ALBERT

Description: Growth of several green and red algae was consistently enhanced under high CO2 conditions, but was statistically different only in the intertidal green alga Ulva lactuca and in the red alga Chondrus crispus only under elevated temperatures. The corresponding photosynthetic rates exhibited the same trend, but differences were insignificant. The two brown algae Fucus vesiculosus and Laminaria hyperborea showed opposite responsestowards CO2 increase: While Laminaria hyperborea enhanced growth andphotosynthesis under elevated CO2 conditions, Fucus vesiculosus unexpectedly had lower growth and photosynthesis rates under this condition.The elemental composition (C/N/P) of Fucus vesiculosus in different CO2 conditions did not change and thus no changes in the nutritional quality of the brown seaweed were detected. Accordingly, there were noimplications for the common mesoherbivore Idotea baltica. The isopod feeding on algae from different CO2 treatments did not show differences in food consumption and respiration rates.

Description: We propose a framework for the exact probabilistic analysis of window-based pattern matching algorithms, such as Boyer–Moore, Horspool, Backward DAWG Matching, Backward Oracle Matching, and more. In particular, we develop an algorithm that efficiently computes the distribution of a pattern matching algorithm’s running time cost (such as the number of text character accesses) for any given pattern in a random text model. Text models range from simple uniform models to higher-order Markov models or hidden Markov models (HMMs). Furthermore, we provide an algorithm to compute the exact distribution of differences in running time cost of two pattern matching algorithms. Methodologically, we use extensions of finite automata which we call deterministic arithmetic automata (DAAs) and probabilistic arithmetic automata (PAAs) [1]. Given an algorithm, a pattern, and a text model, a PAA is constructed from which the sought distributions can be derived using dynamic programming. To our knowledge, this is the first time that substring- or suffix-based pattern matching algorithms are analyzed exactly by computing the whole distribution of running time cost. Experimentally, we compare Horspool’s algorithm, Backward DAWG Matching, and Backward Oracle Matching on prototypical patterns of short length and provide statistics on the size of minimal DAAs for these computations.

Description: We propose a framework for the exact probabilistic analysis of window-based pattern matching algorithms, such as Boyer–Moore, Horspool, Backward DAWG Matching, Backward Oracle Matching, and more. In particular, we develop an algorithm that efficiently computes the distribution of a pattern matching algorithm’s running time cost (such as the number of text character accesses) for any given pattern in a random text model. Text models range from simple uniform models to higher-order Markov models or hidden Markov models (HMMs). Furthermore, we provide an algorithm to compute the exact distribution of differences in running time cost of two pattern matching algorithms. Methodologically, we use extensions of finite automata which we call deterministic arithmetic automata (DAAs) and probabilistic arithmetic automata (PAAs) [1]. Given an algorithm, a pattern, and a text model, a PAA is constructed from which the sought distributions can be derived using dynamic programming. To our knowledge, this is the first time that substring- or suffix-based pattern matching algorithms are analyzed exactly by computing the whole distribution of running time cost. Experimentally, we compare Horspool’s algorithm, Backward DAWG Matching, and Backward Oracle Matching on prototypical patterns of short length and provide statistics on the size of minimal DAAs for these computations.

Description: In the last 15 years, the use of doubly fed induction machines in modern variable-speed wind turbines has increased rapidly. This development has been driven by the cost reduction as well as the low-loss generation of Insulated Gate Bipolar Transistors (IGBT). According to new grid code requirements, wind turbines must remain connected to the grid during grid disturbances. Moreover, they must also contribute to voltage support during and after grid faults. The crowbar system is essential to avoid the disconnection of the doubly fed induction wind generators from the network during faults. The insertion of the crowbar in the rotor circuits for a short period of time enables a more efficient terminal voltage control. As a general rule, the activation and the deactivation of the crowbar system is based only on the DC-link voltage level of the back-to-back converters. In this context, the authors discuss the critical rotor speed to analyze the instability of doubly fed induction generators during grid faults.

