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The synthesis of two novel types of π-expanded coumarins has been developed. Modified Knoevenagel bis-condensation afforded 3,9-dioxa-perylene-2,8-diones. Subsequent oxidative aromatic coupling or light driven electrocyclization reaction led to dibenzo-1,7-dioxacoronene-2,8-dione. Unparalleled synthetic simplicity, straightforward purification and superb optical properties have the potential to bring these perylene and coronene analogs towards various applications.
Two-photon polymerization of hydrogels – versatile solutions to fabricate well-defined 3D structures
(2014)
Hydrogels are cross-linked water-containing polymer networks that are formed by physical, ionic or covalent interactions. In recent years, they have attracted significant attention because of their unique physical properties, which make them promising materials for numerous applications in food and cosmetic processing, as well as in drug delivery and tissue engineering. Hydrogels are highly water-swellable materials, which can considerably increase in volume without losing cohesion, are biocompatible and possess excellent tissue-like physical properties, which can mimic in vivo conditions. When combined with highly precise manufacturing technologies, such as two-photon polymerization (2PP), well-defined three-dimensional structures can be obtained. These structures can become scaffolds for selective cell-entrapping, cell/drug delivery, sensing and prosthetic implants in regenerative medicine. 2PP has been distinguished from other rapid prototyping methods because it is a non-invasive and efficient approach for hydrogel cross-linking. This review discusses the 2PP-based fabrication of 3D hydrogel structures and their potential applications in biotechnology. A brief overview regarding the 2PP methodology and hydrogel properties relevant to biomedical applications is given together with a review of the most important recent achievements in the field.
A new functional luminescent lanthanide complex (LLC) has been synthesized with terbium as a central lanthanide ion and biotin as a functional moiety. Unlike in typical lanthanide complexes assembled via carboxylic moieties, in the presented complex, four phosphate groups are chelating the central lanthanide ion. This special chemical assembly enhances the complex stability in phosphate buffers conventionally used in biochemistry. The complex synthesis strategy and photophysical properties are described as well as the performance in time-resolved Förster Resonance Energy Transfer (FRET) assays. In those assays, this biotin-LLC transferred energy either to acceptor organic dyes (Cy5 or AF680) labelled on streptavidin or to quantum dots (QD655 or QD705) surface-functionalised with streptavidins. The permanent spatial donor–acceptor proximity is assured through strong and stable biotin–streptavidin binding. The energy transfer is evidenced from the quenching observed in donor emission and from a decrease in donor luminescence decay, both associated with simultaneous increase in acceptor intensity and in the decay time. The dye-based assays are realised in TRIS and in PBS, whereas QD-based systems are studied in borate buffer. The delayed emission analysis allows for quantifying the recognition process and for auto-fluorescence-free detection, which is particularly relevant for application in bioanalysis. In accordance with Förster theory, Förster-radii (R0) were found to be around 60 Å for organic dyes and around 105 Å for QDs. The FRET efficiency (η) reached 80% and 25% for dye and QD acceptors, respectively. Physical donor–acceptor distances (r) have been determined in the range 45–60 Å for organic dye acceptors, while for acceptor QDs between 120 Å and 145 Å. This newly synthesised biotin-LLC extends the class of highly sensitive analytical tools to be applied in the bioanalytical methods such as time-resolved fluoroimmunoassays (TR-FIA), luminescent imaging and biosensing.
This book presents an agile and model-driven approach to manage scientific workflows. The approach is based on the Extreme Model Driven Design (XMDD) paradigm and aims at simplifying and automating the complex data analysis processes carried out by scientists in their day-to-day work. Besides documenting the impact the workflow modeling might have on the work of natural scientists, this book serves three major purposes: 1. It acts as a primer for practitioners who are interested to learn how to think in terms of services and workflows when facing domain-specific scientific processes. 2. It provides interesting material for readers already familiar with this kind of tools, because it introduces systematically both the technologies used in each case study and the basic concepts behind them. 3. As the addressed thematic field becomes increasingly relevant for lectures in both computer science and experimental sciences, it also provides helpful material for teachers that plan similar courses.
Potentiality of nanosized materials has been largely proved but a closer look shows that a significant percentage of this research is related to oxides and metals, while the number drastically drops for metallic ceramics, namely transition metal nitrides and metal carbides. The lack of related publications do not reflect their potential but rather the difficulties related to their synthesis as dense and defect-free structures, fundamental prerequisites for advanced mechanical applications.
The present habilitation work aims to close the gap between preparation and processing, indicating novel synthetic pathways for a simpler and sustainable synthesis of transition metal nitride (MN) and carbide (MC) based nanostructures and easier processing thereafter. In spite of simplicity and reliability, the designed synthetic processes allow the production of functional materials, with the demanded size and morphology.
The goal was achieved exploiting classical and less-classical precursors, ranging from common metal salts and molecules (e.g. urea, gelatin, agar, etc), to more exotic materials, such as leafs, filter paper and even wood. It was found that the choice of precursors and reaction conditions makes it possible to control chemical composition (going for instance from metal oxides to metal oxy-nitrides to metal nitrides, or from metal nitrides to metal carbides, up to quaternary systems), size (from 5 to 50 nm) and morphology (going from mere spherical nanoparticles to rod-like shapes, fibers, layers, meso-porous and hierarchical structures, etc). The nature of the mixed precursors also allows the preparation of metal nitrides/carbides based nanocomposites, thus leading to multifunctional materials (e.g. MN/MC@C, MN/MC@PILs, etc) but also allowing dispersion in liquid media. Control over composition, size and morphology is obtained with simple adjustment of the main route, but also coupling it with processes such as electrospin, aerosol spray, bio-templating, etc. Last but not least, the nature of the precursor materials also allows easy processing, including printing, coating, casting, film and thin layers preparation, etc).
The designed routes are, concept-wise, similar and they all start by building up a secondary metal ion-N/C precursor network, which converts, upon heat treatment, into an intermediate “glass”. This glass stabilizes the nascent nanoparticles during their nucleation and impairs their uncontrolled growth during the heat treatment (scheme 1). This way, one of the main problems related to the synthesis of MN/MC, i.e. the need of very high temperature, could also be overcome (from up to 2000°C, for classical synthesis, down to 700°C in the present cases). The designed synthetic pathways are also conceived to allow usage of non-toxic compounds and to minimize (or even avoid) post-synthesis purification, still bringing to phase pure and well-defined (crystalline) nanoparticles.
This research aids to simplify the preparation of MN/MC, making these systems now readily available in suitable amounts both for fundamental and applied science. The prepared systems have been tested (in some cases for the first time) in many different fields, e.g. battery (MnN0.43@C shown a capacity stabilized at a value of 230 mAh/g, with coulombic efficiencies close to 100%), as alternative magnetic materials (Fe3C nanoparticles were prepared with different size and therefore different magnetic behavior, superparamagnetic or ferromagnetic, showing a saturation magnetization value up to 130 emu/g, i.e. similar to the value expected for the bulk material), as filters and for the degradation of organic dyes (outmatching the performance of carbon), as catalysts (both as active phase but also as active support, leading to high turnover rate and, more interesting, to tunable selectivity). Furthermore, with this route, it was possible to prepare for the first time, to the best of our knowledge, well-defined and crystalline MnN0.43, Fe3C and Zn1.7GeN1.8O nanoparticles via bottom-up approaches.
Once the synthesis of these materials can be made straightforward, any further modification, combination, manipulation, is in principle possible and new systems can be purposely conceived (e.g. hybrids, nanocomposites, ferrofluids, etc).
The atmosphere over the Arctic Ocean is strongly influenced by the distribution of sea ice and open water. Leads in the sea ice produce strong convective fluxes of sensible and latent heat and release aerosol particles into the atmosphere. They increase the occurrence of clouds and modify the structure and characteristics of the atmospheric boundary layer (ABL) and thereby influence the Arctic climate.
In the course of this study aircraft measurements were performed over the western Arctic Ocean as part of the campaign PAMARCMIP 2012 of the Alfred Wegener Institute for Polar and Marine Research (AWI). Backscatter from aerosols and clouds within the lower troposphere and the ABL were measured with the nadir pointing Airborne Mobile Aerosol Lidar (AMALi) and dropsondes were launched to obtain profiles of meteorological variables. Furthermore, in situ measurements of aerosol properties, meteorological variables and turbulence were part of the campaign. The measurements covered a broad range of atmospheric and sea ice conditions.
In this thesis, properties of the ABL over Arctic sea ice with a focus on the influence of open leads are studied based on the data from the PAMARCMIP campaign. The height of the ABL is determined by different methods that are applied to dropsonde and AMALi backscatter profiles. ABL heights are compared for different flights representing different conditions of the atmosphere and of sea ice and open water influence. The different criteria for ABL height that are applied show large variation in terms of agreement among each other, depending on the characteristics of the ABL and its history. It is shown that ABL height determination from lidar backscatter by methods commonly used under mid-latitude conditions is applicable to the Arctic ABL only under certain conditions. Aerosol or clouds within the ABL are needed as a tracer for ABL height detection from backscatter. Hence an aerosol source close to the surface is necessary, that is typically found under the present influence of open water and therefore convective conditions. However it is not always possible to distinguish residual layers from the actual ABL. Stable boundary layers are generally difficult to detect.
To illustrate the complexity of the Arctic ABL and processes therein, four case studies are analyzed each of which represents a snapshot of the interplay between atmosphere and underlying sea ice or water surface. Influences of leads and open water on the aerosol and clouds within the ABL are identified and discussed. Leads are observed to cause the formation of fog and cloud layers within the ABL by humidity emission. Furthermore they decrease the stability and increase the height of the ABL and consequently facilitate entrainment of air and aerosol layers from the free troposphere.
Cyanobacteria produce about 40 percent of the world’s primary biomass, but also a variety of often toxic peptides such as microcystin. Mass developments, so called blooms, can pose a real threat to the drinking water supply in many parts of the world. This study aimed at characterizing the biological function of microcystin production in one of the most common bloom-forming cyanobacterium Microcystis aeruginosa.
In a first attempt, the effect of elevated light intensity on microcystin production and its binding to cellular proteins was studied. Therefore, conventional microcystin quantification techniques were combined with protein-biochemical methods. RubisCO, the key enzyme for primary carbon fixation was a major microcystin interaction partner. High light exposition strongly stimulated microcystin-protein interactions. Up to 60 percent of the total cellular microcystin was detected bound to proteins, i.e. inaccessible for standard quantification procedures. Underestimation of total microcystin contents when neglecting the protein fraction was also demonstrated in field samples. Finally, an immuno-fluorescence based method was developed to identify microcystin producing cyanobacteria in mixed populations.
The high light induced microcystin interaction with proteins suggested an impact of the secondary metabolite on the primary metabolism of Microcystis by e.g. modulating the activity of enzymes. For addressing that question, a comprehensive GC/MS-based approach was conducted to compare the accumulation of metabolites in the wild-type of Microcystis aeruginosa PCC 7806 and the microcystin deficient ΔmcyB mutant. From all 501 detected non-redundant metabolites 85 (17 percent) accumulated significantly different in either of both genotypes upon high light exposition. Accumulation of compatible solutes in the ΔmcyB mutant suggests a role of microcystin in fine-tuning the metabolic flow to prevent stress related to excess light, high oxygen concentration and carbon limitation.
Co-analysis of the widely used model cyanobacterium Synechocystis PCC 6803 revealed profound metabolic differences between species of cyanobacteria. Whereas Microcystis channeled more resources towards carbohydrate synthesis, Synechocystis invested more in amino acids. These findings were supported by electron microscopy of high light treated cells and the quantification of storage compounds. While Microcystis accumulated mainly glycogen to about 8.5 percent of its fresh weight within three hours, Synechocystis produced higher amounts of cyanophycin. The results showed that the characterization of species-specific metabolic features should gain more attention with regard to the biotechnological use of cyanobacteria.
Modern microscopic techniques following the stochastic motion of labelled tracer particles have uncovered significant deviations from the laws of Brownian motion in a variety of animate and inanimate systems. Such anomalous diffusion can have different physical origins, which can be identified from careful data analysis. In particular, single particle tracking provides the entire trajectory of the traced particle, which allows one to evaluate different observables to quantify the dynamics of the system under observation. We here provide an extensive overview over different popular anomalous diffusion models and their properties. We pay special attention to their ergodic properties, highlighting the fact that in several of these models the long time averaged mean squared displacement shows a distinct disparity to the regular, ensemble averaged mean squared displacement. In these cases, data obtained from time averages cannot be interpreted by the standard theoretical results for the ensemble averages. Here we therefore provide a comparison of the main properties of the time averaged mean squared displacement and its statistical behaviour in terms of the scatter of the amplitudes between the time averages obtained from different trajectories. We especially demonstrate how anomalous dynamics may be identified for systems, which, on first sight, appear to be Brownian. Moreover, we discuss the ergodicity breaking parameters for the different anomalous stochastic processes and showcase the physical origins for the various behaviours. This Perspective is intended as a guidebook for both experimentalists and theorists working on systems, which exhibit anomalous diffusion.
