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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.
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.
Virtualized cloud data centers provide on-demand resources, enable agile resource provisioning, and host heterogeneous applications with different resource requirements. These data centers consume enormous amounts of energy, increasing operational expenses, inducing high thermal inside data centers, and raising carbon dioxide emissions. The increase in energy consumption can result from ineffective resource management that causes inefficient resource utilization. This dissertation presents detailed models and novel techniques and algorithms for virtual resource management in cloud data centers. The proposed techniques take into account Service Level Agreements (SLAs) and workload heterogeneity in terms of memory access demand and communication patterns of web applications and High Performance Computing (HPC) applications. To evaluate our proposed techniques, we use simulation and real workload traces of web applications and HPC applications and compare our techniques against the other recently proposed techniques using several performance metrics. The major contributions of this dissertation are the following: proactive resource provisioning technique based on robust optimization to increase the hosts' availability for hosting new VMs while minimizing the idle energy consumption. Additionally, this technique mitigates undesirable changes in the power state of the hosts by which the hosts' reliability can be enhanced in avoiding failure during a power state change. The proposed technique exploits the range-based prediction algorithm for implementing robust optimization, taking into consideration the uncertainty of demand. An adaptive range-based prediction for predicting workload with high fluctuations in the short-term. The range prediction is implemented in two ways: standard deviation and median absolute deviation. The range is changed based on an adaptive confidence window to cope with the workload fluctuations. A robust VM consolidation for efficient energy and performance management to achieve equilibrium between energy and performance trade-offs. Our technique reduces the number of VM migrations compared to recently proposed techniques. This also contributes to a reduction in energy consumption by the network infrastructure. Additionally, our technique reduces SLA violations and the number of power state changes. A generic model for the network of a data center to simulate the communication delay and its impact on VM performance, as well as network energy consumption. In addition, a generic model for a memory-bus of a server, including latency and energy consumption models for different memory frequencies. This allows simulating the memory delay and its influence on VM performance, as well as memory energy consumption. Communication-aware and energy-efficient consolidation for parallel applications to enable the dynamic discovery of communication patterns and reschedule VMs using migration based on the determined communication patterns. A novel dynamic pattern discovery technique is implemented, based on signal processing of network utilization of VMs instead of using the information from the hosts' virtual switches or initiation from VMs. The result shows that our proposed approach reduces the network's average utilization, achieves energy savings due to reducing the number of active switches, and provides better VM performance compared to CPU-based placement. Memory-aware VM consolidation for independent VMs, which exploits the diversity of VMs' memory access to balance memory-bus utilization of hosts. The proposed technique, Memory-bus Load Balancing (MLB), reactively redistributes VMs according to their utilization of a memory-bus using VM migration to improve the performance of the overall system. Furthermore, Dynamic Voltage and Frequency Scaling (DVFS) of the memory and the proposed MLB technique are combined to achieve better energy savings.
Permafrost, defined as ground that is frozen for at least two consecutive years, is a distinct feature of the terrestrial unglaciated Arctic. It covers approximately one quarter of the land area of the Northern Hemisphere (23,000,000 km²). Arctic landscapes, especially those underlain by permafrost, are threatened by climate warming and may degrade in different ways, including active layer deepening, thermal erosion, and development of rapid thaw features. In Siberian and Alaskan late Pleistocene ice-rich Yedoma permafrost, rapid and deep thaw processes (called thermokarst) can mobilize deep organic carbon (below 3 m depth) by surface subsidence due to loss of ground ice. Increased permafrost thaw could cause a feedback loop of global significance if its stored frozen organic carbon is reintroduced into the active carbon cycle as greenhouse gases, which accelerate warming and inducing more permafrost thaw and carbon release. To assess this concern, the major objective of the thesis was to enhance the understanding of the origin of Yedoma as well as to assess the associated organic carbon pool size and carbon quality (concerning degradability). The key research questions were:
- How did Yedoma deposits accumulate?
- How much organic carbon is stored in the Yedoma region?
- What is the susceptibility of the Yedoma region's carbon for future decomposition?
To address these three research questions, an interdisciplinary approach, including detailed field studies and sampling in Siberia and Alaska as well as methods of sedimentology, organic biogeochemistry, remote sensing, statistical analyses, and computational modeling were applied. To provide a panarctic context, this thesis additionally includes results both from a newly compiled northern circumpolar carbon database and from a model assessment of carbon fluxes in a warming Arctic.
The Yedoma samples show a homogeneous grain-size composition. All samples were poorly sorted with a multi-modal grain-size distribution, indicating various (re-) transport processes. This contradicts the popular pure loess deposition hypothesis for the origin of Yedoma permafrost. The absence of large-scale grinding processes via glaciers and ice sheets in northeast Siberian lowlands, processes which are necessary to create loess as material source, suggests the polygenetic origin of Yedoma deposits.
