The heavy rainfall event in August 2002 in Saxony/Germany caused the break of a flood retaining basin in a valley of the Erzgebirge Mountains. The rainfall event with ists hyrologic characteristics and dam break event were analysed and an outflow hydrograph was determing. The propagation of the dam break flood wave in the valleyas of the Briesnitz and Müglitz Rivers has been simulated. Calculated values were compared with some observed data.

Eigentümer und Betreiber von Anlgen mit einem großen Gefahrenpotential sind gehalten, den zuständigen Behörden Auskunft über mögliche Folgen eines Störfalles zu erteilen. Für den unwahrscheinlichen Fall des Bruches eines Absperrrbauwerkes können diesbezügliche Informationen erarbeitet werden.

Robust parameter estimation and pivotal inference is crucial for credible statistical conclusions. This thesis addresses these issues in three contexts: long-memory parameter estimation robust to low frequency nonstationary contamination, long-memory properties of financial time series, and inference on structural changes in a joint segmented trend with heterogeneous noise. Chapter 1 considers robust estimation of the long-memory parameter allowing for a wide collection of contamination processes, in particular low frequency nonstationary processes such as random level shifts. We propose a robust modified local-Whittle estimator and show it has the usual asymptotic distribution. We also provide modifications to further account for short-memory dynamics and additive noise. The proposed estimator provides substantial efficiency gains compared to existing methods in the presence of contaminations, without sacrificing efficiency when these are absent. Chapter 2 applies the modified local-Whittle estimator to various volatilities series for stock indices and exchange rates to robustly estimate the long-memory parameter. Our findings suggest that all series are a combination of long and short-memory processes and random level shifts, with the magnitude of each component varying across series. Our results contrast with the view that long-memory is the dominant feature. Chapter 3 is concerned with pivotal inference about structural changes in a joint segmented trend with heterogeneous noise. We provide tests for changes in the slope and the variance of the noise valid when both may be present, each allowed to occur at different dates. We suggest procedures for four testing problems.

The dissertation consists of three chapters on econometric methods related to parameter instability, forecasting and long memory. The first chapter introduces a new frequentist-based approach to forecast time series in the presence of in and out-of-sample breaks in the parameters. We model the parameters as random level shift (RLS) processes and introduce two features to make the changes in parameters forecastable. The first models the probability of shifts according to some covariates. The second incorporates a built-in mean reversion mechanism to the time path of the parameters. Our model can be cast into a non-linear non-Gaussian state-space framework. We use particle filtering and Monte Carlo expectation maximization algorithms to construct the estimates. We compare the forecasting performance with several alternative methods for different series. In all cases, our method allows substantial gains in forecasting accuracy. The second chapter extends the RLS model of Lu and Perron (2010) for the volatility of asset prices. The extensions are in two directions: a) we specify a time-varying probability of shifts as a function of large negative lagged returns; b) we incorporate a mean reverting mechanism so that the sign and magnitude of the jump component change according to the deviations of past jumps from their long run mean. We estimate the model using daily data on four major stock market indices. Compared to competing models, the modified RLS model yields the smallest mean square forecast errors overall. The third chapter proposes a method of inference about the mean or slope of a time trend that is robust to the unknown order of fractional integration of the errors. Our tests have the standard asymptotic normal distribution irrespective of the value of the long-memory parameter. Our procedure is based on using quasi-differences of the data and regressors based on a consistent estimate of the long-memory parameter obtained from the residuals of a least-squares regression. We use the exact local-Whittle estimator proposed by Shimotsu (2010). Simulation results show that our procedure delivers tests with good finite sample size and power, including cases with strong short-term correlations.

One of the main reasons to why a membership in the European Union (EU) is so attractive for prospect countries are the free trade agreements the membership entails. The free trade agreements mean that the whole EU opens up as one big market, where tariffs and tolls are no longer an obstacle to trade for its members. Therefore, this thesis analyses whether EU membership actually yields a positive effect on member’s trade. The time series analysis is based on a three-country sample consisting of Poland, Romania, and Croatia during the time period from 2001 to 2018. By applying multiple and Chow’s breakpoint tests, and country-wise and a pooled cross-section analysis model, we examine if the accession to EU impacts each country’s trade volumes. The results indicate that becoming a member of the European Union does not necessarily have a significant effect on Poland’s, Romania’s, or Croatia’s trade even if it is positive.