Modern microscopic techniques following the stochastic motion of labelled tracer particles have uncovered significant deviations from the laws of Brownian motion in a variety of animate and inanimate systems. Such anomalous diffusion can have different physical origins, which can be identified from careful data analysis. In particular, single particle tracking provides the entire trajectory of the traced particle, which allows one to evaluate different observables to quantify the dynamics of the system under observation. We here provide an extensive overview over different popular anomalous diffusion models and their properties. We pay special attention to their ergodic properties, highlighting the fact that in several of these models the long time averaged mean squared displacement shows a distinct disparity to the regular, ensemble averaged mean squared displacement. In these cases, data obtained from time averages cannot be interpreted by the standard theoretical results for the ensemble averages. Here we therefore provide a comparison of the main properties of the time averaged mean squared displacement and its statistical behaviour in terms of the scatter of the amplitudes between the time averages obtained from different trajectories. We especially demonstrate how anomalous dynamics may be identified for systems, which, on first sight, appear to be Brownian. Moreover, we discuss the ergodicity breaking parameters for the different anomalous stochastic processes and showcase the physical origins for the various behaviours. This Perspective is intended as a guidebook for both experimentalists and theorists working on systems, which exhibit anomalous diffusion.
New porous materials based on covalently connected monomers are presented. The key step of the synthesis is an acetalisation reaction. In previous years we used acetalisation reactions extensively to build up various molecular rods. Based on this approach, investigations towards porous polymeric materials were conducted by us. Here we wish to present the results of these studies in the synthesis of 1D polyacetals and porous 3D polyacetals. By scrambling experiments with 1D acetals we could prove that exchange reactions occur between different building blocks (evidenced by MALDI-TOF mass spectrometry). Based on these results we synthesized porous 3D polyacetals under the same mild conditions.
New porous materials based on covalently connected monomers are presented. The key step of the synthesis is an acetalisation reaction. In previous years we used acetalisation reactions extensively to build up various molecular rods. Based on this approach, investigations towards porous polymeric materials were conducted by us. Here we wish to present the results of these studies in the synthesis of 1D polyacetals and porous 3D polyacetals. By scrambling experiments with 1D acetals we could prove that exchange reactions occur between different building blocks (evidenced by MALDI-TOF mass spectrometry). Based on these results we synthesized porous 3D polyacetals under the same mild conditions.
Picosecond X-ray absorption spectroscopy (XAS) is used to investigate the electronic and structural dynamics initiated by plasmon excitation of 1.8 nm diameter Au nanoparticles (NPs) functionalised with 1-hexanethiol. We show that 100 ps after photoexcitation the transient XAS spectrum is consistent with an 8% expansion of the Au–Au bond length and a large increase in disorder associated with melting of the NPs. Recovery of the ground state occurs with a time constant of ∼1.8 ns, arising from thermalisation with the environment. Simulations reveal that the transient spectrum exhibits no signature of charge separation at 100 ps and allows us to estimate an upper limit for the quantum yield (QY) of this process to be <0.1.
Picosecond X-ray absorption spectroscopy (XAS) is used to investigate the electronic and structural dynamics initiated by plasmon excitation of 1.8 nm diameter Au nanoparticles (NPs) functionalised with 1-hexanethiol. We show that 100 ps after photoexcitation the transient XAS spectrum is consistent with an 8% expansion of the Au–Au bond length and a large increase in disorder associated with melting of the NPs. Recovery of the ground state occurs with a time constant of ∼1.8 ns, arising from thermalisation with the environment. Simulations reveal that the transient spectrum exhibits no signature of charge separation at 100 ps and allows us to estimate an upper limit for the quantum yield (QY) of this process to be <0.1.
We study the thermal Markovian diffusion of tracer particles in a 2D medium with spatially varying diffusivity D(r), mimicking recently measured, heterogeneous maps of the apparent diffusion coefficient in biological cells. For this heterogeneous diffusion process (HDP) we analyse the mean squared displacement (MSD) of the tracer particles, the time averaged MSD, the spatial probability density function, and the first passage time dynamics from the cell boundary to the nucleus. Moreover we examine the non-ergodic properties of this process which are important for the correct physical interpretation of time averages of observables obtained from single particle tracking experiments. From extensive computer simulations of the 2D stochastic Langevin equation we present an in-depth study of this HDP. In particular, we find that the MSDs along the radial and azimuthal directions in a circular domain obey anomalous and Brownian scaling, respectively. We demonstrate that the time averaged MSD stays linear as a function of the lag time and the system thus reveals a weak ergodicity breaking. Our results will enable one to rationalise the diffusive motion of larger tracer particles such as viruses or submicron beads in biological cells.
We study the thermal Markovian diffusion of tracer particles in a 2D medium with spatially varying diffusivity D(r), mimicking recently measured, heterogeneous maps of the apparent diffusion coefficient in biological cells. For this heterogeneous diffusion process (HDP) we analyse the mean squared displacement (MSD) of the tracer particles, the time averaged MSD, the spatial probability density function, and the first passage time dynamics from the cell boundary to the nucleus. Moreover we examine the non-ergodic properties of this process which are important for the correct physical interpretation of time averages of observables obtained from single particle tracking experiments. From extensive computer simulations of the 2D stochastic Langevin equation we present an in-depth study of this HDP. In particular, we find that the MSDs along the radial and azimuthal directions in a circular domain obey anomalous and Brownian scaling, respectively. We demonstrate that the time averaged MSD stays linear as a function of the lag time and the system thus reveals a weak ergodicity breaking. Our results will enable one to rationalise the diffusive motion of larger tracer particles such as viruses or submicron beads in biological cells.
Arsenic-containing hydrocarbons are one group of fat-soluble organic arsenic compounds (arsenolipids) found in marine fish and other seafood. A risk assessment of arsenolipids is urgently needed, but has not been possible because of the total lack of toxicological data. In this study the cellular toxicity of three arsenic-containing hydrocarbons was investigated in cultured human bladder (UROtsa) and liver (HepG2) cells. Cytotoxicity of the arsenic-containing hydrocarbons was comparable to that of arsenite, which was applied as the toxic reference arsenical. A large cellular accumulation of arsenic, as measured by ICP-MS/MS, was observed after incubation of both cell lines with the arsenolipids. Moreover, the toxic mode of action shown by the three arsenic-containing hydrocarbons seemed to differ from that observed for arsenite. Evidence suggests that the high cytotoxic potential of the lipophilic arsenicals results from a decrease in the cellular energy level. This first in vitro based risk assessment cannot exclude a risk to human health related to the presence of arsenolipids in seafood, and indicates the urgent need for further toxicity studies in experimental animals to fully assess this possible risk.
Arsenic-containing hydrocarbons are one group of fat-soluble organic arsenic compounds (arsenolipids) found in marine fish and other seafood. A risk assessment of arsenolipids is urgently needed, but has not been possible because of the total lack of toxicological data. In this study the cellular toxicity of three arsenic-containing hydrocarbons was investigated in cultured human bladder (UROtsa) and liver (HepG2) cells. Cytotoxicity of the arsenic-containing hydrocarbons was comparable to that of arsenite, which was applied as the toxic reference arsenical. A large cellular accumulation of arsenic, as measured by ICP-MS/MS, was observed after incubation of both cell lines with the arsenolipids. Moreover, the toxic mode of action shown by the three arsenic-containing hydrocarbons seemed to differ from that observed for arsenite. Evidence suggests that the high cytotoxic potential of the lipophilic arsenicals results from a decrease in the cellular energy level. This first in vitro based risk assessment cannot exclude a risk to human health related to the presence of arsenolipids in seafood, and indicates the urgent need for further toxicity studies in experimental animals to fully assess this possible risk.
This study aims to further mechanistically understand toxic modes of action after chronic inorganic arsenic exposure. Therefore long-term incubation studies in cultured cells were carried out, to display chronically attained changes, which cannot be observed in the generally applied in vitro short-term incubation studies. Particularly, the cytotoxic, genotoxic and epigenetic effects of an up to 21 days incubation of human urothelial (UROtsa) cells with pico- to nanomolar concentrations of iAsIII and its metabolite thio-DMAV were compared. After 21 days of incubation, cytotoxic effects were strongly enhanced in the case of iAsIII and might partly be due to glutathione depletion and genotoxic effects on the chromosomal level. These results are in strong contrast to cells exposed to thio-DMAV. Thus, cells seemed to be able to adapt to this arsenical, as indicated among others by an increase in the cellular glutathione level. Most interestingly, picomolar concentrations of both iAsIII and thio-DMAV caused global DNA hypomethylation in UROtsa cells, which was quantified in parallel by 5-medC immunostaining and a newly established, reliable, high resolution mass spectrometry (HRMS)-based test system. This is the first time that epigenetic effects are reported for thio-DMAV; iAsIII induced epigenetic effects occur in at least 8000 fold lower concentrations as reported in vitro before. The fact that both arsenicals cause DNA hypomethylation at really low, exposure-relevant concentrations in human urothelial cells suggests that this epigenetic effect might contribute to inorganic arsenic induced carcinogenicity, which for sure has to be further investigated in future studies.
This study aims to further mechanistically understand toxic modes of action after chronic inorganic arsenic exposure. Therefore long-term incubation studies in cultured cells were carried out, to display chronically attained changes, which cannot be observed in the generally applied in vitro short-term incubation studies. Particularly, the cytotoxic, genotoxic and epigenetic effects of an up to 21 days incubation of human urothelial (UROtsa) cells with pico- to nanomolar concentrations of iAsIII and its metabolite thio-DMAV were compared. After 21 days of incubation, cytotoxic effects were strongly enhanced in the case of iAsIII and might partly be due to glutathione depletion and genotoxic effects on the chromosomal level. These results are in strong contrast to cells exposed to thio-DMAV. Thus, cells seemed to be able to adapt to this arsenical, as indicated among others by an increase in the cellular glutathione level. Most interestingly, picomolar concentrations of both iAsIII and thio-DMAV caused global DNA hypomethylation in UROtsa cells, which was quantified in parallel by 5-medC immunostaining and a newly established, reliable, high resolution mass spectrometry (HRMS)-based test system. This is the first time that epigenetic effects are reported for thio-DMAV; iAsIII induced epigenetic effects occur in at least 8000 fold lower concentrations as reported in vitro before. The fact that both arsenicals cause DNA hypomethylation at really low, exposure-relevant concentrations in human urothelial cells suggests that this epigenetic effect might contribute to inorganic arsenic induced carcinogenicity, which for sure has to be further investigated in future studies.
Probably no other field of statistical physics at the borderline of soft matter and biological physics has caused such a flurry of papers as polymer translocation since the 1994 landmark paper by Bezrukov, Vodyanoy, and Parsegian and the study of Kasianowicz in 1996. Experiments, simulations, and theoretical approaches are still contributing novel insights to date, while no universal consensus on the statistical understanding of polymer translocation has been reached. We here collect the published results, in particular, the famous–infamous debate on the scaling exponents governing the translocation process. We put these results into perspective and discuss where the field is going. In particular, we argue that the phenomenon of polymer translocation is non-universal and highly sensitive to the exact specifications of the models and experiments used towards its analysis.
Probably no other field of statistical physics at the borderline of soft matter and biological physics has caused such a flurry of papers as polymer translocation since the 1994 landmark paper by Bezrukov, Vodyanoy, and Parsegian and the study of Kasianowicz in 1996. Experiments, simulations, and theoretical approaches are still contributing novel insights to date, while no universal consensus on the statistical understanding of polymer translocation has been reached. We here collect the published results, in particular, the famous–infamous debate on the scaling exponents governing the translocation process. We put these results into perspective and discuss where the field is going. In particular, we argue that the phenomenon of polymer translocation is non-universal and highly sensitive to the exact specifications of the models and experiments used towards its analysis.
Anomalous diffusion is frequently described by scaled Brownian motion (SBM){,} a Gaussian process with a power-law time dependent diffusion coefficient. Its mean squared displacement is ?x2(t)? [similar{,} equals] 2K(t)t with K(t) [similar{,} equals] t[small alpha]-1 for 0 < [small alpha] < 2. SBM may provide a seemingly adequate description in the case of unbounded diffusion{,} for which its probability density function coincides with that of fractional Brownian motion. Here we show that free SBM is weakly non-ergodic but does not exhibit a significant amplitude scatter of the time averaged mean squared displacement. More severely{,} we demonstrate that under confinement{,} the dynamics encoded by SBM is fundamentally different from both fractional Brownian motion and continuous time random walks. SBM is highly non-stationary and cannot provide a physical description for particles in a thermalised stationary system. Our findings have direct impact on the modelling of single particle tracking experiments{,} in particular{,} under confinement inside cellular compartments or when optical tweezers tracking methods are used.
Geocoder accuracy ranking
(2014)
Finding an address on a map is sometimes tricky: the chosen map application may be unfamiliar with the enclosed region. There are several geocoders on the market, they have different databases and algorithms to compute the query. Consequently, the geocoding results differ in their quality. Fortunately the geocoders provide a rich set of metadata. The workflow described in this paper compares this metadata with the aim to find out which geocoder is offering the best-fitting coordinate for a given address.
Geometric generalization is a fundamental concept in the digital mapping process. An increasing amount of spatial data is provided on the web as well as a range of tools to process it. This jABC workflow is used for the automatic testing of web-based generalization services like mapshaper.org by executing its functionality, overlaying both datasets before and after the transformation and displaying them visually in a .tif file. Mostly Web Services and command line tools are used to build an environment where ESRI shapefiles can be uploaded, processed through a chosen generalization service and finally visualized in Irfanview.