Based on the largest available data set of the key parameters, including organic carbon content, bulk density, ground ice content, and deposit volume (thickness and coverage) from Siberian and Alaskan study sites, this thesis further shows that deep frozen organic carbon in the Yedoma region consists of two distinct major reservoirs, Yedoma deposits and thermokarst deposits (formed in thaw-lake basins). Yedoma deposits contain ~80 Gt and thermokarst deposits ~130 Gt organic carbon, or a total of ~210 Gt. Depending on the approach used for calculating uncertainty, the range for the total Yedoma region carbon store is ±75 % and ±20 % for conservative single and multiple bootstrapping calculations, respectively. Despite the fact that these findings reduce the Yedoma region carbon pool by nearly a factor of two compared to previous estimates, this frozen organic carbon is still capable of inducing a permafrost carbon feedback to climate warming. The complete northern circumpolar permafrost region contains between 1100 and 1500 Gt organic carbon, of which ~60 % is perennially frozen and decoupled from the short-term carbon cycle.
When thawed and reintroduced into the active carbon cycle, the organic matter qualities become relevant. Furthermore, results from investigations into Yedoma and thermokarst organic matter quality studies showed that Yedoma and thermokarst organic matter exhibit no depth-dependent quality trend. This is evidence that after freezing, the ancient organic matter is preserved in a state of constant quality. The applied alkane and fatty-acid-based biomarker proxies including the carbon-preference and the higher-land-plant-fatty-acid indices show a broad range of organic matter quality and thus no significantly different qualities of the organic matter stored in thermokarst deposits compared to Yedoma deposits. This lack of quality differences shows that the organic matter biodegradability depends on different decomposition trajectories and the previous decomposition/incorporation history. Finally, the fate of the organic matter has been assessed by implementing deep carbon pools and thermokarst processes in a permafrost carbon model. Under various warming scenarios for the northern circumpolar permafrost region, model results show a carbon release from permafrost regions of up to ~140 Gt and ~310 Gt by the years 2100 and 2300, respectively. The additional warming caused by the carbon release from newly-thawed permafrost contributes 0.03 to 0.14°C by the year 2100. The model simulations predict that a further increase by the 23rd century will add 0.4°C to global mean surface air temperatures.
In conclusion, Yedoma deposit formation during the late Pleistocene was dominated by water-related (alluvial/fluvial/lacustrine) as well as aeolian processes under periglacial conditions. The circumarctic permafrost region, including the Yedoma region, contains a substantial amount of currently frozen organic carbon. The carbon of the Yedoma region is well-preserved and therefore available for decomposition after thaw. A missing quality-depth trend shows that permafrost preserves the quality of ancient organic matter. When the organic matter is mobilized by deep degradation processes, the northern permafrost region may add up to 0.4°C to the global warming by the year 2300.
Organische Halbleiter besitzen neue, bemerkenswerte Materialeigenschaften, die sie für die grundlegende Forschung wie auch aktuelle technologische Entwicklung (bsw. org. Leuchtdioden, org. Solarzellen) interessant werden lassen. Aufgrund der starken konformative Freiheit der konjugierten Polymerketten führt die Vielzahl der möglichen Anordnungen und die schwache intermolekulare Wechselwirkung für gewöhnlich zu geringer struktureller Ordnung im Festkörper. Die Morphologie hat gleichzeitig direkten Einfluss auf die elektronische Struktur der organischen Halbleiter, welches sich meistens in einer deutlichen Reduktion der Ladungsträgerbeweglichkeit gegenüber den anorganischen Verwandten zeigt. So stellt die Beweglichkeit der Ladungen im Halbleiter einen der limitierenden Faktoren für die Leistungsfähigkeit bzw. den Wirkungsgrad von funktionellen organischen Bauteilen dar. Im Jahr 2009 wurde ein neues auf Naphthalindiimid und Bithiophen basierendes Dornor/Akzeptor Copolymer vorgestellt [P(NDI2OD‑T2)], welches sich durch seine außergewöhnlich hohe Ladungsträgermobilität auszeichnet. In dieser Arbeit wird die Ladungsträgermobilität in P(NDI2OD‑T2) bestimmt, und der Transport durch eine geringe energetischer Unordnung charakterisiert. Obwohl dieses Material zunächst als amorph beschrieben wurde zeigt eine detaillierte Analyse der optischen Eigenschaften von P(NDI2OD‑T2), dass bereits in Lösung geordnete Vorstufen supramolekularer Strukturen (Aggregate) existieren. Quantenchemische Berechnungen belegen die beobachteten spektralen Änderungen. Mithilfe der NMR-Spektroskopie kann die Bildung der Aggregate unabhängig von optischer Spektroskopie bestätigt werden. Die Analytische Ultrazentrifugation an P(NDI2OD‑T2) Lösungen legt nahe, dass sich die Aggregation innerhalb der einzelnen Ketten unter Reduktion des hydrodynamischen Radius vollzieht. Die Ausbildung supramolekularen Strukturen nimmt auch eine signifikante Rolle bei der Filmbildung ein und verhindert gleichzeitig die Herstellung amorpher P(NDI2OD‑T2) Filme. Durch chemische Modifikation der P(NDI2OD‑T2)-Kette und verschiedener Prozessierungs-Methoden wurde eine Änderung des Kristallinitätsgrades und gleichzeitig der Orientierung der kristallinen Domänen erreicht und