Experiment-friendly kinetic analysis of single molecule data in and out of equilibrium

We present a simple and robust technique to extract kinetic rate models and thermodynamic quantities from single molecule time traces. SMACKS (Single Molecule Analysis of Complex Kinetic Sequences) is a maximum likelihood approach that works equally well for long trajectories as for a set of short ones. It resolves all statistically relevant rates and also their uncertainties. This is achieved by optimizing one global kinetic model based on the complete dataset, while allowing for experimental variations between individual trajectories. In particular, neither a priori models nor equilibrium have to be assumed. The power of SMACKS is demonstrated on the kinetics of the multi-domain protein Hsp90 measured by smFRET (single molecule F\"orster resonance energy transfer). Experiments in and out of equilibrium are analyzed and compared to simulations, shedding new light on the role of Hsp90's ATPase function. SMACKS pushes the boundaries of single molecule kinetics far beyond current methods.Comment: 11 pages, 8 figure

Possible applications of a highly ductile sprayed concrete as a measure for ground support and structural upgrade

The possible impacts to our underground infrastructure that might occur during its operational phase are subsequently correlating with the types of goods we are transporting as well as the overall threats to our society. With that in mind, explosions and huge fires, resulting from terroristic attacks or huge accidents, have become valid threats to our tunnels and underground hubs, especially in countries like Great Britain, the United States or Germany. Unfortunately, there are only a limited amount of measures and technical systems available for the systematic upgrade of such underground facilities, especially when talking about combined scenarios (explosion plus fire). The problem is, that most of these protective systems are based on ultra-high performance concrete approaches with a huge amount of reinforcement and additional additives for increasing the explosion and fire resistance of the concrete. For reasons of manufacturing and fabricating such protective layers and shells, these systems can often only be applied to plane structures with simple geometries and clearly defined boundaries. This is not necessarily a typical description of an underground structure, where arches and curved planes are more or less common. Therefore, a highly ductile sprayed concrete, with high fibre or steel content, could help closing this gap, at least in theory. Please click Additional Files below to see the full abstract

Analyse einer Olfactomedin-1 (Pancortin) mutierter Maus mit Myocilin-Defizienz

Hintergrund: Myocilin und Olfactomedin-1 sind Proteine der Olfactomedinfamilie, deren Funktion weitestgehend ungeklärt ist. Myocilin-defiziente Mäuse besitzen sowohl mehr Zellen in allen Retinaschichten als auch eine erhöhte Anzahl an Axonen im N. opticus und zeigen eine geringere Ausprägung der Schädigung in etablierten Schadensmodellen der Netzhaut. Mäuse, die eine mutierte Form von Olfactomedin-1 (Olfm1-mutant) bilden, werden hingegen vermehrt geschädigt. Methoden: Durch Kreuzung von Myoc-/--Mäusen mit Olfm1-mutant Mäusen wurde eine Myoc-/-/Olfm1-mutant Mauslinie generiert und durch PCR genotypisiert. Diese wurde durch Untersuchungen anhand von Semidünnschnitten, TUNEL-Färbungen, Lichtschaden, NMDA-Injektion und Realtime-PCR analysiert. Ergebnisse: Myoc-/-/Olfm1-mutant Mäuse besitzen eine erhöhte Anzahl an Photorezeptoren in der äußeren Körnerschicht. Da die Ursache hierfür im Ablauf des ontogenetischen Zelltodes vermutet wurde, wurden TUNEL-Färbungen durchgeführt. Diese zeigten eine erhöhte Anzahl an apoptotischen Zellen in der inneren Körnerschicht zum Zeitpunkt P9 während in den anderen Retinaschichten kein Unterschied bestand. Weitere Versuche mit Lichtschädigung und exzitatorischer Schädigung durch NMDA-Injektion lieferten zudem keine Hinweise auf einen Unterschied zwischen Myoc-/-/Olfm1-mutant Mäusen und Wildtyptieren bezüglich des Ausprägungsgrads der Schädigung. Da dies durch Gegenregulation anderer Olfactomedinproteine bedingt sein könnte, wurde durch quantitative Realtime-PCR die Expression ausgewählter Vertreter der Olfactomedine untersucht. Dabei zeigte sich tatsächlich eine vermehrte Expression an Latrophilin 1 (zum Zeitpunkt 8 Wochen), während jedoch Latrophilin 2 (zum Zeitpunkt 8 Wochen) und Olfactomedin 3 (zum Zeitpunkt P10), herrunterreguliert werden. Schlussfolgerung: Myoc-/-/Olfm1-mutant Mäuse weisen einen vom Wildtyp abweichenden Phäntotyp auf, der sich auch vom Phänotyp von Myoc-/- oder Olfm1- mutant Mäusen der rein Myocilin defizienten oder Pancortin mutierten Tiere unterscheidet. Somit besteht wahrscheinlich ein gegenseitiger Einfluss von Myocilin und Olfactomedin-1. Ein Effekt durch den unterschiedlichen genetischen Hintergrund kann nicht ausgeschlossen werden