In the geoinformatics field, remote sensing data is often used for analyzing the characteristics of the current investigation area. This includes DEMs, which are simple raster grids containing grey scales representing the respective elevation values. The project CREADED that is presented in this paper aims at making these monochrome raster images more significant and more intuitively interpretable. For this purpose, an executable interactive model for creating a colored and relief-shaded Digital Elevation Model (DEM) has been designed using the jABC framework. The process is based on standard jABC-SIBs and SIBs that provide specific GIS functions, which are available as Web services, command line tools and scripts.
This paper describes the implementation of a workflow model for service-oriented computing of potential areas for wind turbines in jABC. By implementing a re-executable model the manual effort of a multi-criteria site analysis can be reduced. The aim is to determine the shift of typical geoprocessing tools of geographic information systems (GIS) from the desktop to the web. The analysis is based on a vector data set and mainly uses web services of the “Center for Spatial Information Science and Systems” (CSISS). This paper discusses effort, benefits and problems associated with the use of the web services.
Location analyses are among the most common tasks while working with spatial data and geographic information systems. Automating the most frequently used procedures is therefore an important aspect of improving their usability. In this context, this project aims to design and implement a workflow, providing some basic tools for a location analysis. For the implementation with jABC, the workflow was applied to the problem of finding a suitable location for placing an artificial reef. For this analysis three parameters (bathymetry, slope and grain size of the ground material) were taken into account, processed, and visualized with the The Generic Mapping Tools (GMT), which were integrated into the workflow as jETI-SIBs. The implemented workflow thereby showed that the approach to combine jABC with GMT resulted in an user-centric yet user-friendly tool with high-quality cartographic outputs.
Creation of topographic maps
(2014)
Location analyses are among the most common tasks while working with spatial data and geographic information systems. Automating the most frequently used procedures is therefore an important aspect of improving their usability. In this context, this project aims to design and implement a workflow, providing some basic tools for a location analysis. For the implementation with jABC, the workflow was applied to the problem of finding a suitable location for placing an artificial reef. For this analysis three parameters (bathymetry, slope and grain size of the ground material) were taken into account, processed, and visualized with the The Generic Mapping Tools (GMT), which were integrated into the workflow as jETI-SIBs. The implemented workflow thereby showed that the approach to combine jABC with GMT resulted in an user-centric yet user-friendly tool with high-quality cartographic outputs.
GraffDok is an application helping to maintain an overview over sprayed images somewhere in a city. At the time of writing it aims at vandalism rather than at beautiful photographic graffiti in an underpass. Looking at hundreds of tags and scribbles on monuments, house walls, etc. it would be interesting to not only record them in writing but even make them accessible electronically, including images.
GraffDok’s workflow is simple and only requires an EXIF-GPS-tagged photograph of a graffito. It automatically determines its location by using reverse geocoding with the given GPS-coordinates and the Gisgraphy WebService. While asking the user for some more meta data, GraffDok analyses the image in parallel with this and tries to detect fore- and background – before extracting the drawing lines and make them stand alone. The command line based tool ImageMagick is used here as well as for accessing EXIF data.
Any meta data is written to csv-files, which will stay easily accessible and can be integrated in TeX-files as well. The latter ones are converted to PDF at the end of the workflow, containing a table about all graffiti and a summary for each – including the generated characteristic graffiti pattern image.
The protein classification workflow described in this report enables users to get information about a novel protein sequence automatically. The information is derived by different bioinformatic analysis tools which calculate or predict features of a protein sequence. Also, databases are used to compare the novel sequence with known proteins.
Analyses of metagenomes in life sciences present new opportunities as well as challenges to the scientific community and call for advanced computational methods and workflows. The large amount of data collected from samples via next-generation sequencing (NGS) technologies render manual approaches to sequence comparison and annotation unsuitable. Rather, fast and efficient computational pipelines are needed to provide comprehensive statistics and summaries and enable the researcher to choose appropriate tools for more specific analyses. The workflow presented here builds upon previous pipelines designed for automated clustering and annotation of raw sequence reads obtained from next-generation sequencing technologies such as 454 and Illumina. Employing specialized algorithms, the sequence reads are processed at three different levels. First, raw reads are clustered at high similarity cutoff to yield clusters which can be exported as multifasta files for further analyses. Independently, open reading frames (ORFs) are predicted from raw reads and clustered at two strictness levels to yield sets of non-redundant sequences and ORF families. Furthermore, single ORFs are annotated by performing searches against the Pfam database
Exploratory Data Analysis
(2014)
In bioinformatics the term exploratory data analysis refers to different methods to get an overview of large biological data sets. Hence, it helps to create a framework for further analysis and hypothesis testing. The workflow facilitates this first important step of the data analysis created by high-throughput technologies. The results are different plots showing the structure of the measurements. The goal of the workflow is the automatization of the exploratory data analysis, but also the flexibility should be guaranteed. The basic tool is the free software R.
With the jABC it is possible to realize workflows for numerous questions in different fields. The goal of this project was to create a workflow for the identification of differentially expressed genes. This is of special interest in biology, for it gives the opportunity to get a better insight in cellular changes due to exogenous stress, diseases and so on. With the knowledge that can be derived from the differentially expressed genes in diseased tissues, it becomes possible to find new targets for treatment.
A workflow for visualizing server connections using the Google Maps API was built in the jABC. It makes use of three basic services: An XML-based IP address geolocation web service, a command line tool and the Static Maps API. The result of the workflow is an URL leading to an image file of a map, showing server connections between a client and a target host.
Spotlocator is a game wherein people have to guess the spots of where photos were taken. The photos of a defined area for each game are from panoramio.com. They are published at http://spotlocator. drupalgardens.com with an ID. Everyone can guess the photo spots by sending a special tweet via Twitter that contains the hashtag #spotlocator, the guessed coordinates and the ID of the photo. An evaluation is published for all tweets. The players are informed about the distance to the real photo spots and the positions are shown on a map.
Through the use of next generation sequencing (NGS) technology, a lot of newly sequenced organisms are now available. Annotating those genes is one of the most challenging tasks in sequence biology. Here, we present an automated workflow to find homologue proteins, annotate sequences according to function and create a three-dimensional model.
In this project I constructed a workflow that takes a DNA sequence as input and provides a phylogenetic tree, consisting of the input sequence and other sequences which were found during a database search. In this phylogenetic tree the sequences are arranged depending on similarities. In bioinformatics, constructing phylogenetic trees is often used to explore the evolutionary relationships of genes or organisms and to understand the mechanisms of evolution itself.
Civil society is either considered as a motor of democratization or stabilizer of authoritarian rule. This dichotomy is partly due to the dominance of domains-based definitions of the concept that reduce civil society to a small range of formally organized, independent and democratically oriented NGOs. Additionally, research often treats civil society as a ‘black box’ without differentiating between potential variations in impact of different types of civil society actors on existing regime structures. In this thesis, I present an alternative conceptualization of civil society based on the interactions of societal actors to arrive at a more inclusive understanding of the term which is more suited for analysis in non-democratic settings. The operationalization of the action-based approach I develop allows for an empirical assessment of a large range of societal activities that can accordingly be categorized from little to very civil society-like depending on their specific modes of interactions within four dimensions. I employ this operationalization in a qualitative case study including different actors in the authoritarian monarchy of Jordan which suggests that Jordanian societal actors mostly exhibit tolerant and democratically oriented modes of interaction and do not reproduce authoritarian patterns. However, even democratically oriented actors do not necessarily take on an oppositional positions vis-à-vis the authoritarian regime. Thus, the Jordanian civil society might not feature a high potential to challenge existing power structures in the country.
In March 2010, the project CoCoCo (incipient COntinent-COntinent COllision) recorded a 650 km long amphibian N-S wide-angle seismic profile, extending from the Eratosthenes Seamount (ESM) across Cyprus and southern Turkey to the Anatolian plateau. The aim of the project is to reveal the impact of the transition from subduction to continent-continent collision of the African plate with the Cyprus-Anatolian plate. A visual quality check, frequency analysis and filtering were applied to the seismic data and reveal a good data quality. Subsequent first break picking, finite-differences ray tracing and inversion of the offshore wide-angle data leads to a first-arrival tomographic model. This model reveals (1) P-wave velocities lower than 6.5 km/s in the crust, (2) a variable crustal thickness of about 28 - 37 km and (3) an upper crustal reflection at 5 km depth beneath the ESM. Two land shots on Turkey, also recorded on Cyprus, airgun shots south of Cyprus and geological and previous seismic investigations provide the information to derive a layered velocity model beneath the Anatolian plateau and for the ophiolite complex on Cyprus. The analysis of the reflections provides evidence for a north-dipping plate subducting beneath Cyprus. The main features of this layered velocity model are (1) an upper and lower crust with large lateral changes of the velocity structure and thickness, (2) a Moho depth of about 38 - 45 km beneath the Anatolian plateau, (3) a shallow north-dipping subducting plate below Cyprus with an increasing dip and (4) a typical ophiolite sequence on Cyprus with a total thickness of about 12 km. The offshore-onshore seismic data complete and improve the information about the velocity structure beneath Cyprus and the deeper part of the offshore tomographic model. Thus, the wide-angle seismic data provide detailed insights into the 2-D geometry and velocity structures of the uplifted and overriding Cyprus-Anatolian plate. Subsequent gravity modelling confirms and extends the crustal P-wave velocity model. The deeper part of the subducting plate is constrained by the gravity data and has a dip angle of ~ 28°. Finally, an integrated analysis of the geophysical and geological information allows a comprehensive interpretation of the crustal structure related to the collision process.
Scientific inquiry requires that we formulate not only what we know, but also what we do not know and by how much. In climate data analysis, this involves an accurate specification of measured quantities and a consequent analysis that consciously propagates the measurement errors at each step. The dissertation presents a thorough analytical method to quantify errors of measurement inherent in paleoclimate data. An additional focus are the uncertainties in assessing the coupling between different factors that influence the global mean temperature (GMT).
Paleoclimate studies critically rely on `proxy variables' that record climatic signals in natural archives. However, such proxy records inherently involve uncertainties in determining the age of the signal. We present a generic Bayesian approach to analytically determine the proxy record along with its associated uncertainty, resulting in a time-ordered sequence of correlated probability distributions rather than a precise time series. We further develop a recurrence based method to detect dynamical events from the proxy probability distributions. The methods are validated with synthetic examples and
demonstrated with real-world proxy records. The proxy estimation step reveals the interrelations between proxy variability and uncertainty. The recurrence analysis of the East Asian Summer Monsoon during the last 9000 years confirms the well-known `dry' events at 8200 and 4400 BP, plus an additional significantly dry event at 6900 BP.
We also analyze the network of dependencies surrounding GMT. We find an intricate, directed network with multiple links between the different factors at multiple time delays. We further uncover a significant feedback from the GMT to the El Niño Southern Oscillation at quasi-biennial timescales. The analysis highlights the need of a more nuanced formulation of influences between different climatic factors, as well as the limitations in trying to estimate such dependencies.
The data quality of real-world datasets need to be constantly monitored and maintained to allow organizations and individuals to reliably use their data. Especially, data integration projects suffer from poor initial data quality and as a consequence consume more effort and money. Commercial products and research prototypes for data cleansing and integration help users to improve the quality of individual and combined datasets. They can be divided into either standalone systems or database management system (DBMS) extensions. On the one hand, standalone systems do not interact well with DBMS and require time-consuming data imports and exports. On the other hand, DBMS extensions are often limited by the underlying system and do not cover the full set of data cleansing and integration tasks.
We overcome both limitations by implementing a concise set of five data cleansing and integration operators on the parallel data analytics platform Stratosphere. We define the semantics of the operators, present their parallel implementation, and devise optimization techniques for individual operators and combinations thereof. Users specify declarative queries in our query language METEOR with our new operators to improve the data quality of individual datasets or integrate them to larger datasets. By integrating the data cleansing operators into the higher level language layer of Stratosphere, users can easily combine cleansing operators with operators from other domains, such as information extraction, to complex data flows. Through a generic description of the operators, the Stratosphere optimizer reorders operators even from different domains to find better query plans.
As a case study, we reimplemented a part of the large Open Government Data integration project GovWILD with our new operators and show that our queries run significantly faster than the original GovWILD queries, which rely on relational operators. Evaluation reveals that our operators exhibit good scalability on up to 100 cores, so that even larger inputs can be efficiently processed by scaling out to more machines. Finally, our scripts are considerably shorter than the original GovWILD scripts, which results in better maintainability of the scripts.
