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Extended Dynamical Causal Modelling for Phase Coupling (eDCM PC)
No full textWe present a software tool: extended Dynamic Causal Modelling for Phase Coupling(eDCM PC). This framework is implemented in MATLAB as an extension of the DynamicCausal Models for phase coupling method. eDCM PC is able to estimate effectiveconnectivity between oscillating systems using the phase information obtained fromexperimental signals, such as oscillatory activities of neuronal populations in distantbrain regions. With the help of a transformation function, eDCM PC can measureobservable independent coupling functions within and between different frequencybands. This software is available on GitLab under the GNU General Public License(version 3 or later
Predicting forces and shapes during the invasion of apicomplexan parasites into host cells: A vesicle approach
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Chemoenzymatic Natural Product Synthesis - Transferases in the Synthesis of Pyrroloindoles
No full textCongestion in crowds – behaviour and risks at high densities and in crowds
No full textPredicting congestion in pedestrian flows is useful for planning events, transportation hubs, or escape routes in buildings. According to the state of the art, software solutions are based on agent-based models in which pedestrians are represented as two-dimensional objects (e.g., circles, ellipses, etc.). These models are able to predict congestion in complex path networks, but reach their limits when it comes to describing crowds at high densities.The talk will use witness statements from the Love Parade in Duisburg (an event in which 31 people died) to analyse how people behave in crowds and which dynamics lead to life-threatening situations. In a second part, a methodology will be presented for collecting data that provides a three-dimensional description of the movement and interaction of bodies (torsos and limbs) in crowds. This data is used to develop hybrid AI models in which pedestrians interact as three-dimensional objects. Using methods and concepts from social psychology, we are working on models in which the dynamic of motivation changes is described, or which analyse the spread of behaviour in crowds. Empirical data from laboratory experiments confirm the findings from the analysis of witness statements and show how slowly pushing and shoving behaviour spreads in crowds
Movement and waiting of crowds – state of the art models and data
No full textThe contribution starts with a historical review of the connection between modelling and technical possibilities of data collection. This is followed by an overview of current approaches to modelling the movement of individual pedestrians in crowds. These include cellular automata, force as well as speed models, and trajectory prediction models based on machine learning methods. A classification of individual movement options and collective phenomena in different density ranges is used to critically discuss current model approaches and their advantages and disadvantages. The last part of the lecture is dedicated to empirical results on waiting behaviour and first modelling approaches. The focus is on waiting on platforms and in queueing systems for event venues
Determining the Hydrogen Conversion Rates of a Passive Catalytic Recombiner for Hydrogen Risk Mitigation
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Unveiling Iron-Slurry/Air Batteries: A Hybrid Approach Integrating Iron-Air and Flow Battery Systems
No full textThe increasing demand for renewable energy sources, such as wind and solar, is driving the need for efficient and sustainable energy storage systems. Among the promising alternatives to conventional batteries, iron-air batteries have gained significant attention due to their high energy densities (2,500 WhL-1), intrinsic safety, environmental friendliness, and reliance on abundant materials. However, a key challenge with traditional iron-air batteries is the solid iron electrode, where surface passivation caused by oxidation products limits charge transport and leads to extended formation cycles. Therefore, the development of iron electrodes with a high loading of active material to enhance storage capacity, while ensuring efficient charge transport at practical current densities, is essential to fully unlock the potential of iron-air batteries.This study focuses on the investigation of iron-slurry/air battery designed to combine the advantages of conventional iron-air batteries with the design flexibility of flow batteries, enabling independent control of energy capacity and power output. Iron-coated carbon powder was initially synthesized as an active material, where conductive carbon particles facilitate electron transport. Key parameters such as iron content (to maximize capacity) and slurry viscosity (to ensure efficient flow and pumping) were optimized. The synthesized slurry was then characterized using X-ray diffraction (XRD) for phase identification, while morphological and elemental analyses were conducted using transmission electron microscopy (TEM), scanning electron microscopy (SEM), and inductively coupled plasma-optical emission spectroscopy (ICP-OES). Electrochemical behavior was evaluated through open circuit potential (OCP), cyclic voltammetry (CV), and chronopotentiometry (CP) measurements. Based on these physical and electrochemical characterizations, the optimized slurry formulation was selected and mixed with an alkaline electrolyte (KOH solution) to fabricate the iron slurry electrodes. A proof-of-concept iron-slurry/air battery was demonstrated for the first time, offering clear evidence of the system’s practical viability. This demonstration provides critical insight into the potential of slurry-based battery systems and suggests a viable pathway towards enhanced sustainability and efficiency in renewable energy storage applications