Aggregation of Hospital Business Processes

There are estimates that up to 30% of hospital costs are due to inefficiently coordinated hospital processes. As a result many hospitals have tried to model and to reengineer their business processes. These efforts have very often been abandoned, because the normally constructed total models of hospital processes could hardly cope with the rapid technological and medical progress as well as with changing staff. We discuss approaches for a qualitative and quantitative process modularization which improve the understanding of processes and enables better planned simulations. Various methods are discussed which allow a qualitative modularization on the basis of a disaggregated process graph. To cope with this modularization numerically simple semi-stochastic formulas are developed for the calculation of expected values and variances of cycle times and costs from micro-data up to the modular level. Thus a qualitative as well as quantitative discussion of hospital business processes on the modular level become possible.OR in health care service, graph theory, business process reengineering, stochastic processes, simulation

Counting Complexity for Reasoning in Abstract Argumentation

In this paper, we consider counting and projected model counting of extensions in abstract argumentation for various semantics. When asking for projected counts we are interested in counting the number of extensions of a given argumentation framework while multiple extensions that are identical when restricted to the projected arguments count as only one projected extension. We establish classical complexity results and parameterized complexity results when the problems are parameterized by treewidth of the undirected argumentation graph. To obtain upper bounds for counting projected extensions, we introduce novel algorithms that exploit small treewidth of the undirected argumentation graph of the input instance by dynamic programming (DP). Our algorithms run in time double or triple exponential in the treewidth depending on the considered semantics. Finally, we take the exponential time hypothesis (ETH) into account and establish lower bounds of bounded treewidth algorithms for counting extensions and projected extension.Comment: Extended version of a paper published at AAAI-1

Implications of molecular interactions for protein structure, function and design

Protein structures are kept in a delicate balance of stability by the interactions of the amino acid residues among themselves, the solvent and other molecules. On one hand they must be stable enough not to unfold, on the other hand they must be mobile enough to undergo structural changes if necessary. Only thus they are able to fulfil their various functions in living organisms, e.g. the catalytic function of an enzyme, protein-ligand recognition or the rapid reorganisation of the cytoskeleton. In this work, we have investigated the contributions of such molecular interactions to protein structure in a functional enzyme, cystathionine [beta]-synthase. We have further analysed the contribution of ionic interactions to the stability of various designed peptides which form coiled coils. Finally, we have collected a statistics of electrostatic interactions in naturally occurring coiled coils to find out which ionic interactions significantly contribute to a successful formation of coiled coils. The results have important implications for the design of coiled-coil proteins. Cystathionine [beta]-synthase is an enzyme of the transsulfuration pathway in eukaryotic cells which catalyses the condensation of serine and homocysteine to yield cystathionine in a pyridoxal 5'-phosphate-dependent [beta]-replacement reaction. The human enzyme also contains heme as a second cofactor which is not required for catalysis. We have solved the structure of the catalytic domain of human cystathionine [beta]-synthase by X-ray crystallography. This is the first protein structure containing a heme binding motif where the iron of the heme is coordinated by a histidine and a cysteine residue. We have also discovered an oxidoreductase active site motif on the surface which might play a role in enzyme regulation. There are more than 100 point mutations known in this enzyme which can cause homocysteinurea disease in humans, characterised by dislocated eye lenses, skeletal problems, vascular disease and mental retardation. We have mapped the mutations in the catalytic domain on the structure and were able to find an explanation for the harmful effect of some mutations by analysing the molecular interactions of the concerned residues. Coiled coils are a simple and regular structural motif in proteins consisting of [alpha]-helices which coil around each other. They can form dimers, trimers, tetramers and pentamers depending on their amino acid sequence and the environment. The principles and factors which lead to this specific fold can therefore be studied in detail. The stability of coiled coils is mainly achieved by the systematic packing of the side chains of the residues at the interface between the helices, called knobs-into-holes packing. We could show, however, that a complex network of inter- and intrahelical salt bridges also contributes significantly to coiled-coil stability by designing short peptides which form dimeric or trimeric coiled coils. The importance of the ionic interactions could be demonstrated by removing a single interhelical salt bridge which abolished the formation of the coiled coil. The peptides were characterised by circular dichroism, analytical ultracentrifugation and X-ray crystallography. We have developed the computer program SBSCC to collect a statistics of intrahelical salt bridges in pure [alpha]-helices and coiled coils from the protein database. We have identified the salt-bridge configurations that have the highest probability to form the ionic interaction and which occur most frequently in [alpha]-helices and coiled coils. We have found interesting differences between [alpha]-helices, parallel and antiparallel 2-stranded coiled-coils with important implications for the coiled-coil design. We have found a positive correlation between the probabilities of different salt-bridge configurations to form the ionic interaction and their frequencies in [alpha]-helices and coiled coils. This indicates that nature relies indeed on ionic interactions to stabilise [alpha]-helices and coiled coils, an issue which was hitherto controversially discussed