We study the diffusion of a tracer particle, which moves in continuum space between a lattice of excluded volume, immobile non-inert obstacles. In particular, we analyse how the strength of the tracer–obstacle interactions and the volume occupancy of the crowders alter the diffusive motion of the tracer. From the details of partitioning of the tracer diffusion modes between trapping states when bound to obstacles and bulk diffusion, we examine the degree of localisation of the tracer in the lattice of crowders. We study the properties of the tracer diffusion in terms of the ensemble and time averaged mean squared displacements, the trapping time distributions, the amplitude variation of the time averaged mean squared displacements, and the non-Gaussianity parameter of the diffusing tracer. We conclude that tracer–obstacle adsorption and binding triggers a transient anomalous diffusion. From a very narrow spread of recorded individual time averaged trajectories we exclude continuous type random walk processes as the underlying physical model of the tracer diffusion in our system. For moderate tracer–crowder attraction the motion is found to be fully ergodic, while at stronger attraction strength a transient disparity between ensemble and time averaged mean squared displacements occurs. We also put our results into perspective with findings from experimental single-particle tracking and simulations of the diffusion of tagged tracers in dense crowded suspensions. Our results have implications for the diffusion, transport, and spreading of chemical components in highly crowded environments inside living cells and other structured liquids.
We study the diffusion of a tracer particle, which moves in continuum space between a lattice of excluded volume, immobile non-inert obstacles. In particular, we analyse how the strength of the tracer–obstacle interactions and the volume occupancy of the crowders alter the diffusive motion of the tracer. From the details of partitioning of the tracer diffusion modes between trapping states when bound to obstacles and bulk diffusion, we examine the degree of localisation of the tracer in the lattice of crowders. We study the properties of the tracer diffusion in terms of the ensemble and time averaged mean squared displacements, the trapping time distributions, the amplitude variation of the time averaged mean squared displacements, and the non-Gaussianity parameter of the diffusing tracer. We conclude that tracer–obstacle adsorption and binding triggers a transient anomalous diffusion. From a very narrow spread of recorded individual time averaged trajectories we exclude continuous type random walk processes as the underlying physical model of the tracer diffusion in our system. For moderate tracer–crowder attraction the motion is found to be fully ergodic, while at stronger attraction strength a transient disparity between ensemble and time averaged mean squared displacements occurs. We also put our results into perspective with findings from experimental single-particle tracking and simulations of the diffusion of tagged tracers in dense crowded suspensions. Our results have implications for the diffusion, transport, and spreading of chemical components in highly crowded environments inside living cells and other structured liquids.
Inferring gene regulatory networks and cellular phases from time-resolved transcriptomics data
(2014)
An important contribution of geosciences to the renewable energy production portfolio is the exploration and utilization of geothermal resources. For the development of a geothermal project at great depths a detailed geological and geophysical exploration program is required in the first phase. With the help of active seismic methods high-resolution images of the geothermal reservoir can be delivered. This allows potential transport routes for fluids to be identified as well as regions with high potential of heat extraction to be mapped, which indicates favorable conditions for geothermal exploitation. The presented work investigates the extent to which an improved characterization of geothermal reservoirs can be achieved with the new methods of seismic data processing. The summations of traces (stacking) is a crucial step in the processing of seismic reflection data. The common-reflection-surface (CRS) stacking method can be applied as an alternative for the conventional normal moveout (NMO) or the dip moveout (DMO) stack. The advantages of the CRS stack beside an automatic determination of stacking operator parameters include an adequate imaging of arbitrarily curved geological boundaries, and a significant increase in signal-to-noise (S/N) ratio by stacking far more traces than used in a conventional stack. A major innovation I have shown in this work is that the quality of signal attributes that characterize the seismic images can be significantly improved by this modified type of stacking in particular. Imporoved attribute analysis facilitates the interpretation of seismic images and plays a significant role in the characterization of reservoirs. Variations of lithological and petro-physical properties are reflected by fluctuations of specific signal attributes (eg. frequency or amplitude characteristics). Its further interpretation can provide quality assessment of the geothermal reservoir with respect to the capacity of fluids within a hydrological system that can be extracted and utilized. The proposed methodological approach is demonstrated on the basis on two case studies. In the first example, I analyzed a series of 2D seismic profile sections through the Alberta sedimentary basin on the eastern edge of the Canadian Rocky Mountains. In the second application, a 3D seismic volume is characterized in the surroundings of a geothermal borehole, located in the central part of the Polish basin. Both sites were investigated with the modified and improved stacking attribute analyses. The results provide recommendations for the planning of future geothermal plants in both study areas.
It is generally agreed upon that stars typically form in open clusters and stellar associations, but little is known about the structure of the open cluster system. Do open clusters and stellar associations form isolated or do they prefer to form in groups and complexes? Open cluster groups and complexes could verify star forming regions to be larger than expected, which would explain the chemical homogeneity over large areas in the Galactic disk. They would also define an additional level in the hierarchy of star formation and could be used as tracers for the scales of fragmentation in giant molecular clouds? Furthermore, open cluster groups and complexes could affect Galactic dynamics and should be considered in investigations and simulations on the dynamical processes, such as radial migration, disc heating, differential rotation, kinematic resonances, and spiral structure.
In the past decade there were a few studies on open cluster pairs (de La Fuente Marcos & de La Fuente Marcos 2009a,b,c) and on open cluster groups and complexes (Piskunov et al. 2006). The former only considered spatial proximity for the identification of the pairs, while the latter also required tangential velocities to be similar for the members. In this work I used the full set of 6D phase-space information to draw a more detailed picture on these structures. For this purpose I utilised the most homogeneous cluster catalogue available, namely the Catalogue of Open Cluster Data (COCD; Kharchenko et al. 2005a,b), which contains parameters for 650 open clusters and compact associations, as well as for their uniformly selected members. Additional radial velocity (RV) and metallicity ([M/H]) information on the members were obtained from the RAdial Velocity Experiment (RAVE; Steinmetz et al. 2006; Kordopatis et al. 2013) for 110 and 81 clusters, respectively. The RAVE sample was cleaned considering quality parameters and flags provided by RAVE (Matijevič et al. 2012; Kordopatis et al. 2013). To ensure that only real members were included for the mean values, also the cluster membership, as provided by Kharchenko et al. (2005a,b), was considered for the stars cross-matched in RAVE.
6D phase-space information could be derived for 432 out of the 650 COCD objects and I used an adaption of the Friends-of-Friends algorithm, as used in cosmology, to identify potential groupings. The vast majority of the 19 identified groupings were pairs, but I also found four groups of 4-5 members and one complex with 15 members. For the verification of the identified structures, I compared the results to a randomly selected subsample of the catalogue for the Milky Way global survey of Star Clusters (MWSC; Kharchenko et al. 2013), which became available recently, and was used as reference sample. Furthermore, I implemented Monte-Carlo simulations with randomised samples created from two distinguished input distributions for the spatial and velocity parameters. On the one hand, assuming a uniform distribution in the Galactic disc and, on the other hand, assuming the COCD data distributions to be representative for the whole open cluster population.
The results suggested that the majority of identified pairs are rather by chance alignments, but the groups and the complex seemed to be genuine. A comparison of my results to the pairs, groups and complexes proposed in the literature yielded a partial overlap, which was most likely because of selection effects and different parameters considered. This is another verification for the existence of such structures.
The characteristics of the found groupings favour that members of an open cluster grouping originate from a common giant molecular cloud and formed in a single, but possibly sequential, star formation event. Moreover, the fact that the young open cluster population showed smaller spatial separations between nearest neighbours than the old cluster population indicated that the lifetime of open cluster groupings is most likely comparable to that of the Galactic open cluster population itself. Still even among the old open clusters I could identify groupings, which suggested that the detected structure could be in some cases more long lived as one might think.
In this thesis I could only present a pilot study on structures in the Galactic open cluster population, since the data sample used was highly incomplete. For further investigations a far more complete sample would be required. One step in this direction would be to use data from large current surveys, like SDSS, RAVE, Gaia-ESO and VVV, as well as including results from studies on individual clusters. Later the sample can be completed by data from upcoming missions, like Gaia and 4MOST. Future studies using this more complete open cluster sample will reveal the effect of open cluster groupings on star formation theory and their significance for the kinematics, dynamics and evolution of the Milky Way, and thereby of spiral galaxies.
The adaptation of cell growth and proliferation to environmental changes is essential for the surviving of biological systems. The evolutionary conserved Ser/Thr protein kinase “Target of Rapamycin” (TOR) has emerged as a major signaling node that integrates the sensing of numerous growth signals to the coordinated regulation of cellular metabolism and growth. Although the TOR signaling pathway has been widely studied in heterotrophic organisms, the research on TOR in photosynthetic eukaryotes has been hampered by the reported land plant resistance to rapamycin. Thus, the finding that Chlamydomonas reinhardtii is sensitive to rapamycin, establish this unicellular green alga as a useful model system to investigate TOR signaling in photosynthetic eukaryotes.
The observation that rapamycin does not fully arrest Chlamydomonas growth, which is different from observations made in other organisms, prompted us to investigate the regulatory function of TOR in Chlamydomonas in context of the cell cycle. Therefore, a growth system that allowed synchronously growth under widely unperturbed cultivation in a fermenter system was set up and the synchronized cells were characterized in detail. In a highly resolved kinetic study, the synchronized cells were analyzed for their changes in cytological parameters as cell number and size distribution and their starch content. Furthermore, we applied mass spectrometric analysis for profiling of primary and lipid metabolism. This system was then used to analyze the response dynamics of the Chlamydomonas metabolome and lipidome to TOR-inhibition by rapamycin
The results show that TOR inhibition reduces cell growth, delays cell division and daughter cell release and results in a 50% reduced cell number at the end of the cell cycle. Consistent with the growth phenotype we observed strong changes in carbon and nitrogen partitioning in the direction of rapid conversion into carbon and nitrogen storage through an accumulation of starch, triacylglycerol and arginine. Interestingly, it seems that the conversion of carbon into triacylglycerol occurred faster than into starch after TOR inhibition, which may indicate a more dominant role of TOR in the regulation of TAG biosynthesis than in the regulation of starch.
This study clearly shows, for the first time, a complex picture of metabolic and lipidomic dynamically changes during the cell cycle of Chlamydomonas reinhardtii and furthermore reveals a complex regulation and adjustment of metabolite pools and lipid composition in response to TOR inhibition.
The looping of polymers such as DNA is a fundamental process in the molecular biology of living cells, whose interior is characterised by a high degree of molecular crowding. We here investigate in detail the looping dynamics of flexible polymer chains in the presence of different degrees of crowding. From the analysis of the looping–unlooping rates and the looping probabilities of the chain ends we show that the presence of small crowders typically slows down the chain dynamics but larger crowders may in fact facilitate the looping. We rationalise these non-trivial and often counterintuitive effects of the crowder size on the looping kinetics in terms of an effective solution viscosity and standard excluded volume. It is shown that for small crowders the effect of an increased viscosity dominates, while for big crowders we argue that confinement effects (caging) prevail. The tradeoff between both trends can thus result in the impediment or facilitation of polymer looping, depending on the crowder size. We also examine how the crowding volume fraction, chain length, and the attraction strength of the contact groups of the polymer chain affect the looping kinetics and hairpin formation dynamics. Our results are relevant for DNA looping in the absence and presence of protein mediation, DNA hairpin formation, RNA folding, and the folding of polypeptide chains under biologically relevant high-crowding conditions.
The looping of polymers such as DNA is a fundamental process in the molecular biology of living cells, whose interior is characterised by a high degree of molecular crowding. We here investigate in detail the looping dynamics of flexible polymer chains in the presence of different degrees of crowding. From the analysis of the looping–unlooping rates and the looping probabilities of the chain ends we show that the presence of small crowders typically slows down the chain dynamics but larger crowders may in fact facilitate the looping. We rationalise these non-trivial and often counterintuitive effects of the crowder size on the looping kinetics in terms of an effective solution viscosity and standard excluded volume. It is shown that for small crowders the effect of an increased viscosity dominates, while for big crowders we argue that confinement effects (caging) prevail. The tradeoff between both trends can thus result in the impediment or facilitation of polymer looping, depending on the crowder size. We also examine how the crowding volume fraction, chain length, and the attraction strength of the contact groups of the polymer chain affect the looping kinetics and hairpin formation dynamics. Our results are relevant for DNA looping in the absence and presence of protein mediation, DNA hairpin formation, RNA folding, and the folding of polypeptide chains under biologically relevant high-crowding conditions.
