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Institute
- Mathematisch-Naturwissenschaftliche Fakultät (539) (remove)
In order to evade detection by network-traffic analysis, a growing proportion of malware uses the encrypted HTTPS protocol. We explore the problem of detecting malware on client computers based on HTTPS traffic analysis. In this setting, malware has to be detected based on the host IP address, ports, timestamp, and data volume information of TCP/IP packets that are sent and received by all the applications on the client. We develop a scalable protocol that allows us to collect network flows of known malicious and benign applications as training data and derive a malware-detection method based on a neural networks and sequence classification. We study the method's ability to detect known and new, unknown malware in a large-scale empirical study.
In this paper, I review observational evidence from spectroscopy and polarimetry for the presence of small and large scale structure in the winds of Wolf-Rayet (WR) stars. Clumping is known to be ubiquitous in the winds of these stars and many of its characteristics can be deduced from spectroscopic time-series and polarisation lightcurves. Conversely, a much smaller fraction of WR stars have been shown to harbour larger scale structures in their wind (∼ 1/5) while they are thought to be present is the winds of most of their O-star ancestors. The reason for this difference is still unknown.
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.
A dramatic efficiency improvement of bulk heterojunction solar cells based on electron-donating conjugated polymers in combination with soluble fullerene derivatives has been achieved over the past years. Certified and reported power conversion efficiencies now reach over 9% for single junctions and exceed the 10% benchmark for tandem solar cells. This trend brightens the vision of organic photovoltaics becoming competitive with inorganic solar cells including the realization of low-cost and large-area organic photovoltaics. For the best performing organic materials systems, the yield of charge generation can be very efficient. However, a detailed understanding of the free charge carrier generation mechanisms at the donor acceptor interface and the energy loss associated with it needs to be established. Moreover, organic solar cells are limited by the competition between charge extraction and free charge recombination, accounting for further efficiency losses. A conclusive picture and the development of precise methodologies for investigating the fundamental processes in organic solar cells are crucial for future material design, efficiency optimization, and the implementation of organic solar cells into commercial products.
In order to advance the development of organic photovoltaics, my thesis focuses on the comprehensive understanding of charge generation, recombination and extraction in organic bulk heterojunction solar cells summarized in 6 chapters on the cumulative basis of 7 individual publications.
The general motivation guiding this work was the realization of an efficient hybrid inorganic/organic tandem solar cell with sub-cells made from amorphous hydrogenated silicon and organic bulk heterojunctions. To realize this project aim, the focus was directed to the low band-gap copolymer PCPDTBT and its derivatives, resulting in the examination of the charge carrier dynamics in PCPDTBT:PC70BM blends in relation to by the blend morphology. The phase separation in this blend can be controlled by the processing additive diiodooctane, enhancing domain purity and size. The quantitative investigation of the free charge formation was realized by utilizing and improving the time delayed collection field technique. Interestingly, a pronounced field dependence of the free carrier generation for all blends is found, with the field dependence being stronger without the additive. Also, the bimolecular recombination coefficient for both blends is rather high and increases with decreasing internal field which we suggest to be caused by a negative field dependence of mobility. The additive speeds up charge extraction which is rationalized by the threefold increase in mobility.
By fluorine attachment within the electron deficient subunit of PCPDTBT, a new polymer F-PCPDTBT is designed. This new material is characterized by a stronger tendency to aggregate as compared to non-fluorinated PCPDTBT. Our measurements show that for F-PCPDTBT:PCBM blends the charge carrier generation becomes more efficient and the field-dependence of free charge carrier generation is weakened. The stronger tendency to aggregate induced by the fluorination also leads to increased polymer rich domains, accompanied in a threefold reduction in the non-geminate recombination coefficient at conditions of open circuit. The size of the polymer domains is nicely correlated to the field-dependence of charge generation and the Langevin reduction factor, which highlights the importance of the domain size and domain purity for efficient charge carrier generation. In total, fluorination of PCPDTBT causes the PCE to increase from 3.6 to 6.1% due to enhanced fill factor, short circuit current and open circuit voltage. Further optimization of the blend ratio, active layer thickness, and polymer molecular weight resulted in 6.6% efficiency for F-PCPDTBT:PC70BM solar cells.
