本篇論文驗證SABR模型與SABR-LMM模型的動態設定與市場選擇權價格下標的未來價格之隱含分配是否一致，判斷準則為SABR模型與SABR-LMM模型校準出的參數是否符合市場直覺。根據實證結果答案是肯定的，所以在SABR模型與SABR-LMM模型下評價選擇權不需要再做任何的主觀判斷或調整。此外本篇論文對於SABR模型與SABR-LMM模型的參數校準方法做了詳細的分析，並且清楚的閳述SABR模型與SABR-LMM模型的模型直覺。

The topic of this thesis is to solve spatial heterogenity in forestry models by means of utilizing linear mixed-effects models (LMM) and geographically weighted regression (GWR) to model a height-diameter curve. Both of these methods were previously tested, and they have a high potential to reduce the minimal necessary amount of data needed, and at the same time, increase precision. The data come from VŠLP Křtiny, LÚ Borky, a complex of forests utilized for educational purposes by Mendel’s university in Brno. We choosed beech as the model species. We split the data into training and validation sets for fitting, and consequent prediction assessment. Resulting models were compared with OLS fitted global model. Local OLS models were unreliable, as only a very few measured trees were available for each plot. Results were different for GWR and LMM. GWR models failed at prediction, but had good results on training plots, especially considering the reduction of autocorrelation of model residuals. LMM provided the best results for both training and validation plots

No / This paper investigates the impact of corporate risk levels on aggregated, voluntary and mandatory risk disclosures in the annual report narratives of UK non-financial listed companies. We find that firms characterised by higher levels of systematic, financing risks and risk-adjusted returns and those with lower levels of stock return variability are likely to exhibit significantly higher levels of aggregated and voluntary risk disclosures. The results also show that firms of large size, high dividend-yield, high board independence, low (high) insider (outsider) ownership, and effective audit environments are likely to exhibit higher levels of aggregated and voluntary risk disclosures than other firms. Similarly, mandatory risk disclosures are influenced positively by firm size, dividend-yield and board independence and negatively by high leverage. The results suggest that managers of firms exhibiting greater compliance with mandatory regulations have a greater propensity to make voluntary risk disclosures. When we distinguish between high- and low-risk firms, we find that high-risk firms appear to be more sensitive to underlying risk levels, resulting in more disclosure of both voluntary and mandatory risk information than in the case of low-risk firms. The results generally support the present UK emphasis on encouraging rather than mandating risk disclosure. Nevertheless, under this regime, the voluntary risk disclosures of some firms, e.g., those characterised by higher-volatility market returns, do not reflect their underlying risk levels.

Methylmercury (MeHg) is a neurotoxic compound that threatens the well-being of humans and wildlife. It is formed through the methylation of inorganic mercury (HgII) under suboxic/anoxic conditions in soils, sediment and waters. The chemical speciation of HgII, including specific HgII species in aqueous and solid/adsorbed phases, plays a key role in MeHg formation. Chemical forms of HgII which have been reported to be available for uptake in methylating bacteria include neutral HgII–sulfide complexes, HgII complexes with specific low molecular mass (LMM) thiols, and nanoparticulate HgS(s). Accurate determination of the chemical speciation of HgII is thus crucial when elucidating the mechanism of MeHg formation. The concentration of HgII–LMM thiols complexes is predicted to be extremely low (sub fM range). Current analytical methods do not allow direct quantification of HgII complexes due to the very low concentration of these complexes, and therefore determination rely on thermodynamic modeling. Accurate stability constants for HgII–LMM thiols complexes and quantification of LMM thiol ligands in environments are thus required to precisely determine the concentration of such complexes. In this thesis, a novel analytical method was developed based on online pre-concentration coupled with liquid chromatography tandem mass spectrometry to determine the concentration of 16 LMM thiols (Paper I). This method was successful in detecting 8 LMM thiols in boreal wetland porewaters, with mercaptoacetic acid and cysteine being the most abundant. The total concentration of individual detected LMM thiols ranged from sub nM (LOD=0.1 nM) to 77 nM. Moreover, the stability constant (β2) for HgII complexes with 15 LMM thiols were directly determined for the first time by competing ligand exchange experiments combined with liquid chromatography ICPMS analysis (Paper II). Values of log β2 for the reaction Hg2+ + 2LMM-RS- = Hg(LMM-RS)2 ranged from 34.6 for. Based on the determined constants of Hg(LMM-RS)2 complexes and state-of-the-art constants from literature for other HgII complexes, we established comprehensive thermodynamic speciation models for MeHg and HgII in boreal wetlands (Paper III). The speciation of HgII was coupled with the HgII methylation rate constant (km) determined with different enriched Hg isotope tracers (Paper IV). There was a good correlation (R2=0.88) between the km determined by a HgII(aq) tracer added as Hg(NO3)2 with high bioavailability and a tracer where HgII was bond to thiol groups in natural organic matter (HgII-NOM(ads)) and has a lower bioavailability. The HgII(aq) tracer was consistently methylated at 5 times higher rate than the HgII-NOM(ads) tracer. A good correlation was observed between the concentration of biologically produced LMM thiols and km in the boreal wetlands. In a mesocosm study of estuarine sediment-brackish water systems, increased concentration of phytoplankton chlorophyll α due to macro nutrient additions led to an increase in HgII methylation rate of the HgII(aq) but not of the HgII-NOM(ads) tracer or ambient HgII species (Paper V). Furthermore, simulated newly deposited HgII species from atmospheric and terrestrial sources were exhibited significantly higher HgII methylation rates when compared with simulated aged sediment HgII pools. Through the development and adoption of novel analytical methods, this thesis reveals the significance of LMM thiols in Hg biogeochemistry by precise determination of HgII–LMM thiol complexes in natural environmental systems.

