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Efficient algorithms for object recognition are crucial for the newly robotics and computer vision applications that demand real-time and on-line methods. Some examples are autonomous systems, navigating robots, autonomous driving. In this work, we focus on efficient semantic segmentation, which is the problem of labeling each pixel of an image with a semantic class.
Our aim is to speed-up all of the parts of the semantic segmentation pipeline. We also aim at delivering a labeling solution on a time budget, that can be decided on-the-fly. For this purpose, we analyze all the components of the semantic segmentation pipeline, and identify the computational bottleneck of each of them. The different components of the pipeline are over-segmenting the image with local regions, extracting features and classify the local regions, and the final inference of the image labeling with semantic classes. We focus on each of these steps.
First, we introduce a new superpixel algorithm to over-segment the image. Our superpixel method runs in real-time and can deliver a solution at any time budget. Then, for feature extraction, we focus on the framework that computes descriptors and encodes them, followed by a pooling step. We see that the encoding step is the bottleneck, for computational efficiency and performance. We present a novel assignment-based encoding formulation, that allows for the design of a new, very efficient, encoding. Finally, the image labeling output is obtained modeling the dependencies with a Conditional Random Field (CRF). In semantic image segmentation, the computational cost of instantiating the potentials is much higher than MAP inference. We introduce Active MAP inference to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest as unknown, and to estimate the MAP labeling from such incomplete energy function.
We perform experiments on all proposed methods for the different parts of the semantic segmentation pipeline. We show that our superpixel extraction achieves higher accuracy than state-of-the-art on standard superpixel benchmark, while it runs in real-time. We test our feature encoding on standard image classification and segmentation benchmarks, and we show that our method achieves competitive results with the state-of-the-art, and requires less time and memory. Finally, results for semantic segmentation benchmark show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains.
The composition of cellular membranes is extremely complex and the mechanisms underlying their homeostasis are poorly understood. Organelles within a eukaryotic cell require a non-random distribution of membrane lipids and a tight regulation of the membrane lipid composition is a prerequisite for the maintenance of specific organellar functions. Physical membrane properties such as bilayer thickness, lipid packing density and surface charge are governed by the lipid composition and change gradually from the early to the late secretory pathway. As the endoplasmic reticulum (ER) is situated at the beginning of the cells secretory pathway, it has to accept and accommodate a great variety and quantity of secretory and transmembrane proteins, which enter the ER on their way to their final cellular destination. Secretory proteins can be translocated into the lumen of the ER co- or posttanslationally and membrane proteins are being inserted and released into the ER membrane. In the oxidative milieu of the ER-lumen, supported by a variety of chaperones, proteins can fold into their native form.
If the folding capacity of the ER-lumen is exceeded, an accumulation of mis- or unfolded proteins in the lumen of the ER occurs, consequently triggering the unfolded protein response (UPR). This highly conserved program activates a wide-spread transcriptional response to restore protein folding homeostasis. In fact, 7 – 8% of all genes in the yeast Saccharomyces cerevisiae (S. cerevisiae) are regulated by the UPR. The mechanism underlying the activation of the UPR by protein folding stress has been investigated thoroughly in the last decades and many of its mechanistic details have been elucidated. Recently, it became evident that aberrant lipid compositions of the ER membrane, collectively referred to as lipid bilayer stress, are equally potent in activating the UPR. The underlying molecular mechanism of this membrane-activated UPR, however, remained unclear.
This study focuses on the UPR in S. cerevisiae and characterizes the inositol requiring enzyme 1 (Ire1) as the sole UPR sensor in S. cerevisiae. Active Ire1 forms oligomers and, collaboratively with the tRNA ligase Rlg1, splices immature mRNA of the transcription factor HAC1, which results in the synthesis of mature HAC1 mRNA and the production of the active Hac1 protein, which binds to UPR-elements in the nucleus and activates the expression of UPR target genes. Here, the combination of in vivo and in vitro experiments is being used, which is supplemented by molecular dynamics (MD) simulations performed by Roberto Covino and Gerhard Hummer (MPI for Biophysics, Frankfurt), aiming to identify the molecular mechanism of Ire1 activation by lipid bilayer stress. This study focuses on the analysis of the juxta- and transmembrane region of Ire1. Bioinformatic analyses revealed a putative ER-lumenal amphipathic helix (AH) N-terminally of and partially overlapping with the transmembrane helix (TMH). This predicted AH contains a large hydrophobic face, which inserts into the ER membrane, forcing the TMH into a tilted orientation within the membrane. The resulting unusual architecture of Ire1’s AH and TMH constitutes a unique structural element required for the activation of Ire1 by lipid bilayer stress.
To investigate the function of the AH in the physiological context, different variants of Ire1 were produced under the control of their endogenous promoter and from their endogenous locus. The functional role of the AH was tested, by disrupting its amphipathic character by the introduction of charged residues into the hydrophobic face of the AH. The role of a conserved negative residue between the TMH and the AH (E540 in S. cerevisiae) was tested by substituting it by a unipolar, polar, or positively charged residue. These variants were intensively characterized using a series of assays:
This thesis provides evidence that the AH is crucial for the function of Ire1: Mutant variants with a disrupted (F531R, V535R) or otherwise modified AH (E540A) exhibited a lower degree of oligomerization and failed to catalyze the splicing of the HAC1 mRNA as the Wildtype control. Likewise, the induction of PDI1, a target gene of the UPR, was greatly reduced in mutants with a disrupted or defective AH. These data revealed an important functional role of the AH for normal Ire1 function.
An in vitro system was established to analyze the membrane-mediated oligomerization of Ire1. This system enabled the isolated functional analysis of the AH and TMH during Ire1 activation by lipid bilayer stress. A fusion construct, coding for the maltose binding protein (MBP) from Escherichia coli (E. coli), N-terminally to the AH and TMH of Ire1 was produced. The heterologous production in E. coli, the purification and reconstitution of this minimal sensor of Ire1 in liposomes was established as part of this study. To analyze the oligomeric status of the minimal sensor in different lipid environments, continuous wave electron paramagnetic resonance (cwEPR) spectroscopic experiments were performed. These experiments revealed that the molecular packing density of the lipids had a significant influence of the oligomerization of the spin-labeled membrane sensor: increasing packing densities resulted in sensor oligomerization. The AH-disruptive F531R mutant, in which the amphipathic character of the AH was destroyed, showed no membrane-sensitive changes in its oligomerization status.
Thus, the activation of Ire1 by lipid bilayer stress is achieved by a membrane-based mechanism. According to the current model, the AH induces a local membrane compression by inserting its large hydrophobic face into the membrane. As membrane thickness and acyl chain order are interconnected, this compression simultaneously results in an increased local disordering of lipid acyl chains. Supporting MD simulations performed by Roberto Covino and Gerhard Hummer revealed that the bilayer compression is significantly more pronounced in a densely packed lipid environment, than in a lipid environment of lower lipid packing density. Hence, the energetic cost of the local compression increases with the packing density of the membrane, but is compensated for by the oligomerization of Ire1. This minimization of energetic cost induced by the membrane deformation of Ire1 forms the basis for the activation of Ire1 by lipid bilayer stress.
