Numerical and Experimental Investigation of Thermoplastics in Multi-Axis Forming Processes

Process planning for multi-axis forming presses is a particular challenge. This process provides the option to actively influencing the material flow in the forming process by defining a six dimensional tool motion path and the tool velocity. By comprehending this interaction, it is possible to control and thereby tailor the induced local material properties of the workpiece. Experiments were conducted with a multi-axis press, which is based on a Stewart platform. A simple plane workpiece geometry is chosen to analyse the flow behaviour and the temperature evolution of the glass mat thermoplastics (GMT) during the forming process. Subsequently, a numerical simulation of the multi-axis forming process is carried out and validated with the experimental data. The numerical analysis focuses on the material modelling as well as the prediction of the flow characteristics. Regarding material modelling of GMT, an extensive material characterization is performed to describe the flow behaviour. A prediction of the flow behaviour of GMT with reference to tool motion is enabled. For the FE simulation the element-free Galerkin method (EFG) is applied for modelling the fluid structure interaction and adaptive procedures

High-resolution neural network-driven mapping of multiple diffusion metrics leveraging asymmetries in the balanced steady-state free precession frequency profile

We propose to utilize the rich information content about microstructural tissue properties entangled in asymmetric balanced steady-state free precession (bSSFP) profiles to estimate multiple diffusion metrics simultaneously by neural network (NN) parameter quantification. A 12-point bSSFP phase-cycling scheme with high-resolution whole-brain coverage is employed at 3 and 9.4 T for NN input. Low-resolution target diffusion data are derived based on diffusion-weighted spin-echo echo-planar-imaging (SE-EPI) scans, that is, mean, axial, and radial diffusivity (MD, AD, and RD), fractional anisotropy (FA), as well as the spherical coordinates (azimuth Φ and inclination ϴ) of the principal diffusion eigenvector. A feedforward NN is trained with incorporated probabilistic uncertainty estimation. The NN predictions yielded highly reliable results in white matter (WM) and gray matter structures for MD. The quantification of FA, AD, and RD was overall in good agreement with the reference but the dependence of these parameters on WM anisotropy was somewhat biased (e.g. in corpus callosum). The inclination ϴ was well predicted for anisotropic WM structures, while the azimuth Φ was overall poorly predicted. The findings were highly consistent across both field strengths. Application of the optimized NN to high-resolution input data provided whole-brain maps with rich structural details. In conclusion, the proposed NN-driven approach showed potential to provide distortion-free high-resolution whole-brain maps of multiple diffusion metrics at high to ultrahigh field strengths in clinically relevant scan times

Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification

Autism spectrum disorder (ASD) is a prevalent psychiatric condition characterized by atypical cognitive, emotional, and social patterns. Timely and accurate diagnosis is crucial for effective interventions and improved outcomes in individuals with ASD. In this study, we propose a novel Multi-Atlas Enhanced Transformer framework, METAFormer, ASD classification. Our framework utilizes resting-state functional magnetic resonance imaging data from the ABIDE I dataset, comprising 406 ASD and 476 typical control (TC) subjects. METAFormer employs a multi-atlas approach, where flattened connectivity matrices from the AAL, CC200, and DOS160 atlases serve as input to the transformer encoder. Notably, we demonstrate that self-supervised pretraining, involving the reconstruction of masked values from the input, significantly enhances classification performance without the need for additional or separate training data. Through stratified cross-validation, we evaluate the proposed framework and show that it surpasses state-of-the-art performance on the ABIDE I dataset, with an average accuracy of 83.7% and an AUC-score of 0.832. The code for our framework is available at https://github.com/Lugges991/METAForme

The Reference System in the Model of PGE: Proposing a Generalized Description of Reference Products and their Interrelations

Samsung recently introduced a new smartphone display with increased breaking resistance, which will probably be relevant for future cars as well. This example shows that subsystems, in general artefacts from former development processes can be relevant for subsequent projects. Their integration has to be planned, i.a. even before the original product is in the market and across branches. The research on supporting methods requires a suitable description model for this phenomenon. Research in design reuse and PGE – product generation engineering addresses this only partially yet. Design reuse focuses on the informational aspect, PGE refers primarily to reference products. This contribution aims at closing this gap as a basis for future research. Two case studies from industry projects by the authors and an example from foresight and product planning show the role of artefacts from former development processes in running projects. It is described which artefacts are used as a reference, why they are used and when. Based on these findings the authors propose the term “reference system” to depict the whole set of artefacts, which serves as a basis for every product development project

Excitability and synaptic transmission in the enteric nervous system: Does diet play a role?