Gemäß der Gefährdungsbeurteilung sind die Arbeitsplätze hinsichtlich ihrer Gefährdungsfaktoren zu bewerten. Bestandteil dessen ist ebenso die Beurteilung der physischen Belastungen. Diese können auf unterschiedliche Weise erfasst werden. In der betrieblichen Praxis werden sehr oft die Leitmerkmalmethoden (LMM) zur Beurteilung der physischen Belastung angewendet. Im Zuge des MEGAPHYS Projekts wurden bestehende LMM überarbeitet sowie neue LMM zur Erfassung weiterer Arbeitsprozesse entwickelt. Im Verlauf der vorliegenden Masterthesis wurden die physischen Belastungen in den Arbeitsbereichen des Entladens und Beladens beispielhaft mit Hilfe der LMM ermittelt. Die Ergebnisse zeigen, dass eine hohe biomechanische Belastung in bei den Arbeitsbereichen vorhanden ist. Das subjektive Empfinden der Mitarbeiter wurde anhand eines selbst entwickelten Fragebogens ermittelt. Die körperlichen Beschwerden und das Empfinden hinsichtlich der Arbeitsorganisation standen im Mittelpunkt dieser Erhebung. Anschließend wurden Maßnahmen, die zu einer Reduktion der physischen Belastung führen, abgeleitet. Hierfür wurde ein Katalog an möglichen Maßnahmen entwickelt, welcher der Geschäftsleitung vorgestellt werden kann. Zum Abschluss wurde eine Verfahrensanweisung für das Erstellen der LMM für den Entlader und Belader erstellt. Anhand dieser sollen die Fachkräfte für Arbeitssicherheit bei zukünftig die örtlichen Erhebungen der physischen Belastung mit Hilfe der LMM selbstständig durchführen. Hierfür wurde zugleich eine LMM Multi E erstellt, anhand welcher mehr als 24 Teiltätigkeiten einer Belastungsart erfasst und automatisch berechnet werden. / Based on the concept of risk assessment, workplaces are to be evaluated concerning existing risk factors. This also includes the assessment of physical strain. Physical strain can be made measurable in different ways. In operational practice, the Key Indactor Method (KIM) is very often used to assess physical strain. Within the scope of the MEGAPHYS project, existing KIMs were revised and new KIMs developed to record additional work processes. The physical strains pertaining to unloading and loading tasks were determined based on the KIM. The results show that a high biomechanical strain is present in both work areas. The subjective feeling of the employees was assessed using a self-developed questionnaire. The physical complaints and the perception regarding the established work procedures were the focus of this survey. Subsequently, measures leading to a reduction in physical strain were derived from the results of the study. To limit the effects of physical strain, a catalog of possible measures to be presented to the management was developed. Finally, handling instructions were drawn up for the preparation of the KIM for unloading and loading tasks. Based on these instructions, the occupational safety specialists at are to independently carry out local surveys examining physical strain with the help of the KIM. A KIM Multi E was compiled for this purpose, where more than 24 partial activities of a loading task type were recorded and automatically calculated.

The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer¿s Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment. / Universiti Utara Malaysia and Ministry of Higher Education of Malaysia

The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer's Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment.