Matthias Rädle
Mannheim University of Applied Sciences
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Publication
Featured researches published by Matthias Rädle.
Journal of Agricultural and Food Chemistry | 2010
Stefan Castritius; Alexander Kron; Thomas Schäfer; Matthias Rädle; Diedrich Harms
A new approach of combination of near-infrared (NIR) spectroscopy and refractometry was developed in this work to determine the concentration of alcohol and real extract in various beer samples. A partial least-squares (PLS) regression, as multivariate calibration method, was used to evaluate the correlation between the data of spectroscopy/refractometry and alcohol/extract concentration. This multivariate combination of spectroscopy and refractometry enhanced the precision in the determination of alcohol, compared to single spectroscopy measurements, due to the effect of high extract concentration on the spectral data, especially of nonalcoholic beer samples. For NIR calibration, two mathematical pretreatments (first-order derivation and linear baseline correction) were applied to eliminate light scattering effects. A sample grouping of the refractometry data was also applied to increase the accuracy of the determined concentration. The root mean squared errors of validation (RMSEV) of the validation process concerning alcohol and extract concentration were 0.23 Mas% (method A), 0.12 Mas% (method B), and 0.19 Mas% (method C) and 0.11 Mas% (method A), 0.11 Mas% (method B), and 0.11 Mas% (method C), respectively.
PLOS ONE | 2014
José Fernando García Molina; Lei Zheng; Metin Sertdemir; Dietmar Dinter; Stefan O. Schönberg; Matthias Rädle
Robust detection of prostatic cancer is a challenge due to the multitude of variants and their representation in MR images. We propose a pattern recognition system with an incremental learning ensemble algorithm using support vector machines (SVM) tackling this problem employing multimodal MR images and a texture-based information strategy. The proposed system integrates anatomic, texture, and functional features. The data set was preprocessed using B-Spline interpolation, bias field correction and intensity standardization. First- and second-order angular independent statistical approaches and rotation invariant local phase quantization (RI-LPQ) were utilized to quantify texture information. An incremental learning ensemble SVM was implemented to suit working conditions in medical applications and to improve effectiveness and robustness of the system. The probability estimation of cancer structures was calculated using SVM and the corresponding optimization was carried out with a heuristic method together with a 3-fold cross-validation methodology. We achieved an average sensitivity of 0.844±0.068 and a specificity of 0.780±0.038, which yielded superior or similar performance to current state of the art using a total database of only 41 slices from twelve patients with histological confirmed information, including cancerous, unhealthy non-cancerous and healthy prostate tissue. Our results show the feasibility of an ensemble SVM being able to learn additional information from new data while preserving previously acquired knowledge and preventing unlearning. The use of texture descriptors provides more salient discriminative patterns than the functional information used. Furthermore, the system improves selection of information, efficiency and robustness of the classification. The generated probability map enables radiologists to have a lower variability in diagnosis, decrease false negative rates and reduce the time to recognize and delineate structures in the prostate.
Particle & Particle Systems Characterization | 1998
Camiel Heffels; Reinhard Polke; Matthias Rädle; Bernd Sachweh; Michael Schäfer; Norbert Scholz
This paper gives an overview of recent work in the field of particle characterization methods which have been developed for the on-line characterization of particulate process in industry. Especially the potential and benefits of optical sensor technology are discussed and illustrated with some practical examples.