Decomposing protein sequence space into domains

Domains are the structural subunits of proteins. They are considered to be the basic units of folding, evolution and function. Understanding the domain structure helps to improve the functional annotation of proteins, tertiary protein structure prediction, protein engineering and protein mutagenesis . Domains are the minimal functional units of a protein. To elucidate the cellular functions of a protein we need to understand the molecular functions of its domains. Protein sequences are annotated by the matches to domains in domain family databases such as Pfam, SCOP or CATH. However, existing domain databases cover less than half of the known sequence space and encompass only a small fraction of all protein domain families. Here, we developed an algorithm based on a Bayesian statistical model, called Pdom, with which we can consistently decompose the entire protein sequence space into its evolutionary units. Pdom predicts domains on the basis of an all-against-all search of protein Hidden Markov models with HHblits. An alignment of HHblits indicate the shared homologous region between the query and a template. This shared homologous region encompasses usually one or multiple domains shared by query and template. We can infer the domain borders of the query from its alignments to different templates. For this purpose, we can use the probabilities for the beginning and ending of an homologous region calculated by HHblits. HHblits is an iterative protein homology detection tool that is more sensitive, generates more accurate alignments and is faster than its best competitors, PSI-BLAST and HMMER3. HHblits searches with a query Hidden Markov Model (HMM) against a database of HMMs of multiple sequence alignments. For the clustering of the Uniprot sequence database to the uniprot20 HMM database, we expect the sequences within a cluster to cover each other by at least 90%. Therefore, the HMMs of the uniprot20 are very conservative with few mostly very similar sequences contained in each cluster. For the domain decomposition with Pdom we wanted to increase the sensitivity of HHblits to detect more remote homologs. For this purpose, we enriched our database clusters by jumpstarting HHblits with each cluster alignment in the uniprot20 and adding significant matches to the cluster alignments. The resulting uniprot_boost1 database (boost1 for one iteration with HHblits) has ~14x more sequences per cluster than uniprot20. The effective number of sequences is raised from 1.18 to 3.78. We developed efficient sparse compression and alignment handling algorithms that keep memory size nearly the same. HHblits finds with the uniprot_boost1 ~20% more homologs in three iterations compared to the uniprot20. The alignments of HHblits with the uniprot_boost1 have a 11.32% and 17.39% increased per-residue precision and sensitivity, respectively. The structural models of global alignments with fixed query template pairs against the uniprot_boost1 have on average a 4.9% higher TMscore with the native structure. Especially, the structural models of queries with a TMscore <= 0.3 in the uniprot20 can be improved with the uniprot_boost1. In a simple homology modeling pipeline with free template selection we showed that the TMscore of models built with the uniprot_boost1 is on average 4.9% higher. In summary, HHblits finds with the diversity-enriched uniprot_boost1 database more homologs and generates more accurate alignments that lead to better structure models than with the uniprot20. It further widens the gap to HHblits' competitors HMMER and PSI-BLAST. We showed that the performance of HHblits with the uniprot_boost1 can be transferred to the downstream application of homology modeling. The uniprot_boost1 is capable to become a default database for HHblits and may impact sequence-based predictions of evolutionarily conserved properties, such as secondary or tertiary structure, disorder, catalytic sites, post-translational modifications, short linear motifs, or interaction interface. Protein domains occur in different proteins with different protein architectures. Pairwise alignments of a query protein against multiple homologous template proteins reveal with the different alignment start and end positions the boundaries of protein domains in the query protein. Some of those alignments encompass a single domain, others might encompass multiple domains. On the basis of an all-against-all search of HHblits within the uniprot_boost1, we decomposed the protein sequence space into its domains with Pdom. We compared the predictions of Pdom, ADDA and Pfam to SCOP annotations mapped onto full length protein sequences. ADDA applies the same fundamental idea as Pdom. ADDA predicts domains on the basis of an all-against-all search of protein sequences with BLAST. Pfam uses manually curated seed alignments that incorporate available data from literature. On average ADDA covers 32%, Pfam covers 80% and Pdom covers 75% of the reference domain annotations. ADDA predicts domain start and end sites within 20 residues in 15% of the reference domain start and end sites. Pfam annotates domain start sites within 20 residues in 67% of the reference domain start sites and annotates domain end sites within 20 residues in 58% of the reference domain end sites. Pdom predicts domain start sites within 20 residues in 50% of the reference domain start sites and predicts domain end sites within 20 residues in 45% of the reference domain end sites. The seed alignments of Pfam have a very high quality due to the manual curation effort. But those seed alignments are limited to domains analyzed in literature. With our fully automatic approach in Pdom we are able to find new domains in the protein sequence space. The clustered database of Pdom's domain predictions, UniDom, has the potential to become a fundamental tool for homology-based protein sequence annotation efforts