This thesis investigates the acquisition pace and the typical developmental path in eL2 acquisition of selected phenomena of German morphosyntax and semantics and compared them to monolingual acquisition. In addition, the influence of ‘Age of Onset’ and of external factors on eL2 acquisition is examined.
To date, the most studies on eL2 acquisition focused on language production. Based on mostly longitudinal spontaneous speech data of only small number of children, they indicate that eL2 learners acquire sentence structure and subject-verb-agreement faster than monolingual children, whereas the acquisition of case marking causes them more difficulties. Moreover, similar developmental paths to those of monolingual children are claimed. Only several studies examined comprehension abilities in eL2 learners, however overwhelmingly in cross-sectional design. The findings from comprehension studies on telic and atelic verbs, and on wh-questions indicate that eL2 children acquire their target-like interpretation faster than monolingual children. The same acquisition stages towards target-like interpretation like in monolingual acquisition are assumed as well. Taking together, to date, no study exists, that examines comprehension and production abilities in a large group of eL2 learners of German in a longitudinal design.
This thesis extends the previous results by investigating pace of acquisition, impact of factors, and individual developmental paths in a longitudinal design with large groups of participants. Language data of 29 eL2 learners of German (age at T1: 3;7 years, LoE: 10 months) and 45 monolingual German-speaking children (age at T1: 3;7) are examined. The eL2 learners were tested in six test rounds (age at T6: 6;9 years). The monolingual children were tested in five test rounds (are at T5: 5;7). The standardized test LiSe-DaZ (Schulz & Tracy, 2011) was employed to examine children’s language skills.
eL2 learners show a significantly greater rate of change, thus faster acquisition pace, than monolingual children in the following scales: comprehension of telicity, comprehension of wh-questions, production of prepositions, and production of conjunctions. These phenomena are acquired early in monolingual children. No differences regarding acquisition pace between eL2 children and monolingual children are found for comprehension of negation, production of case marking, and production of focus particles. These phenomena are acquired late in monolingual development and involve semantic and pragmatic knowledge. The findings of faster acquisition pace of several phenomena are in line with several studies that reported that eL2 children develop faster than monolingual children.
Independent on whether a phenomenon is acquired early or late, no effects of external factors on eL2 children’s performance are found. These findings indicate that acquisition of core, rule-based phenomena is not sensitive to external factors if the first exposure to L2 takes place around the age of three.
Moreover, eL2 children show the same developmental stages and error types in comprehension of telicity, comprehension of negation, production of matrix and subordinate clauses. This is also independent on how fast they acquire a structure under consideration. Thus, these findings provide a further support for similar developmental paths of eL2 and monolingual children towards target-like comprehension and production.
Echolocation allows bats to orientate in darkness without using visual information. Bats emit spatially directed high frequency calls and infer spatial information from echoes coming from call reflections in objects (Simmons 2012; Moss and Surlykke 2001, 2010). The echoes provide momentary snapshots, which have to be integrated to create an acoustic image of the surroundings. The spatial resolution of the computed image increases with the quantity of received echoes. Thus, a high call rate is required for a detailed representation of the surroundings.
One important parameter that the bats extract from the echoes is an object’s distance. The distance is inferred from the echo delay, which represents the duration between call emission and echo arrival (Kössl et al. 2014). The echo delay decreases with decreasing distance and delay-tuned neurons have been characterized in the ascending auditory pathway, which runs from the inferior colliculus (Wenstrup et al. 2012; Macías et al. 2016; Wenstrup and Portfors 2011; Dear and Suga 1995) to the auditory cortex (Hagemann et al. 2010; Suga and O'Neill 1979; O'Neill and Suga 1982).
Electrophysiological studies usually characterize neuronal processing by using artificial and simplified versions of the echolocation signals as stimuli (Hagemann et al. 2010; Hagemann et al. 2011; Hechavarría and Kössl 2014; Hechavarría et al. 2013). The high controllability of artificial stimuli simplifies the inference of the neuronal mechanisms underlying distance processing. But, it remains largely unexplored how the neurons process delay information from echolocation sequences. The main purpose of the thesis is to investigate how natural echolocation sequences are processed in the brain of the bat Carollia perspicillata. Bats actively control the sensory information that it gathers during echolocation. This allows experimenters to easily identify and record the acoustic stimuli that are behaviorally relevant for orientation. For recording echolocation sequences, a bat was placed in the mass of a swinging pendulum (Kobler et al. 1985; Beetz et al. 2016b). During the swing the bat emitted echolocation calls that were reflected in surrounding objects. An ultrasound sensitive microphone traveling with the bat and positioned above the bat’s head recorded the echolocation sequence. The echolocation sequence carried delay information of an approach flight and was used as stimulus for neuronal recordings from the auditory cortex and inferior colliculus of the bats.
Presentation of high stimulus rates to other species, such as rats, guinea pigs, suppresses cortical neuron activity (Wehr and Zador 2005; Creutzfeldt et al. 1980). Therefore, I tested if neurons of bats are suppressed when they are stimulated with high acoustic rates represented in echolocation sequences (sequence situation). Additionally, the bats were stimulated with randomized call echo elements of the sequence and an interstimulus time interval of 400 ms (element situation). To quantify neuronal suppression induced by the sequence, I compared the response pattern to the sequence situation with the concatenated response patterns to the element situation. Surprisingly, although the bats should be adapted for processing high acoustic rates, their cortical neurons are vastly suppressed in the sequence situation (Beetz et al. 2016b). However, instead of being completely suppressed during the sequence situation, the neurons partially recover from suppression at a unit specific call echo element. Multi-electrode recordings from the cortex allow assessment of the representation of echo delays along the cortical surface. At the cortical level, delay-tuned neurons are topographically organized. Cortical suppression improves sharpness of neuronal tuning and decreases the blurriness of the topographic map. With neuronal recordings from the inferior colliculus, I tested whether the echolocation sequence also induced neuronal suppression at subcortical level. The sequence induced suppression was weaker in the inferior colliculus than in the cortex. The collicular response makes the neurons able to track the acoustic events in the echolocation sequence. Collicular suppression mainly improves the signal-to-noise ratio. In conclusion, the results demonstrate that cortical suppression is not necessarily a shortcoming for temporal processing of rapidly occurring stimuli as it has previously been interpreted.
Natural environments are usually composed of multiple objects. Thus, each echolocation call reflects off multiple objects resulting in multiple echoes following the calls. At present, it is largely unexplored how neurons process echolocation sequences containing echo information from more than one object (multi-object sequences). Therefore, I stimulated bats with a multi-object sequence which contained echo information from three objects. The objects were different distances away from each other. I tested the influence of each object on the neuronal tuning by stimulating the bats with different sequences created from filtering object specific echoes from the multi-object sequence. The cortex most reliably processes echo information from the nearest object whereas echo information from distant objects is not processed due to neuronal suppression. Collicular neurons process less selectively echo information from certain objects and respond to each echo.
