Permanent Hydrothermal Exposure on Load-bearing Adhesives in Glass Constructions

The German research team FABIG develops a bioenergy building skin including modules of glass which contain a liquid medium processing biomass. Inside the facade modules, load-bearing adhesives were applied that are subject to permanent water exposure. Water is known as a major hazard for adhesives because water molecules diffuse into the adhesive polymer matrix and into the interface between adhesive and substrate. As a result, material characteristics as well as the adhesion properties may change significantly. Additionally, the adhesive is exposed to conventional aging in building skin as the temperature ranges between -20°C and +80°C. This paper focuses on the effect of water on load-bearing adhesives in a bioenergy facade. It evaluates potential adhesives for permanent hydrothermal application.  The paper introduces water as a key aging medium. Furthermore, it describes the construction of an innovative flat plate photobioreactor as an example for load-bearing adhesives under permanent hydrothermal treatment. The conditions inside the photobioreactor, which lead to particular mechanical, physical and chemical loads for constructive elements in comparison with conventional facade systems are presented. The main part describes the results of experimental tensile tests on the adhesive short-term behavior considering temperature conditioning and chemical treatment with substances emerging from bio-processing like storing in acid, base and hydrogen peroxide solution. The paper concludes with an outlook on future research work of the team including ARUP Deutschland GmbH (Berlin, Germany), ADCO Technik GmbH (Rostock, Germany), SSC GmbH (Hamburg, Germany) and Technische Universität Dresden (Dresden, Germany)

Thermally Curved Glass - Research and Standardisation of the Four-Point Bending Test

Research has shown that the general approach to determine the bending strength of thermally curved glass with the aid of the four-point bending test for flat glass according to EN 1288-3 is applicable. At the moment, however, there is no statutory method available for directly extrapolating the breaking strain from the breaking load without the use of expensive strain gauges. Such a method is developed by means of an experimental and numerical study in a research project between the Bundesverband Flachglas e.V. (Federal Flat Glass Association) and the Fachverband Konstruktiver Glasbau e.V. (Professional Association Structural Glass Constructions), the Institute of Building Construction at the Technische Universität Dresden and four glass bending specialists. Moreover, it will provide the basis for testing cylindrically curved glass of any bending radius. The project partners have already submitted a proposal for a new standard to the Deutsches Institut für Normung e.V. (German Institute for Standardisation). The paper gives the theoretical background for determining the strength of flat glass according to EN 1288‑3 and quantifies the additional effects for the testing of thermally curved glass. Furthermore, the testing method of the executed experimental study on thermally curved glass is described. The range of parameters for the tested specimens included the glass thickness from 3 mm to 12 mm and the bending radii from 400 mm to 2000 mm. We recorded the strain at selected points at the tensioned side and the input force for each specimen. The measured relation between strain and load validates a numerical model, which is able to depict the actual two-dimensional stress distribution for thermally curved glass and includes non-linear aspects. The model allows for the determination of correction factors. With those, the bending strength of thermally curved glass can be calculated by measuring merely the input force during the four-point bending tests. The correction factors are summarised in charts depending on the radius and the thickness of the glass sample

Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly

Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody–antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69–99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.Peer Reviewe

Verifying a Glass Pane Under Combined In-Plane Compression and Out-of-Plane Lateral Loads

Using glass elements as designated members of the structural design of buildings does not only require conscientious planning of structural redundancies, but also proof of safety for single components. In reality, random loads act in an unknown combination on a component, which is not directly resembled by the modelling process a priori. Hence, understanding the mechanical behaviour of glass components under probabilistic combination of static and dynamic loads is required. To serve this understanding best, the most critically loaded component of a glass shelter was examined experimentally by exposing extracted specimens to on-surface lateral loads and in-plane compressive loads simultaneously. Additionally, in-plane compressive loads were combined with soft-body impacts. This combination of static loads with short-term lateral loads is interesting in terms of stability and the residual load bearing capacity. The results show how compressive in-plane loads increase stress and deformation according to first and second order deformations and indicate that premature stability failure occurs due to soft-body impacting