mittels Röntgenbeugung quantifiziert. In hochauflösenden Elektronenmikroskopie-Messungen werden die Netzebenen und deren Einbettung in die semikristallinen Strukturen direkt abgebildet. Aus der Kombination der verschiedenen Methoden erschließt sich ein Gesamtbild der Nah- und Fernordnung in P(NDI2OD‑T2). Über die Messung der Elektronenmobilität dieser Schichten wird die Anisotropie des Ladungstransports in den kristallographischen Raumrichtungen von P(NDI2OD‑T2) charakterisiert und die Bedeutung der intramolekularen Wechselwirkung für effizienten Ladungstransport herausgearbeitet. Gleichzeitig wird deutlich, wie die Verwendung von größeren und planaren funktionellen Gruppen zu höheren Ladungsträgermobilitäten führt, welche im Vergleich zu klassischen semikristallinen Polymeren weniger sensitiv auf die strukturelle Unordnung im Film sind.
Despite remarkable progress made in the past century, which has revolutionized our understanding of the universe, there are numerous open questions left in theoretical physics. Particularly important is the fact that the theories describing the fundamental interactions of nature are incompatible. Einstein's theory of general relative describes gravity as a dynamical spacetime, which is curved by matter and whose curvature determines the motion of matter. On the other hand we have quantum field theory, in form of the standard model of particle physics, where particles interact via the remaining interactions - electromagnetic, weak and strong interaction - on a flat, static spacetime without gravity. A theory of quantum gravity is hoped to cure this incompatibility by heuristically replacing classical spacetime by quantum spacetime'. Several approaches exist attempting to define such a theory with differing underlying premises and ideas, where it is not clear which is to be preferred. Yet a minimal requirement is the compatibility with the classical theory, they attempt to generalize. Interestingly many of these models rely on discrete structures in their definition or postulate discreteness of spacetime to be fundamental. Besides the direct advantages discretisations provide, e.g. permitting numerical simulations, they come with serious caveats requiring thorough investigation: In general discretisations break fundamental diffeomorphism symmetry of gravity and are generically not unique. Both complicates establishing the connection to the classical continuum theory. The main focus of this thesis lies in the investigation of this relation for spin foam models. This is done on different levels of the discretisation / triangulation, ranging from few simplices up to the continuum limit. In the regime of very few simplices we confirm and deepen the connection of spin foam models to discrete gravity. Moreover, we discuss dynamical, e.g. diffeomorphism invariance in the discrete, to fix the ambiguities of the models. In order to satisfy these conditions, the discrete models have to be improved in a renormalisation procedure, which also allows us to study their continuum dynamics. Applied to simplified spin foam models, we uncover a rich, non--trivial fixed point structure, which we summarize in a phase diagram. Inspired by these methods, we propose a method to consistently construct the continuum theory, which comes with a unique vacuum state.
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.
Characterization of drought tolerance in potato cultivars for identification of molecular markers
(2014)
Galaxies are observational probes to study the Large Scale Structure. Their gravitational motions are tracers of the total matter density and therefore of the Large Scale Structure. Besides, studies of structure formation and galaxy evolution rely on numerical cosmological simulations. Still, only one universe observable from a given position, in time and space, is available for comparisons with simulations. The related cosmic variance affects our ability to interpret the results. Simulations constrained by observational data are a perfect remedy to this problem. Achieving such simulations requires the projects Cosmic flows and CLUES. Cosmic flows builds catalogs of accurate distance measurements to map deviations from the expansion. These measures are mainly obtained with the galaxy luminosity-rotation rate correlation. We present the calibration of that relation in the mid-infrared with observational data from Spitzer Space Telescope. Resulting accurate distance estimates will be included in the third catalog of the project. In the meantime, two catalogs up to 30 and 150 Mpc/h have been released. We report improvements and applications of the CLUES' method on these two catalogs. The technique is based on the constrained realization algorithm. The cosmic displacement field is computed with the Zel'dovich approximation. This latter is then reversed to relocate reconstructed three-dimensional constraints to their precursors' positions in the initial field. The size of the second catalog (8000 galaxies within 150 Mpc/h) highlighted the importance of minimizing the observational biases. By carrying out tests on mock catalogs, built from cosmological simulations, a method to minimize observational bias can be derived. Finally, for the first time, cosmological simulations are constrained solely by peculiar velocities. The process is successful as resulting simulations resemble the Local Universe. The major attractors and voids are simulated at positions approaching observational positions by a few megaparsecs, thus reaching the limit imposed by the linear theory.
