A5021665404- Additive Manufacturing and 3D Printing Technologies
- Additive Manufacturing Materials and Processes
- Manufacturing Process and Optimization
- COVID-19 epidemiological studies
- SARS-CoV-2 and COVID-19 Research
- Gene Regulatory Network Analysis
- Vaccine Coverage and Hesitancy
- Laser Material Processing Techniques
- Cellular and Composite Structures
- Viral Infections and Outbreaks Research
- Machine Learning and Data Classification
- Protein Structure and Dynamics
- Product Development and Customization
- Reservoir Engineering and Simulation Methods
- Energy Load and Power Forecasting
- Microbial Metabolic Engineering and Bioproduction
- Technology Assessment and Management
- Probabilistic and Robust Engineering Design
- Molecular Communication and Nanonetworks
- Bioinformatics and Genomic Networks
- Gaussian Processes and Bayesian Inference
- Model Reduction and Neural Networks
- Orthopedic Surgery and Rehabilitation
- Wireless Body Area Networks
- vaccines and immunoinformatics approaches
University of Bonn
2020-2024
RWTH Aachen University
2011-2017
Fraunhofer Institute for Laser Technology
2014-2017
This paper focusses on the investigation of mechanical properties lattice structures manufactured by selective laser melting using contour-hatch scan strategy. The motivation for this research is systematic elastic and plastic deformation TiAl6V4 at different strain rates. To investigate influence rate response (e.g., energy absorption) structures, compression tests TiAl6V4-lattice with rates are carried out to determine from resulting stress-strain curves. Results compared stainless steel...
Reproducibility and reusability of the results data-based modeling studies are essential. Yet, there has been—so far—no broadly supported format for specification parameter estimation problems in systems biology. Here, we introduce PEtab, a which facilitates using Systems Biology Markup Language (SBML) models set tab-separated value files describing observation model experimental data as well parameters to be estimated. We already implemented PEtab support into eight well-established...
BackgroundOver 1 year since the first reported case, true COVID-19 burden in Ethiopia remains unknown due to insufficient surveillance. We aimed investigate seroepidemiology of SARS-CoV-2 among front-line hospital workers and communities Ethiopia.MethodsWe did a population-based, longitudinal cohort study at two tertiary teaching hospitals involving workers, rural residents, urban Jimma Addis Ababa. Hospital were recruited both hospitals, community participants by convenience sampling...
Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large complex systems. pyPESTO is a modular framework systematic parameter estimation, with scalable algorithms optimization uncertainty quantification. While tailored ordinary differential equation problems, broadly applicable black-box problems. Besides own implementations, it provides unified interface...
Under-reporting of COVID-19 and the limited information about circulating SARS-CoV-2 variants remain major challenges for many African countries. We analyzed infection dynamics in Addis Ababa Jimma, Ethiopia, focusing on reinfection, immunity, vaccination effects. conducted an antibody serology study spanning August 2020 to July 2022 with five rounds data collection across a population 4723, sequenced PCR-test positive samples, used available test positivity rates, constructed two...
Epidemiological models are widely used to analyze the spread of diseases such as global COVID-19 pandemic caused by SARS-CoV-2. However, all based on simplifying assumptions and often sparse data. This limits reliability parameter estimates predictions. In this manuscript, we demonstrate relevance these limitations pitfalls associated with use overly simplistic models. We considered data for early phase outbreak in Wuhan, China, an example, perform estimation, uncertainty analysis model...
Abstract Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As sizes and datasets steadily growing, established parameter optimization approaches for mechanistic become computationally extremely challenging. Mini-batch methods, as employed deep learning, have better scaling properties. In this work, we adapt, apply, benchmark mini-batch ordinary differential...
Selective laser melting (SLM) is a manufacturing process that builds up metallic or ceramic parts layer by directly from 3D-computer-aided design data, offering, for example, the advantage of imposing little restrictions in terms geometric complexity. One main challenges SLM to improve its efficiency increasing build rate and thereby decreasing time cost. way achieving this applied power beam diameter, more volume shorter period time. Another option improving reducing material which has be...
ENGLISH ABSTRACT: Selective laser melting (SLM) is becoming an economically viable choice for manufacturing complex serial parts. This paper focuses on a geometric complexity analysis as part of the integrative technology evaluation model (ITEM) presented here. In contrast to conventional methodologies, ITEM considers interactions between product and process innovations generated by SLM. The processes that compete with SLM main goal ITEM. includes test from Festo AG. closes discussion how...
Abstract Standard finger implants, manufactured by conventional techniques (e.g. machining), as they are used today for patients suffering from inflammatoryrheumatic diseases such rheumatoid arthritis (RA) or degenerative like osteoarthritis, lacking of individuality and long‐term stability. In this study here, a way to generate patient tailored implants based on XtremeCT technique is described. First Selective Laser Melting (SLM) illustrate the feasibility manufacturing with additional...
This study aimed to retrospectively assess the cost-effectiveness of various COVID-19 vaccination strategies in Ethiopia. It involved healthcare workers (HCWs) and community participants; was conducted through interviews serological tests. Local SARS-CoV-2 variants seroprevalence rates, as well national reports status were also analyzed. A analysis performed determine most economical settings with limited vaccine access high seroprevalence. Before arrival vaccines, 65% HCWs had antibodies...
The design and manufacture of profile extrusion dies is characterised by costly running-in trials. Significant cost time savings can be achieved replacing the experimental trials virtual ones. A simulative optimisation, however, often leads to complex, free-formed flow channels. feasible such only possible with additive manufacturing processes as Selective Laser Melting (SLM). Against this background, SLM investigated. major challenge ensure a specific surface quality extruded plastics...
This paper gives an overview about Additive Manufacturing (AM) in general and Selective Laser Melting (SLM) more detail. We discuss the economic potential of AM show that it is directly correlated to process efficiency AM. present different new machine concept order increase efficiency. one new, diode laser based SLM concepts.
This paper focuses on the evaluation of manufacturing processes that are competing with Selective Laser Melting (SLM). In 3D-part production serial parts SLM is starting to be an economic choice for manufacturing. An integrated technology model (ITEM) presented helps decision makers determine potential while comparing conventional technologies. contrast methodologies ITEM considers interactions between product and process innovations generated by SLM. The closes a technical economical test...
Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large complex systems. We present pyPESTO, a modular framework systematic parameter estimation, with scalable algorithms optimization uncertainty quantification. While tailored ordinary differential equation problems, pyPESTO is broadly applicable black-box problems. Besides own implementations, it provides...
Abstract Under-reporting of COVID-19 cases and the lack information about circulating SARS-CoV-2 variants remain major challenges for many African countries to date. To address this, we present a comprehensive analysis dynamics infections in Ethiopia, focusing on reinfection dynamics, (variant-specific) immunity, impact vaccination rates. We conducted an antibody serology study, sequenced positive polymerase chain reaction tests, used available test positivity rates, constructed two...
Abstract Epidemiological models are widely used to analyse the spread of diseases such as global COVID-19 pandemic caused by SARS-CoV-2. However, all based on simplifying assumptions and sparse data. This limits reliability parameter estimates predictions. In this manuscript, we demonstrate relevance these limitations performing a study outbreak in Wuhan, China. We perform estimation, uncertainty analysis model selection for range established epidemiological models. Amongst others, employ...