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The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties. Unlike sequence-similarity-based methods and covariance models, GraPPLE is demonstrated to be more robust with regard to increasing sequence divergence, and when combined with existing methods, leads to a significant improvement of prediction accuracy. Furthermore, graph properties identified as most informative are shown to provide an understanding as to what particular structural features render RNA molecules functional. Thus, GraPPLE may offer a valuable computational filtering tool to identify potentially interesting RNA molecules among large candidate datasets.
Demografie im Wandel
(2009)
Aus dem Editorial: „Negativzuwanderung“ wählten die Österreicher zu ihrem Unwort des Jahres 2005. Dieser Begriff verdeutlicht einen Aspekt des gesamtgesellschaftlichen Problems des demografischen Wandels, der nicht nur in Österreich seit einiger Zeit für jeden zu spüren ist. Verstanden wird darunter die quantitative und qualitative Veränderung der Bevölkerungsstruktur, die sich für Deutschland und die meisten westeuropäischen Länder mit drei Schlagworten beschreiben lässt: weniger Kinder, mehr Alte, also insgesamt weniger Menschen. Allein für Deutschland wird bis 2050 ein Bevölkerungsrückgang um 20% erwartet. Davon betroffen sind alle Politikfelder, unter anderem die Bildungs- und Sozialpolitik sowie die Arbeitsmarkt- und Infrastrukturpolitik. Eine Herausforderung, die für Politik und Verwaltung gleichermaßen einmalig in der jüngeren Geschichte ist. Als „unterste“ Ebene sind die Kommunen und ihre Einrichtungen besonders stark betroffen, denn sie halten die Mehrzahl der infrastrukturellen und sonstigen öffentlichen Einrichtungen für die Menschen vor, sie sind über einwohnerbezogene Finanzzuweisungssysteme abhängig von „ihren Menschen“ und haben gleichzeitig wenig Einfluss auf die wirtschaftlich bedingten Zu- oder Wegzüge der Einwohner. Sind diese Entwicklungen seit längerer Zeit bekannt und werden intensiv diskutiert, so sind in letzter Zeit eine Reihe von Strategien und Handlungskonzepten entwickelt worden, um mit diesem Problem umgehen zu können. Das Kommunalwissenschaftliche Institut der Universität Potsdam (KWI) veranstaltete am 3. April 2006 eine Fachtagung „Demografie im Wandel. Herausforderungen für die Kommunen“. Zum 12. Mal trafen sich seit der Gründung des Institutes ca. 250 Vertreter der Wissenschaft, der Politik, der Verbände, insbesondere aber der Kommunen, um über aktuelle Demografieprobleme zu diskutieren. Dabei standen sowohl die wissenschaftliche Analyse als auch politische Handlungsstrategien im Fokus der Diskussion. Wichtige Ergebnisse dieser Tagung sind im nachfolgenden KWI-Arbeitsheft festgehalten und werden durch weitere Beiträge zum Thema ergänzt.
Despite general concern that the massive deposits of methane stored under permafrost underground and undersea could be released into the atmosphere due to rising temperatures attributed to global climate change, little is known about the methanogenic microorganisms in permafrost sediments, their role in methane emissions, and their phylogeny. The aim of this thesis was to increase knowledge of uncultivated methanogenic microorganisms in submarine and terrestrial permafrost deposits, their community composition, the role they play with regard to methane emissions, and their phylogeny. It is assumed that methanogenic communities in warmer submarine permafrost may serve as a model to anticipate the response of methanogenic communities in colder terrestrial permafrost to rising temperatures. The compositions of methanogenic communities were examined in terrestrial and submarine permafrost sediment samples. The submarine permafrost studied in this research was 10°C warmer than the terrestrial permafrost. By polymerase chain reaction (PCR), DNA was extracted from each of the samples and analyzed by molecular microbiological methods such as PCR-DGGE, RT-PCR, and cloning. Furthermore, these samples were used for in vitro experiment and FISH. The submarine permafrost analysis of the isotope composition of CH4 suggested a relationship between methane content and in situ active methanogenesis. Furthermore, active methanogenesis was proven using 13C-isotope measurements of methane in submarine permafrost sediment with a high TOC value and a high methane concentration. In the molecular-microbiological studies uncultivated lines of Methanosarcina, Methanomicrobiales, Methanobacteriacea and the Groups 1.3 and Marine Benthic from Crenarchaeota were found in all submarine and terrestrial permafrost samples. Methanosarcina was the dominant group of the Archaea in all submarine and terrestrial permafrost samples. The archaeal community composition, in particular, the methanogenic community composition showed diversity with changes in temperatures. Furthermore, cell count of methanogens in submarine permafrost was 10 times higher than in terrestrial permafrost. In vitro experiments showed that methanogens adapt quickly and well to higher temperatures. If temperatures rise due to climate change, an increase in methanogenic activity can be expected as long as organic material is sufficiently available and qualitatively adequate.
