A note on stress-driven anisotropic diffusion and its role in active deformable media

We propose a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to use diffusion tensors directly coupled to mechanical stress. A proof-of-concept experiment and the proposed generalised reaction-diffusion-mechanics model reveal that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the experiment, the model, and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-assisted diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electrical feedback in actively deforming bio-materials such as the heart

The impact on innovation off-shoring on organizational adaptability

We analyze the effects of captive off-shoring of innovation activities on the firms’ ability to adapt their organizational processes and structures. Starting from complexity theory, we use three consecutive waves of the German part of the Community Innovation Survey to test our hypotheses. We find an inverted u-shape of innovation off-shoring on the effectiveness of organizational adaptability, implying an optimal threshold value of innovation off-shoring. This value is 11% for share of off-shored R&D, 15% for downstream innovation activities such as local market adaptation, and 34% for design activities. We also analyze several contingency variables. In particular we show that the costs of innovation off-shoring in terms of reduced organizational adaptability are exacerbated by a strong focus on R&D and a strong embeddedness in on-shore networks. Smaller firms find it easier to deal with the management complexity induced by geographical dispersion of innovation activities because of their greater flexibility

Zur Entwicklung der Gewalt in Deutschland : Schwerpunkte: Jugendliche und Flüchtlinge als Täter und Opfer

Unter Mitarbeit von Prof. Dr. Thomas Mößle, Laura Beckmann und Eberhard Mecklenbur

An Efficient Similarity Digests Database Lookup -- a Logarithmic Divide and Conquer Approach

Investigating seized devices within digital forensics represents a challenging task due to the increasing amount of data. Common procedures utilize automated file identification, which reduces the amount of data an investigator has to examine manually. In the past years the research field of approximate matching arises to detect similar data. However, if n denotes the number of similarity digests in a database, then the lookup for a single similarity digest is of complexity of O(n). This paper presents a concept to extend existing approximate matching algorithms, which reduces the lookup complexity from O(n) to O(log(n)). Our proposed approach is based on the well-known divide and conquer paradigm and builds a Bloom filter-based tree data structure in order to enable an efficient lookup of similarity digests. Further, it is demonstrated that the presented technique is highly scalable operating a trade-off between storage requirements and computational efficiency. We perform a theoretical assessment based on recently published results and reasonable magnitudes of input data, and show that the complexity reduction achieved by the proposed technique yields a 220-fold acceleration of look-up costs

An Efficient Similarity Digests Database Lookup – A Logarithmic Divide & Conquer Approach

Investigating seized devices within digital forensics represents a challenging task due to the increasing amount of data. Common procedures utilize automated file identification, which reduces the amount of data an investigator has to examine manually. In the past years the research field of approximate matching arises to detect similar data. However, if n denotes the number of similarity digests in a database, then the lookup for a single similarity digest is of complexity of O(n). This paper presents a concept to extend existing approximate matching algorithms, which reduces the lookup complexity from O(n) to O(log(n)). Our proposed approach is based on the well-known divide and conquer paradigm and builds a Bloom filter-based tree data structure in order to enable an efficient lookup of similarity digests. Further, it is demonstrated that the presented technique is highly scalable operating a trade-off between storage requirements and computational efficiency. We perform a theoretical assessment based on recently published results and reasonable magnitudes of input data, and show that the complexity reduction achieved by the proposed technique yields a 2 20-fold acceleration of look-up costs

Auf der Suche nach dem Narrativ. Fritz Breithaupt erkundet das narrative Gehirn und übersieht eine Leerstelle

Rezension zu: Fritz Breithaupt: Das narrative Gehirn. Was unsere Neuronen erzählen. Berlin: Suhrkamp 2022. 368 S. EUR 28,-. ISBN 978-3-518-58778-

Auf der Suche nach dem Narrativ. Fritz Breithaupt erkundet das narrative Gehirn und übersieht eine Leerstelle

Review of: Fritz Breithaupt: Das narrative Gehirn. Was unsere Neuronen erzählen. Berlin: Suhrkamp 2022. 368 S. EUR 28,-. ISBN 978-3-518-58778-