Uncertainty Analysis and Toxicity Classification in Life-Cycle Assessment Using the Case-study of Gas Purification Systems

This comprehensive thesis structures the decision-making process for making a choice of the most adequate gas purification system (GasPS). Various gas purification technologies (biofilter, activated carbon filter, catalytic oxidation, thermo-reactor) have been evaluated based on an industrial case-study for waste gas streams. The ecological performance was quantified using the life-cycle impact assessment methods Eco-Indicator 95 and Swiss Ecopoints (environmental scarcities). Both life-cycle impact assessment methods have been improved by a new classification method for volatile organic compounds (VOCs) which considers the environmental fate and exposure as well as the toxicity of these compounds. For life-cycle assessment, a detailed quantitative uncertainty analysis was carried out using Monte Carlo simulation. Based on the uncertainty analysis, developing statements about the significance of the results and of relative differences between various GasPS alternatives has been possible. The eco-efficiency of the investigated GasPSs was finally characterised based on four indicators: Net Ecological Benefit (NEBN), Ecological Yield Efficiency (lgEYE), Net Present Value (NPV), and Ecological-Economic Efficiency (EEE

Aggregation of Hospital Business Processes

There are estimates that up to 30% of hospital costs are due to inefficiently coordinated hospital processes. As a result many hospitals have tried to model and to reengineer their business processes. These efforts have very often been abandoned, because the normally constructed total models of hospital processes could hardly cope with the rapid technological and medical progress as well as with changing staff. We discuss approaches for a qualitative and quantitative process modularization which improve the understanding of processes and enables better planned simulations. Various methods are discussed which allow a qualitative modularization on the basis of a disaggregated process graph. To cope with this modularization numerically simple semi-stochastic formulas are developed for the calculation of expected values and variances of cycle times and costs from micro-data up to the modular level. Thus a qualitative as well as quantitative discussion of hospital business processes on the modular level become possible

Invariant prime ideals in equivariant Lazard rings

Let $A$ be an abelian compact Lie group. In this paper we compute the spectrum of invariant prime ideals of the $A$-equivariant Lazard ring, or equivalently the spectrum of points of the moduli stack of $A$-equivariant formal groups. We further show that this spectrum is homeomorphic to the Balmer spectrum of compact $A$-spectra, with the comparison map induced by equivariant complex bordism homology.Comment: 43 pages, comments welcom

Harmonic oscillator model for current- and field-driven magnetic vortices

In experiments the distinction between spin-torque and Oersted-field driven magnetization dynamics is still an open problem. Here, the gyroscopic motion of current- and field-driven magnetic vortices in small thin-film elements is investigated by analytical calculations and by numerical simulations. It is found that for small harmonic excitations the vortex core performs an elliptical rotation around its equilibrium position. The global phase of the rotation and the ratio between the semi-axes are determined by the frequency and the amplitude of the Oersted field and the spin torque