For proper echolocation, bats have to distinguish between own biosonar signals and the signals coming from conspecifics. This can be quite challenging when many bats echolocate adjacent to each other. In behavioral experiments, the echolocation performance of C. perspicillata was tested in the presence of potentially interfering sounds. In the presence of acoustic noise, the bats increase the sensory acquisition rate which may increase the update rate of sensory processing. Neuronal recordings from the auditory cortex and inferior colliculus could strengthen the hypothesis. Although there were signs of acoustic interference or jamming at neuronal level, the neurons were not completely suppressed and responded to the rest of the echolocation sequence.
One of the key functions of blood vessels is to transport nutrients and oxygen to distant tissues and organs in the body. When blood supply is insufficient, new vessels form to meet the metabolic tissue demands and to re-establish cellular homeostasis. Expansion of the vascular network through sprouting angiogenesis requires the specification of ECs into leading (sprouting) tip and following (non-sprouting) stalk cells. Attracted by guidance cues tip cells dynamically extend and retract filopodia to navigate the nascent vessel sprout, whereas trailing stalk cells proliferate to form the extending vascular tube. All of these processes are under the control of environmental signals (e.g. hypoxia, metabolism) and numerous cytokines and peptide growth factors. The Dll4/Notch pathway coordinates several critical steps of angiogenic blood vessel growth. Even subtle alterations in Notch activity can profoundly influence endothelial cell behavior and blood vessel formation, yet little is known about the intrinsic regulation and dynamics of Notch signaling in endothelial cells. In addition, it remains an open question, how different growth factor signals impinging on sprouting ECs are coordinated with local environmental cues originating from nutrient-deprived, hypoxic tissue to achieve a balanced endothelial cell response. Acetylation of lysines is a critical posttranslational modification of histones, which acts as an important regulatory mechanism to control chromatin structure and gene transcription. In addition to histones, several non-histone proteins are targeted for acetylation reversible acetylation is emerging as a fundamental regulatory mechanism to control protein function, interaction and stability. Previous studies from our group identified the NAD+-dependent deacetylase SIRT1 as a key regulator of blood vessel growth controlling endothelial angiogenic responses. These studies revealed that SIRT1 is highly expressed in the vascular endothelium during blood vessel development, where it controls the angiogenic activity of endothelial cells. Moreover, in this work SIRT1 has been shown to control the activity of key regulators of cardiovascular homeostasis such as eNOS, Foxo1 and p53. The present study describes that SIRT1 antagonizes Notch signaling by deacetylating the Notch intracellular domain (NICD). We showed that loss of SIRT1 enhances DLL4-induced endothelial Notch responses as assessed by different luciferase responsive elements as well as transcriptional analysis of Notch endogenous target genes activation. Conversely, SIRT1 gain of function by overexpression of pharmacological activation decreases induction of Notch targets in response to DLL4 stimulation. We also showed that the NICD can be directly acetylated by PC AF and p300 and that SIRT1 promotes deacetylation of NICD. We have identified 14 lysines that are targeted for acetylation and their mutation abolishes the effects of SIRT1 of Notch responses. Furthermore, over-expression or activation of SIRT1 significantly reduces the levels of NICD protein. Moreover, SIRT1-mediated NICD degradation can be reversed by blockade of the proteasome suggesting a mechanism resulting from ubiquitin-mediated proteolysis. Indeed, we have shown that SIRT1 knockdown or pharmacological inhibition decreased NICD ubiquitination. We propose a novel molecular mechanism of modulation of the amplitude and duration of Notch responses in which acetylation increases NICD stability and therefore permanence at the promoters, while SIRT1, by inducing NICD degradation through its deacetylation, shortens Notch responses. In order to evaluate the physiological relevance of our findings we used different models in which the Notch functions during blood vessel formation have been extensively characterized. First, retinal angiogenesis in mice lacking SIRT1 activity shows decreased branching and reduced endothelial proliferation, similar to what happens after Notch gain of function mutations. ECs from these mice exhibit increased expression of Notch target genes. Second, these results were reproducible during intersomitic vessel growth in sirt1-deficient zebrafish. In both models, the defects could be partially rescued by inhibition of Notch activation. Third, we used an in vitro model of vessel sprouting from differentiating embryonic bodies in response to VEGF in a collagen matrix. Our results showed that Sirt1-deficient cells shows impaired sprouting which correlated with increased NICD levels. In addition, when in competition with wild-type cells in this assay, Sirt1-deficient cells are more prone to occupy the stalk cell position. Taken together, our study identifies reversible acetylation of NICD as a novel molecular mechanism to adapt the dynamics of Notch signaling and suggest that SIRT1 acts as a rheostat to fine-tune endothelial Notch responses. The NAD+-dependent feature of SIRT1 activity possibly links endothelial Notch responses to environmental cues and metabolic changes during nutrient deprivation in ischemic environments or upon other cellular stresses.
The enzyme acetyl-CoA carboxylase (ACC) plays a fundamental role in the fatty acid metabolism. It regulates the first and rate limiting step in the biosynthesis of fatty acids by catalyzing the carboxylation of acetyl-CoA to malonyl-CoA and exists as two different isoforms, ACC1 and ACC2. In the last few years, ACC has been reported as an attractive drug target for treating different diseases, such as insulin resistance, hepatic steatosis, dyslipidemia, obesity, metabolic syndrome and nonalcoholic fatty liver disease. An altered fatty acid metabolism is also associated with cancer cell proliferation. In general, the inhibition of ACC provides two possibilities to regulate the fatty acid metabolism: It blocks the de novo lipogenesis in lipogenic tissues and stimulates the mitochondrial fatty acid β-oxidation. Surprisingly, the role of ACC in human vascular endothelial cells has been neglected so far. This work aimed to investigate the role of the ACC/fatty acid metabolism in regulating important endothelial cell functions like proliferation, migration and tube formation.
To investigate the function of ACC, the ACC-inhibitor soraphen A as well as an siRNA-based approach were used. This study revealed that ACC1 is the predominant isoform both in human umbilical vein endothelial cells (HUVECs) and in human dermal microvascular endothelial cells (HMECs). Inhibition of ACC via soraphen A resulted in decreased levels of malonyl-CoA and shifted the lipid composition of endothelial cell membranes. Consequently, membrane fluidity, filopodia formation and the migratory capacity were attenuated. Increasing amounts of longer acyl chains within the phospholipid subgroup phosphatidylcholine (PC) were suggested to overcompensate the shift towards shorter acyl chains within phosphatidylglycerol (PG), which resulted in a dominating effect on regulating the membrane fluidity. Most importantly, this work provided a link between changes in the phospholipid composition and altered endothelial cell migration. The antimigratory effect of soraphen A was linked to a reduced amount of PG and to an increased amount of polyunsaturated fatty acids (PUFAs) within the phospholipid cell membrane. This link was unknown in the literature so far. Interestingly, a reduced filopodia formation was observed upon ACC inhibition via soraphen A, which presumably caused the impaired migratory capacity.