Interestingly, the double fluorinated version 2F-PCPDTBT exhibited poorer FF despite a further reduction of geminate and non-geminate recombination losses. To further analyze this finding, a new technique is developed that measures the effective extraction mobility under charge carrier densities and electrical fields comparable to solar cell operation conditions. This method involves the bias enhanced charge extraction technique. With the knowledge of the carrier density under different electrical field and illumination conditions, a conclusive picture of the changes in charge carrier dynamics leading to differences in the fill factor upon fluorination of PCPDTBT is attained. The more efficient charge generation and reduced recombination with fluorination is counterbalanced by a decreased extraction mobility. Thus, the highest fill factor of 60% and efficiency of 6.6% is reached for F-PCPDTBT blends, while 2F-PCPDTBT blends have only moderate fill factors of 54% caused by the lower effective extraction mobility, limiting the efficiency to 6.5%.
To understand the details of the charge generation mechanism and the related losses, we evaluated the yield and field-dependence of free charge generation using time delayed collection field in combination with sensitive measurements of the external quantum efficiency and absorption coefficients for a variety of blends. Importantly, both the yield and field-dependence of free charge generation is found to be unaffected by excitation energy, including direct charge transfer excitation below the optical band gap. To access the non-detectable absorption at energies of the relaxed charge transfer emission, the absorption was reconstructed from the CT emission, induced via the recombination of thermalized charges in electroluminescence. For a variety of blends, the quantum yield at energies of charge transfer emission was identical to excitations with energies well above the optical band-gap. Thus, the generation proceeds via the split-up of the thermalized charge transfer states in working solar cells. Further measurements were conducted on blends with fine-tuned energy levels and similar blend morphologies by using different fullerene derivatives. A direct correlation between the efficiency of free carrier generation and the energy difference of the relaxed charge transfer state relative to the energy of the charge separated state is found. These findings open up new guidelines for future material design as new high efficiency materials require a minimum energetic offset between charge transfer and the charge separated state while keeping the HOMO level (and LUMO level) difference between donor and acceptor as small as possible.
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.
Magnetite is an iron oxide, which is ubiquitous in rocks and is usually deposited as small nanoparticulate matter among other rock material. It differs from most other iron oxides because it contains divalent and trivalent iron. Consequently, it has a special crystal structure and unique magnetic properties. These properties are used for paleoclimatic reconstructions where naturally occurring magnetite helps understanding former geological ages. Further on, magnetic properties are used in bio- and nanotechnological applications –synthetic magnetite serves as a contrast agent in MRI, is exploited in biosensing, hyperthermia or is used in storage media.
Magnetic properties are strongly size-dependent and achieving size control under preferably mild synthesis conditions is of interest in order to obtain particles with required properties. By using a custom-made setup, it was possible to synthesize stable single domain magnetite nanoparticles with the co-precipitation method. Furthermore, it was shown that magnetite formation is temperature-dependent, resulting in larger particles at higher temperatures. However, mechanistic approaches about the details are incomplete.
Formation of magnetite from solution was shown to occur from nanoparticulate matter rather than solvated ions. The theoretical framework of such processes has only started to be described, partly due to the lack of kinetic or thermodynamic data. Synthesis of magnetite nanoparticles at different temperatures was performed and the Arrhenius plot was used determine an activation energy for crystal growth of 28.4 kJ mol-1, which led to the conclusion that nanoparticle diffusion is the rate-determining step.
Furthermore, a study of the alteration of magnetite particles of different sizes as a function of their storage conditions is presented. The magnetic properties depend not only on particle size but also depend on the structure of the oxide, because magnetite oxidizes to maghemite under environmental conditions. The dynamics of this process have not been well described. Smaller nanoparticles are shown to oxidize more rapidly than larger ones and the lower the storage temperature, the lower the measured oxidation. In addition, the magnetic properties of the altered particles are not decreased dramatically, thus suggesting that this alteration will not impact the use of such nanoparticles as medical carriers.