The aim of this thesis is to achieve a deep understanding of the working mechanism of polymer based solar cells and to improve the device performance. Two types of the polymer based solar cells are studied here: all-polymer solar cells comprising macromolecular donors and acceptors based on poly(p-phenylene vinylene) and hybrid cells comprising a PPV copolymer in combination with a novel small molecule electron acceptor. To understand the interplay between morphology and photovoltaic properties in all-polymer devices, I compared the photocurrent characteristics and excited state properties of bilayer and blend devices with different nano-morphology, which was fine tuned by using solvents with different boiling points. The main conclusion from these complementary measurements was that the performance-limiting step is the field-dependent generation of free charge carriers, while bimolecular recombination and charge extraction do not compromise device performance. These findings imply that the proper design of the donor-acceptor heterojunction is of major importance towards the goal of high photovoltaic efficiencies. Regarding polymer-small molecular hybrid solar cells I combined the hole-transporting polymer M3EH-PPV with a novel Vinazene-based electron acceptor. This molecule can be either deposited from solution or by thermal evaporation, allowing for a large variety of layer architectures to be realized. I then demonstrated that the layer architecture has a large influence on the photovoltaic properties. Solar cells with very high fill factors of up to 57 % and an open circuit voltage of 1V could be achieved by realizing a sharp and well-defined donor-acceptor heterojunction. In the past, fill factors exceeding 50 % have only been observed for polymers in combination with soluble fullerene-derivatives or nanocrystalline inorganic semiconductors as the electron-accepting component. The finding that proper processing of polymer-vinazene devices leads to similar high values is a major step towards the design of efficient polymer-based solar cells.
Complex networks in climate dynamics : comparing linear and nonlinear network construction methods
(2009)
Complex network theory provides a powerful framework to statistically investigate the topology of local and non- local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system.
Bimodal temperature behavior of structure and mobility in high molecular weight p3ht thin films
(2009)
We report a temperature dependent crystalline structure of spin-coated thin films of high molecular weight regioregular poly(3-hexylthiophene) (P3HT) (M-n similar to 30000 g/mol) and its correlation with charge carrier mobility. These investigations show a reversible change of the crystalline structure, where the interlayer lattice spacing (100)along the alkyl side chains continuously increases up to a temperature of about 220 degrees C; in contrast, the in-plane pi-pi distance reduces with increasing temperature. These changes in structure are reversible and can be repeated several times. The temperature-induced structural properties differ for thick and thin films, pointing to a surface/interface role in stabilization of the layer morphology. In contrast to the structural changes, the carrier mobility is rather constant in the temperature range from room temperature up to 100-120 degrees C, followed by a continuous decrease. For thick layers this drop is significant and the transistor performance almost vanishes at high temperature, however, it completely recovers upon cooling back to roorn temperature. The drop of the charge carrier mobility at higher temperatures is in contrast with expectations front the structural studies, considering the increase of crystalline fraction of the polycrystalline layer. our electrical measurements Underscore that the reduction of the macroscopic mobility is mostly caused by it pronounced decrease of the intergrain transport. The thermally induced crystallization along(100) direction and the creation of numerous small crystallites at the film-substrate interface reduce the number of long polymer chain, bridging crystalline domains, which ultimately limits the macroscopic charge transport.
The authors present organic photovoltaic (OPV) devices comprising a small molecule electron acceptor based on 2- vinyl-4,5-dicyanoimidazole (Vinazene (TM)) and a soluble poly(p-phenylenevinylene) derivative as the electron donor. A strong dependence of the fill factor (FF) and the external quantum efficiency [incident photons converted to electrons (IPCE)] on the heterojunction topology is observed. As-prepared blends provided relatively low FF and IPCE values of 26% and 4.5%, respectively, which are attributed to significant recombination of geminate pairs and free carriers in a highly intermixed blend morphology. Going to an all-solution processed bilayer device, the FF and IPCE dramatically increased to 43% and 27%, respectively. The FF increases further to 57% in devices comprising thermally deposited Vinazene layers where there is virtually no interpenetration at the donor/acceptor interface. This very high FF is comparable to values reported for OPV using fullerenes as the electron acceptor. Furthermore, the rather low electron affinity of Vinazene compound near 3.5 eV enabled a technologically important open circuit voltage (V-oc) of 1.0 V.