This work revealed a relationship between ACC/fatty acid metabolism, membrane lipid composition and endothelial cell migration. The natural compound soraphen A emerged as a valuable chemical tool to analyze the role of ACC/fatty acid metabolism in regulating important endothelial cell functions. Furthermore, regulating endothelial cell migration via ACC inhibition promises beneficial therapeutic perspectives for the treatment of cell migration-related disorders, such as ischemia reperfusion injury, diabetic angiopathy, macular degeneration, rheumatoid arthritis, wound healing defects and cancer.
Der Begriff psychologische Akkulturation beschreibt jene Veränderungen, die infolge des dauerhaften Aufeinandertreffens verschiedener kultureller Gruppen auf individueller Ebene zu beobachten sind (Berry, 1997). Die vorliegende Arbeit umfasst drei Publikationen, die sich mit Akkulturationsprozessen von Kindern und Jugendlichen mit Migrationshintergrund in Deutschland befassen. Zunächst wird ein Überblick über den aktuellen Stand der Forschung zur Situation junger Migranten in Deutschland vorgelegt. An zentraler Stelle steht dabei die Frage, wie die Migrationsgeschichte und Immigrationspolitik Deutschlands sowie die öffentliche Einstellung gegenüber Migranten die transkulturelle Adaptation von Kindern und Jugendlichen nicht-deutscher ethno-kultureller Herkunft beeinflussen. Bereits bestehende wissenschaftliche Erkenntnisse werden verknüpft mit den Ergebnissen neuerer empirischer Studien um zu einem tieferen Verständnis der Ursachen für die vielfach berichteten problematischen Verläufe psychologischer und soziokultureller Adaptation von Migranten beizutragen. Neben anderen Risiken und protektiven Faktoren wird diskutiert, wie sich Besonderheiten Deutschlands als Aufnahmeland, wie z.B. die Eigenarten des Schulsystems, auf Adaptationsverläufe auswirken können. Unsere eigenen Studien tragen zum Verständnis der Anpassungsprozesse junger Migranten bei, indem sie aufzeigen, dass nicht die Akkulturationsstrategie der Integration, sondern speziell die Orientierung an der deutschen Kultur bei Individuen zu den günstigsten psychologischen und soziokulturellen Ergebnissen zu führen scheint. Im Rahmen dieser Arbeit wird weiterhin ein empirischer und methodologischer Beitrag zur Akkulturationsforschung geleistet, indem ein Messinstrument zur Erfassung psychologischer Akkulturation bei Kindern im deutschen Sprachraum – die Frankfurter Akkulturationsskala für Kinder (FRAKK-K)– entwickelt, validiert und schließlich anhand einer Fragestellung praktisch angewandt wird. Die Skalenentwicklung und –optimierung erfolgte auf der Grundlage von zwei Studien, welche Daten von 387 Grundschülern aus zwei städtischen Regionen in Deutschland umfassen (Frankenberg & Bongard, 2013). Die Ergebnisse konfirmatorischer Faktorenanalysen sprechen für zwei Faktoren, Orientierung an der Aufnahmekultur und Orientierung an der Herkunftskultur, die jeweils mittels 6 Items erfasst werden. Beide Subskalen weisen eine zufriedenstellende interne Reliabilität und Kriteriumsvalidität auf und lassen sich zwecks Erfassung der Akkulturationsstrategie kombinieren (i.e. Assimilation, Integration, Separation und Marginalisierung). In einer ersten praktischen Anwendung der Skala wird der Frage nachgegangen, inwiefern erweiterter Musikunterricht und Orchesterspiel in der Grundschule über verstärkte Gruppenkohäsion zur Förderung kultureller Integration beitragen können.
Grundschüler, die in einem Orchester gespielt haben, zeigen über einen Zeitraum von 1,5 Jahren einen stärkeren Anstieg der Orientierung an der deutschen Kultur als Schüler, die keinen erweiterten Musikunterricht erhielten. Musikschüler fühlen sich außerdem stärker in die Klassengemeinschaft integriert. Dies deutet darauf hin, dass die Erfahrung der Zusammenarbeit und des Musizierens innerhalb einer Gruppengemeinschaft zu einer stärkeren Orientierung an der deutschen Kultur geführt hat. Die Orientierung an der Herkunftskultur blieb unbeeinflusst. Somit können Programme, die jungen Migranten die Gelegenheit bieten Musik innerhalb einer größeren, kulturell heterogenen Gruppe aufzuführen, als eine effektive Intervention zur Förderung der kulturellen Anpassung an die Mehrheitskultur und der Integration innerhalb – und außerhalb – des Klassenzimmers führen.
Abschließend werden die Ergebnisse der empirischen Untersuchungen vor dem Hintergrund des aktuellen Forschungsstandes zu neueren Akkulturationsmodellen sowie zu der Terminologie und den methodischen Herausforderungen des Forschungsfeldes in Beziehung gesetzt und kritisch reflektiert. Daraus abgeleitet werden Implikationen für zukünftige Interventionen und Forschung diskutiert.
Mitochondial NADH:ubiquinone oxidoreductase (complex I) the largest multiprotein enzyme of the respiratory chain, catalyses the transfer of two electrons from NADH to ubiquinone, coupled to the translocation of four protons across the membrane. In addition to the 14 strictly conserved central subunits it contains a variable number of accessory subunits. At present, the best characterized enzyme is complex I from bovine heart with a molecular mass of about 980 kDa and 32 accessory proteins. In this study, the subunit composition of mitochondrial complex I from the aerobic yeast Y. lipolytica has been analysed by a combination of proteomic and genomic approaches. The sequences of 37 complex I subunits were identified. The sum of their individual molecular masses (about 930 kDa) was consistent with the native molecular weight of approximately 900 kDa for Y. lipolytica complex I obtained by BN-PAGE. A genomic analysis with Y. lipolytica and other eukaryotic databases to search for homologues of complex I subunits revealed 31 conserved proteins among the examined species. A novel protein named “X” was found in purified Y. lipolytica complex I by MALDI-MS. This protein exhibits homology to the thiosulfate sulfurtransferase enzyme referred to as rhodanese. The finding of a rhodanese-like protein in isolated complex I of Y. lipolytica allows to assume a special regulatory mechanism of complex I activity through control of the status of its iron-sulfur clusters. The second part of this study was aimed at investigating the possible role of one of these extra subunits, 39 kDa (NUEM) subunit which is related to the SDRs-enzyme family. The members of this family function in different redox and isomerization reactions and contain a conserved NAD(P)H-binding site. It was proposed that the 39 kDa subunit may be involved in a biosynthetic pathway, but the role of this subunit in complex I is unknown. In contrast to the situation in N. crassa, deletion of the 39 kDa encoding gene in Y. lipolytica led to the absence of fully assembled complex I. This result might indicate a different pathway of complex I assembly in both organisms. Several site-directed mutations were generated in the nucleotide binding motif. These had either no effect on enzyme activity and NADPH binding, or prevented complex I assembly. Mutations of arginine-65 that is located at the end of the second b-strand and responsible for selective interaction with the 2’-phosphate group of NADPH retained complex I activity in mitochondrial membranes but the affinity for the cofactor was markedly decreased. Purification of complex I from mutants resulted in decrease or loss of ubiquinone reductase activity. It is very likely that replacement of R65 not only led to a decrease in affinity for NADPH but also caused instability of the enzyme due to steric changes in the 39 kDa subunit. These data indicate that NADPH bound to the 39 kDa subunit (NUEM) is not essential for complex I activity, but probably involved in complex I assembly in Y. lipolytica.
