Graue Literatur
Filtern
Erscheinungsjahr
- 2020 (5) (entfernen)
Dokumenttyp
- Sonstiges (5) (entfernen)
Sprache
- Englisch (5) (entfernen)
Referierte Publikation
- nein (5)
Schlagworte
- ACEnano (1)
- Active thermography (1)
- Compressed sensing (1)
- Deep learning (1)
- Diagnostics (1)
- ELISA (1)
- Environment (1)
- Imaging (1)
- Immunoassay (1)
- Internal defects (1)
Organisationseinheit der BAM
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
Laser excited super resolution thermal imaging for nondestructive inspection of internal defects
(2020)
A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple measurement events. This concerted approach of experimental measurement strategy and numerical optimization enables the resolution of internal defects and outperforms conventional thermographic inspection techniques.
You Ask – ACEnano Replies
(2020)
The workshop starts with introductory information about the workshop and the H2020 project ACEnano, followed by two expert round tables, focussing on how the project could address regulator and industry needs, respectively. This is be followed by parallel sessions on tools (based on preferences expressed by those registered to attend, see “Questions”) and finally a question-and-answer session with the attendees.
The experts invited in Round Table 1 have been prepared to answer to questions related to obstacles and advantages for stakeholders such as SMEs to use the ACEnano approaches/tools. Standardisation needs are discussed.
There is growing interest in quantifying microplastics in environmental samples. This application note presents a thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) method that is well suited to automation and increased sample throughput. The method is also able to detect all particle sizes in the sample as long as the limit of detection (LOD) is reached and allows analysis of larger samples of 15 to 25 mg or more. Samples were decomposed by thermogravimetric analysis (TGA), and the gaseous decomposition products were trapped on a solid-phase sorbent, followed by thermal desorption‑gas chromatography/mass spectrometry (TD-GC/MS) using an Agilent 5977B GC/MSD coupled to an Agilent 7890B GC. Target microplastic particle (MP) polymers were identified in environmental samples including surface water, finished compost, house dust, and drinking water. Quantification of MP polymers in environmental samples provided LODs of 0.06 to 2.2 μg, allowing the detection of MPs in trace amounts with sample weights of up to 1 g. Method repeatability was adequate for reliable quantification with RSDs of approximately 6 to 12%.
Thousands of antibodies for diagnostic and other analytical purposes are on the market. However, it is often difficult to identify duplicates, reagent changes, and to assign the correct original publications to an antibody. This slows down scientific progress and might even be a cause of irreproducible research and a waste of resources. Recently, activities were started to suggest the sole use of recombinant antibodies in combination with the open communication of their sequence. In this case, such uncertainties should be eliminated. Unfortunately, this approach seems to be rather a long-term vision since the development and manufacturing of recombinant antibodies
remain quite expensive in the foreseeable future. Also, nearly all commercial antibody suppliers may be reluctant to publish the sequence of their antibodies, since they fear counterfeiting. De-novo sequencing of antibodies is also not feasible today for a reagent user without access to the hybridoma clone. Nevertheless, it seems to be crucial for any scientist to have the opportunity to identify an antibody undoubtedly to guarantee the traceability of any research activity using antibodies from a third party as a tool. For this purpose, we developed a method for the identification of antibodies based on a MALDI-TOF-MS fingerprint. To circumvent lengthy denaturation, reduction, alkylation, and enzymatic digestion steps, the fragmentation was performed with a simple formic acid hydrolysis step. Eighty-nine unknown monoclonal antibodies were used for this study to examine the feasibility of this approach. Although the molecular assignment of peaks was rarely possible, antibodies could be easily recognized in a blinded test, simply from their mass-spectral fingerprint. A general protocol is given, which could be used without any optimization to generate fingerprints for a database. We want to propose that in most scientific projects relying critically on antibody reagents, such a fingerprint should be established to prove and document the identity of the used antibodies and to assign a specific reagent to a datasheet of a commercial supplier, a public database record or an antibody ID.