Grundlagen zur Entwicklung adaptiver Schalungssysteme für frei geformte Betonbauteile

Für die Realisierung nach bionischen Prinzipien entworfener Betontragwerke mit frei geformten Bauteilkonturen ist die erforderliche Schalung in technischer und ökonomischer Hinsicht von eminenter Bedeutung. Im Forschungsvorhaben wurde sich mit der Entwicklung adaptiver und aktiv regulierbarer Schalungssysteme befasst, welche durch den Einsatz neuartiger Materialen und Konstruktionsprinzipien flexibel auf beliebig geneigte und gekrümmte Bauteiloberflächen reagieren kann. Das Schalungssystem selbst soll nach bionischen Prinzipien agieren. Computergestützt ansteuerbare, elektrisch regulierbare Stellgliedsysteme ermöglichen effiziente, materialsparende Herstellverfahren und minimieren die Beanspruchung des Schalungssystems.Formwork has great significance for the realisation of concrete load-bearing structures designed according to bionic principles with free-formed contours in technical and economic regard. The research project focussed on developing adaptive and actively controllable formwork systems that can flexibly respond to arbitrarily inclined and curved building part surfaces using new material and construction principles. The formwork itself is supposed to act according to bionic principles. Computer-aided, electrically controllable control element systems allow for efficient, material-saving manufacturing methods and minimise the load on the formwork system

Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging

Deep learning implementations using convolutional neural nets have recently demonstrated promise in many areas of medical imaging. In this article we lay out the methods by which we have achieved consistently high quality, high throughput computation of intra-cranial segmentation from whole head magnetic resonance images, an essential but typically time-consuming bottleneck for brain image analysis. We refer to this output as “production-level” because it is suitable for routine use in processing pipelines. Training and testing with an extremely large archive of structural images, our segmentation algorithm performs uniformly well over a wide variety of separate national imaging cohorts, giving Dice metric scores exceeding those of other recent deep learning brain extractions. We describe the components involved to achieve this performance, including size, variety and quality of ground truth, and appropriate neural net architecture. We demonstrate the crucial role of appropriately large and varied datasets, suggesting a less prominent role for algorithm development beyond a threshold of capability

Unsupervised Deep Representation Learning Enables Phenotype Discovery For Genetic association Studies of Brain Imaging

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants\u27 T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes

Fluorescent Discrimination between Traces of Chemical Warfare Agents and Their Mimics

An array of fluorogenic probes is able to discriminate between nerve agents, sarin, soman, tabun, VX and their mimics, in water or organic solvent, by qualitative fluorescence patterns and quantitative multivariate analysis, thus making the system suitable for the inthe- field detection of traces of chemical warfare agents as well as to differentiate between the real nerve agents and other related compounds.Ministerio de Economía y Competitividad, Spain (Project CTQ2012- 31611), Junta de Castilla y León, Consejería de Educación y Cultura y Fondo Social Europeo (Project BU246A12-1), the European Commission, Seventh Framework Programme (Project SNIFFER FP7-SEC-2012-312411) and the Swedish Ministry of Defence (no. A403913

Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging.

Deep learning implementations using convolutional neural nets have recently demonstrated promise in many areas of medical imaging. In this article we lay out the methods by which we have achieved consistently high quality, high throughput computation of intra-cranial segmentation from whole head magnetic resonance images, an essential but typically time-consuming bottleneck for brain image analysis. We refer to this output as "production-level" because it is suitable for routine use in processing pipelines. Training and testing with an extremely large archive of structural images, our segmentation algorithm performs uniformly well over a wide variety of separate national imaging cohorts, giving Dice metric scores exceeding those of other recent deep learning brain extractions. We describe the components involved to achieve this performance, including size, variety and quality of ground truth, and appropriate neural net architecture. We demonstrate the crucial role of appropriately large and varied datasets, suggesting a less prominent role for algorithm development beyond a threshold of capability

Grundlagen zur Entwicklung adaptiver Schalungssysteme für frei geformte Betonbauteile

Für die Realisierung nach bionischen Prinzipien entworfener Betontragwerke mit frei geformten Bauteilkonturen ist die erforderliche Schalung in technischer und ökonomischer Hinsicht von eminenter Bedeutung. Im Forschungsvorhaben wurde sich mit der Entwicklung adaptiver und aktiv regulierbarer Schalungssysteme befasst, welche durch den Einsatz neuartiger Materialen und Konstruktionsprinzipien flexibel auf beliebig geneigte und gekrümmte Bauteiloberflächen reagieren kann. Das Schalungssystem selbst soll nach bionischen Prinzipien agieren. Computergestützt ansteuerbare, elektrisch regulierbare Stellgliedsysteme ermöglichen effiziente, materialsparende Herstellverfahren und minimieren die Beanspruchung des Schalungssystems.Formwork has great significance for the realisation of concrete load-bearing structures designed according to bionic principles with free-formed contours in technical and economic regard. The research project focussed on developing adaptive and actively controllable formwork systems that can flexibly respond to arbitrarily inclined and curved building part surfaces using new material and construction principles. The formwork itself is supposed to act according to bionic principles. Computer-aided, electrically controllable control element systems allow for efficient, material-saving manufacturing methods and minimise the load on the formwork system

Grundlagen zur Entwicklung adaptiver Schalungssysteme für frei geformte Betonbauteile

Für die Realisierung nach bionischen Prinzipien entworfener Betontragwerke mit frei geformten Bauteilkonturen ist die erforderliche Schalung in technischer und ökonomischer Hinsicht von eminenter Bedeutung. Im Forschungsvorhaben wurde sich mit der Entwicklung adaptiver und aktiv regulierbarer Schalungssysteme befasst, welche durch den Einsatz neuartiger Materialen und Konstruktionsprinzipien flexibel auf beliebig geneigte und gekrümmte Bauteiloberflächen reagieren kann. Das Schalungssystem selbst soll nach bionischen Prinzipien agieren. Computergestützt ansteuerbare, elektrisch regulierbare Stellgliedsysteme ermöglichen effiziente, materialsparende Herstellverfahren und minimieren die Beanspruchung des Schalungssystems.Formwork has great significance for the realisation of concrete load-bearing structures designed according to bionic principles with free-formed contours in technical and economic regard. The research project focussed on developing adaptive and actively controllable formwork systems that can flexibly respond to arbitrarily inclined and curved building part surfaces using new material and construction principles. The formwork itself is supposed to act according to bionic principles. Computer-aided, electrically controllable control element systems allow for efficient, material-saving manufacturing methods and minimise the load on the formwork system