Acceleration of Biomedical Image Processing and Reconstruction with FPGAs
Increasing chip sizes and better programming tools have made it possible to increase the boundaries of application acceleration with reconfigurable computer chips. In this thesis the potential of acceleration with Field Programmable Gate Arrays (FPGAs) is examined for applications that perform biomedical image processing and reconstruction. The dataflow paradigm was used to port the analysis of image data for localization microscopy and for 3D electron tomography from an imperative description towards the FPGA for the first time.
After the primitives of image processing on FPGAs are presented, a general workflow is given for analyzing imperative source code and converting it to a hardware pipeline where every node processes image data in parallel. The theoretical foundation is then used to accelerate both example applications. For localization microscopy, an acceleration of 185 compared to an Intel i5 450 CPU was achieved, and electron tomography could be sped up by a factor of 5 over an Nvidia Tesla C1060 graphics card while maintaining full accuracy in both cases.
The ab-initio molecular dynamics framework has been the cornerstone of computational solid state physics in the last few decades. Although it is already a mature field it is still rapidly developing to accommodate the growth in solid state research as well as to efficiently utilize the increase in computing power. Starting from the first principles, the ab-initio molecular dynamics provides essential information about structural and electronic properties of matter under various external conditions. In this thesis we use the ab-initio molecular dynamics to study the behavior of BaFe2As2 and CaFe2As2 under the application of external pressure. BaFe2As2 and CaFe2As2 belong to the family of iron based superconductors which are a novel and promising superconducting materials. The application of pressure is one of two key methods by which electronic and structural properties of iron based superconductors can be modified, the other one being doping (or chemical pressure). In particular, it has been noted that pressure conditions have an important effect, but their exact role is not fully understood. To better understand the effect of different pressure conditions we have performed a series of ab-initio simulations of pressure application. In order to apply the pressure with arbitrary stress tensor we have developed a method based on the Fast Inertial Relaxation Engine, whereby the unit cell and the atomic positions are evolved according to the metadynamical equations of motion. We have found that the application of hydrostatic and c axis uniaxial pressure induces a phase transition from the magnetically ordered orthorhombic phase to the non-magnetic collapsed tetragonal phase in both BaFe2As2 and CaFe2As2. In the case of BaFe2As2, an intermediate tetragonal non-magnetic tetragonal phase is observed in addition. Application of the uniaxial pressure parallel to the c axis reduces the critical pressure of the phase transition by an order of magnitude, in agreement with the experimental findings. The in-plane pressure application did not result in transition to the non-magnetic tetragonal phase and instead, rotation of the magnetic order direction could be observed. This is discussed in the context of Ginzburg-Landau theory. We have also found that the magnetostructural phase transition is accompanied by a change in the Fermi surface topology, whereby the hole cylinders centered around the Gamma point disappear, restricting the possible Cooper pair scattering channels in the tetragonal phase. Our calculations also permit us to estimate the bulk moduli and the orthorhombic elastic constants of BaFe2As2 and CaFe2As2.
To study the electronic structure in systems with broken translational symmetry, such as doped iron based superconductors, it is necessary to develop a method to unfold the complicated bandstructures arising from the supercell calculations. In this thesis we present the unfolding method based on group theoretical techniques. We achieve the unfolding by employing induced irreducible representations of space groups. The unique feature of our method is that it treats the point group operations on an equal footing with the translations. This permits us to unfold the bandstructures beyond the limit of translation symmetry and also formulate the tight-binding models of reduced dimensionality if certain conditions are met. Inclusion of point group operations in the unfolding formalism allows us to reach important conclusions about the two versus one iron picture in iron based superconductors.
And finally, we present the results of ab-initio structure prediction in the cases of giant volume collapse in MnS2 and alkaline doped picene. In the case of MnS2, a previously unobserved high pressure arsenopyrite structure of MnS2 is predicted and stability regions for the two competing metastable phases under pressure are determined. In the case of alkaline doped picene, crystal structures with different levels of doping were predicted and used to study the role of electronic correlations.
First-principles modeling techniques offer the ability to simulate a wide range of systems under different physical conditions, such as temperature, pressure, and composition, without relying on empirical knowledge. Density functional theory (DFT), a quantum mechanical method, has become an exceptionally successful framework for materials science modeling. Employing DFT makes it possible to gain valuable insights into the fundamental state of a system, enabling the reliable determination of equilibrium crystal structures. Over time, DFT has become an essential tool that can be incorporated into various schemes for predicting the properties of a material related to its structure, insulating/metallic behavior, magnetism, and optics. DFT is regularly applied in numerous fields, spanning from fundamental subjects in condensed matter physics to the study of large-scale phenomena in geosciences. In the latter, the effectiveness of DFT stems from its ability to simulate the properties found on the Earth, other planets, and meteorites, which may pose challenges for their direct study or laboratory investigation.
In this thesis, a comprehensive examination of a family of monosulfides and a perovskite heterostructure was conducted. These materials are relevant for their potential applications in technology, energy harvesting, and in the case of monosulfides, their speculated abundance on the planet Mercury.
Firstly, a DFT approach was used to analyze two non-magnetic monosulfides, CaS and MgS. We determined their structural properties and then focused on the modeling of their reflectivity in the infrared region. The calculation of the reflectivity considered both harmonic and anharmonic contributions. In the harmonic limit, the non-analytic correction was employed to accurately determine the LO/TO splitting, which is necessary to delimit the retstrahlend band, that is, the maximum of the reflectivity. The anharmonic effects given by up to three-phonon and isotopic scatterings, which were included using perturbation theory, primarily smeared the reflectivity spectra edges in the high-wave region.