In Chapter 1 of the dissertation, the role of social networks is analyzed as an important determinant in the search behavior of the unemployed. Based on the hypothesis that the unemployed generate information on vacancies through their social network, search theory predicts that individuals with large social networks should experience an increased productivity of informal search, and reduce their search in formal channels. Due to the higher productivity of search, unemployed with a larger network are also expected to have a higher reservation wage than unemployed with a small network. The model-theoretic predictions are tested and confirmed empirically. It is found that the search behavior of unemployed is significantly affected by the presence of social contacts, with larger networks implying a stronger substitution away from formal search channels towards informal channels. The substitution is particularly pronounced for passive formal search methods, i.e., search methods that generate rather non-specific types of job offer information at low relative cost. We also find small but significant positive effects of an increase of the network size on the reservation wage. These results have important implications on the analysis of the job search monitoring or counseling measures that are usually targeted at formal search only. Chapter 2 of the dissertation addresses the labor market effects of vacancy information during the early stages of unemployment. The outcomes considered are the speed of exit from unemployment, the effects on the quality of employment and the short-and medium-term effects on active labor market program (ALMP) participation. It is found that vacancy information significantly increases the speed of entry into employment; at the same time the probability to participate in ALMP is significantly reduced. Whereas the long-term reduction in the ALMP arises in consequence of the earlier exit from unemployment, we also observe a short-run decrease for some labor market groups which suggest that caseworker use high and low intensity activation measures interchangeably which is clearly questionable from an efficiency point of view. For unemployed who find a job through vacancy information we observe a small negative effect on the weekly number of hours worked. In Chapter 3, the long-term effects of participation in ALMP are assessed for unemployed youth under 25 years of age. Complementary to the analysis in Chapter 2, the effects of participation in time- and cost-intensive measures of active labor market policies are examined. In particular we study the effects of job creation schemes, wage subsidies, short-and long-term training measures and measures to promote the participation in vocational training. The outcome variables of interest are the probability to be in regular employment, and participation in further education during the 60 months following program entry. The analysis shows that all programs, except job creation schemes have positive and long-term effects on the employment probability of youth. In the short-run only short-term training measures generate positive effects, as long-term training programs and wage subsidies exhibit significant locking-in'' effects. Measures to promote vocational training are found to increase the probability of attending education and training significantly, whereas all other programs have either no or a negative effect on training participation. Effect heterogeneity with respect to the pre-treatment level education shows that young people with higher pre-treatment educational levels benefit more from participation most programs. However, for longer-term wage subsidies we also find strong positive effects for young people with low initial education levels. The relative benefit of training measures is higher in West than in East Germany. In the evaluation studies of Chapters 2 and 3 semi-parametric balancing methods of Propensity Score Matching (PSM) and Inverse Probability Weighting (IPW) are used to eliminate the effects of counfounding factors that influence both the treatment participation as well as the outcome variable of interest, and to establish a causal relation between program participation and outcome differences. While PSM and IPW are intuitive and methodologically attractive as they do not require parametric assumptions, the practical implementation may become quite challenging due to their sensitivity to various data features. Given the importance of these methods in the evaluation literature, and the vast number of recent methodological contributions in this field, Chapter 4 aims to reduce the knowledge gap between the methodological and applied literature by summarizing new findings of the empirical and statistical literature and practical guidelines for future applied research. In contrast to previous publications this study does not only focus on the estimation of causal effects, but stresses that the balancing challenge can and should be discussed independent of question of causal identification of treatment effects on most empirical applications. Following a brief outline of the practical implementation steps required for PSM and IPW, these steps are presented in detail chronologically, outlining practical advice for each step. Subsequently, the topics of effect estimation, inference, sensitivity analysis and the combination with parametric estimation methods are discussed. Finally, new extensions of the methodology and avenues for future research are presented.
The term Linked Data refers to connected information sources comprising structured data about a wide range of topics and for a multitude of applications. In recent years, the conceptional and technical foundations of Linked Data have been formalized and refined. To this end, well-known technologies have been established, such as the Resource Description Framework (RDF) as a Linked Data model or the SPARQL Protocol and RDF Query Language (SPARQL) for retrieving this information. Whereas most research has been conducted in the area of generating and publishing Linked Data, this thesis presents novel approaches for improved management. In particular, we illustrate new methods for analyzing and processing SPARQL queries. Here, we present two algorithms suitable for identifying structural relationships between these queries. Both algorithms are applied to a large number of real-world requests to evaluate the performance of the approaches and the quality of their results. Based on this, we introduce different strategies enabling optimized access of Linked Data sources. We demonstrate how the presented approach facilitates effective utilization of SPARQL endpoints by prefetching results relevant for multiple subsequent requests. Furthermore, we contribute a set of metrics for determining technical characteristics of such knowledge bases. To this end, we devise practical heuristics and validate them through thorough analysis of real-world data sources. We discuss the findings and evaluate their impact on utilizing the endpoints. Moreover, we detail the adoption of a scalable infrastructure for improving Linked Data discovery and consumption. As we outline in an exemplary use case, this platform is eligible both for processing and provisioning the corresponding information.
Planetary research is often user-based and requires considerable skill, time, and effort. Unfortunately, self-defined boundary conditions, definitions, and rules are often not documented or not easy to comprehend due to the complexity of research. This makes a comparison to other studies, or an extension of the already existing research, complicated. Comparisons are often distorted, because results rely on different, not well defined, or even unknown boundary conditions. The purpose of this research is to develop a standardized analysis method for planetary surfaces, which is adaptable to several research topics. The method provides a consistent quality of results. This also includes achieving reliable and comparable results and reducing the time and effort of conducting such studies. A standardized analysis method is provided by automated analysis tools that focus on statistical parameters. Specific key parameters and boundary conditions are defined for the tool application. The analysis relies on a database in which all key parameters are stored. These databases can be easily updated and adapted to various research questions. This increases the flexibility, reproducibility, and comparability of the research. However, the quality of the database and reliability of definitions directly influence the results. To ensure a high quality of results, the rules and definitions need to be well defined and based on previously conducted case studies. The tools then produce parameters, which are obtained by defined geostatistical techniques (measurements, calculations, classifications). The idea of an automated statistical analysis is tested to proof benefits but also potential problems of this method. In this study, I adapt automated tools for floor-fractured craters (FFCs) on Mars. These impact craters show a variety of surface features, occurring in different Martian environments, and having different fracturing origins. They provide a complex morphological and geological field of application. 433 FFCs are classified by the analysis tools due to their fracturing process. Spatial data, environmental context, and crater interior data are analyzed to distinguish between the processes involved in floor fracturing. Related geologic processes, such as glacial and fluvial activity, are too similar to be separately classified by the automated tools. Glacial and fluvial fracturing processes are merged together for the classification. The automated tools provide probability values for each origin model. To guarantee the quality and reliability of the results, classification tools need to achieve an origin probability above 50 %. This analysis method shows that 15 % of the FFCs are fractured by intrusive volcanism, 20 % by tectonic activity, and 43 % by water & ice related processes. In total, 75 % of the FFCs are classified to an origin type. This can be explained by a combination of origin models, superposition or erosion of key parameters, or an unknown fracturing model. Those features have to be manually analyzed in detail. Another possibility would be the improvement of key parameters and rules for the classification. This research shows that it is possible to conduct an automated statistical analysis of morphologic and geologic features based on analysis tools. Analysis tools provide additional information to the user and are therefore considered assistance systems.
The H.E.S.S. array is a third generation Imaging Atmospheric Cherenkov Telescope (IACT) array. It is located in the Khomas Highland in Namibia, and measures very high energy (VHE) gamma-rays. In Phase I, the array started data taking in 2004 with its four identical 13 m telescopes. Since then, H.E.S.S. has emerged as the most successful IACT experiment to date. Among the almost 150 sources of VHE gamma-ray radiation found so far, even the oldest detection, the Crab Nebula, keeps surprising the scientific community with unexplained phenomena such as the recently discovered very energetic flares of high energy gamma-ray radiation. During its most recent flare, which was detected by the Fermi satellite in March 2013, the Crab Nebula was simultaneously observed with the H.E.S.S. array for six nights. The results of the observations will be discussed in detail during the course of this work. During the nights of the flare, the new 24 m × 32 m H.E.S.S. II telescope was still being commissioned, but participated in the data taking for one night. To be able to reconstruct and analyze the data of the H.E.S.S. Phase II array, the algorithms and software used by the H.E.S.S. Phase I array had to be adapted. The most prominent advanced shower reconstruction technique developed by de Naurois and Rolland, the template-based model analysis, compares real shower images taken by the Cherenkov telescope cameras with shower templates obtained using a semi-analytical model. To find the best fitting image, and, therefore, the relevant parameters that describe the air shower best, a pixel-wise log-likelihood fit is done. The adaptation of this advanced shower reconstruction technique to the heterogeneous H.E.S.S. Phase II array for stereo events (i.e. air showers seen by at least two telescopes of any kind), its performance using MonteCarlo simulations as well as its application to real data will be described.
Biological materials have ever been used by humans because of their remarkable properties. This is surprising since the materials are formed under physiological conditions and with commonplace constituents. Nature thus not only provides us with inspiration for designing new materials but also teaches us how to use soft molecules to tune interparticle and external forces to structure and assemble simple building blocks into functional entities. Magnetotactic bacteria and their chain of magnetosomes represent a striking example of such an accomplishment where a very simple living organism controls the properties of inorganics via organics at the nanometer-scale to form a single magnetic dipole that orients the cell in the Earth magnetic field lines. My group has developed a biological and a bio-inspired research based on these bacteria. My research, at the interface between chemistry, materials science, physics, and biology focuses on how biological systems synthesize, organize and use minerals. We apply the design principles to sustainably form hierarchical materials with controlled properties that can be used e.g. as magnetically directed nanodevices towards applications in sensing, actuating, and transport. In this thesis, I thus first present how magnetotactic bacteria intracellularly form magnetosomes and assemble them in chains. I developed an assay, where cells can be switched from magnetic to non-magnetic states. This enabled to study the dynamics of magnetosome and magnetosome chain formation. We found that the magnetosomes nucleate within minutes whereas chains assembles within hours. Magnetosome formation necessitates iron uptake as ferrous or ferric ions. The transport of the ions within the cell leads to the formation of a ferritin-like intermediate, which subsequently is transported and transformed within the magnetosome organelle in a ferrihydrite-like precursor. Finally, magnetite crystals nucleate and grow toward their mature dimension. In addition, I show that the magnetosome assembly displays hierarchically ordered nano- and microstructures over several levels, enabling the coordinated alignment and motility of entire populations of cells. The magnetosomes are indeed composed of structurally pure magnetite. The organelles are partly composed of proteins, which role is crucial for the properties of the magnetosomes. As an example, we showed how the protein MmsF is involved in the control of magnetosome size and morphology. We have further shown by 2D X-ray diffraction that the magnetosome particles are aligned along the same direction in the magnetosome chain. We then show how magnetic properties of the nascent magnetosome influence the alignment of the particles, and how the proteins MamJ and MamK coordinate this assembly. We propose a theoretical approach, which suggests that biological forces are more important than physical ones for the chain formation. All these studies thus show how magnetosome formation and organization are under strict biological control, which is associated with unprecedented material properties. Finally, we show that the magnetosome chain enables the cells to find their preferred oxygen conditions if the magnetic field is present. The synthetic part of this work shows how the understanding of the design principles of magnetosome formation enabled me to perform biomimetic synthesis of magnetite particles within the highly desired size range of 25 to 100 nm. Nucleation and growth of such particles are based on aggregation of iron colloids termed primary particles as imaged by cryo-high resolution TEM. I show how additives influence magnetite formation and properties. In particular, MamP, a so-called magnetochrome proteins involved in the magnetosome formation in vivo, enables the in vitro formation of magnetite nanoparticles exclusively from ferrous iron by controlling the redox state of the process. Negatively charged additives, such as MamJ, retard magnetite nucleation in vitro, probably by interacting with the iron ions. Other additives such as e.g. polyarginine can be used to control the colloidal stability of stable-single domain sized nanoparticles. Finally, I show how we can “glue” magnetic nanoparticles to form propellers that can be actuated and swim with the help of external magnetic fields. We propose a simple theory to explain the observed movement. We can use the theoretical framework to design experimental conditions to sort out the propellers depending on their size and effectively confirm this prediction experimentally. Thereby, we could image propellers with size down to 290 nm in their longer dimension, much smaller than what perform so far.
This work introduces concepts and corresponding tool support to enable a complementary approach in dealing with recovery. Programmers need to recover a development state, or a part thereof, when previously made changes reveal undesired implications. However, when the need arises suddenly and unexpectedly, recovery often involves expensive and tedious work. To avoid tedious work, literature recommends keeping away from unexpected recovery demands by following a structured and disciplined approach, which consists of the application of various best practices including working only on one thing at a time, performing small steps, as well as making proper use of versioning and testing tools. However, the attempt to avoid unexpected recovery is both time-consuming and error-prone. On the one hand, it requires disproportionate effort to minimize the risk of unexpected situations. On the other hand, applying recommended practices selectively, which saves time, can hardly avoid recovery. In addition, the constant need for foresight and self-control has unfavorable implications. It is exhaustive and impedes creative problem solving. This work proposes to make recovery fast and easy and introduces corresponding support called CoExist. Such dedicated support turns situations of unanticipated recovery from tedious experiences into pleasant ones. It makes recovery fast and easy to accomplish, even if explicit commits are unavailable or tests have been ignored for some time. When mistakes and unexpected insights are no longer associated with tedious corrective actions, programmers are encouraged to change source code as a means to reason about it, as opposed to making changes only after structuring and evaluating them mentally. This work further reports on an implementation of the proposed tool support in the Squeak/Smalltalk development environment. The development of the tools has been accompanied by regular performance and usability tests. In addition, this work investigates whether the proposed tools affect programmers’ performance. In a controlled lab study, 22 participants improved the design of two different applications. Using a repeated measurement setup, the study examined the effect of providing CoExist on programming performance. The result of analyzing 88 hours of programming suggests that built-in recovery support as provided with CoExist positively has a positive effect on programming performance in explorative programming tasks.
