Learning deep dynamical models from image pixels

Modeling dynamical systems is important in many disciplines, e.g., control, robotics, or neurotechnology. Commonly the state of these systems is not directly observed, but only available through noisy and potentially high-dimensional observations. In these cases, system identification, i.e., finding the measurement mapping and the transition mapping (system dynamics) in latent space can be challenging. For linear system dynamics and measurement mappings efficient solutions for system identification are available. However, in practical applications, the linearity assumptions does not hold, requiring non-linear system identification techniques. If additionally the observations are high-dimensional (e.g., images), non-linear system identification is inherently hard. To address the problem of non-linear system identification from high-dimensional observations, we combine recent advances in deep learning and system identification. In particular, we jointly learn a low-dimensional embedding of the observation by means of deep auto-encoders and a predictive transition model in this low-dimensional space. We demonstrate that our model enables learning good predictive models of dynamical systems from pixel information only.Comment: 10 pages, 11 figure

Innovative Milchvieh-Stallsysteme für den ökologischen Landbau

Stallanlagen gemäß EG-Öko-VO haben gegenüber konventionellen Anlagen einen we-sentlich höheren Flächenanteil pro Tierplatz. Bei Milchviehställen ergibt sich dies vor allem über zusätzliche Auslaufflächen, die zunächst Mehrkosten verursachen. Um diese zu kompensieren, wurden unterschiedliche Stallbautypen auf Einsparpotenziale untersucht. Hauptkriterium waren dabei unterschiedliche Bauweisen bei Stallgebäuden und Anord-nungsweisen bei Melkhäusern. Eine Kostenerhebung auf der Basis vorhandener Milch-viehställe zeigt eine große Bandbreite (3.000-6.500 €/Kuhplatz ohne Eigenleistung) zwi-schen z. T. gleichen Systemen und lässt keine belastbaren Aussagen darüber zu, welche Baulösungen kostengünstiger sind. Deshalb wurden Modellkalkulationen zu unterschied-lichen Bau- und Anordnungsweisen auf der Grundlage einer einheitlichen Planung durch-geführt. Dabei zeigte sich, dass durch zusätzliche Funktionsflächen wie einen Warte- bzw. Selektionsbereich zur Verbesserung der Arbeitsabläufe im Stall gleichzeitig das notwen-dige Flächenangebot gemäß EG-Öko-VO erreicht wird. Im Vergleich der unterschiedlichen Bauweisen verringert sich bei mehrhäusigen Gebäude-lösungen der Investitionsbedarf um bis zu 30 - 33 %. Die wesentlichen Einsparungen wer-den durch die Wahl der Tragkonstruktion erzielt. Neben den reinen Baukosten sind bei der Bewertung der einzelnen Stallbauweisen auch noch andere Faktoren wie der mögliche Umfang an Eigenleistungen oder eine spätere Umnutzung zu berücksichtigen. Die Anordnung des Melkhauses im Stall hat erhebliche Auswirkungen auf die Funktiona-lität. Integrierte Melkhäuser eignen sich bevorzugt in beengter Hoflage. Abgesehen von einer geringfügigen Flächeneinsparung zeigt die seitliche Anordnung des Melkhauses kei-ne Vorteile hinsichtlich der Gebrauchsfähigkeit gegenüber der integrierten bzw. separaten Anordnung. Die separate Anordnung des Melkhauses ergibt für die gesamte Stallanlage die größte Flexibilität und Funktionalität. Bei gleichem Raumprogramm, gleicher Ausstat-tung und gleicher Größe ergeben sich für die Melkhäuser allein keine wesentlichen Kos-tenunterschiede zwischen den Varianten. Mehrkosten entstehen bei der integrierten Anordnung vor allem durch die teurere Überdachung des Melkhauses und die Überda-chung des Wartebereiches. Darüber hinaus führen zusätzliche Funktionsflächen vor dem Melkhaus für den Fressgang und Futtertisch zu höheren Kosten. Auf Grund der funktionalen Vorteile ist eine separate Anordnung auch bei kleineren Anlagen in Betracht zu ziehen

Nanoparticular surface-bound PCBs, PCDDs, and PCDFs-a novel class of potentially higher toxic POPs

In a previous study, Env Sci Poll Res:1-7, 2015 showed that polychlorinated biphenyls (PCBs), polychlorinated dibenzo dioxins (PCDDs), and polychlorinated dibenzo furanes (PCDFs) are found in commercially available (nano) particular titanium dioxide as a result of the fabrication. Here, we give a brief perspective and reason the toxicity of these new classes of persistent organic pollutants (POPs) by reviewing also their nanoparticular properties, such as surface-to-volume ratio, photocatalytic activity, polarity shifts, and stealth effect. These insights point towards a new class of POPs and toxicologic effects, which are related to the size but not a result of nanotechnology itself. We pave the way to the understanding of until now unresolved very complex phenomena, such as the indoor exposure, formation, and transformation of POP and sick-building syndrome. This is a fundamental message for nanotoxicology and kinetics and should be taken into account when determining the toxicity of nanomaterials and POPs separately and as a combination

Europäische Raumentwicklungspolitik

In der europäischen Raumentwicklungspolitik stimmen die für die Raumentwicklung zuständigen Ministerinnen und Minister der EU-Mitgliedstaaten raumbedeutsame Entscheidungen untereinander und mit der Europäischen Kommission ab. Sie vereinbaren strategische Papiere, kooperieren mit Fachpolitiken, werden unterstützt durch Forschung und setzen Elemente ihrer Politik in europäischen Kooperationsprogrammen um

