D-printed multi-chamber structure has been realized. As a test microorganism, Escherichia coli K12 (E. coli K12) were used for cell-based measurements. Multi-chamber structures were developed to determine the metabolic activity of E. coli K12 in suspension for a different number of cells, responding to the addition of a constant or variable amount of glucose concentrations, enabling differential and simultaneous measurements.
Determination of the frictional coefficient of the implant-antler interface : experimental approach
(2012)
The similar bone structure of reindeer antler to human bone permits studying the osseointegration of dental implants in the jawbone. As the friction is one of the major factors that have a significant influence on the initial stability of immediately loaded dental implants, it is essential to define the frictional coefficient of the implant-antler interface. In this study, the kinetic frictional forces at the implant-antler interface were measured experimentally using an optomechanical setup and a stepping motor controller under different axial loads and sliding velocities. The corresponding mean values of the static and kinetic frictional coefficients were within the range of 0.5–0.7 and 0.3–0.5, respectively. An increase in the frictional forces with increasing applied axial loads was registered. The measurements showed an evidence of a decrease in the magnitude of the frictional coefficient with increasing sliding velocity. The results of this study provide a considerable assessment to clarify the suitable frictional coefficient to be used in the finite element contact analysis of antler specimens.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
The capacitive electrolyte–insulator–semiconductor (EIS) structure is a typical device based on a field-effect sensor platform. With a simple silicon-based structure, EIS have been useful for several sensing applications, especially with incorporation of nanostructured films to modulate the ionic transport and the flat-band potential. In this paper, we report on ion transport and changes in flat-band potential in EIS sensors made with layer-by-layer films containing poly(amidoamine) (PAMAM) dendrimer and single-walled carbon nanotubes (SWNTs) adsorbed on p-Si/SiO 2 /Ta 2 O 5 chips with an Al ohmic contact. The impedance spectra were fitted using an equivalent circuit model, from which we could determine parameters such as the double-layer capacitance. This capacitance decreased with the number of bilayers owing to space charge accumulated at the electrolyte–insulator interface, up to three PAMAM/SWNTs bilayers, after which it stabilized. The charge-transfer resistance was also minimum for three bilayers, thus indicating that this is the ideal architecture for an optimized EIS performance. The understanding of the influence of nanostructures and the fine control of operation parameters pave the way for optimizing the design and performance of new EIS sensors.
Booster stations can fulfill a varying pressure demand with high energy-efficiency, because individual pumps can be deactivated at smaller loads. Although this is a seemingly simple approach, it is not easy to decide precisely when to activate or deactivate pumps. Contemporary activation controls derive the switching points from the current volume flow through the system. However, it is not measured directly for various reasons. Instead, the controller estimates the flow based on other system properties. This causes further uncertainty for the switching decision. In this paper, we present a method to find a robust, yet energy-efficient activation strategy.