Numerical-experimental observation of shape bistability of red blood cells flowing in a microchannel

Red blood cells flowing through capillaries assume a wide variety of different shapes owing to their high deformability. Predicting the realized shapes is a complex field as they are determined by the intricate interplay between the flow conditions and the membrane mechanics. In this work we construct the shape phase diagram of a single red blood cell with a physiological viscosity ratio flowing in a microchannel. We use both experimental in-vitro measurements as well as 3D numerical simulations to complement the respective other one. Numerically, we have easy control over the initial starting configuration and natural access to the full 3D shape. With this information we obtain the phase diagram as a function of initial position, starting shape and cell velocity. Experimentally, we measure the occurrence frequency of the different shapes as a function of the cell velocity to construct the experimental diagram which is in good agreement with the numerical observations. Two different major shapes are found, namely croissants and slippers. Notably, both shapes show coexistence at low (<1 mm/s) and high velocities (>3 mm/s) while in-between only croissants are stable. This pronounced bistability indicates that RBC shapes are not only determined by system parameters such as flow velocity or channel size, but also strongly depend on the initial conditions.Comment: 13 pages, 9 figures (main text). 13 pages, 31 figures (SI

Hierarchical Hybrid Monitoring for Autonomous Systems

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Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization

The use of distributed optimization in machine learning can be motivated either by the resulting preservation of privacy or the increase in computational efficiency. On the one hand, training data might be stored across multiple devices. Training a global model within a network where each node only has access to its confidential data requires the use of distributed algorithms. Even if the data is not confidential, sharing it might be prohibitive due to bandwidth limitations. On the other hand, the ever-increasing amount of available data leads to large-scale machine learning problems. By splitting the training process across multiple nodes its efficiency can be significantly increased. This paper aims to demonstrate how dual decomposition can be applied for distributed training of $K$-means clustering problems. After an overview of distributed and federated machine learning, the mixed-integer quadratically constrained programming-based formulation of the $K$-means clustering training problem is presented. The training can be performed in a distributed manner by splitting the data across different nodes and linking these nodes through consensus constraints. Finally, the performance of the subgradient method, the bundle trust method, and the quasi-Newton dual ascent algorithm are evaluated on a set of benchmark problems. While the mixed-integer programming-based formulation of the clustering problems suffers from weak integer relaxations, the presented approach can potentially be used to enable an efficient solution in the future, both in a central and distributed setting

The Impact of Individual Differences in Fine Motor Abilities on Wheelchair Control Behavior and Especially on Safety-Critical Collisions with Objects in the Surroundings

In order to significantly reduce the number of safety-critical collisions of wheelchair users with objects spread in their environment, a study has been conducted which relates wheelchair user's fine motor abilities with the collisions while driving through a standardized course in a realistic office environment. The conducted inferential statistics demonstrate that especially the participants' aiming capacity can sign significantly predict the collisions occurring while driving through the course. A graphical and qualitative analysis of these effects demonstrates in addition that specific maneuvering tasks influence this relationship and that especially driving next to an object without colliding requires a high level of aiming capacity. The results demonstrate the need to develop a wheelchair system which adapts its assistive functionality to the aiming capacity and the difficulty of the maneuvering task in order to provide as much help as necessary without risking the degradation of the wheelchair user's skills

An Integrated Monitor-Diagnosis-Reconfiguration Scheme for (Semi-) Autonomous Systems

A nested monitoring, diagnosis and reconfiguration (MDR) scheme is proposed for a Recursive Nested Behavior based Control structure (RNBC)constituting a generic system architecture for (semi-) autonomous mobile systems. Each behavior layer within the RNBC structure is associated with a MDR schema, which is responsible to ensure the dependability of every single layer. An online dependability measurement and diagnosis procedure is integrated into monitor and diagnosis blocks under consideration of performance and safety acceptability factors. The reconfiguration blocks within the MDR-scheme switch from components with unacceptable behavior to redundant components, which may have degraded performance but more robust and safe behavior. The MDR blocks at each layer are nested through unified interfaces in order to utilize the distributed modeling of system behavior and to facilitate the system design and implementation process. In a small case study the MDR scheme is demonstrated for an assistant wheelchair on the body velocity control and axis velocity control levels. Simulation results show the feasibility and effectiveness of the approach

Dependable System Design for Assistance Systems for Electrically Powered Wheelchairs

In this paper a system design approach is proposed, which is based on a user needs assessment and a flexible and adaptable architecture for dependable system integration. The feasibility of the approach is shown on the example of an assistance system for electrically powered wheelchairs. The system requirements correspond to the cognitive and motor abilities of the wheelchair users. For the wheelchair system built up based on a commercial powered wheelchair several behaviors have been realized such as collision avoidance, local navigation and path planning well known from robotic systems, which are enhanced by human-interfacing components. Furthermore, the system design will be high lighted which is based on robotic systems engineering. Due to the fundamental properties of the system architecture the resulting assistance system is inherently dependable, flexible, and adaptable. Corresponding to the current situation and the users’ abilities the system changes the level of assistance during real-time operation. The resulting system behavior is evaluated using system performance and usability tests

Transient permeabilization of living cells: combining shear flow and acoustofluidic trapping for the facilitated uptake of molecules

Here, we present a novel approach for the transient permeabilization of cells. We combined laminar shear flow in a microchannel with chaotic advection employing surface acoustic waves. First, as a fundamental result on the one hand, and as a kind of reference measurement for the more complex acoustofluidic approach on the other hand, we studied the permeabilization of cells in pure shear flow in a microchannel with Y-geometry. As a proof of principle, we used fluorescent dyes as model drugs and investigated their internalization into HeLa cells. We found that drug uptake scaled non-linearly with flow rate and thus shear stress. For calcein, we obtained a maximal enhancement factor of about 12 at an optimum flow rate of Q = 500 µL/h in the geometry used here compared to static incubation. This result is discussed in the light of structural phase transitions of lipid membranes accompanied by non-linear effects, as the plasma membrane is the main barrier to overcome. Second, we demonstrated the enhanced permeabilization of acoustically trapped cells in surface acoustic wave induced vortices in a microchannel, with an enhancement factor of about 18 compared to quasi-static incubation. Moreover, we optimized the trapping conditions regarding flow rate, the power level of the surface acoustic wave, and trapping time. Finally, we showed that our method is not limited to small molecules but can also be applied to compounds with higher molecular weight