© Springer International Publishing Switzerland 2016. Changes in diet are a challenge to the gastrointestinal tract which needs to alter its processing mechanisms to continue to process nutrients and maintain health. In particular, the enteric nervous system (ENS) needs to adapt its motor and secretory programs to deal with changes in nutrient type and load in order to optimise nutrient absorption. The nerve circuits in the gut are complex, and the numbers and types of neurons make recordings of specific cell types difficult, time-consuming, and prone to sampling errors. Nonetheless, traditional research methods like intracellular electrophysiological approaches have provided the basis for our understanding of the ENS circuitry. In particular, animal models of intestinal inflammation have shown us that we can document changes to neuronal excitability and synaptic transmission. Recent studies examining diet-induced changes to ENS programming have opted to use fast imaging techniques to reveal changes in neuron function. Advances in imaging techniques using voltage- or calcium-sensitive dyes to record neuronal activity promise to overcome many limitations inherent to electrophysiological approaches. Imaging techniques allow access to a wide range of ENS phenotypes and to the changes they undergo during dietary challenges. These sorts of studies have shown that dietary variation or obesity can change how the ENS processes information-in effect reprogramming the ENS. In this review, the data gathered from intracellular recordings will be compared with measurements made using imaging techniques in an effort to determine if the lessons learnt from inflammatory changes are relevant to the understanding of diet-induced reprogramming

A Synthesis of Marine Monitoring Methods With the Potential to Enhance the Status Assessment of the Baltic Sea

Highlights - We rated novel methods regarding their ability to improve the Baltic Sea monitoring. - Methods were assessed with respect to their costs and applicability. - All methods can potentially increase data resolution or monitor novel ecosystem elements. - We recommend several novel methods for the Baltic status assessment.A multitude of anthropogenic pressures deteriorate the Baltic Sea, resulting in the need to protect and restore its marine ecosystem. For an efficient conservation, comprehensive monitoring and assessment of all ecosystem elements is of fundamental importance. The Baltic Marine Environment Protection Commission HELCOM coordinates conservation measures regulated by several European directives. However, this holistic assessment is hindered by gaps within the current monitoring schemes. Here, twenty-two novel methods with the potential to fill some of these gaps and improve the monitoring of the Baltic marine environment are examined. We asked key stakeholders to point out methods likely to improve current Baltic Sea monitoring. We then described these methods in a comparable way and evaluated them based on their costs and applicability potential (i.e., possibility to make them operational). Twelve methods require low to very low costs, while five require moderate and two high costs. Seventeen methods were rated with a high to very high applicability, whereas four methods had moderate and one low applicability for Baltic Sea monitoring. Methods with both low costs and a high applicability include the Manta Trawl, Rocket Sediment Corer, Argo Float, Artificial Substrates, Citizen Observation, Earth Observation, the HydroFIA®pH system, DNA Metabarcoding and Stable Isotope Analysis

Identification of six new susceptibility loci for invasive epithelial ovarian cancer.

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 ] HEALTH ]F2 ]2009 ]223175). The CIMBA data management and data analysis were supported by Cancer Research.UK grants 12292/A11174 and C1287/A10118. The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME ]ON Post ]GWAS Initiative (U19 ]CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The cBio portal is developed and maintained by the Computational Biology Center at Memorial Sloan ] Kettering Cancer Center. SH is supported by an NHMRC Program Grant to GCT. Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium, funding for which was provided by the Wellcome Trust under award 076113. The results published here are, in part, based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancerhttp://dx.doi.org/10.1038/ng.3185This is the Author Accepted Manuscript of 'Identification of six new susceptibility loci for invasive epithelial ovarian cancer' which was published in Nature Genetics 47, 164–171 (2015) © Nature Publishing Group - content may only be used for academic research