A New Optimization Technique for Improving Resource Exploitation and Critical Path Minimization

This paper presents a novel approach to algebraic optimization of data-flow graphs in the domain of computationally intensive applications. The presented approach is based upon the paradigm of simulated evolution which has been proven to be a powerful method for solving large non-linear optimization problems. We introduce a genetic algorithm with a new chromosomal representation of data-flow graphs that serves as a basis for preserving the correctness of algebraic transformations and allows an efficient implementation of the genetic operators. Furthermore, we introduce a new class of hardware-related transformation rules which for the first time allow to take existing component libraries into account. The efficiency of our method is demonstrated by encouraging experimental results for several standard benchmarks

Introducing Complex Components into Architectural Synthesis

In this paper, we extend the set of library components which are usually considered in architectural synthesis by components with built-in chaining. For such components, the result of some internally computed arithmetic function is made available as an argument to some other function through a local connection. These components can be used to implement chaining in a data-path in a single component. Components with built-in chaining are combinatorial circuits. They correspond to ``complex gates in logic synthesis. If compared to implementations with several components, components with built-in chaining usually provide a denser layout, reduced power consumption, and a shorter delay time. Multiplier/accumulators are the most prominent example of such components. Such components require new approaches for library mapping in architectural synthesis. In this paper, we describe an IP-based approach taken in our OSCAR synthesis system

Predicting The Resale Asking Price Of Wind Turbines Using A ML Model Trained On Data From An Online Resale Platform

Around half of the currently 30,000 active wind turbines in Germany will reach the end of their service life by 2030, which is generally defined by the manufacturer as 20 years of operation. The most common strategy for the subsequent use of a wind farm is repowering, provided this is (legally) possible at the respective location. One option for dealing with old turbines is to resell them. At the time of repowering, in Germany after an average of around 17 years, the wind turbines usually still have a remaining operating time of several years before critical parts such as generators fail. This article presents a machine learning model for predicting the resale value of used wind turbines. This model can be used to approximately predict the resale value of comparable wind turbines based on certain input parameters such as the power output or the age of the wind turbines. The model was trained using an adjusted data set from an online trading platform for wind turbines. The necessary pre-processing steps such as the removal of extreme outlier values and the addition or replacement of missing or incorrect wind turbinespecific data from a second data source using a self-developed matching algorithm are presented. Finally, the prediction accuracy of different ML algorithms is tested using test data to find the best method for predicting the resale value of wind turbines

Built-in Chaining: Introducing Complex Components into Architectural Synthesis

Abstract-In this paper, we extend the set of library components which are usually considered in architectural synthesis by components with built-in chaining. For such components, the result of some internally computed arithmetic function is made available as an argument to some other function through a local connection. These components can be used to implement chaining in a datapath in a single component. Components with built-in chaining are combinatorial circuits. They correspond to "complex gates" in logic synthesis. If compared to implementations with several components, components with built-in chaining usually provide a denser layout, reduced power consumption, and a shorter delay time. Multiplier/accumulators are the most prominent example of such components. Such components require new approaches for library mapping in architectural synthesis. In this paper, we describe an IP-based approach taken in our OSCAR synthesis system

Association of Caldendrin splice isoforms with secretory vesicles in neurohypophyseal axons and the pituitary

AbstractCaldendrin is a neuronal calcium-binding protein, which is highly enriched in the postsynaptic density fraction and exhibits a prominent somato-dendritic distribution in brain. Two additional splice variants derive from the caldendrin gene, which have unrelated N-termini and were previously only detected in the retina. We now show that these isoforms are present in neurohypophyseal axons and on secretory granules of endocrine cells. In light of the described interaction of the Caldendrin C-terminus with Q-type Cav2.1 calcium channels these data suggest that this interaction takes place in neurohypophyseal axons and pituitary cells indicating functions of the short splice variants in triggering Ca2+ transients to a vesicular target interaction

Caldendrin–Jacob: A Protein Liaison That Couples NMDA Receptor Signalling to the Nucleus

