9,435 research outputs found
Oskar Becker
No full textAnalisi dell'estetica di Oskare Becker e dei suoi legami con Schelling e Solger
The Past, Present and Future of Organizational Routines:Introduction to the Handbook of Organizational Routines
No full textThe Past, Present and Future of Organizational Routines:Introduction to the Handbook of Organizational Routines
No full textVegetation-environment relationships in a heavy metal-dry grassland complex
No full textHeavy-metal content is assumed to be the most important edaphic factor that determines vegetation composition on contaminated soil. We compared the effects of heavy metals on species composition and species richness in the heavy metal-dry grassland complex of the Bottendorf Hills (Central Germany) with those of other environmental factors. Based on 206 releves, we distinguished nine communities of the classes Koelerio-Corynephoretea and Festuco-Brometea. Four communities in which the metallophytes Armeria maritima subsp. halleri and Minuartia verna subsp. hercynica occurred with high frequency were classified as heavy metal subassociations of four different dry grassland associations because of the dominance of dry grassland species. We measured the soil content of copper, zinc and lead, and the carbonate content, C/N ratio, pH and conductivity of the soil, soil depth and incident radiation per site. The first axis resulting from a DCA was positively correlated with the cover and height of the herb layer, the soil depth and soil carbonate content, and negatively with the soil content of copper, the proportion of rocks, the soil C/N ratio and incident radiation per site. The number of vascular plants, bryophyte and lichen species per plot increased with pH up to 7.5 and then decreased slightly. Species richness increased with carbonate content and conductivity of the soil and decreased with the soil C/N ratio. Heavy metal content of the soil and species richness were not correlated. The occurrence of the metallophytes was strongly related to the copper content of the soil. In conclusion our study has shown that heavy metal content is not necessarily the main factor determining the total composition and richness of grasslands on soil containing heavy metals. Heavy metal grasslands are not necessarily floristically distinct from "normal" dry grasslands
How to Avoid Innovation Competence Loss in R&D Outsourcing
Full text linkCompanies developing complex products face a crucial dilemma: the benefits of research and development (R&D) outsourcing such as lower costs, access to specialist knowledge, or shorter development lead times often have negative consequences for competence development due to the loss of opportunities for learning by doing. Having experienced the problems of outsourcing R&D, Fiat developed a novel organizational solution that offers new insights as to how firms can organize R&D to protect against innovation competence loss in R&D outsourcing
Small-Molecule-Induced Soluble Oligomers of α-Synuclein with Helical Structure
Full text linkAccumulation of α-synuclein (αSyn) aggregates constitutes the hallmark of synucleinopathies including Parkinson's disease. However, many steps from the innocuous, monomeric αSyn toward misfolded oligomers and fibrillar species remain unclear. Here, we show that αSyn can form in solution α-helical oligomers, which are off-pathway to fibrillization, through interaction with the tetrapyrrole phthalocyanine tetrasulfonate. Chemical cross-linking combined with mass spectrometry reveals a large number of intermolecular cross-links along the entire αSyn sequence in the phthalocyanine tetrasulfonate-stabilized αSyn oligomers. Our study suggests that stabilization of structured oligomers by small molecules provides a viable strategy to interfere with αSyn fibrillization.Fil: Fonseca Ornelas, Luis. Max Planck Institute for Biophysical Chemistry; AlemaniaFil: Schmidt, Carla. Martin Luther University Halle-Wittenberg; AlemaniaFil: Camacho Zarco, Aldo R.. German Center for Neurodegenerative Diseases ; AlemaniaFil: Fernandez, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones para el Descubrimiento de Fármacos de Rosario. Universidad Nacional de Rosario. Instituto de Investigaciones para el Descubrimiento de Fármacos de Rosario; Argentina. Max Planck Institute for Biophysical Chemistry; AlemaniaFil: Becker, Stefan. Max Planck Institute for Biophysical Chemistry; AlemaniaFil: Zweckstetter, Markus. Max Planck Institute for Biophysical Chemistry; Alemania. German Center for Neurodegenerative Diseases ; Alemania. Universität Göttingen; Alemani
Tatjana Bartsch, Markus Becker, Horst Bredekamp & Charlotte Schreiter (Ed.), Das Originale der Kopie. Kopien als Produkte und Medien der Transformation von Antike, (Transformationen der Antike, 17) 2010
No full textBalty Jean-Charles. Tatjana Bartsch, Markus Becker, Horst Bredekamp & Charlotte Schreiter (Ed.), Das Originale der Kopie. Kopien als Produkte und Medien der Transformation von Antike, (Transformationen der Antike, 17) 2010. In: L'antiquité classique, Tome 80, 2011. pp. 676-678
Active Learning - An Explicit Treatment of Unreliable Parameters
Full text linkInstitute for Communicating and Collaborative SystemsActive learning reduces annotation costs for supervised learning by concentrating labelling efforts on the most informative data. Most active learning methods assume that the model structure is fixed in advance and focus upon improving parameters within
that structure. However, this is not appropriate for natural language processing where the model structure and associated parameters are determined using labelled data. Applying traditional active learning methods to natural language processing can fail to produce expected reductions in annotation cost. We show that one of the reasons for this problem is that active learning can only select examples which are already covered by the model. In this thesis, we better tailor active learning to the need of natural language processing as follows. We formulate the Unreliable Parameter Principle:
Active learning should explicitly and additionally address unreliably trained
model parameters in order to optimally reduce classification error. In order
to do so, we should target both missing events and infrequent events.
We demonstrate the effectiveness of such an approach for a range of natural language
processing tasks: prepositional phrase attachment, sequence labelling, and syntactic
parsing. For prepositional phrase attachment, the explicit selection of unknown prepositions significantly improves coverage and classification performance for all examined active learning methods. For sequence labelling, we introduce a novel active learning method which explicitly targets unreliable parameters by selecting sentences with many unknown words and a large number of unobserved transition probabilities. For parsing, targeting unparseable sentences significantly improves coverage and f-measure in active learning
Innovation routines:Exploring the role of procedures and stable behaviour patterns in innovation
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