Three-dimensional quantification of structures in trabecular bone using measures of complexity
(2009)
The study of pathological changes of bone is an important task in diagnostic procedures of patients with metabolic bone diseases such as osteoporosis as well as in monitoring the health state of astronauts during long-term space flights. The recent availability of high-resolution three-dimensional (3D) imaging of bone challenges the development of data analysis techniques able to assess changes of the 3D microarchitecture of trabecular bone. We introduce an approach based on spatial geometrical properties and define structural measures of complexity for 3D image analysis. These measures evaluate different aspects of organization and complexity of 3D structures, such as complexity of its surface or shape variability. We apply these measures to 3D data acquired by high-resolution microcomputed tomography (mu CT) from human proximal tibiae and lumbar vertebrae at different stages of osteoporotic bone loss. The outcome is compared to the results of conventional static histomorphometry and exhibits clear relationships between the analyzed geometrical features of trabecular bone and loss of bone density, but also indicate that the measures reveal additional information about the structural composition of bone, which were not revealed by the static histomorphometry. Finally, we have studied the dependency of the developed measures of complexity on the spatial resolution of the mu CT data sets.
We investigate solar cells comprised of a vinazene derivative (HV-BT) as the electron acceptor and the well- known polymer poly(3-hexylthiophene) as the electron donor. In the as-prepared blend, most of the excited state species, including the excimers on HV-BT, are quenched at the heterojunction. Although the photophysical properties of the blends change upon annealing, the blend solar cells largely remain uninfluenced by such treatments. A significant improvement is, however, observed when inducing phase separation at a longer length scale, for example, in solution-processed bilayer devices. Hereby, both the fill factor (FF) and the open circuit voltage are considerably increased, pointing to the importance of the heterojunction topology and the layer composition at the charge extracting contacts. An optimized device exhibits a power conversion efficiency of close to 1%.
Current-voltage analysis of single-carrier transport is a popular method for the determination of charge carrier mobilities in organic semiconductors. Although in widespread use for the analysis of hole transport, only a few reports can be found where the method was applied to electron transport. Here, we summarize the experimental difficulties related to the metal electrode leakage currents and nonlinear differential resistance (NDR) effects and explain their origin. We present a modified preparation technique for the metal electrodes and show that it significantly increases the reliability of such measurements. It allows to produce test devices with low leakage currents and without NDR even for thin organic layers. Metal oxides were often discussed as a possible cause of NDR. Our measurements on forcibly oxidized metal electrodes demonstrate that oxide layers are not exclusively responsible for NDR effects. We present electron transport data for two electron-conducting polymers often applied in all-polymer solar cells for a large variety of layer thicknesses and temperatures. The results can be explained by established exponential trapping models.
Aims. Sunspot distribution in the northern and southern solar hemispheres exibit striking synchronous behaviour on the scale of a Schwabe cycle. However, sometimes the bilateral symmetry of the Butterfly diagram relative to the solar equatorial plane breaks down. The investigation of this phenomenon is important to explaining the almost-periodic behaviour of solar cycles. Methods. We use cross-recurrence plots for the study of the time-varying phase asymmetry of the northern and southern hemisphere and compare our results with the latitudinal distribution of the sunspots. Results. We observe a long-term persistence of phase leading in one of the hemispheres, which lasts almost 4 solar cycles and probably corresponds to the Gleissberg cycle. Long-term variations in the hemispheric-leading do not demonstrate clear periodicity but are strongly anti-correlated with the long-term variations in the magnetic equator.
In the recent article "Stochastic analysis of recurrence plots with applications to the detection of deterministic signals" (Physica D 237 (2008) 619-629), Rohde et al. stated that the performance of RQA in order to detect deterministic signals would be below traditional and well-known detectors. However, we have concerns about such a general statement. Based on our own studies we cannot confirm their conclusions. Our findings suggest that the measures of complexity provided by RQA are useful detectors outperforming well-known traditional detectors, in particular for the detection of signals of complex systems, with phase differences or signals modified due to the measurement process.