Wood is used for many applications because of its excellent mechanical properties, relative abundance and as it is a renewable resource. However, its wider utilization as an engineering material is limited because it swells and shrinks upon moisture changes and is susceptible to degradation by microorganisms and/or insects. Chemical modifications of wood have been shown to improve dimensional stability, water repellence and/or durability, thus increasing potential service-life of wood materials. However current treatments are limited because it is difficult to introduce and fix such modifications deep inside the tissue and cell wall. Within the scope of this thesis, novel chemical modification methods of wood cell walls were developed to improve both dimensional stability and water repellence of wood material. These methods were partly inspired by the heartwood formation in living trees, a process, that for some species results in an insertion of hydrophobic chemical substances into the cell walls of already dead wood cells, In the first part of this thesis a chemistry to modify wood cell walls was used, which was inspired by the natural process of heartwood formation. Commercially available hydrophobic flavonoid molecules were effectively inserted in the cell walls of spruce, a softwood species with low natural durability, after a tosylation treatment to obtain “artificial heartwood”. Flavonoid inserted cell walls show a reduced moisture absorption, resulting in better dimensional stability, water repellency and increased hardness. This approach was quite different compared to established modifications which mainly address hydroxyl groups of cell wall polymers with hydrophilic substances. In the second part of the work in-situ styrene polymerization inside the tosylated cell walls was studied. It is known that there is a weak adhesion between hydrophobic polymers and hydrophilic cell wall components. The hydrophobic styrene monomers were inserted into the tosylated wood cell walls for further polymerization to form polystyrene in the cell walls, which increased the dimensional stability of the bulk wood material and reduced water uptake of the cell walls considerably when compared to controls. In the third part of the work, grafting of another hydrophobic and also biodegradable polymer, poly(ɛ-caprolactone) in the wood cell walls by ring opening polymerization of ɛ-caprolactone was studied at mild temperatures. Results indicated that polycaprolactone attached into the cell walls, caused permanent swelling of the cell walls up to 5%. Dimensional stability of the bulk wood material increased 40% and water absorption reduced more than 35%. A fully biodegradable and hydrophobized wood material was obtained with this method which reduces disposal problem of the modified wood materials and has improved properties to extend the material’s service-life. Starting from a bio-inspired approach which showed great promise as an alternative to standard cell wall modifications we showed the possibility of inserting hydrophobic molecules in the cell walls and supported this fact with in-situ styrene and ɛ-caprolactone polymerization into the cell walls. It was shown in this thesis that despite the extensive knowledge and long history of using wood as a material there is still room for novel chemical modifications which could have a high impact on improving wood properties.
In this thesis we consider diverse aspects of existence and correctness of asymptotic solutions to elliptic differential and pseudodifferential equations. We begin our studies with the case of a general elliptic boundary value problem in partial derivatives. A small parameter enters the coefficients of the main equation as well as into the boundary conditions. Such equations have already been investigated satisfactory, but there still exist certain theoretical deficiencies. Our aim is to present the general theory of elliptic problems with a small parameter. For this purpose we examine in detail the case of a bounded domain with a smooth boundary. First of all, we construct formal solutions as power series in the small parameter. Then we examine their asymptotic properties. It suffices to carry out sharp two-sided \emph{a priori} estimates for the operators of boundary value problems which are uniform in the small parameter. Such estimates failed to hold in functional spaces used in classical elliptic theory. To circumvent this limitation we exploit norms depending on the small parameter for the functions defined on a bounded domain. Similar norms are widely used in literature, but their properties have not been investigated extensively. Our theoretical investigation shows that the usual elliptic technique can be correctly carried out in these norms. The obtained results also allow one to extend the norms to compact manifolds with boundaries. We complete our investigation by formulating algebraic conditions on the operators and showing their equivalence to the existence of a priori estimates. In the second step, we extend the concept of ellipticity with a small parameter to more general classes of operators. Firstly, we want to compare the difference in asymptotic patterns between the obtained series and expansions for similar differential problems. Therefore we investigate the heat equation in a bounded domain with a small parameter near the time derivative. In this case the characteristics touch the boundary at a finite number of points. It is known that the solutions are not regular in a neighbourhood of such points in advance. We suppose moreover that the boundary at such points can be non-smooth but have cuspidal singularities. We find a formal asymptotic expansion and show that when a set of parameters comes through a threshold value, the expansions fail to be asymptotic. The last part of the work is devoted to general concept of ellipticity with a small parameter. Several theoretical extensions to pseudodifferential operators have already been suggested in previous studies. As a new contribution we involve the analysis on manifolds with edge singularities which allows us to consider wider classes of perturbed elliptic operators. We examine that introduced classes possess a priori estimates of elliptic type. As a further application we demonstrate how developed tools can be used to reduce singularly perturbed problems to regular ones.
Metabolic systems tend to exhibit steady states that can be measured in terms of their concentrations and fluxes. These measurements can be regarded as a phenotypic representation of all the complex interactions and regulatory mechanisms taking place in the underlying metabolic network. Such interactions determine the system's response to external perturbations and are responsible, for example, for its asymptotic stability or for oscillatory trajectories around the steady state. However, determining these perturbation responses in the absence of fully specified kinetic models remains an important challenge of computational systems biology. Structural kinetic modeling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a parameterised representation of the system's Jacobian matrix in which the model parameters encode information about the enzyme-metabolite interactions. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. The parameter space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Because the sampled parameters are equivalent to the elasticities used in metabolic control analysis (MCA), the results are easy to interpret biologically. In this project, the SKM framework was extended by several novel methodological improvements. These improvements were evaluated in a simulation study using a set of small example pathways with simple Michaelis Menten rate laws. Afterwards, a detailed analysis of the dynamic properties of the neuronal TCA cycle was performed in order to demonstrate how the new insights obtained in this work could be used for the study of complex metabolic systems. The first improvement was achieved by examining the biological feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, the findings showed that the majority of sampled SK-models would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion was formulated that mitigates such infeasible models and the application of this criterion changed the conclusions of the SKM experiment. The second improvement of this work was the application of supervised machine-learning approaches in order to analyse SKM experiments. So far, SKM experiments have focused on the detection of individual enzymes to identify single reactions important for maintaining the stability or oscillatory trajectories. In this work, this approach was extended by demonstrating how SKM enables the detection of ensembles of enzymes or metabolites that act together in an orchestrated manner to coordinate the pathways response to perturbations. In doing so, stable and unstable states served as class labels, and classifiers were trained to detect elasticity regions associated with stability and instability. Classification was performed using decision trees and relevance vector machines (RVMs). The decision trees produced good classification accuracy in terms of model bias and generalizability. RVMs outperformed decision trees when applied to small models, but encountered severe problems when applied to larger systems because of their high runtime requirements. The decision tree rulesets were analysed statistically and individually in order to explore the role of individual enzymes or metabolites in controlling the system's trajectories around steady states. The third improvement of this work was the establishment of a relationship between the SKM framework and the related field of MCA. In particular, it was shown how the sampled elasticities could be converted to flux control coefficients, which were then investigated for their predictive information content in classifier training. After evaluation on the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle with respect to their intrinsic mechanisms responsible for stability or instability. The findings showed that several elasticities were jointly coordinated to control stability and that the main source for potential instabilities were mutations in the enzyme alpha-ketoglutarate dehydrogenase.
The tropical warm pool waters surrounding Indonesia are one of the equatorial heat and moisture sources that are considered as a driving force of the global climate system. The climate in Indonesia is dominated by the equatorial monsoon system, and has been linked to El Niño-Southern Oscillation (ENSO) events, which often result in severe droughts or floods over Indonesia with profound societal and economic impacts on the populations living in the world's fourth most populated country. The latest IPCC report states that ENSO will remain the dominant mode in the tropical Pacific with global effects in the 21st century and ENSO-related precipitation extremes will intensify. However, no common agreement exists among climate simulation models for projected change in ENSO and the Australian-Indonesian Monsoon. Exploring high-resolution palaeoclimate archives, like tree rings or varved lake sediments, provide insights into the natural climate variability of the past, and thus helps improving and validating simulations of future climate changes. Centennial tree-ring stable isotope records | Within this doctoral thesis the main goal was to explore the potential of tropical tree rings to record climate signals and to use them as palaeoclimate proxies. In detail, stable carbon (δ13C) and oxygen (δ18O) isotopes were extracted from teak trees in order to establish the first well-replicated centennial (AD 1900-2007) stable isotope records for Java, Indonesia. Furthermore, different climatic variables were tested whether they show significant correlation with tree-ring proxies (ring-width, δ13C, δ18O). Moreover, highly resolved intra-annual oxygen isotope data were established to assess the transfer of the seasonal precipitation signal into the tree rings. Finally, the established oxygen isotope record was used to reveal possible correlations with ENSO events. Methodological achievements | A second goal of this thesis was to assess the applicability of novel techniques which facilitate and optimize high-resolution and high-throughput stable isotope analysis of tree rings. Two different UV-laser-based microscopic dissection systems were evaluated as a novel sampling tool for high-resolution stable isotope analysis. Furthermore, an improved procedure of tree-ring dissection from thin cellulose laths for stable isotope analysis was designed. The most important findings of this thesis are: I) The herein presented novel sampling techniques improve stable isotope analyses for tree-ring studies in terms of precision, efficiency and quality. The UV-laser-based microdissection serve as a valuable tool for sampling plant tissue at ultrahigh-resolution and for unprecedented precision. II) A guideline for a modified method of cellulose extraction from wholewood cross-sections and subsequent tree-ring dissection was established. The novel technique optimizes the stable isotope analysis process in two ways: faster and high-throughput cellulose extraction and precise tree-ring separation at annual to high-resolution scale. III) The centennial tree-ring stable isotope records reveal significant correlation with regional precipitation. High-resolution stable oxygen values, furthermore, allow distinguishing between dry and rainy season rainfall. IV) The δ18O record reveals significant correlation with different ENSO flavors and demonstrates the importance of considering ENSO flavors when interpreting palaeoclimatic data in the tropics. The findings of my dissertation show that seasonally resolved δ18O records from Indonesian teak trees are a valuable proxy for multi-centennial reconstructions of regional precipitation variability (monsoon signals) and large-scale ocean-atmosphere phenomena (ENSO) for the Indo-Pacific region. Furthermore, the novel methodological achievements offer many unexplored avenues for multidisciplinary research in high-resolution palaeoclimatology.
These lecture notes are intended as a short introduction to diffusion processes on a domain with a reflecting boundary for graduate students, researchers in stochastic analysis and interested readers. Specific results on stochastic differential equations with reflecting boundaries such as existence and uniqueness, continuity and Markov properties, relation to partial differential equations and submartingale problems are given. An extensive list of references to current literature is included. This book has its origins in a mini-course the author gave at the University of Potsdam and at the Technical University of Berlin in Winter 2013.
The Adana Basin of southern Turkey, situated at the SE margin of the Central Anatolian Plateau is ideally located to record Neogene topographic and tectonic changes in the easternmost Mediterranean realm. Using industry seismic reflection data we correlate 34 seismic profiles with corresponding exposed units in the Adana Basin. The time-depth conversion of the interpreted seismic profiles allows us to reconstruct the subsidence curve of the Adana Basin and to outline the occurrence of a major increase in both subsidence and sedimentation rates at 5.45 – 5.33 Ma, leading to the deposition of almost 1500 km3 of conglomerates and marls. Our provenance analysis of the conglomerates reveals that most of the sediment is derived from and north of the SE margin of the Central Anatolian Plateau. A comparison of these results with the composition of recent conglomerates and the present drainage basins indicates major changes between late Messinian and present-day source areas. We suggest that these changes in source areas result of uplift and ensuing erosion of the SE margin of the plateau. This hypothesis is supported by the comparison of the Adana Basin subsidence curve with the subsidence curve of the Mut Basin, a mainly Neogene basin located on top of the Central Anatolian Plateau southern margin, showing that the Adana Basin subsidence event is coeval with an uplift episode of the plateau southern margin. The collection of several fault measurements in the Adana region show different deformation styles for the NW and SE margins of the Adana Basin. The weakly seismic NW portion of the basin is characterized by extensional and transtensional structures cutting Neogene deposits, likely accomodating the differential uplift occurring between the basin and the SE margin of the plateau. We interpret the tectonic evolution of the southern flank of the Central Anatolian Plateau and the coeval subsidence and sedimentation in the Adana Basin to be related to deep lithospheric processes, particularly lithospheric delamination and slab break-off.
The work elaborates on the question if coaches in non-professional soccer can influence referee decisions. Modeled from a principal-agent perspective, the managing referee boards can be seen as the principal. They aim at facilitating a fair competition which is in accordance with the existing rules and regulations. In doing so, the referees are assigned as impartial agents on the pitch. The coaches take over a non-legitimate principal-like role trying to influence the referees even though they do not have the formal right to do so.
Separate questionnaires were set up for referees and coaches. The coach questionnaire aimed at identifying the extent and the forms of influencing attempts by coaches. The referee questionnaire tried to elaborate on the questions if referees take notice of possible influencing attempts and how they react accordingly.
The results were put into relation with official match data in order to identify significant influences on personal sanctions (yellow cards, second yellow cards, red cards) and the match result.
It is found that there is a slight effect on the referee’s decisions. However, this effect is rather disadvantageous for the influencing coach and there is no evidence for an impact on the match result itself.
