Shared Memory Concurrent System Verification using Kronecker Algebra

The verification of multithreaded software is still a challenge. This comes mainly from the fact that the number of thread interleavings grows exponentially in the number of threads. The idea that thread interleavings can be studied with a matrix calculus is a novel approach in this research area. Our sparse matrix representations of the program are manipulated using a lazy implementation of Kronecker algebra. One goal is the generation of a data structure called Concurrent Program Graph (CPG) which describes all possible interleavings and incorporates synchronization while preserving completeness. We prove that CPGs in general can be represented by sparse adjacency matrices. Thus the number of entries in the matrices is linear in their number of lines. Hence efficient algorithms can be applied to CPGs. In addition, due to synchronization only very small parts of the resulting matrix are actually needed, whereas the rest is unreachable in terms of automata. Thanks to the lazy implementation of the matrix operations the unreachable parts are never calculated. This speeds up processing significantly and shows that this approach is very promising. Various applications including data flow analysis can be performed on CPGs. Furthermore, the structure of the matrices can be used to prove properties of the underlying program for an arbitrary number of threads. For example, deadlock freedom is proved for a large class of programs.Comment: 31 page

Timing Analysis of Concurrent Programs

Worst-case execution time analysis of multi-threaded software is still a challenge. This comes mainly from the fact that the number of thread interleavings grows exponentially in the number of threads and that synchronization has to be taken into account. In particular, a suitable graph based model has been missing. The idea that thread interleavings can be studied with a matrix calculus is a novel approach in this research area. Our sparse matrix representations of the program are manipulated using Kronecker algebra. The resulting graph represents the multi-threaded program and plays a similar role for concurrent systems as control flow graphs do for sequential programs. Thus a suitable graph model for timing analysis of multi-threaded software has been set up. Due to synchronization it turns out that often only very small parts of the resulting graph are actually needed, whereas the rest is unreachable. A lazy implementation of the matrix operations ensures that the unreachable parts are never calculated. This speeds up processing significantly and shows that our approach is very promising

Unraveling the glyco-puzzle : glycan structure identification by capillary electrophoresis

State-of-the-art high-resolution separation techniques play an important role in the full structural elucidation of glycans. Capillary electrophoresis (CE) offers a rapid yet simple method for exhaustive carbohydrate profiling. CE is a versatile analytical platform, which can be operated in several separation modes, simply by altering separation conditions during operation. For in-depth glycan structural analysis, CE has also gained significantly from the additional resolution introduced by complementary and orthogonal separation techniques such as ion exchange or hydrophilic interaction chromatography. Commercially available mass spectrometry (MS) interfaces have not only brought this information-rich detection technique within reach, but CE also represents an expedient highly efficient separation inlet for MS, capable of separating isobaric oligosaccharide isomers prior to MS detection and MS/MS fragmentation based identification. This Perspective gives a sophisticated impression of the versatility of capillary electrophoresis for deep structural elucidation of carbohydrates derived from glycoproteins of biomedical interest. Different separation modes for the analysis of both charged and neutral glycans, such as influencing electroosmotic flow, using complexation/interaction based secondary equilibria, and the use of charged and neutral labels are compared. The merits of introducing orthogonal and complementary techniques, such as exoglycosidase digestion arrays, analytical/preparative chromatography and mass spectrometric detection, extending the dynamic range and resolution of CE are all thoroughly discussed

Simultaneous analysis of δ13C, δ15N and δ34S ratios uncovers food web relationships and the trophic importance of epiphytes in an eelgrass, Zostera marina community

