Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

IMU-based joint angle measurement for gait analysis.

Abstract: This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°.

Reversible amorphization and the catalytically active state of crystalline Co3O4 during oxygen evolution

Abstract: Water splitting catalysed by earth-abundant materials is pivotal for global-scale production of non-fossil fuels, yet our understanding of the active catalyst structure and reactivity is still insufficient. Here we report on the structurally reversible evolution of crystalline Co3O4 electrocatalysts during oxygen evolution reaction identified using advanced in situ X-ray techniques. At electrode potentials facilitating oxygen evolution, a sub-nanometre shell of the Co3O4 is transformed into an X-ray amorphous CoOx(OH)y which comprises di-μ-oxo-bridged Co(3+/4+) ions. Unlike irreversible amorphizations, here, the formation of the catalytically-active layer is reversed by re-crystallization upon return to non-catalytic electrode conditions. The Co3O4 material thus combines the stability advantages of a controlled, stable crystalline material with high catalytic activity, thanks to the structural flexibility of its active amorphous oxides. We propose that crystalline oxides may be tailored for generating reactive amorphous surface layers at catalytic potentials, just to return to their stable crystalline state under rest conditions.

The influence of relational competencies on supply chain resilience: a relational view

Abstract: Purpose – The purpose of this research is to explore the resilience domain, which is important in the field of supply chain management; it investigates the effects relational competencies have for resilience and the effect resilience, in turn, has on a supply chain ' s customer value. Design/methodology/approach – The research is empirical in nature and employs a confirmatory approach that builds on the relational view as a primary theoretical foundation. It utilizes survey data collected from manufacturing firms from three countries, which is analyzed using structural equation modeling. Findings – It is found that communicative and cooperative relationships have a positive effect on resilience, while integration does not have a significant effect. It is also found that improved resilience, obtained by investing in agility and robustness, enhances a supply chain ' s customer value. Practical implications – Some findings contrast the expectations derived from theory. Particularly, practitioners can learn t...

Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data

Abstract: Federated learning allows multiple parties to jointly train a deep learning model on their combined data, without any of the participants having to reveal their local data to a centralized server. This form of privacy-preserving collaborative learning, however, comes at the cost of a significant communication overhead during training. To address this problem, several compression methods have been proposed in the distributed training literature that can reduce the amount of required communication by up to three orders of magnitude. These existing methods, however, are only of limited utility in the federated learning setting, as they either only compress the upstream communication from the clients to the server (leaving the downstream communication uncompressed) or only perform well under idealized conditions, such as i.i.d. distribution of the client data, which typically cannot be found in federated learning. In this article, we propose sparse ternary compression (STC), a new compression framework that is specifically designed to meet the requirements of the federated learning environment. STC extends the existing compression technique of top- $k$ gradient sparsification with a novel mechanism to enable downstream compression as well as ternarization and optimal Golomb encoding of the weight updates. Our experiments on four different learning tasks demonstrate that STC distinctively outperforms federated averaging in common federated learning scenarios. These results advocate for a paradigm shift in federated optimization toward high-frequency low-bitwidth communication, in particular in the bandwidth-constrained learning environments.

Riparian plant litter quality increases with latitude

Abstract: Plant litter represents a major basal resource in streams, where its decomposition is partly regulated by litter traits. Litter-trait variation may determine the latitudinal gradient in decomposition in streams, which is mainly microbial in the tropics and detritivore-mediated at high latitudes. However, this hypothesis remains untested, as we lack information on large-scale trait variation for riparian litter. Variation cannot easily be inferred from existing leaf-trait databases, since nutrient resorption can cause traits of litter and green leaves to diverge. Here we present the first global-scale assessment of riparian litter quality by determining latitudinal variation (spanning 107°) in litter traits (nutrient concentrations; physical and chemical defences) of 151 species from 24 regions and their relationships with environmental factors and phylogeny. We hypothesized that litter quality would increase with latitude (despite variation within regions) and traits would be correlated to produce ‘syndromes’ resulting from phylogeny and environmental variation. We found lower litter quality and higher nitrogen:phosphorus ratios in the tropics. Traits were linked but showed no phylogenetic signal, suggesting that syndromes were environmentally determined. Poorer litter quality and greater phosphorus limitation towards the equator may restrict detritivore-mediated decomposition, contributing to the predominance of microbial decomposers in tropical streams.