Diese Arbeit befasst sich mit den sogenannten relativähnlichen Sätzen im Frühneuhochdeutschen und leistet somit einen Beitrag zur Subordinationsforschung des älteren Deutsch. Relativähnliche Sätze sind formal durch ein satzinitiales anaphorisches d-Element und die Endstellung des finiten Verbs gekennzeichnet. Semantisch gesehen beziehen sie sich auf den vorangehenden Satz als Ganzes, indem sie ihn in bestimmter Weise weiterführen oder kommentieren. In der bisherigen Forschung werden diese Sätze satztypologisch als Hauptsätze mit Verbendstellung analysiert (vgl. dazu Maurer 1926, Behaghel 1932 und Lötscher 2000). Nach der ausführlichen Diskussion der formalen Abhängigkeitsmarker im älteren Deutsch sowie anhand einer umfangreichen korpusbasierten Untersuchung wird in dieser Arbeit gezeigt, dass relativähnliche Sätze im Frühneuhochdeutschen auch als abhängige Sätze - analog zu den weiterführenden Relativsätzen im Gegenwartsdeutschen - analysiert werden können. Die weiterführenden Relativsätze im Gegenwartsdeutschen enthalten satzinitial auch ein anaphorisches Element, das sich auf das Gesagte in dem vorangehenden Satz bezieht. Verbendstellung weisen sie ebenfalls auf (mehr zur Grammatik der weiterführenden Relativsätze vgl. insb. Brandt 1990 und Holler 2005). Über die Untersuchung relativähnlicher Sätze hinaus befasst sich diese Arbeit ausführlich mit formalen Abhängigkeitsmarkern des älteren Deutsch, wie Verbendstellung, Einleiter und afinite Konstruktion.
The purpose of this thesis is to develop an automated inversion scheme to derive point and finite source parameters for weak earthquakes, here intended with the unusual meaning of earthquakes with magnitudes at the limit or below the bottom magnitude threshold of standard source inversion routines. The adopted inversion approaches entirely rely on existing inversion software, the methodological work mostly targeting the development and tuning of optimized inversion flows. The resulting inversion scheme is tested for very different datasets, and thus allows the discussion on the source inversion problem at different scales. In the first application, dealing with mining induced seismicity, the source parameters determination is addressed at a local scale, with source-sensor distance of less than 3 km. In this context, weak seismicity corresponds to event below magnitude MW 2.0, which are rarely target of automated source inversion routines. The second application considers a regional dataset, namely the aftershock sequence of the 2010 Maule earthquake (Chile), using broadband stations at regional distances, below 300 km. In this case, the magnitude range of the target aftershocks range down to MW 4.0. This dataset is here considered as a weak seismicity case, since the analysis of such moderate seismicity is generally investigated only by moment tensor inversion routines, with no attempt to resolve source duration or finite source parameters. In this work, automated multi-step inversion schemes are applied to both datasets with the aim of resolving point source parameters, both using double couple (DC) and full moment tensor (MT) models, source duration and finite source parameters. A major result of the analysis of weaker events is the increased size of resulting moment tensor catalogues, which interpretation may become not trivial. For this reason, a novel focal mechanism clustering approach is used to automatically classify focal mechanisms, allowing the investigation of the most relevant and repetitive rupture features. The inversion of the mining induced seismicity dataset reveals the repetitive occurrence of similar rupture processes, where the source geometry is controlled by the shape of the mined panel. Moreover, moment tensor solutions indicate a significant contribution of tensile processes. Also the second application highlights some characteristic geometrical features of the fault planes, which show a general consistency with the orientation of the slab. The additional inversion for source duration allowed to verify the empirical correlation for moment normalized earthquakes in subduction zones among a decreasing rupture duration with increasing source depth, which was so far only observed for larger events.
Polypeptoid block coloymers
(2014)