Layers made from soluble low molecular weight polythiophene PQT-12 with low polydispersity exhibit a highly ordered structure and charge-carrier mobilities of the order of 10(-3) cm(2)/(V s), which we attribute to its proximity to monodispersity. We propose that polydispersity is a decisive factor with regard to structure formation and transport properties of soluble low molecular weight polythiophenes.
In the recent past, recurrence quantification analysis (RQA) has gained an increasing interest in various research areas. The complexity measures the RQA provides have been useful in describing and analysing a broad range of data. It is known to be rather robust to noise and nonstationarities. Yet, one key question in empirical research concerns the confidence bounds of measured data. In the present Letter we suggest a method for estimating the confidence bounds of recurrence-based complexity measures. We study the applicability of the suggested method with model and real- life data.
Carrier transport and recombination have been studied in single component layers and blends of the soluble PPV- derivative poly[2,5-dimethoxy-1,4-phenylenevinylene-2-methoxy-5-(2-ethyl-hexyloxy)- 1,4-phenylenevinylene] (M3EH-PPV) and the small molecule acceptor 4,7-bis(2-(1-hexyl-4,5-dicyanoimidazole-2-yl)vinyl) benzo[c][1,2,5]-thiadiazole (HV-BT). Measurements on single carrier devices show significantly smaller electron mobility in the blend compared to the pure HV- BT layer, which is suggestive of the formation of isolated clusters of the acceptor in a continuous polymer matrix. The significant change in fill factor (FF) with increasing illumination intensity is consistently explained by a model taking into account bimolecular recombination and space charge effects. The decay of the carrier density after photoexcitation has been studied by performing photo-CELIV measurements on pure and blend layers. It is found that the decay at long delay times follows a power-law dependence, which is, however, not consistent with a Langevin-type bimolecular recombination of free charges. A good description of the data is obtained by assuming trimolecular recombination to govern the charge carrier dynamics in these systems.
The EEG is one of the most commonly used tools in brain research. Though of high relevance in research, the data obtained is very noisy and nonstationary. In the present article we investigate the applicability of a nonlinear data analysis method, the recurrence quantification analysis (RQA), to Such data. The method solely rests on the natural property of recurrence which is a phenomenon inherent to complex systems, such as the brain. We show that this method is indeed suitable for the analysis of EEG data and that it might improve contemporary EEG analysis.
Background: Biological systems adapt to changing environments by reorganizing their cellula r and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underl ying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic conditiondependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple ob servation s about the changes of metabolic concentrations. The approach was tested with Escherichia colias a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diau xie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical path ways, and (3) ind ependently of the response scale, based on their importance in the reorganization of the cor relation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-ba sed approach does not rely on major changes in concentration to identify metabolites important for st ress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.
Classical semiconductor physics has been continuously improving electronic components such as diodes, light-emitting diodes, solar cells and transistors based on highly purified inorganic crystals over the past decades. Organic semiconductors, notably polymeric, are a comparatively young field of research, the first light-emitting diode based on conjugated polymers having been demonstrated in 1990. Polymeric semiconductors are of tremendous interest for high-volume, low-cost manufacturing ("printed electronics"). Due to their rather simple device structure mostly comprising only one or two functional layers, polymeric diodes are much more difficult to optimize compared to small-molecular organic devices. Usually, functions such as charge injection and transport are handled by the same material which thus needs to be highly optimized. The present work contributes to expanding the knowledge on the physical mechanisms determining device performance by analyzing the role of charge injection and transport on device efficiency for blue and white-emitting devices, based on commercially relevant spiro-linked polyfluorene derivatives. It is shown that such polymers can act as very efficient electron conductors and that interface effects such as charge trapping play the key role in determining the overall device efficiency. This work contributes to the knowledge of how charges drift through the polymer layer to finally find neutral emissive trap states and thus allows a quantitative prediction of the emission color of multichromophoric systems, compatible with the observed color shifts upon driving voltage and temperature variation as well as with electrical conditioning effects. In a more methodically oriented part, it is demonstrated that the transient device emission observed upon terminating the driving voltage can be used to monitor the decay of geminately-bound species as well as to determine trapped charge densities. This enables direct comparisons with numerical simulations based on the known properties of charge injection, transport and recombination. The method of charge extraction under linear increasing voltages (CELIV) is investigated in some detail, correcting for errors in the published approach and highlighting the role of non-idealized conditions typically present in experiments. An improved method is suggested to determine the field dependence of charge mobility in a more accurate way. Finally, it is shown that the neglect of charge recombination has led to a misunderstanding of experimental results in terms of a time-dependent mobility relaxation.