Methods for Dimensioning an Adhesive Joint for Use in Fluid-Filled Façade Element

Fluids in the cavity can be used to integrate additional functions into insulating glazing. However, the high permanent load exerted by the fluid on the glazing and surrounding components is problematic. Conventional design methods result in large adhesive joints, which are not desirable from an aesthetic point of view. ETAG 002-1 is typically used for the design of structural adhesive bonds for use in structural glazing façades. However, the calculation is considered to be conservative. In particular, it is criticised for its deterministic safety concept. Therefore, in recent years, a number of researchers have looked at different methods for the design of adhesive joints. Such methods are presented by the Fachverband Konstruktiver Glasbau e.V. in the Technical Note FKG 01/2021. A further approach is presented by Drass & Kraus (2020, 2021a, 2021b), who proposes an approximation to the semi-probabilistic safety concept and thus to the current Eurocode 0 design standard by determining a material safety factor. This paper is concerned with the design of a load-bearing adhesive joint for use in a fluid-filled insulating glass unit. A specific façade element is used as an example for the calculations. Three dimensioning methods are compared: the analytical method according to ETAG 002-1, a numerical method according to Technical Note FKG 01/2021 and the approximation of a semi-probabilistic safety concept according to Drass & Kraus (2020, 2021a, 2021b). The results show significant differences between the design methods in terms of utilisation.

Controlling Text-to-Image Diffusion by Orthogonal Finetuning

Large text-to-image diffusion models have impressive capabilities in generating photorealistic images from text prompts. How to effectively guide or control these powerful models to perform different downstream tasks becomes an important open problem. To tackle this challenge, we introduce a principled finetuning method -- Orthogonal Finetuning (OFT), for adapting text-to-image diffusion models to downstream tasks. Unlike existing methods, OFT can provably preserve hyperspherical energy which characterizes the pairwise neuron relationship on the unit hypersphere. We find that this property is crucial for preserving the semantic generation ability of text-to-image diffusion models. To improve finetuning stability, we further propose Constrained Orthogonal Finetuning (COFT) which imposes an additional radius constraint to the hypersphere. Specifically, we consider two important finetuning text-to-image tasks: subject-driven generation where the goal is to generate subject-specific images given a few images of a subject and a text prompt, and controllable generation where the goal is to enable the model to take in additional control signals. We empirically show that our OFT framework outperforms existing methods in generation quality and convergence speed.Comment: NeurIPS 2023 (43 pages, 34 figures, project page: https://oft.wyliu.com/

Fahreignung älterer Pkw-Fahrer

FAHREIGNUNG ÄLTERER PKW-FAHRER Fahreignung älterer Pkw-Fahrer / Weller, Gert (Rights reserved) ( -

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

Large foundation models are becoming ubiquitous, but training them from scratch is prohibitively expensive. Thus, efficiently adapting these powerful models to downstream tasks is increasingly important. In this paper, we study a principled finetuning paradigm -- Orthogonal Finetuning (OFT) -- for downstream task adaptation. Despite demonstrating good generalizability, OFT still uses a fairly large number of trainable parameters due to the high dimensionality of orthogonal matrices. To address this, we start by examining OFT from an information transmission perspective, and then identify a few key desiderata that enable better parameter-efficiency. Inspired by how the Cooley-Tukey fast Fourier transform algorithm enables efficient information transmission, we propose an efficient orthogonal parameterization using butterfly structures. We apply this parameterization to OFT, creating a novel parameter-efficient finetuning method, called Orthogonal Butterfly (BOFT). By subsuming OFT as a special case, BOFT introduces a generalized orthogonal finetuning framework. Finally, we conduct an extensive empirical study of adapting large vision transformers, large language models, and text-to-image diffusion models to various downstream tasks in vision and language.Comment: Technical Report (33 pages, 18 figures