Facilitating collaboration in high-performance computing projects with an interaction room

The design, development and deployment of scientific computing applications can be quite complex as they require scientific, High-Performance Computing (HPC), and software engineering expertise. Often, HPC applications are however developed by end users who are experts in their scientific domain, but need support from a supercomputing centre for the engineering and optimization aspects. The cooperation and communication between experts from these quite different disciplines can be difficult though. We therefore propose to employ the Interaction Room, a technique that facilitates interdisciplinary collaboration in complex software projects.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement No. 754304 DEEP-EST.Peer Reviewed Camera Read

Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems

Multi-GPU systems are in continuous development to deal with the challenges of intensive computational big data problems. On the one hand, parallel architectures provide a tremendous computation capacity and outstanding scalability. On the other hand, the production path in multi-user environments faces several roadblocks since they do not grant root privileges to the users. Containers provide flexible strategies for packing, deploying and running isolated application processes within multi-user systems and enable scientific reproducibility. This paper describes the usage and advantages that the uDocker container tool offers for the development of deep learning models in the described context. The experimental results show that uDocker is more transparent to deploy for less tech-savvy researchers and allows the application to achieve processing time with negligible overhead compared to an uncontainerized environment

Processing Miscanthus to high-value chemicals: A techno-economic analysis based on process simulation

Thermochemical biorefineries for the production of chemicals and materials can play an important role in the bioeconomy. However, their economic viability is often questioned under the premise of the economy of scale. This paper presents a regional, modular biorefinery concept for the production of the platform chemicals hydroxymethylfurfural (HMF), furfural and phenols from the lignocellulosic perennial miscanthus, which can be cultivated on marginal and degraded areas. The paper focuses on the question of the minimum selling price of HMF and the optimal plant size for this purpose, using the region of Baden-Württemberg, Germany, as an example. Based on small pilot plant results, a scalable process simulation was created via AspenPlus. This allows different scenarios and process combinations of this multi-output biorefinery concept to be compared with each other. Using this, a minimum sales price for the main product HMF is calculated using methods of dynamic investment cost calculation according to the net present value method. Based on this, the plant capacity was scaled. The scenarios and sensitivity analyses show that, with an accuracy of ±15%, regional biorefineries could already offer platform chemicals at prices of 2.21–2.90 EUR/kg HMF at the current stage of development. This corresponds to three to four times the price of today\u27s comparative fossil base chemicals and is thus a competitive option from the authors’ point of view. The local biomass and the heat prices were identified as the main influencing factors. As a result, the selection of the location will have a decisive influence on the economic viability of such concepts in the case of further development and optimization of the process in first demonstration plants

Deep learning approaches to building rooftop thermal bridge detection from aerial images

Thermal bridges are weak points of building envelopes that can lead to energy losses, collection of moisture, and formation of mould in the building fabric. To detect thermal bridges of large building stocks, drones with thermographic cameras can be used. As the manual analysis of comprehensive image datasets is very time-consuming, we investigate deep learning approaches for its automation. For this, we focus on thermal bridges on building rooftops recorded in panorama drone images from our updated dataset of Thermal Bridges on Building Rooftops (TBBRv2), containing 926 images with 6,927 annotations. The images include RGB, thermal, and height information. We compare state-of-the-art models with and without pretraining from five different neural network architectures: MaskRCNN R50, Swin-T transformer, TridentNet, FSAF, and a MaskRCNN R18 baseline. We find promising results, especially for pretrained models, scoring an Average Recall above 50% for detecting large thermal bridges with a pretrained Swin-T Transformer model