Finally, the effect of biological additives on magnetite formation was investigated. Magnetotactic bacteria¬¬ are able to synthesize and align magnetite nanoparticles of well-defined size and morphology due to the involvement of special proteins with specific binding properties. Based on this model of morphology control, phage display experiments were performed to determine peptide sequences that preferably bind to (111)-magnetite faces. The aim was to control the shape of magnetite nanoparticles during the formation. Magnetotactic bacteria are also able to control the intracellular redox potential with proteins called magnetochromes. MamP is such a protein and its oxidizing nature was studied in vitro via biomimetic magnetite formation experiments based on ferrous ions. Magnetite and further trivalent oxides were found.
This work helps understanding basic mechanisms of magnetite formation and gives insight into non-classical crystal growth. In addition, it is shown that alteration of magnetite nanoparticles is mainly based on oxidation to maghemite and does not significantly influence the magnetic properties. Finally, biomimetic experiments help understanding the role of MamP within the bacteria and furthermore, a first step was performed to achieve morphology control in magnetite formation via co-precipitation.
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.
Pulsar wind nebulae (PWNe) are the most abundant TeV gamma-ray emitters in the Milky Way. The radiative emission of these objects is powered by fast-rotating pulsars, which donate parts of their rotational energy into winds of relativistic particles. This thesis presents an in-depth study of the detected population of PWNe at high energies. To outline general trends regarding their evolutionary behaviour, a time-dependent model is introduced and compared to the available data. In particular, this work presents two exceptional PWNe which protrude from the rest of the population, namely the Crab Nebula and N 157B. Both objects are driven by pulsars with extremely high rotational energy loss rates. Accordingly, they are often referred to as energetic twins. Modelling the non-thermal multi-wavelength emission of N157B gives access to specific properties of this object, like the magnetic field inside the nebula. Comparing the derived parameters to those of the Crab Nebula reveals large intrinsic differences between the two PWNe. Possible origins of these differences are discussed in context of the resembling pulsars.
Compared to the TeV gamma-ray regime, the number of detected PWNe is much smaller in the MeV-GeV gamma-ray range. In the latter range, the Crab Nebula stands out by the recent detection of gamma-ray flares. In general, the measured flux enhancements on short time scales of days to weeks were not expected in the theoretical understanding of PWNe. In this thesis, the variability of the Crab Nebula is analysed using data from the Fermi Large Area Telescope (Fermi-LAT). For the presented analysis, a new gamma-ray reconstruction method is used, providing a higher sensitivity and a lower energy threshold compared to previous analyses. The derived gamma-ray light curve of the Crab Nebula is investigated for flares and periodicity. The detected flares are analysed regarding their energy spectra, and their variety and commonalities are discussed. In addition, a dedicated analysis of the flare which occurred in March 2013 is performed. The derived short-term variability time scale is roughly 6h, implying a small region inside the Crab Nebula to be responsible for the enigmatic flares. The most promising theories explaining the origins of the flux eruptions and gamma-ray variability are discussed in detail.
In the technical part of this work, a new analysis framework is presented. The introduced software, called gammalib/ctools, is currently being developed for the future CTA observa- tory. The analysis framework is extensively tested using data from the H. E. S. S. experiment. To conduct proper data analysis in the likelihood framework of gammalib/ctools, a model describing the distribution of background events in H.E.S.S. data is presented. The software provides the infrastructure to combine data from several instruments in one analysis. To study the gamma-ray emitting PWN population, data from Fermi-LAT and H. E. S. S. are combined in the likelihood framework of gammalib/ctools. In particular, the spectral peak, which usually lies in the overlap energy regime between these two instruments, is determined with the presented analysis framework. The derived measurements are compared to the predictions from the time-dependent model. The combined analysis supports the conclusion of a diverse population of gamma-ray emitting PWNe.