Tm-technisches Messen | 2016
Frank Braun; Robert Schalk; Jochen Brunner; Hanns Simon Eckhardt; Michael Theuer; Ute Veith; Steffen Hennig; Wolfgang Ferstl; Frank-Jürgen Methner; Thomas Beuermann; Norbert Gretz; Matthias Rädle
Zusammenfassung Trotz der bekannten Vorteile der Raman-Spektroskopie, wie bspw. eine höhere chemische Selektivität gegenüber Messmethoden im nahen Infrarot (NIR) oder die im Vergleich zum mittleren Infrarotbereich (MIR) niedrigen Matrixeinflüsse des Wassermoleküls, ist diese optische Messtechnik in der Online-Prozessanalysentechnik nicht weit verbreitet. Ein wesentliches Problem besteht in einem oftmals kostenintensiven Nachrüsten einer Messstelle durch den Einbau sogenannter Immersionssonden in eine produktführende Rohrleitung oder einen Behälter. Eine praktikable Alternative stellt das hier entwickelte neuartige Sondensystem dar, welches eine Strahlführung über Linsen mit relativ großen Durchmessern beinhaltet, da dieses an vorhandene Schauglasarmaturen angekoppelt werden kann. Mit diesem robusten Sondenaufbau sind Brennweiten weit über 25 mm möglich, welche Echtzeit-Messungen von außerhalb der produktführenden Leitungen durch optische Schaugläser gestatten. Die dadurch entstehenden Messoptionen werden exemplarisch am Nachweis von Ethanol durch Schaugläser unterschiedlicher Dicken sowie bei einer quantitativen Echtzeit-Verfolgung eines Propylencarbonat-Wasser-Gemisches durch eine Schauglasarmatur (Nenndruck PN 16, Nennweite DN 50) im Technikumsmaßstab untersucht. Die vorgestellte Raman-Sonde hat durch einfache Adaption an bereits vorhandene Armaturen industrieller Anlagen das Potential einer preiswerten und kontaktlosen Inline-Messlösung mit hoher Standzeit in der Prozessanalysentechnik (PAT).
PLOS ONE | 2015
Andreas Ziegler; Daniel Schock-Kusch; Dominik Bopp; Sandra Dounia; Matthias Rädle; Ulf Stahl
In this technical report we demonstrate a low-cost online unit allowing movement tracking of flagellated bacteria on a single-cell level during fermentation processes. The system’s ability to distinguish different metabolic states (viability) of bacteria by movement velocity was investigated. A flow-through cuvette with automatically adjustable layer thickness was developed. The cuvette can be used with most commercially available laboratory microscopes equipped with 40× amplification and a digital camera. In addition, an automated sample preparation unit and a software module was developed measuring size, moved distance, and speed of bacteria. In a proof of principle study the movement velocities of Bacillus amyloliquefaciens FZB42 during three batch fermentation processes were investigated. In this process the bacteria went through different metabolic states, vegetative growth, diauxic shift, vegetative growth after diauxic shift, and sporulation. It was shown that the movement velocities during the different metabolic states significantly differ from each other. Therefore, the described setup has the potential to be used as a bacteria viability monitoring tool. In contrast to some other techniques, such as electro-optical techniques, this method can even be used in turbid production media.
Bioprocess and Biosystems Engineering | 2017
Robert Schalk; Frank Braun; Rudolf Frank; Matthias Rädle; Norbert Gretz; Frank-Jürgen Methner; Thomas Beuermann
The monitoring of microbiological processes using Raman spectroscopy has gained in importance over the past few years. Commercial Raman spectroscopic equipment consists of a laser, spectrometer, and fiberoptic immersion probe in direct contact with the fermentation medium. To avoid possible sterilization problems and biofilm formation on the probe tip, a large-aperture Raman probe was developed. The design of the probe enables non-contact in-line measurements through glass vessels or inspection glasses of bioreactors and chemical reactors. The practical applicability of the probe was tested during yeast fermentations by monitoring the consumption of substrate glucose and the formation of ethanol as the product. Multiple linear regression models were applied to evaluate the Raman spectra. Reference values were determined by high-performance liquid chromatography. The relative errors of prediction for glucose and ethanol were 5 and 3%, respectively. The presented Raman probe allows simple adaption to a wide range of processes in the chemical, pharmaceutical, and biotechnological industries.