Due to the high efficiency and productivity of continuous casting process, this method has been the most employed process to produce steel in past decades. The need to improve and optimize the finished product made it essential to gain more knowledge about the process, types of defects that may occur and the reasons for them. Moreover, the solutions for reducing the shortcomings in continuous casting process have been an intriguing subject to study. Many attempts have been done in order to reach this goal. Understanding, determining and optimizing the mould flux slag properties is especially important, since it plays an important and significant role in this process. For this, it is of outmost importance to acquire more knowledge about different properties of mould flux powders. Hence, there has been a world wide effort to measure and model the properties of mould flux properties, such as liquidus and solidus temperatures, heat capacity, enthalpy, thermal expansion, density, viscosity, electrical conductivity, surface tension and thermal conductivity. This thesis presents a brief review on continuous casting process, mould flux powder and its properties and characteristics. Furthermore, it focuses on the thermo-physical properties of mould fluxes. In present work, different industrial mould flux powders have been analyzed to measure their viscosity, break temperature, physical properties such as density, flowablity of powder, slag structure and chemical composition. The experimental data have been compared to some of the most commonly used models such as Riboud model, Urbain model, Iida model and KTH model.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Planning of resources is a powerful tool in the field of supply chain management and control and in general. Global large-scale companies and enterprises have this implemented in their planning processes. Today, experts in the subject have found issues regarding the implementation of such tools in small- and medium-sized enterprises (SMEs). Therefore, this paper aims to develop an application for the methodology of continual improvement of processes, referred to as the Deming cycle or Plan–Do–Check–Act (PDCA), which adapts to continuous improvements of processes and products in SMEs. The methodology was modeled in a SME dedicated to manufacture and distribution of wine and products (wine and Pisco). The model was simulated through a simulation software, obtaining results of improvement regarding problems like break of stock, taking into account the satisfaction of the client, productivity in the delivery, and shipment time.

Hutchinson-Gilford progeria syndrome (HGPS) is a rare genetic disorder because of a LMNA gene mutation that produces a mutant lamin A protein (progerin). Progerin also has been correlated to physiological aging and related diseases. However, how progerin causes the progeria remains unknown. Here, we report that the large subunit (RFC1) of replication factor C is cleaved in HGPS cells, leading to the production of a truncated RFC1 of ∼75kDa, which appears to be defective in loading proliferating cell nuclear antigen (PCNA) and pol δ onto DNA for replication. Interestingly, the cleavage can be inhibited by a serine protease inhibitor, suggesting that RFC1 is cleaved by a serine protease. Because of the crucial role of RFC in DNA replication, our findings provide a mechanistic interpretation for the observed early replicative arrest and premature aging phenotypes of HPGS and may lead to novel strategies in HGPS treatment. Furthermore, this unique truncated form of RFC1 may serve as a potential marker for HGPS.

RPA (replication protein A) is an essential factor for DNA DSB (double-strand break) repair and cell cycle checkpoint activation. The 32 kDa subunit of RPA undergoes hyperphosphorylation in response to cellular genotoxic insults. However, the potential involvement of hyperphosphorylated RPA in DSB repair and check-point activation remains unclear. Using co-immunoprecipitation assays, we showed that cellular interaction of RPA with two DSB repair factors, Rad51 and Rad52, was predominantly mediated by the hyperphosphorylated species of RPA in cells after UV and camptothecin treatment. Moreover, Rad51 and Rad52 displayed higher affinity for the hyperphosphorylated RPA than native RPA in an in vitro binding assay. Checkpoint kinase ATR (ataxia telangiectasia mutated and Rad3-related) also interacted more efficiently with the hyperphosphorylated RPA than with native RPA following DNA damage. Consistently, immunofluorescence microscopy demonstrated that the hyperphosphorylated RPA was able to co-localize with Rad52 and ATR to form significant nuclear foci in cells. Our results suggest that hyperphosphorylated RPA is preferentially localized to DSB repair and the DNA damage checkpoint complexes in response to DNA damage.

Non-homologous end joining (NHEJ) is one of two pathways responsible for the repair of double-strand breaks in eukaryotic cells. The mechanism involves the alignment of broken DNA ends with minimal homology, fill in of short gaps by DNA polymerase(s), and ligation by XRCC4-DNA ligase IV complex. The gap-filling polymerase has not yet been positively identified, but recent biochemical studies have implicated DNA polymerase λ (pol λ), a novel DNA polymerase that has been assigned to the pol X family, in this process. Here we demonstrate that purified pol λ can efficiently catalyze gap-filling synthesis on DNA substrates mimicking NHEJ. By designing two truncated forms of pol λ, we also show that the unique proline-rich region in pol λ plays a role in limiting strand displacement synthesis, a feature that may help its participation in in vivo NHEJ. Moreover, pol λ interacts with XRCC4-DNA ligase IV via its N-terminal BRCT domain and the interaction stimulates the DNA synthesis activity of pol λ. Taken together, these data strongly support that pol λ functions in DNA polymerization events during NHEJ.