Simultaneous analysis of carbon, nitrogen and sulphur stable isotope ratios was applied in this pilot study to examine the food web of a Zostera marina L. system in the western Baltic Sea. Samples of three potential food sources: eelgrass, epiphytic algae and seston, as well as 69 consumer species were collected during the growing season of Z. marina from March to September 2011. The measured δ13C values of epiphytes (-14.1‰ ± 1.8 SD) were close to δ13C values of eelgrass (-11.6‰ ± 1.8 SD), impeding a clear distinction of those two carbon sources, whereas seston δ13C values (-20.9‰ ± 3.5 SD) were clearly different. This frequently encountered problem was solved by the additional use of δ34S, which resulted in easily distinguishable values for sediment and seawater derived sulphur. Values of primary producer δ34S ranged from 5.6‰ (± 2.3 SD) for Z. marina leaves to 14.2‰ (± 1.6 SD) for epiphytes and 11.9‰ (± 3.3 SD) for seston. The combination of δ34S and δ13C values made a separation of carbon sources possible and enabled the allocation of potential food sources to consumers and a description of their trophic relationships. The data of stable isotope ratio analysis of this eelgrass community strongly indicate a food web based on epiphyte and seston production. δ15N values show a food web consisting of large numbers of generalists and a high degree of omnivory amongst the consumer species analysed. This implies an occupation of every trophic position possible, which is supported by a continuous distribution of δ15N values. Previously described eelgrass food webs may have to be re-evaluated to include sulfur in order to provide a clear picture on primary carbon sources

Influence of Beam Figure on Porosity of Electron Beam Welded Thin-Walled Aluminum Plates

Welded aluminum components in the aerospace industry are subject to more stringent safety regulations than in other industries. Electron beam welding as a highly precise process fulfills this requirement. The welding of aluminum poses a challenge due to its high tendency to pore formation. To gain a better understanding of pore formation during the process, 1.5 mm thick aluminum AW6082 plates were welded using specially devised beam figures in different configurations. The obtained welds were examined with radiographic testing to evaluate the size, distribution, and the number of pores. Cross-sections of the welds were investigated with light microscopy and an electron probe microanalyzer to decipher the potential mechanisms that led to porosity. The examined welds showed that the porosity is influenced in various ways by the used figures, but it cannot be completely avoided. Chemical and microstructural analyzes have revealed that the main mechanism for pore formation was the evaporation of the alloying elements Mg and Zn. This study demonstrates that the number of pores can be reduced and their size can be minimized using a proper beam figure and energy distribution

The influence of sodium and magnesium sulphate on the penetration of chlorides in mortar

Marine environments are very aggressive to concrete, mainly due to the presence of chlorides and sulphates. The influence of sulphates on chloride penetration in mortars was investigated by immersion in combined test solutions containing 165 g/l NaCl and 33.8 g/l SO42- (as MgSO4 or Na2SO4) at temperatures of 5, 20 and 35 degrees C. After immersion periods ranging from 7 weeks up to 37 weeks, chloride profiles were measured by means of potentiometric titrations, XRD analysis and electron probe micro analysis. In general, chloride ions penetrate much deeper into the mortar than sulphate ions. Nevertheless, chloride penetration is clearly influenced by the presence of sulphates in the environment. Sulphate ions compete with chloride ions to bind to aluminate phases. Therefore, the presence of sulphates initially increases chloride diffusion. When magnesium sulphate is present the formation of Mg-related reaction products such as brucite additionally influences the chloride penetration. Later, up to 37 weeks of immersion, a decreasing chloride diffusion is noticed compared to samples exposed to a single chloride solution, due to pore blocking products of the sulphate reaction. Contrarily, immersion periods longer than 37 weeks in combined solutions result in increasing chloride diffusion due to sulphate induced cracking at the outermost layers. Notwithstanding the reciprocal influence of chlorides and sulphates, the magnitude of the effect of sulphate on the chloride diffusion coefficient was limited. Chloride diffusion generally increases with increasing temperature. The presence of sulphates decreases chloride binding even more significantly at 5 and 35 degrees C than at 20 degrees C

Auswirkung von extracurrikulären Sport- und Bewegungseinheiten auf anthropometrische Parameter und die sportmotorische Leistungsfähigkeit österreichischer Kinder und Jugendlicher im Alter von 10-15 Jahren