NMDA (N-methyl-D-aspartate) receptors and calcium can exert multiple and very divergent effects within neuronal cells, thereby impacting opposing occurrences such as synaptic plasticity and neuronal degeneration. The neuronal Ca2+ sensor Caldendrin is a postsynaptic density component with high similarity to calmodulin. Jacob, a recently identified Caldendrin binding partner, is a novel protein abundantly expressed in limbic brain and cerebral cortex. Strictly depending upon activation of NMDA-type glutamate receptors, Jacob is recruited to neuronal nuclei, resulting in a rapid stripping of synaptic contacts and in a drastically altered morphology of the dendritic tree. Jacob's nuclear trafficking from distal dendrites crucially requires the classical Importin pathway. Caldendrin binds to Jacob's nuclear localization signal in a Ca2+-dependent manner, thereby controlling Jacob's extranuclear localization by competing with the binding of Importin-α to Jacob's nuclear localization signal. This competition requires sustained synapto-dendritic Ca2+ levels, which presumably cannot be achieved by activation of extrasynaptic NMDA receptors, but are confined to Ca2+ microdomains such as postsynaptic spines. Extrasynaptic NMDA receptors, as opposed to their synaptic counterparts, trigger the cAMP response element-binding protein (CREB) shut-off pathway, and cell death. We found that nuclear knockdown of Jacob prevents CREB shut-off after extrasynaptic NMDA receptor activation, whereas its nuclear overexpression induces CREB shut-off without NMDA receptor stimulation. Importantly, nuclear knockdown of Jacob attenuates NMDA-induced loss of synaptic contacts, and neuronal degeneration. This defines a novel mechanism of synapse-to-nucleus communication via a synaptic Ca2+-sensor protein, which links the activity of NMDA receptors to nuclear signalling events involved in modelling synapto-dendritic input and NMDA receptor–induced cellular degeneration

Kriterien für die Auswahl einer Softwarelösung für den Betrieb eines Repositoriums für Forschungsdaten

Die öffentliche Bereitstellung von Forschungsdaten zur Nachnutzung im Sinne von Open Science ist Bestandteil des Lebenszyklus von Forschungsdaten und erlangt zunehmende Relevanz. Eine zitierbare Veröffentlichung dieser Daten zeugt von einer transparenten Forschung, belegt die Forschungsleistung eines Forschenden sowie der jeweiligen Einrichtung und macht Forschung reproduzierbar und damit überprüfbar. Forschungsförderer erwarten bereits bei der Antragstellung die Dokumentation und Planung eines umsichtigen und nachhaltigen Umgangs mit Forschungsdaten, bspw. in Form eines Datenmanagementplans, der unter anderem Angaben zu geplanten Lizenzen für Forschungsdaten, Rechten an Daten etc. enthält. Die Umsetzung des Datenmanagementplans ist ein kontinuierlicher Prozess im Laufe eines Projekts und nicht auf eine Datenveröffentlichung zum Projektende hin beschränkt. Der Umgang mit Forschungsdaten wird unter anderem in den Richtlinien Guter Wissenschaftlicher Praxis[1], den Open-Access-Policies von Hochschulen, Forschungsinstituten und Forschungsförderern sowie in den “Data Policies” von Zeitschriften adressiert. Repositorien bilden das technische Grundgerüst für das Forschungsdatenmanagement, da sie den gesamten Prozess von der Übernahme über die Qualitätskontrolle bis hin zur zitierfähigen Veröffentlichung unterstützen. Softwarelösungen für Repositorien sind für unterschiedliche Zwecke und Einsatzszenarien verfügbar. Zu den verbreitetsten zählen beispielsweise Fedora, DSpace, MyCoRe, Islandora, EPrints, Dataverse, Rosetta, Archivematica und Invenio. Die Bestimmung von Kriterien für die Auswahl eines Repositoriums ist nicht trivial und es müssen neben Aspekten der Wirtschaftlichkeit, Skalierbarkeit und Funktionalität noch weitere Kriterien wie die Dokumentation, Verbreitung, Entwicklungsperspektive sowie das Daten- und Lizenzmodell berücksichtigt werden. Der Aufwand für die Erarbeitung eines Kriterienkatalogs darf nicht unterschätzt werden. Im Folgenden bezeichnet Repositorium eine Softwarelösung, die - eingebettet in eine Organisationsstruktur und gegebenenfalls im Kontext weiterer Systeme - Forschungsdaten übernimmt, verwaltet und publiziert. Daraus ergeben sich zwangsläufig Abhängigkeiten zur betreibenden organisatorischen Einheit und der grundlegenden technischen Infrastruktur für den Betrieb der Software und die Speicherung der Daten. In diesem Artikel werden verschiedene Aspekte präsentiert, die für den Auswahlprozess potentiell relevant sind. [1] Siehe auch Kodex der DFG zur guten wissenschaftlichen Praxis: https://www.dfg.de/foerderung/grundlagen_rahmenbedingungen/gwp