Computers & Mathematics With Applications | 2018
Maximilian Gaedtke; Simon Wachter; Matthias Rädle; Hermann Nirschl; Mathias J. Krause
Abstract In this work the simulation of velocity and temperature distributions inside a refrigerated vehicle is evaluated. For this purpose a 3D double distribution lattice Boltzmann method (LBM) with the Bhatnagar–Gross–Krook (BGK) collision operator is coupled by the buoyancy force calculated with the Boussinesq approximation. This LBM is extended by a Smagorinsky subgrid method, which numerically stabilizes the BGK scheme for low resolutions and high Reynolds and Rayleigh numbers. Besides validation against the two benchmark cases porous plate and natural convection in a square cavity evaluated at resolutions of y + ≈ 2 for Ra numbers between 103 and 1010, the method and its implementation are tested via comparison with experimental data for a refrigerated vehicle at R e ≈ 53 000 . The aim of the investigation is to provide a deeper understanding of the refrigerated vehicle’s insulation processes including its thermal performance under turbulent flow conditions. Therefore, we extend this method by the half lattice division scheme for conjugate heat transfer to simulate in the geometry of a refrigerated vehicle including its insulation walls. This newly developed method combination enables us to accurately predict velocity and temperature distributions inside the cooled loading area, while spatially resolving the heat flux through the insulation walls. We simulate the time dependent heating process of the open door test and validate against measurements at four characteristic velocity and 13 temperature positions in the truck.
Computers & Mathematics With Applications | 2018
Jesse Ross-Jones; Maximilian Gaedtke; Sebastian Sonnick; Matthias Rädle; Hermann Nirschl; Mathias J. Krause
Abstract Due to reduced thermal conductivity, vacuum insulation panels (VIPs) provide significant thermal insulation performance. Our novel vacuum panels operate at reduced pressure and are filled with a powder of precipitated silicic acid to further hinder convection and provide static stability against atmospheric pressure. To obtain an in depth understanding of heat transfer mechanisms, their interactions and their dependencies inside VIPs, detailed microscale simulations are conducted. Particle characteristics for silica are used with a discrete element method (DEM) simulation, using open source software Yade-DEM, to generate a periodic compressed packing of precipitated silicic acid particles. This aggregate packing is then imported into OpenLB (openlb.net) as a fully resolved geometry, and used to study the effects on heat transfer at the microscale. A three dimensional Lattice Boltzmann method (LBM) for conjugated heat transfer is implemented with open source software OpenLB, which is extended to include radiative heat transport. The infrared intensity distribution is solved and coupled with the temperature through the emissivity, absorption and scattering of the studied media using the radiative transfer equation by means of LBM. This new holistic approach provides a distinct advantage over similar porous media approaches by providing direct control and tuning of particle packing characteristics such as aggregate size, shape and pore size distributions and studying their influence directly on conduction and radiation independently. Our aim is to generate one holistic tool which can be used to generate silica geometry and then simulate automatically the thermal conductivity through the generated geometry.
Bioconjugate Chemistry | 2018
Marc Pretze; Andreas Hien; Matthias Rädle; Ralf Schirrmacher; Carmen Wängler; Björn Wängler
Gold nanoparticles (AuNPs) have widely been used for 70 years in cancer treatment, but only in the last 15 years has the focus been on specific AuNPs with homogeneous size and shape for various areas in science. They constitute a perfect platform for multifunctionalization and therefore enable the enhancement of target affinity. Here we report on the development of tumor specific AuNPs as diagnostic tools intended for the detection of prostate cancer via fluorescence imaging and positron emission tomography (PET). The AuNPs were further evaluated in vitro and in vivo and exhibited favorable diagnostic properties concerning tumor cell uptake, biodistribution, clearance, and tumor retention.
Czasopismo Techniczne | 2016
Georg Brösigke; Jens-Uwe Repke; Alexander Herter; Matthias Rädle
Analysis of the Influence of Turbulence on the Heat Transfer Between Spherical Particles and Planar Surfaces