In the field of disk-based parallel database management systems exists a great variety of solutions based on a shared-storage or a shared-nothing architecture. In contrast, main memory-based parallel database management systems are dominated solely by the shared-nothing approach as it preserves the in-memory performance advantage by processing data locally on each server. We argue that this unilateral development is going to cease due to the combination of the following three trends: a) Nowadays network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory inside a server and of a remote server to and even below a single order of magnitude. b) Modern storage systems scale gracefully, are elastic, and provide high-availability. c) A modern storage system such as Stanford's RAMCloud even keeps all data resident in main memory. Exploiting these characteristics in the context of a main-memory parallel database management system is desirable. The advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible.
This thesis describes building a columnar database on shared main memory-based storage. The thesis discusses the resulting architecture (Part I), the implications on query processing (Part II), and presents an evaluation of the resulting solution in terms of performance, high-availability, and elasticity (Part III).
In our architecture, we use Stanford's RAMCloud as shared-storage, and the self-designed and developed in-memory AnalyticsDB as relational query processor on top. AnalyticsDB encapsulates data access and operator execution via an interface which allows seamless switching between local and remote main memory, while RAMCloud provides not only storage capacity, but also processing power. Combining both aspects allows pushing-down the execution of database operators into the storage system. We describe how the columnar data processed by AnalyticsDB is mapped to RAMCloud's key-value data model and how the performance advantages of columnar data storage can be preserved.
The combination of fast network technology and the possibility to execute database operators in the storage system opens the discussion for site selection. We construct a system model that allows the estimation of operator execution costs in terms of network transfer, data processed in memory, and wall time. This can be used for database operators that work on one relation at a time - such as a scan or materialize operation - to discuss the site selection problem (data pull vs. operator push). Since a database query translates to the execution of several database operators, it is possible that the optimal site selection varies per operator. For the execution of a database operator that works on two (or more) relations at a time, such as a join, the system model is enriched by additional factors such as the chosen algorithm (e.g. Grace- vs. Distributed Block Nested Loop Join vs. Cyclo-Join), the data partitioning of the respective relations, and their overlapping as well as the allowed resource allocation.
We present an evaluation on a cluster with 60 nodes where all nodes are connected via RDMA-enabled network equipment. We show that query processing performance is about 2.4x slower if everything is done via the data pull operator execution strategy (i.e. RAMCloud is being used only for data access) and about 27% slower if operator execution is also supported inside RAMCloud (in comparison to operating only on main memory inside a server without any network communication at all). The fast-crash recovery feature of RAMCloud can be leveraged to provide high-availability, e.g. a server crash during query execution only delays the query response for about one second. Our solution is elastic in a way that it can adapt to changing workloads a) within seconds, b) without interruption of the ongoing query processing, and c) without manual intervention.
Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. In response to specific environmental stresses the cell activates several stress-specific molecules such as sigma factors. They reversibly bind the RNA polymerase to form the so-called holoenzyme and direct it towards the appropriate stress response genes. In exponentially growing E. coli cells, the majority of the transcriptional activity is carried out by the housekeeping sigma factor, while stress responses are often under the control of alternative sigma factors. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross talk between genes or gene classes via the sharing of expression machinery. To quantitatively analyze the contribution of sigma factor competition to global changes in gene expression, we develop a thermodynamic model that describes binding between sigma factors and core RNAP at equilibrium, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components.
Association of housekeeping sigma factor to RNAP is generally favored by its abundance and higher binding affinity to the core. In order to promote transcription by alternative sigma subunits, the bacterial cell modulates the transcriptional efficiency in a reversible manner through several strategies such as anti-sigma factors, 6S RNA and generally any kind of transcriptional regulators (e.g. activators or inhibitors). By shifting the outcome of sigma factor competition for the core, these modulators bias the transcriptional program of the cell. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. We observe that transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected.
Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross talk effects and raising the question of how their in vitro measure is relevant in the cell. We also estimate that sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors, and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program and gives new insights into RNAP partitioning in the cell.
In the presented thesis, the most advanced photon reconstruction technique of ground-based γ-ray astronomy is adapted to the H.E.S.S. 28 m telescope. The method is based on a semi-analytical model of electromagnetic particle showers in the atmosphere. The properties of cosmic γ-rays are reconstructed by comparing the camera image of the telescope with the Cherenkov emission that is expected from the shower model. To suppress the dominant background from charged cosmic rays, events are selected based on several criteria. The performance of the analysis is evaluated with simulated events. The method is then applied to two sources that are known to emit γ-rays. The first of these is the Crab Nebula, the standard candle of ground-based γ-ray astronomy. The results of this source confirm the expected performance of the reconstruction method, where the much lower energy threshold compared to H.E.S.S. I is of particular importance. A second analysis is performed on the region around the Galactic Centre. The analysis results emphasise the capabilities of the new telescope to measure γ-rays in an energy range that is interesting for both theoretical and experimental astrophysics. The presented analysis features the lowest energy threshold that has ever been reached in ground-based γ-ray astronomy, opening a new window to the precise measurement of the physical properties of time-variable sources at energies of several tens of GeV.
Boolean constraint solving technology has made tremendous progress over the last decade, leading to industrial-strength solvers, for example, in the areas of answer set programming (ASP), the constraint satisfaction problem (CSP), propositional satisfiability (SAT) and satisfiability of quantified Boolean formulas (QBF). However, in all these areas, there exist multiple solving strategies that work well on different applications; no strategy dominates all other strategies. Therefore, no individual solver shows robust state-of-the-art performance in all kinds of applications. Additionally, the question arises how to choose a well-performing solving strategy for a given application; this is a challenging question even for solver and domain experts. One way to address this issue is the use of portfolio solvers, that is, a set of different solvers or solver configurations. We present three new automatic portfolio methods: (i) automatic construction of parallel portfolio solvers (ACPP) via algorithm configuration,(ii) solving the $NP$-hard problem of finding effective algorithm schedules with Answer Set Programming (aspeed), and (iii) a flexible algorithm selection framework (claspfolio2) allowing for fair comparison of different selection approaches. All three methods show improved performance and robustness in comparison to individual solvers on heterogeneous instance sets from many different applications. Since parallel solvers are important to effectively solve hard problems on parallel computation systems (e.g., multi-core processors), we extend all three approaches to be effectively applicable in parallel settings. We conducted extensive experimental studies different instance sets from ASP, CSP, MAXSAT, Operation Research (OR), SAT and QBF that indicate an improvement in the state-of-the-art solving heterogeneous instance sets. Last but not least, from our experimental studies, we deduce practical advice regarding the question when to apply which of our methods.
Nowadays, software systems are getting more and more complex. To tackle this challenge most diverse techniques, such as design patterns, service oriented architectures (SOA), software development processes, and model-driven engineering (MDE), are used to improve productivity, while time to market and quality of the products stay stable. Multiple of these techniques are used in parallel to profit from their benefits. While the use of sophisticated software development processes is standard, today, MDE is just adopted in practice. However, research has shown that the application of MDE is not always successful. It is not fully understood when advantages of MDE can be used and to what degree MDE can also be disadvantageous for productivity. Further, when combining different techniques that aim to affect the same factor (e.g. productivity) the question arises whether these techniques really complement each other or, in contrast, compensate their effects. Due to that, there is the concrete question how MDE and other techniques, such as software development process, are interrelated. Both aspects (advantages and disadvantages for productivity as well as the interrelation to other techniques) need to be understood to identify risks relating to the productivity impact of MDE. Before studying MDE's impact on productivity, it is necessary to investigate the range of validity that can be reached for the results. This includes two questions. First, there is the question whether MDE's impact on productivity is similar for all approaches of adopting MDE in practice. Second, there is the question whether MDE's impact on productivity for an approach of using MDE in practice remains stable over time. The answers for both questions are crucial for handling risks of MDE, but also for the design of future studies on MDE success. This thesis addresses these questions with the goal to support adoption of MDE in future. To enable a differentiated discussion about MDE, the term MDE setting'' is introduced. MDE setting refers to the applied technical setting, i.e. the employed manual and automated activities, artifacts, languages, and tools. An MDE setting's possible impact on productivity is studied with a focus on changeability and the interrelation to software development processes. This is done by introducing a taxonomy of changeability concerns that might be affected by an MDE setting. Further, three MDE traits are identified and it is studied for which manifestations of these MDE traits software development processes are impacted. To enable the assessment and evaluation of an MDE setting's impacts, the Software Manufacture Model language is introduced. This is a process modeling language that allows to reason about how relations between (modeling) artifacts (e.g. models or code files) change during application of manual or automated development activities. On that basis, risk analysis techniques are provided. These techniques allow identifying changeability risks and assessing the manifestations of the MDE traits (and with it an MDE setting's impact on software development processes). To address the range of validity, MDE settings from practice and their evolution histories were capture in context of this thesis. First, this data is used to show that MDE settings cover the whole spectrum concerning their impact on changeability or interrelation to software development processes. Neither it is seldom that MDE settings are neutral for processes nor is it seldom that MDE settings have impact on processes. Similarly, the impact on changeability differs relevantly. Second, a taxonomy of evolution of MDE settings is introduced. In that context it is discussed to what extent different types of changes on an MDE setting can influence this MDE setting's impact on changeability and the interrelation to processes. The category of structural evolution, which can change these characteristics of an MDE setting, is identified. The captured MDE settings from practice are used to show that structural evolution exists and is common. In addition, some examples of structural evolution steps are collected that actually led to a change in the characteristics of the respective MDE settings. Two implications are: First, the assessed diversity of MDE settings evaluates the need for the analysis techniques that shall be presented in this thesis. Second, evolution is one explanation for the diversity of MDE settings in practice. To summarize, this thesis studies the nature and evolution of MDE settings in practice. As a result support for the adoption of MDE settings is provided in form of techniques for the identification of risks relating to productivity impacts.
In processing and data storage mainly ferromagnetic (FM) materials are being used. Approaching physical limits, new concepts have to be found for faster, smaller switches, for higher data densities and more energy efficiency. Some of the discussed new concepts involve the material classes of correlated oxides and materials with antiferromagnetic coupling. Their applicability depends critically on their switching behavior, i.e., how fast and how energy efficient material properties can be manipulated. This thesis presents investigations of ultrafast non-equilibrium phase transitions on such new materials. In transition metal oxides (TMOs) the coupling of different degrees of freedom and resulting low energy excitation spectrum often result in spectacular changes of macroscopic properties (colossal magneto resistance, superconductivity, metal-to-insulator transitions) often accompanied by nanoscale order of spins, charges, orbital occupation and by lattice distortions, which make these material attractive. Magnetite served as a prototype for functional TMOs showing a metal-to-insulator-transition (MIT) at T = 123 K. By probing the charge and orbital order as well as the structure after an optical excitation we found that the electronic order and the structural distortion, characteristics of the insulating phase in thermal equilibrium, are destroyed within the experimental resolution of 300 fs. The MIT itself occurs on a 1.5 ps timescale. It shows that MITs in functional materials are several thousand times faster than switching processes in semiconductors. Recently ferrimagnetic and antiferromagnetic (AFM) materials have become interesting. It was shown in ferrimagnetic GdFeCo, that the transfer of angular momentum between two opposed FM subsystems with different time constants leads to a switching of the magnetization after laser pulse excitation. In addition it was theoretically predicted that demagnetization dynamics in AFM should occur faster than in FM materials as no net angular momentum has to be transferred out of the spin system. We investigated two different AFM materials in order to learn more about their ultrafast dynamics. In Ho, a metallic AFM below T ≈ 130 K, we found that the AFM Ho can not only be faster but also ten times more energy efficiently destroyed as order in FM comparable metals. In EuTe, an AFM semiconductor below T ≈ 10 K, we compared the loss of magnetization and laser-induced structural distortion in one and the same experiment. Our experiment shows that they are effectively disentangled. An exception is an ultrafast release of lattice dynamics, which we assign to the release of magnetostriction. The results presented here were obtained with time-resolved resonant soft x-ray diffraction at the Femtoslicing source of the Helmholtz-Zentrum Berlin and at the free-electron laser in Stanford (LCLS). In addition the development and setup of a new UHV-diffractometer for these experiments will be reported.
The economic impact analysis contained in this book shows how irrigation farming is particularly susceptible when applying certain water management policies in the Australian Murray-Darling Basin, one of the world largest river basins and Australia’s most fertile region. By comparing different pricing and non-pricing water management policies with the help of the Water Integrated Market Model, it is found that the impact of water demand reducing policies is most severe on crops that need to be intensively irrigated and are at the same time less water productive. A combination of increasingly frequent and severe droughts and the application of policies that decrease agricultural water demand, in the same region, will create a situation in which the highly water dependent crops rice and cotton cannot be cultivated at all.
