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Pressure distribution to the distal biceps tendon at the radial tuberosity: a biomechanical study
(2020)
Purpose
Mechanical impingement at the narrow radioulnar space of the tuberosity is believed to be an etiological factor in the injury of the distal biceps tendon. The aim of the study was to compare the pressure distribution at the proximal radioulnar space between 2 fixation techniques and the intact state.
Methods
Six right arms and 6 left arms from 5 female and 6 male frozen specimens were used for this study. A pressure transducer was introduced at the height of the radial tuberosity with the intact distal biceps tendon and after 2 fixation methods: the suture-anchor and the cortical button technique. The force (N), maximum pressure (kPa) applied to the radial tuberosity, and the contact area (mm²) of the radial tuberosity with the ulna were measured and differences from the intact tendon were detected from 60° supination to 60° pronation in 15° increments with the elbow in full extension and in 45° and 90° flexion of the elbow.
Results
With the distal biceps tendon intact, the pressures during pronation were similar regardless of extension and flexion and were the highest at 60° pronation with 90° elbow flexion (23.3 ± 53.5 kPa). After repair of the tendon, the mean peak pressure, contact area, and total force showed an increase regardless of the fixation technique. Highest peak pressures were found using the cortical button technique at 45° flexion of the elbow and 60° pronation. These differences were significantly different from the intact tendon. The contact area was significantly larger in full extension and 15°, 30°, and 60° pronation using the cortical button technique.
Conclusions
Pressures on the distal biceps tendon at the radial tuberosity increase during pronation, especially after repair of the tendon.
Clinical relevance
Mechanical impingement could play a role in both the etiology of primary distal biceps tendon ruptures and the complications occurring after fixation of the tendon using certain techniques.
We present and discuss an exploration of the possibilities and properties of 3D printing with a printing space of 1 cubic meter, and how those can be integrated into architectural education through an experimental design and research course with students of architecture.We expand on issues presented at the eCAADe conference 2017 in Rome [Ref 6] by increasing the complexity and size of our prints, printing not a model to scale, but a full scale funtional prototype of a usable architectural object: A coffee bar.
Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability.
The problem of fair and privacy-preserving ordered set reconciliation arises in a variety of applications like auctions, e-voting, and appointment reconciliation. While several multi-party protocols have been proposed that solve this problem in the semi-honest model, there are no multi-party protocols that are secure in the malicious model so far. In this paper, we close this gap. Our newly proposed protocols are shown to be secure in the malicious model based on a variety of novel non-interactive zero-knowledge-proofs. We describe the implementation of our protocols and evaluate their performance in comparison to protocols solving the problem in the semi-honest case.
Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.
During the Covid-19 pandemic, vocational colleges, universities of applied science and technical universities often had to cancel laboratory sessions requiring students’ attendance. These above of all are of decisive importance in order to give learners an understanding of theory through practical work.This paper is a contribution to the implementation of distance learning for laboratory work applicable for several upper secondary educational facilities. Its aim is to provide a paradigm for hybrid teaching to analyze and control a non-linear system depicted by a tank model. For this reason, we redesign a full series of laboratory sessions on the basis of various challenges. Thus, it is suitable to serve different reference levels of the European Qualifications Framework (EQF).We present problem-based learning through online platforms to compensate the lack of a laboratory learning environment. With a task deduced from their future profession, we give students the opportunity to develop own solutions in self-defined time intervals. A requirements specification provides the framework conditions in terms of time and content for students having to deal with the challenges of the project in a self-organized manner with regard to inhomogeneous previous knowledge. If the concept of Complete Action is introduced in classes before, they will automatically apply it while executing the project.The goal is to combine students’ scientific understanding with a procedural knowledge. We suggest a series of remote laboratory sessions that combine a problem formulation from the subject area of Measurement, Control and Automation Technology with a project assignment that is common in industry by providing extracts from a requirements specification.