Thema: Studien, die den Zusammenhang von vermehrter körperlicher Aktivität, Körperbau und Gesundheit wissenschaftlich belegen, sind vielfältig in der Literatur zu finden. Auch die positiven Auswirkungen von körperlicher Aktivität sind unbestritten. Zentrales Thema dieser Studie ist die Auswirkung von extracurriculären Bewegungseinheiten und somit auch vermehrte körperliche Aktivität, im Zuge von Vereinsaktivität von Kindern und Jugendlichen. Eines der unzähligen Ziele von Sportvereinen ist deren umfassende sportliche Ausbildung. Die sportmotorische Leistungsfähigkeit und auch die Körperkonstitution repräsentieren in hohem Maße den gesundheitlichen Zustand von Kindern und Jugendlichen, darum wurden diese Parameter für die Untersuchung herangezogen. Ziel: Die vorliegende Untersuchung versucht festzustellen, ob vermehrte körperliche Aktivität anhand von extracurriculären Bewegungseinheiten im Zuge einer Sportvereinsmitgliedschaft von Kindern und Jugendlichen, Auswirkungen auf die sportmotorische Leistungsfähigkeit und den anthropometrischen Parameter anhand des Body Mass Index zeigt. Methoden: Die Untersuchung erfolgte im Zuge einer Querschnittsstudie und besteht aus einer Stichprobe von 23.723 Kindern und Jugendlichen im Alter von 10 bis 15 Jahren. Die Probanden wurden aufgeteilt in Sportvereinsmitglieder und Nicht- Sportvereinmitgliedern. Zur Bestimmung der anthropometrischen Parameter wurden die Größe und das Gewicht gemessen und anhand dieser Daten der Body Mass Index berechnet. Die sportmotorische Leistungsfähigkeit wurde mit folgenden Tests bestimmt: 20m Lauf, Standweitsprung, Reaktionstest, Rumpfvorbeuge im Sitz, Beidarmiger Medizinballweitwurf, Einbeiniges Balancieren, Schlängellauf und zur Bestimmung der Ausdauer der 2000m Lauf. Ergebnisse: Bei dem Vergleich der sportlichen Leistungsfähigkeit zwischen den Vereinssportlern und jenen Kindern und Jugendlichen, welche keinen Vereinssport betreiben, stellte sich heraus, dass bis auf wenige Ausnahmen die Vereinssportler signifikant bessere Leistungen erbringen. Nicht-Vereinsmitglieder konnten in keinem sportmotorischen Test bessere Mittelwerte als Vereinssportler erbringen. Fazit: Die Teilnahme an extracurriculären Bewegungseinheiten im Zuge einer Sportvereinsaktivität steht im Zusammenhang mit höherer sportlichen Leistungsfähigkeit und besseren anthropometrischen Voraussetzungen