Description: Background: An ion mobility (IM) spectrometer coupled with a multi-capillary column (MCC) measures volatile organic compounds (VOCs) in the air or in exhaled breath. This technique is utilized in several biotechnological and medical applications. Each peak in an MCC/IM measurement represents a certain compound, which may be known or unknown. For clustering and classification of measurements, the raw data matrix must be reduced to a set of peaks. Each peak is described by its coordinates (retention time in the MCC and reduced inverse ion mobility) and shape (signal intensity, further shape parameters). This fundamental step is referred to as peak extraction. It is the basis for identifying discriminating peaks, and hence putative biomarkers, between two classes of measurements, such as a healthy control group and a group of patients with a confirmed disease. Current state-of-the-art peak extraction methods require human interaction, such as hand-picking approximate peak locations, assisted by a visualization of the data matrix. In a high-throughput context, however, it is preferable to have robust methods for fully automated peak extraction. Results: We introduce PEAX, a modular framework for automated peak extraction. The framework consists of several steps in a pipeline architecture. Each step performs a specific sub-task and can be instantiated by different methods implemented as modules. We provide open-source software for the framework and several modules for each step. Additionally, an interface that allows easy extension by a new module is provided. Combining the modules in all reasonable ways leads to a large number of peak extraction methods. We evaluate all combinations using intrinsic error measures and by comparing the resulting peak sets with an expert-picked one. Conclusions: Our software PEAX is able to automatically extract peaks from MCC/IM measurements within a few seconds. The automatically obtained results keep up with the results provided by current state-of-theart peak extraction methods. This opens a high-throughput context for the MCC/IM application field. Our software is available at http://www.rahmannlab.de/research/ims.

Description: In recent years, only a small number of publications have been presented addressing power system stability with the increased use of large-scale photovoltaic (PV) generation around the world. The focus of these publications was on classical stability problems, such as transient and small signal stability, without considering frequency stability. Nevertheless, with increased PV generation, its effects on system frequency response during contingencies can no longer be ignored, especially in the case of weakly interconnected networks or isolated power systems. This paper addresses the impacts of large scale PV generation on the frequency stability of power systems. The positive effects of deloaded PV power plants (PV-PPs) able to support system frequency recovery during the initial seconds after major contingencies are also examined. Because this type of frequency support is not covered by current definitions, a new terminology is proposed that includes the frequency response of inertia-less generation units immediately after major power imbalances. We refer to this type of frequency support as fast frequency response (FFR). Finally, a discussion is also presented regarding the applicability and pertinence of frequency-related grid requirements for PV-PPs in the case of real power systems. The investigation is based on the isolated power system of northern Chile. The obtained results indicate that in the case of major power imbalances, no significant effects arise on the system frequency response until PV penetration levels exceed approximately 20%. From a system security perspective, the problems arise for PV penetration levels of approximately 50%, in which case, the frequency response capability in PV-PPs would be justified during certain hours of the year.

Description: Chromatin remodeling complexes are known to modify chemical marks on histones or to induce conformational changes in the chromatin in order to regulate transcription. De novo dominant mutations in different members of the SWI/SNF chromatin remodeling complex have recently been described in individuals with Coffin–Siris (CSS) and Nicolaides–Baraitser (NCBRS) syndromes. Using a combination of whole-exome sequencing, NGS-based sequencing of 23 SWI/SNF complex genes, and molecular karyotyping in 46 previously undescribed individuals with CSS and NCBRS, we identified a de novo 1-bp deletion (c.677delG, p.Gly226Glufs*53) and a de novo missense mutation (c.914G〉T, p.Cys305Phe) in PHF6 in two individuals diagnosed with CSS. PHF6 interacts with the nucleosome remodeling and deacetylation (NuRD) complex implicating dysfunction of a second chromatin remodeling complex in the pathogenesis of CSS-like phenotypes. Altogether, we identified mutations in 60% of the studied individuals (28/46), located in the genes ARID1A, ARID1B, SMARCB1, SMARCE1 , SMARCA2, and PHF6 . We show that mutations in ARID1B are the main cause of CSS, accounting for 76% of identified mutations. ARID1B and SMARCB1 mutations were also found in individuals with the initial diagnosis of NCBRS. These individuals apparently belong to a small subset who display an intermediate CSS/NCBRS phenotype. Our proposed genotype-phenotype correlations are important for molecular screening strategies.

Description: : Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow. It is the first system to support the use of automatically inferred multiple named wildcards (or variables) in input and output filenames. Availability: http://snakemake.googlecode.com . Contact: johannes.koester@uni-due.de

Description: A novel optimization methodology consisting of finding the near optimal location of wind turbines (WTs) on a planned transmission network in a secure and cost-effective way is presented on this paper. While minimizing the investment costs of WTs, the algorithm allocates the turbines so that a desired wind power energy-penetration level is reached. The optimization considers both transmission security and power system stability constraints. The results of the optimization provide regulators with a support instrument to give proper signals to WT investors, in order to achieve secure and cost effective wind power network integration. The proposal is especially aimed at countries in the initial stage of wind power development, where the WT network integration process can still be influenced by policy-makers. The proposed methodology is validated with a real power system. Obtained results are compared with those generated from a business-as-usual (BAU) scenario, in which the WT network allocation is made according to existing WT projects. The proposed WT network allocation scheme not only reduces the total investment costs associated with a determined wind power energy target, but also improves power system stability.