Secondly, four polymorphs of MnS were studied using a combination of first-principles methods to simulate their antiferromagnetic (AFM) and paramagnetic (PM) states. The integration of DFT+$U$ with special quasirandom structures (SQS) supercells, and occupation matrix control techniques was crucial for achieving convergence, structural optimization accuracy, and obtaining finite energy band gaps and local magnetic moments in the PM phases. The addition of the Hubbard $U$ correction was necessary to treat the highly-correlated Mn $d$-electrons. The success of our approach was clear based on our electronic structure predictions for the PM rock-salt B1-MnS polymorph. Experimentally this phase has been observed to be an insulator, but multiple \emph{ab initio} works resulted previously in metallic behavior. Our computations, on the other hand, predicted insulating and magnetic properties that compare well with available measurements. Additionally, the pressure-field stability of the four MnS polymorphs was studied. In the case of the PM phases, B1-MnS was identified to be the most stable up to about 21 GPa, then transforming into the B31-MnS polymorph. This finding was in close agreement with high-pressure experiments reporting a similar phase transformation. The optical properties of B1-, B4-, and B31-MnS were also simulated. The SQS technique was used to obtain soft-mode-free phonon band structures within the harmonic approximation. Then, the anharmonic effects were included, and the reflectivity was calculated for B1-MnS and B4-MnS. In both cases, a good agreement for the LO/TO splitting was achieved in comparison to experimental results.
Lastly, the oxygen-deficient heterostructure of LaAlO$_{3-\delta}$ /SrTiO$_{3-\delta}$ was investigated also employing DFT+$U$, with a particular emphasis on the potential impact of vacancy clustering at the interface. Six distinct configurations of pairs of vacancies were studied and their energies were compared to find the most stable one. The orbital reconstruction of Ti orbitals was also examined based on their location with respect to the vacancies and the local magnetic moments were calculated. The final results showed that linearly arranged vacancies located opposite to Ti ions give the most energetically stable configuration.
Das Gehirn ist die wohl komplexeste Struktur auf Erden, die der Mensch erforscht. Es besteht aus einem riesigen Netzwerk von Nervenzellen, welches in der Lage ist eingehende sensorische Informationen zu verarbeiten um daraus eine sinnvolle Repräsentation der Umgebung zu erstellen. Außerdem koordiniert es die Aktionen des Organismus um mit der Umgebung zu interagieren. Das Gehirn hat die bemerkenswerte Fähigkeit sowohl Informationen zu speichern als auch sich ständig an ändernde Bedingungen anzupassen, und zwar über die gesamte Lebensdauer. Dies ist essentiell für Mensch oder Tier um sich zu entwickeln und zu lernen. Die Grundlage für diesen lebenslangen Lernprozess ist die Plastizität des Gehirns, welche das riesige Netzwerk von Neuronen ständig anpasst und neu verbindet. Die Veränderungen an den synaptischen Verbindungen und der intrinsischen Erregbarkeit jedes Neurons finden durch selbstorganisierte Mechanismen statt und optimieren das Verhalten des Organismus als Ganzes. Das Phänomen der neuronalen Plastizität beschäftigt die Neurowissenschaften und anderen Disziplinen bereits über mehrere Jahrzehnte. Dabei beschreibt die intrinsische Plastizität die ständige Anpassung der Erregbarkeit eines Neurons um einen ausbalancierten, homöostatischen Arbeitsbereich zu gewährleisten. Aber besonders die synaptische Plastizität, welche die Änderungen in der Stärke bestehender Verbindungen bezeichnet, wurde unter vielen verschiedenen Bedingungen erforscht und erwies sich mit jeder neuen Studie als immer komplexer. Sie wird durch ein komplexes Zusammenspiel von biophysikalischen Mechanismen induziert und hängt von verschiedenen Faktoren wie der Frequenz der Aktionspotentiale, deren Timing und dem Membranpotential ab und zeigt außerdem eine metaplastische Abhängigkeit von vergangenen Ereignissen. Letztlich beeinflusst die synaptische Plastizität die Signalverarbeitung und Berechnung einzelner Neuronen und der neuronalen Netzwerke.
Der Schwerpunkt dieser Arbeit ist es das Verständnis der biologischen Mechanismen und deren Folgen, die zu den beobachteten Plastizitätsphänomene führen, durch eine stärker vereinheitlichte Theorie voranzutreiben.Dazu stelle ich zwei funktionale Ziele für neuronale Plastizität auf, leite Lernregeln aus diesen ab und analysiere deren Konsequenzen und Vorhersagen.
Kapitel 3 untersucht die Unterscheidbarkeit der Populationsaktivität in Netzwerken als funktionales Ziel für neuronale Plastizität. Die Hypothese ist dabei, dass gerade in rekurrenten aber auch in vorwärtsgekoppelten Netzwerken die Populationsaktivität als Repräsentation der Eingangssignale optimiert werden kann, wenn ähnliche Eingangssignale eine möglichst unterschiedliche Repräsentation haben und dadurch für die nachfolgende Verarbeitung besser unterscheidbar sind. Das funktionale Ziel ist daher diese Unterscheidbarkeit durch Veränderungen an den Verbindungsstärke und der Erregbarkeit der Neuronen mithilfe von lokalen selbst-organisierten Lernregeln zu maximieren. Aus diesem funktionale Ziel lassen sich eine Reihe von Standard-Lernenregeln für künstliche neuronale Netze gemeinsam abzuleiten.
Kapitel 4 wendet einen ähnlichen funktionalen Ansatz auf ein komplexeres, biophysikalisches Neuronenmodell an. Das Ziel ist eine spärliche, stark asymmetrische Verteilung der synaptischen Stärke, wie sie auch bereits mehrfach experimentell gefunden wurde, durch lokale, synaptische Lernregeln zu maximieren. Aus diesem funktionalen Ansatz können alle wichtigen Phänomene der synaptischen Plastizität erklärt werden. Simulationen der Lernregel in einem realistischen Neuronmodell mit voller Morphologie erklären die Daten von timing-, raten- und spannungsabhängigen Plastizitätsprotokollen. Die Lernregel hat auch eine intrinsische Abhängigkeit von der Position der Synapse, welche mit den experimentellen Ergebnissen übereinstimmt. Darüber hinaus kann die Lernregel ohne zusätzliche Annahmen metaplastische Phänomene erklären. Dabei sagt der Ansatz eine neue Form der Metaplastizität voraus, welche die timing-abhängige Plastizität beeinflusst. Die formulierte Lernregel führt zu zwei neuartigen Vereinheitlichungen für synaptische Plastizität: Erstens zeigt sie, dass die verschiedenen Phänomene der synaptischen Plastizität als Folge eines einzigen funktionalen Ziels verstanden werden können. Und zweitens überbrückt der Ansatz die Lücke zwischen der funktionalen und mechanistische Beschreibungsweise. Das vorgeschlagene funktionale Ziel führt zu einer Lernregel mit biophysikalischer Formulierung, welche mit etablierten Theorien der biologischen Mechanismen in Verbindung gebracht werden kann. Außerdem kann das Ziel einer spärlichen Verteilung der synaptischen Stärke als Beitrag zu einer energieeffizienten synaptischen Signalübertragung und optimierten Codierung interpretiert werden.