Entwicklung einer array-basierten Karte für das Zuckerrübengenom

Abstract The sugarbeet Beta vulgaris var. vulgaris is a biannual plant that belongs to the Amaranthaceae family with a genome size of 758Mb and a diploid chromosome set of 18 chromosomes. Almost all of the consumed sugar in Europe derives from the sugar of sugarbeets, which are cultivated in Europe. This is one reason why it is important to have dense genetic maps of the sugarbeets’ genome. Another reason is the breeding of resistance sugarbeet lines. The point of this project was to find new genetic markers for the sugarbeet genome with a new array-based method, which could connect a genetic with a physical map. To detect polymorphisms between two parental sugarbeet lines (P1 and P2) amplicons were made from their genomic DNA. The amplicons were fluorescence marked and got hybridized on a Microarray. The Oligonukleotide of these array derived from sugarbeet BAC-endsequences and ESTs, which are also used in a physical mapping project. The custom-made Microarrays were ordered by Agilent Technologies. The oligonucleotides which detect a polymorphism, almost 14500 of 45200 tested, were set up to a new Microarray. On this Microarray 196 genotypes of the F2-generation of the parental lines (P1 and P2) had been hybridized in order to calculate a genetic map with this data. The program Mapmaker 3.0 calculated 293 of the 14500 marker-candidates into a known genetic map with already more than 715 known markers.Inhaltsverzeichnis Inhaltsverzeichnis........................................ 3 1. Zusammenfassung........................................... 5 2. Zielsetzung .......................................................... 7 3. Einleitung .......................................................... 8 3.1 Zuckerrübeallgemein....................................8 3.1.1 Anbau und Ertrag der Zuckerrübe....................................... .........9 3.1.2 Verwendungen der Zuckerrübe................................................ 9 3.2 Genetische und physikalische Kartierung und deren Verknüpfung..10 3.2.1 Genetische Kartierung.............................. 10 3.2.2 Molekulare Markierung...............................13 3.2.2.1 RFLP (restriction fragment length polymorphism)............................................ 13 3.2.2.2 RAPD (random amplified polymorphic DNA) ................................................... ......13 3.2.2.3 AFLP (amplified fragment length polymorphism) ............................................. ............14 3.2.3 Physikalische Kartierung.............................................. 14 3.2.4 Verknüpfung von genetischen und physikalischen Karten 16 3.3 DNA-Microarrays .........................................................16 3.3.1 Microarrays der Firma Agilent Technologies ........................................................ 17 4. Material und Methoden ........................................................ 18 4.1 Materialien ........................................................ 18 4.1.1 Puffer und Lösungen ........................................................ 18 4.1.2 Pflanzenmaterial........................................ 19 4.1.3 Kontrollklone (Bacterial Artificial Chromosome) .........................................................19 4.1.4 Elektrophoresegele ........................................................ 19 4.1.5 DNA- Marker ........................................................ 20 4.1.6 Microarrays ........................................................ 20 4.2 Molekularbiologische Methoden................................................ 21 4.2.1 DNA Extraktion ........................................................ 21 4.2.1.1 Präparation von Plasmid-DNA im großen Maßstab ........................................... 21 4.2.1.2 Isolierung von genomischer DNA aus Zuckerrübenpflänzchen ......................... .........22 4.2.2 Herstellung von DNA-Amplikons ........................................................ 23 4.2.2.1 Verdau der DNA ........................................................ 23 4.2.2.2 Ligation der Adaptoren an die verdaute DNA .................................................... ....23 4.2.2.3 Polymerase-Ketten-Reaktion (PCR) ........................................................ 24 4.2.2.4 Aufreinigung der PCR-Produkte............................................ 24 4.2.2.5 Fluoreszenz- Markierung der DNA- Fragmente ................................................. .......25 4.2.2.6 Aufreinigung der fluoreszenz- markierten Produkte................................................ 25 4.2.3 Hybridisierung der Microarrays ........................................................ 26 4.2.4 Waschen und Scannen der Microarrays ........................................................ 27 4.3 Bioinformatische Methoden................................................ 29 4.3.1. Erstellung der Oligos.................................................. 29 4.3.2. Auswertung der Microarrays mittels Feature Extraction ...................................... ..................30 4.3.3 Normalisierung und Verarbeitung der Signalwerte zu Genotypisierungswerten... ...............................31 4.3.3.1 Normalisierung des 4x44K- Microarrays und des 2x105K- Microarrays........... ..........................31 4.3.3.2 Normalisierung der 8x15K- Microarrays ........................................................ 32 4.3.3.3 Zuteilung der Genotypisierungswerte (Scores).................................................33 4.3.4 Einschränkung der Oligonukleotide auf relevante Markerkandidaten................... .....................33 4.3.5 Berechnung einer Placement-Map mittels Mapmaker 3.0 ..................................... ...................33 5. ..................................................... 35 5.1 DNA- Extraktion ........................................................ 37 4 5.2 DNA- Verdau ........................................................ 37 5.2.1 Ergebnisse der Verdaue................................................. 38 5.2.2 Virtuelle Restriktionskarte von Kontrollklonen.......................................... 39 5.3 Polymerase-Ketten-Reaktion (PCR) ........................................................ 40 5.3.1 Ergebnisse der PCR..................................................... 41 5.4 DNA-Markierung ........................................................ 42 5.4.1 Ergebnisse der Markierungsreaktionen................................... 43 5.5 Microarrays ........................................................ 43 5.5.1 4x44K Microarray.............................................. 45 5.5.2 2x105K Microarray.............................................. 47 5.5.3 8x15K Microarray.............................................. 48 5.6 Placement-Map berechnet mit Mapmaker 3.0 ........................................................ 50 6. Diskussion ........................................................ 54 7. Literaturverzeichnis................................. 57 7.1 Webadressen der Internetquellen ........................................................ 60 8. Anhang ........................................................ 61 8.1 Anhang A ........................................................ 62 8.2 Anhang B..................................................... 8.3 Anhang C....................................................... 66 9. Abkürzungen ........................................................ 69 10. Lebenslauf ......................................... 7