Effect of benzylglucosinolate on signaling pathways associated with type 2 diabetes prevention
(2014)
Type 2 diabetes (T2D) is a health problem throughout the world. In 2010, there were nearly 230 million individuals with diabetes worldwide and it is estimated that in the economically advanced countries the cases will increase about 50% in the next twenty years. Insulin resistance is one of major features in T2D, which is also a risk factor for metabolic and cardiovascular complications. Epidemiological and animal studies have shown that the consumption of vegetables and fruits can delay or prevent the development of the disease, although the underlying mechanisms of these effects are still unclear. Brassica species such as broccoli (Brassica oleracea var. italica) and nasturtium (Tropaeolum majus) possess high content of bioactive phytochemicals, e.g. nitrogen sulfur compounds (glucosinolates and isothiocyanates) and polyphenols largely associated with the prevention of cancer. Isothiocyanates (ITCs) display their anti-carcinogenic potential by inducing detoxicating phase II enzymes and increasing glutathione (GSH) levels in tissues. In T2D diabetes an increase in gluconeogenesis and triglyceride synthesis, and a reduction in fatty acid oxidation accompanied by the presence of reactive oxygen species (ROS) are observed; altogether is the result of an inappropriate response to insulin. Forkhead box O (FOXO) transcription factors play a crucial role in the regulation of insulin effects on gene expression and metabolism, and alterations in FOXO function could contribute to metabolic disorders in diabetes. In this study using stably transfected human osteosarcoma cells (U-2 OS) with constitutive expression of FOXO1 protein labeled with GFP (green fluorescent protein) and human hepatoma cells HepG2 cell cultures, the ability of benzylisothiocyanate (BITC) deriving from benzylglucosinolate, extracted from nasturtium to modulate, i) the insulin-signaling pathway, ii) the intracellular localization of FOXO1 and iii) the expression of proteins involved in glucose metabolism, ROS detoxification, cell cycle arrest and DNA repair was evaluated. BITC promoted oxidative stress and in response to that induced FOXO1 translocation from cytoplasm into the nucleus antagonizing the insulin effect. BITC stimulus was able to down-regulate gluconeogenic enzymes, which can be considered as an anti-diabetic effect; to promote antioxidant resistance expressed by the up-regulation in manganese superoxide dismutase (MnSOD) and detoxification enzymes; to modulate autophagy by induction of BECLIN1 and down-regulation of the mammalian target of rapamycin complex 1 (mTORC1) pathway; and to promote cell cycle arrest and DNA damage repair by up-regulation of the cyclin-dependent kinase inhibitor (p21CIP) and Growth Arrest / DNA Damage Repair (GADD45). Except for the nuclear factor (erythroid derived)-like2 (NRF2) and its influence in the detoxification enzymes gene expression, all the observed effects were independent from FOXO1, protein kinase B (AKT/PKB) and NAD-dependent deacetylase sirtuin-1 (SIRT1). The current study provides evidence that besides of the anticarcinogenic potential, isothiocyanates might have a role in T2D prevention. BITC stimulus mimics the fasting state, in which insulin signaling is not triggered and FOXO proteins remain in the nucleus modulating gene expression of their target genes, with the advantage of a down-regulation of gluconeogenesis instead of its increase. These effects suggest that BITC might be considered as a promising substance in the prevention or treatment of T2D, therefore the factors behind of its modulatory effects need further investigation.
Concepts and techniques for integration, analysis and visualization of massive 3D point clouds
(2014)
Remote sensing methods, such as LiDAR and image-based photogrammetry, are established approaches for capturing the physical world. Professional and low-cost scanning devices are capable of generating dense 3D point clouds. Typically, these 3D point clouds are preprocessed by GIS and are then used as input data in a variety of applications such as urban planning, environmental monitoring, disaster management, and simulation. The availability of area-wide 3D point clouds will drastically increase in the future due to the availability of novel capturing methods (e.g., driver assistance systems) and low-cost scanning devices. Applications, systems, and workflows will therefore face large collections of redundant, up-to-date 3D point clouds and have to cope with massive amounts of data. Hence, approaches are required that will efficiently integrate, update, manage, analyze, and visualize 3D point clouds. In this paper, we define requirements for a system infrastructure that enables the integration of 3D point clouds from heterogeneous capturing devices and different timestamps. Change detection and update strategies for 3D point clouds are presented that reduce storage requirements and offer new insights for analysis purposes. We also present an approach that attributes 3D point clouds with semantic information (e.g., object class category information), which enables more effective data processing, analysis, and visualization. Out-of-core real-time rendering techniques then allow for an interactive exploration of the entire 3D point cloud and the corresponding analysis results. Web-based visualization services are utilized to make 3D point clouds available to a large community. The proposed concepts and techniques are designed to establish 3D point clouds as base datasets, as well as rendering primitives for analysis and visualization tasks, which allow operations to be performed directly on the point data. Finally, we evaluate the presented system, report on its applications, and discuss further research challenges.
African weakly electric fishes (Mormyridae) underwent an outstanding adaptive radiation (about 200 species), putatively owing to their ability to communicate through species-specific weak electric signals. The electric organ discharge (EOD) is produced by muscle-derived electrocytes organized in piles to form an electric organ. Despite the importance of this trait as a prezygotic isolation mechanism, genomic resources remained limited. We present here a first draft of the skeletal muscle and electric organ transcriptomes from the weakly electric fish species Campylomormyrus compressirostris, obtained using the Illumina HiSeq2000 sequencing technology. Approximately 6.8 Gbp of cDNA sequence data were produced from both tissues, resulting in 57268109 raw reads for the skeletal muscle and 46934923 for the electric organ, and assembled de novo into 46143 and 89270 contigs, respectively. About 50% of both transcriptomes were annotated after protein databases search. The two transcriptomes show similar profiles in terms of Gene Ontology categories composition. We identified several candidate genes which are likely to play a central role in the production and evolution of the electric signal. For most of these genes, and for many other housekeeping genes, we were able to obtain the complete or partial coding DNA sequences (CDS), which can be used for the development of primers to be utilized in qRT-PCR experiments. We present also the complete mitochondrial genome and compare it to those available from other weakly electric fish species. Additionally, we located 1671 SSR-containing regions with their flanking sites and designed the relative primers. This study establishes a first step in the development of genomic tools aimed at understanding the role of electric communication during speciation.
Plants are sessile organisms that gauge stressful conditions to ensure survival and reproductive success. While plants in nature often encounter chronic or recurring stressful conditions, the strategies to cope with those are poorly understood. Here, we demonstrate the involvement of ARGONAUTE1 and the microRNA pathway in the adaptation to recurring heat stress (HS memory) at the physiological and molecular level. We show that miR156 isoforms are highly induced after HS and are functionally important for HS memory. miR156 promotes sustained expression of HS-responsive genes and is critical only after HS, demonstrating that the effects of modulating miR156 on HS memory do not reflect preexisting developmental alterations. miR156 targets SPL transcription factor genes that are master regulators of developmental transitions. SPL genes are posttranscriptionally downregulated by miR156 after HS, and this is critical for HS memory. Altogether, the miR156-SPL module mediates the response to recurring HS in Arabidopsis thaliana and thus may serve to integrate stress responses with development.
Transposons are massively abundant in all eukaryotic genomes and are suppressed by epigenetic silencing. Transposon activity contributes to the evolution of species; however, it is unclear how much transposition-induced variation exists at a smaller scale and how transposons are targeted for silencing. Here, we exploited differential silencing of the AtMu1c transposon in the Arabidopsis thaliana accessions Columbia (Col) and Landsberg erecta (Ler). The difference persisted in hybrids and recombinant inbred lines and was mapped to a single expression quantitative trait locus within a 20-kb interval. In Ler only, this interval contained a previously unidentified copy of AtMu1c, which was inserted at the 39 end of a protein-coding gene and showed features of expressed genes. By contrast, AtMu1c(Col) was intergenic and associated with heterochromatic features. Furthermore, we identified widespread natural AtMu1c transposition from the analysis of over 200 accessions, which was not evident from alignments to the reference genome. AtMu1c expression was highest for insertions within 39 untranslated regions, suggesting that this location provides protection from silencing. Taken together, our results provide a species-wide view of the activity of one transposable element at unprecedented resolution, showing that AtMu1c transposed in the Arabidopsis lineage and that transposons can escape epigenetic silencing by inserting into specific genomic locations, such as the 3' end of genes.
Software maintenance encompasses any changes made to a software system after its initial deployment and is thereby one of the key phases in the typical software-engineering lifecycle. In software maintenance, we primarily need to understand structural and behavioral aspects, which are difficult to obtain, e.g., by code reading. Software analysis is therefore a vital tool for maintaining these systems: It provides - the preferably automated - means to extract and evaluate information from their artifacts such as software structure, runtime behavior, and related processes. However, such analysis typically results in massive raw data, so that even experienced engineers face difficulties directly examining, assessing, and understanding these data. Among other things, they require tools with which to explore the data if no clear question can be formulated beforehand. For this, software analysis and visualization provide its users with powerful interactive means. These enable the automation of tasks and, particularly, the acquisition of valuable and actionable insights into the raw data. For instance, one means for exploring runtime behavior is trace visualization. This thesis aims at extending and improving the tool set for visual software analysis by concentrating on several open challenges in the fields of dynamic and static analysis of software systems. This work develops a series of concepts and tools for the exploratory visualization of the respective data to support users in finding and retrieving information on the system artifacts concerned. This is a difficult task, due to the lack of appropriate visualization metaphors; in particular, the visualization of complex runtime behavior poses various questions and challenges of both a technical and conceptual nature. This work focuses on a set of visualization techniques for visually representing control-flow related aspects of software traces from shared-memory software systems: A trace-visualization concept based on icicle plots aids in understanding both single-threaded as well as multi-threaded runtime behavior on the function level. The concept’s extensibility further allows the visualization and analysis of specific aspects of multi-threading such as synchronization, the correlation of such traces with data from static software analysis, and a comparison between traces. Moreover, complementary techniques for simultaneously analyzing system structures and the evolution of related attributes are proposed. These aim at facilitating long-term planning of software architecture and supporting management decisions in software projects by extensions to the circular-bundle-view technique: An extension to 3-dimensional space allows for the use of additional variables simultaneously; interaction techniques allow for the modification of structures in a visual manner. The concepts and techniques presented here are generic and, as such, can be applied beyond software analysis for the visualization of similarly structured data. The techniques' practicability is demonstrated by several qualitative studies using subject data from industry-scale software systems. The studies provide initial evidence that the techniques' application yields useful insights into the subject data and its interrelationships in several scenarios.
Computational brain maps as opposed to maps of receptor surfaces strongly reflect functional neuronal design principles. In echolocating bats, computational maps are established that topographically represent the distance of objects. These target range maps are derived from the temporal delay between emitted call and returning echo and constitute a regular representation of time (chronotopy). Basic features of these maps are innate, and in different bat species the map size and precision varies. An inherent advantage of target range maps is the implementation of mechanisms for lateral inhibition and excitatory feedback. Both can help to focus target ranging depending on the actual echolocation situation. However, these maps are not absolutely necessary for bat echolocation since there are bat species without cortical target-distance maps, which use alternative ensemble computation mechanisms.
Biosensors for the detection of benzaldehyde and g-aminobutyric acid (GABA) are reported using aldehyde oxidoreductase PaoABC from Escherichia coli immobilized in a polymer containing bound low potential osmium redox complexes. The electrically connected enzyme already electrooxidizes benzaldehyde at potentials below −0.15 V (vs. Ag|AgCl, 1 M KCl). The pH-dependence of benzaldehyde oxidation can be strongly influenced by the ionic strength. The effect is similar with the soluble osmium redox complex and therefore indicates a clear electrostatic effect on the bioelectrocatalytic efficiency of PaoABC in the osmium containing redox polymer. At lower ionic strength, the pH-optimum is high and can be switched to low pH-values at high ionic strength. This offers biosensing at high and low pH-values. A “reagentless” biosensor has been formed with enzyme wired onto a screen-printed electrode in a flow cell device. The response time to addition of benzaldehyde is 30 s, and the measuring range is between 10–150 µM and the detection limit of 5 µM (signal to noise ratio 3:1) of benzaldehyde. The relative standard deviation in a series (n = 13) for 200 µM benzaldehyde is 1.9%. For the biosensor, a response to succinic semialdehyde was also identified. Based on this response and the ability to work at high pH a biosensor for GABA is proposed by coimmobilizing GABA-aminotransferase (GABA-T) and PaoABC in the osmium containing redox polymer.
There is robust evidence showing a link between executive function (EF) and theory of mind (ToM) in 3-to 5-year-olds. However, it is unclear whether this relationship extends to middle childhood. In addition, there has been much discussion about the nature of this relationship. Whereas some authors claim that ToM is needed for EF, others argue that ToM requires EF. To date, however, studies examining the longitudinal relationship between distinct sub components of EF [i.e., attention shifting, working memory (WM) updating, inhibition] and ToM in middle childhood are rare. The present study examined (1) the relationship between three EF subcomponents (attention shifting, WM updating, inhibition) and ToM in middle childhood, and (2) the longitudinal reciprocal relationships between the EF subcomponents and ToM across a 1-year period. EF and ToM measures were assessed experimentally in a sample of 1,657 children (aged 6-11 years) at time point one (t1) and 1 year later at time point two (t2). Results showed that the concurrent relationships between all three EF subcomponents and ToM pertained in middle childhood at t1 and t2, respectively, even when age, gender, and fluid intelligence were partialle dout. Moreover, cross-lagged structural equation modeling (again, controlling for age, gender, and fluid intelligence, as well as for the earlier levels of the target variables), revealed partial support for the view that early ToM predictslater EF, but stronger evidence for the assumption that early EF predictslater ToM. The latter was found for attention shifting and WM updating, but not for inhibition. This reveals the importance of studying the exact interplay of ToM and EF across childhood development, especially with regard to different EF subcomponents. Most likely, understanding others' mental states at different levels of perspective-taking requires specific EF subcomponents, suggesting developmental change in the relations between EF and ToM across childhood.