Unsupervised dynamic modeling of medical image transformation

Spatiotemporal imaging has applications in e.g. cardiac diagnostics, surgical guidance, and radiotherapy monitoring, In this paper, we explain the temporal motion by identifying the underlying dynamics, only based on the sequential images. Our dynamical model maps the inputs of observed high-dimensional sequential images to a low-dimensional latent space wherein a linear relationship between a hidden state process and the lower-dimensional representation of the inputs holds. For this, we use a conditional variational auto-encoder (CVAE) to nonlinearly map the higher-dimensional image to a lower-dimensional space, wherein we model the dynamics with a linear Gaussian state-space model (LG-SSM). The model, a modified version of the Kalman variational auto-encoder, is end-to-end trainable, and the weights, both in the CVAE and LG-SSM, are simultaneously updated by maximizing the evidence lower bound of the marginal likelihood. In contrast to the original model, we explain the motion with a spatial transformation from one image to another. This results in sharper reconstructions and the possibility of transferring auxiliary information, such as segmentation, through the image sequence. Our experiments, on cardiac ultrasound time series, show that the dynamic model outperforms traditional image registration in execution time, to a similar performance. Further, our model offers the possibility to impute and extrapolate for missing samples.Comment: published in 2022 25th International Conference on Information Fusion (FUSION

Impaired Induction of Adhesion Molecule Expression in Immortalized Endothelial Cells Leads to Functional Defects in Dynamic Interactions With Lymphocytes

Immortalization should overcome the problem of short lifespan and difficult culture of endothelial cells that limited their use in functional studies. We used four different immortalized endothelial cell lines to study dynamic interactions with lymphocytes. Surprisingly, tumor necrosis factor (TNF)α-stimulated human umbilical vein endothelial cells (HUVECs) or human dermal microvascular endothelial cells (HDMECs) readily supported rolling and binding of lymphocytes, whereas none of the immortalized cell lines did. As rolling interactions are primarily mediated by selectins and vascular cell adhesion molecule (VCAM)-1, the endothelial cells were analyzed regarding expression of selectins and other adhesion molecules. Interestingly, cell surface expression of E-selectin could only be detected on HUVEC and HDMEC. Immunocytochemistry showed that some immortalized endothelial cells expressed E-selectin intracellularly following TNFα stimulation, suggesting translation but defective post-translational processing or transport of the molecule. In contrast, other immortalized cell lines did not have detectable levels of E-selectin mRNA, suggesting impaired transcription. VCAM-1 could only be induced on normal and human placental microvascular endothelial cell-A2 endothelial cells, whereas all cell lines expressed intercellular adhesion molecule-1 following TNF stimulation. The immortalized endothelial cells tested here have lost functions that are required for dynamic interactions with immune cells and that are common to primary endothelial cells

Quantitative mapping of surface elastic moduli in silica-reinforced rubbers and rubber blends across the length scales by AFM

The surface elastic moduli of silica-reinforced rubbers and rubber blends were investigated by atomic force microscopy (AFM)-based HarmoniX material mapping. Styrene–butadiene rubbers (SBR) and ethylene–propylene–diene rubbers (EPDM) and SBR/EPDM rubber blends with varying concentrations of silica nanoparticles (0, 5, 10, 20, 50 parts per hundred rubber, phr) were prepared to investigate the effect of different composition on the resulting morphology, filler distribution and elastic moduli of a specific rubber or rubber blend sample. For SBR, the elastic modulus values varied from 0.5 MPa for unfilled SBR to 5 MPa for 50 phr reinforced SBR with the increase in the concentration of filler. For EPDM, the corresponding values increased from 1.4 MPa for unfilled EPDM to 4.5 MPa for 50 phr reinforced EPDM. Local stiff and soft domains in silica-reinforced SBR and EPDM rubbers and rubber blends were identified by HarmoniX AFM imaging. While the stiff silica particles show modulus values as high as 2 GPa, the rubber matrix reveals modulus values in the range of ca. 30 MPa for the rubber blends to ca. 300 MPa for the unfilled rubbers. The lower value of elastic modulus of the EPDM phase in the blend, compared to the blank EPDM compound can be attributed to the presence of Sunpar oil in the compound which has a very good affinity with EPDM and decreases the rubber modulus. The elastic moduli maps revealed an increase of the areal fraction of silica particles showing an intrinsic surface modulus value with rising silica content in the compound preparation mixture. HarmoniX AFM measurements revealed the formation of larger silica aggregates in EPDM in contrast to SBR where isolated silica particles were observed. For silica-reinforced rubber blends a phase separation into a soft (ca. 40 MPa) and a significantly harder phase could be observed (ca. 500 MPa–1.5 GPa) indicating the incorporation of silica particles in the SBR phase. Using HarmoniX AFM imaging significantly higher surface elastic moduli were observed compared to those obtained by bulk tensile testing. Possible reasons for the observed differences between bulk modulus values and those measured by AFM are discussed in detail, including the aspect of different averaging procedures like inherent to surface probing by AFM versus bulk tensile testing, different filler distributions in SBR and EPDM and the AFM modulus calibratio