A stochastic model for the joint evaluation of burstiness and regularity in oscillatory spike trains
(2013)
The thesis provides a stochastic model to quantify and classify neuronal firing patterns of oscillatory spike trains. A spike train is a finite sequence of time points at which a neuron has an electric discharge (spike) which is recorded over a finite time interval. In this work, these spike times are analyzed regarding special firing patterns like the presence or absence of oscillatory activity and clusters (so called bursts). These bursts do not have a clear and unique definition in the literature. They are often fired in response to behaviorally relevant stimuli, e.g., an unexpected reward or a novel stimulus, but may also appear spontaneously. Oscillatory activity has been found to be related to complex information processing such as feature binding or figure ground segregation in the visual cortex. Thus, in the context of neurophysiology, it is important to quantify and classify these firing patterns and their change under certain experimental conditions like pharmacological treatment or genetical manipulation. In neuroscientific practice, the classification is often done by visual inspection criteria without giving reproducible results. Furthermore, descriptive methods are used for the quantification of spike trains without relating the extracted measures to properties of the underlying processes.
For that reason, a doubly stochastic point process model is proposed and termed 'Gaussian Locking to a free Oscillator' - GLO. The model has been developed on the basis of empirical observations in dopaminergic neurons and in cooperation with neurophysiologists. The GLO model uses as a first stage an unobservable oscillatory background rhythm which is represented by a stationary random walk whose increments are normally distributed. Two different model types are used to describe single spike firing or clusters of spikes. For both model types, the distribution of the random number of spikes per beat has different probability distributions (Bernoulli in the single spike case or Poisson in the cluster case). In the second stage, the random spike times are placed around their birth beat according to a normal distribution. These spike times represent the observed point process which has five easily interpretable parameters to describe the regularity and the burstiness of the firing patterns.
It turns out that the point process is stationary, simple and ergodic. It can be characterized as a cluster process and for the bursty firing mode as a Cox process. Furthermore, the distribution of the waiting times between spikes can be derived for some parameter combination. The conditional intensity function of the point process is derived which is also called autocorrelation function (ACF) in the neuroscience literature. This function arises by conditioning on a spike at time zero and measures the intensity of spikes x time units later. The autocorrelation histogram (ACH) is an estimate for the ACF. The parameters of the GLO are estimated by fitting the ACF to the ACH with a nonlinear least squares algorithm. This is a common procedure in neuroscientific practice and has the advantage that the GLO ACF can be computed for all parameter combinations and that its properties are closely related to the burstiness and regularity of the process. The precision of estimation is investigated for different scenarios using Monte-Carlo simulations and bootstrap methods.
The GLO provides the neuroscientist with objective and reproducible classification rules for the firing patterns on the basis of the model ACF. These rules are inspired by visual inspection criteria often used in neuroscientific practice and thus support and complement usual analysis of empirical spike trains. When applied to a sample data set, the model is able to detect significant changes in the regularity and burst behavior of the cells and provides confidence intervals for the parameter estimates.
Computational oral absorption models, in particular PBBM models, provide a powerful tool for researchers and pharmaceutical scientists in drug discovery and formulation development, as they mimic and can describe the physiologically processes relevant to the oral absorption. PBBM models provide in vivo context to in vitro data experiments and allow for a dynamic understanding of in vivo drug disposition that is not typically provided by data from standard in vitro assays. Investigations using these models permit informed decision-making, especially regarding to formulation strategies in drug development. PBBM models, but can also be used to investigate and provide insight into mechanisms responsible for complex phenomena such as food effect in drug absorption. Although there are obviously still some gaps regarding the in silico construction of the gastrointestinal environment, ongoing research in the area of oral drug absorption (e.g. the UNGAP, AGE-POP and InPharma projects) will increase knowledge and enable improvement of these models.
PBBM can nowadays provide an alternative approach to the development of in vitro–in vivo correlations. The case studies presented in this thesis demonstrate how PBBM can address a mechanistic understanding of the negative food effect and be used to set clinically relevant dissolution specification for zolpidem immediate release tablets. In both cases, we demonstrated the importance of integrating drug properties with physiological variables to mechanistically understand and observe the impact of these parameters on oral drug absorption.
Various complex physiological processes are initiated upon food consumption, which can enhance or reduce a drug’s dissolution, solubility, and permeability and thus lead to changes in drug absorption. With improvements in modeling and simulation software and design of in vitro studies, PBBM modeling of food effects may eventually serve as a surrogate for clinical food effect studies for new doses and formulations or drugs. Furthermore, the application of these models may be even more critical in case of compounds where execution of clinical studies in healthy volunteers would be difficult (e.g., oncology drugs).
In the fourth chapter we have demonstrated the establishment of the link between biopredictive in vitro dissolution testing (QC or biorelevant method) PBBM coupled with PD modeling opens the opportunity to set truly clinically relevant specifications for drug release. This approach can be extended to other drugs regardless of its classification according to the BCS.
With the increased adoption of PBBM, we expect that best practices in development and verification of these models will be established that can eventually inform a regulatory guidance. Therefore, the application of Physiologically Based Biopharmaceutical Modelling is an area with great potential to streamline late-stage drug development and impact on regulatory approval procedures.
The miniaturization of electronics is reaching its limits. Structures necessary to build integrated circuits from semiconductors are shrinking and could reach the size of only a few atoms within the next few years. It will be at the latest at this point in time that the physics of nanostructures gains importance in our every day life. This thesis deals with the physics of quantum impurity models. All models of this class exhibit an identical structure: the simple and small impurity only has few degrees of freedom. It can be built out of a small number of atoms or a single molecule, for example. In the simplest case it can be described by a single spin degree of freedom, in many quantum impurity models, it can be treated exactly. The complexity of the description arises from its coupling to a large number of fermionic or bosonic degrees of freedom (large meaning that we have to deal with particle numbers of the order of 10^{23}). An exact treatment thus remains impossible. At the same time, physical effects which arise in quantum impurity systems often cannot be described within a perturbative theory, since multiple energy scales may play an important role. One example for such an effect is the Kondo effect, where the free magnetic moment of the impurity is screened by a "cloud" of fermionic particles of the quantum bath.
The Kondo effect is only one example for the rich physics stemming from correlation effects in many body systems. Quantum impurity models, and the oftentimes related Kondo effect, have regained the attention of experimental and theoretical physicists since the advent of quantum dots, which are sometimes also referred to as as artificial atoms. Quantum dots offer a unprecedented control and tunability of many system parameters. Hence, they constitute a nice "playground" for fundamental research, while being promising candidates for building blocks of future technological devices as well.
Recently Loss' and DiVincenzo's p roposal of a quantum computing scheme based on spins in quantum dots, increased the efforts of experimentalists to coherently manipulate and read out the spins of quantum dots one by one. In this context two topics are of paramount importance for future quantum information processing: since decoherence times have to be large enough to allow for good error correction schemes, understanding the loss of phase coherence in quantum impurity systems is a prerequisite for quantum computation in these systems. Nonequilibrium phenomena in quantum impurity systems also have to be understood, before one may gain control of manipulating quantum bits.
As a first step towards more complicated nonequilibrium situations, the reaction of a system to a quantum quench, i.e. a sudden change of external fields or other parameters of the system can be investigated. We give an introduction to a powerful numerical method used in this field of research, the numerical renormalization group method, and apply this method and its recent enhancements to various quantum impurity systems.
The main part of this thesis may be structured in the following way:
- Ferromagnetic Kondo Model,
- Spin-Dynamics in the Anisotropic Kondo and the Spin-Boson Model,
- Two Ising-coupled Spins in a Bosonic Bath,
- Decoherence in an Aharanov-Bohm Interferometer.
A novel role for mutant mRNA degradation in triggering transcriptional adaptation to mutations
(2020)
Robustness to mutations promotes organisms’ well-being and fitness. The increasing number of mutants in various model organisms, and humans, showing no obvious phenotype (Bouche and Bouchez, 2001; Chen et al., 2016b; Giaever et al., 2002; Kok et al., 2015) has renewed interest into how organisms adapt to gene loss. In the presence of deleterious mutations, genetic compensation by transcriptional upregulation of related gene(s) (also known as transcriptional adaptation) has been reported in numerous systems (El-Brolosy and Stainier, 2017; Rossi et al., 2015; Tondeleir et al., 2012); however, the molecular mechanisms underlying this response remained unclear. To investigate this phenomenon, I develop and study multiple models of transcriptional adaptation in zebrafish and mouse cell lines. I first show that transcriptional adaptation is not caused by loss of protein function, indicating that the trigger lies upstream, and find that the response involves enhanced transcription of the related gene(s). Furthermore, I observe a correlation between levels of mutant mRNA degradation and upregulation of related genes. To investigate the role of mutant mRNA degradation in triggering the response, I generate mutant alleles that do not transcribe the mutated gene and find that they fail to induce a transcriptional response and display stronger phenotypes. Transcriptome analysis of alleles displaying mutant mRNA degradation revealed upregulation of a significant proportion of genes displaying sequence similarity with the mutated gene’s mRNA, suggesting a model whereby mRNA degradation intermediates induce transcriptional adaptation via sequence similarity. Further mechanistic analyses suggested RNA-decay factors-dependent chromatin remodeling, and repression of antisense RNAs to be implicated in the response. These results identify a novel role for mutant mRNA degradation in buffering against mutations. Besides, they hold huge implications on understanding disease-causing mutations and shall help in designing mutations that lead to minimal transcriptional adaptation-induced compensation, facilitating studying gene function in model organisms.
In this dissertation a non-deterministic lambda-calculus with call-by-need evaluation is treated. Call-by-need means that subexpressions are evaluated at most once and only if their value must be known to compute the overall result. Also called "sharing", this technique is inevitable for an efficient implementation. In the lambda-ND calculus of chapter 3 sharing is represented explicitely by a let-construct. Above, the calculus has function application, lambda abstractions, sequential evaluation and pick for non-deterministic choice. Non-deterministic lambda calculi play a major role as a theoretical foundation for concurrent processes or side-effected input/output. In this work, non-determinism additionally makes visible when sharing is broken. Based on the bisimulation method this work develops a notion of equality which respects sharing. Using bisimulation to establish contextual equivalence requires substitutivity within contexts, i.e., the ability to "replace equals by equals" within every program or term. This property is called congruence or precongruence if it applies to a preorder. The open similarity of chapter 4 represents a new concept, insofar that the usual definition of a bisimulation is impossible in the lambda-ND calculus. So in section 3.2 a further calculus lambda-Approx has to be defined. Section 3.3 contains the proof of the so-called Approximation Theorem which states that the evaluation in lambda-ND and lambda-Approx agrees. The foundation for the non-trivial precongruence proof is set out in chapter 2 where the trailblazing method of Howe is extended to be capable with sharing. By the use of this (extended) method, the Precongruence Theorem proves open similarity to be a precongruence, involving the so-called precongruence candidate relation. Joining with the Approximation Theorem we obtain the Main Theorem which says that open similarity of the lambda-Approx calculus is contained within the contextual preorder of the lambda-ND calculus. However, this inclusion is strict, a property whose non-trivial proof involves the notion of syntactic continuity. Finally, chapter 6 discusses possible extensions of the base calculus such as recursive bindings or case and constructors. As a fundamental study the calculus lambda-ND provides neither of these concepts, since it was intentionally designed to keep the proofs as simple as possible. Section 6.1 illustrates that the addition case and constructors could be accomplished without big hurdles. However, recursive bindings cannot be represented simply by a fixed point combinator like Y, thus further investigations are necessary.
Seit einigen Jahrzehnten ist Lysozym eines der am meisten erforschten Proteine in der Literatur und wird hauptsächlich als Modell Protein zur Aufklärung der Faltungs- und Entfaltungsprozesse genutzt. Da die Frage nach Fehlfaltung und deren Verknüpfung mit neurodegenerativen Krankheiten bis zum heutigen Tag nicht vollständig geklärt ist, besteht hier ein großer Spielraum für weitere Forschungsansätze. In der vorliegenden Arbeit wurden daher zwei Modellsysteme verwendet, Hühereiweiß-Lysozym und menschliches Lysozym, jeweils in ihrem nicht-nativen ungefalteten Zustand. Diese ungefalteten Ensembles wurden mit Hilfe NMR spektroskopischer Methoden untersucht und ergaben sehr detaillierte, zum Teil auch überraschende neue Einblicke in Struktur und Dynamik der beiden Proteine und liefern somit wichtige Erkenntnisse zu Faltungs- und Aggregationsprozessen. ...
This work is concerned with two topics at the intersection of convex algebraic geometry and optimization.
We develop a new method for the optimization of polynomials over polytopes. From the point of view of convex algebraic geometry the most common method for the approximation of polynomial optimization problems is to solve semidefinite programming relaxations coming from the application of Positivstellensätze. In optimization, non-linear programming problems are often solved using branch and bound methods. We propose a fused method that uses Positivstellensatz-relaxations as lower bounding methods in a branch and bound scheme. By deriving a new error bound for Handelman's Positivstellensatz, we show convergence of the resulting branch and bound method. Through the application of Positivstellensätze, semidefinite programming has gained importance in polynomial optimization in recent years. While it arises to be a powerful tool, the underlying geometry of the feasibility regions (spectrahedra) is not yet well understood. In this work, we study polyhedral and spectrahedral containment problems, in particular we classify their complexity and introduce sufficient criteria to certify the containment of one spectrahedron in another one.