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Stretchable Tissue-Like Gold Nanowire Composites with Long-Term Stability for Neural Interfaces
No full textSoft and stretchable nanocomposites can match the mechanical properties of neural tissue, thereby minimizing foreign body reactions to provide optimal stimulation and recording specificity. Soft materials for neural interfaces should simultaneously fulfill a wide range of requirements, including low Young’s modulus (<<1 MPa), stretchability (≥30%), high conductivity (>> 1000 S cm−1), biocompatibility, and chronic stability (>> 1 year). Current nanocomposites do not fulfill the above requirements, in particular not the combination of softness and high conductivity. Here, this challenge is addressed by developing a scalable and robust synthesis route based on polymeric reducing agents for smooth, high-aspect ratio gold nanowires (AuNWs) of controllable dimensions with excellent biocompatibility. AuNW-silicone composites show outstanding performance with nerve-like softness (250 kPa), high conductivity (16 000 S cm−1), and reversible stretchability. Soft multielectrode cuffs based on the composite achieve selective functional stimulation, recordings of sensory stimuli in rat sciatic nerves, and show an accelerated lifetime stability of >3 years. The scalable synthesis method provides a chemically stable alternative to the widely used AgNWs, thereby enabling new applications within electronics, biomedical devices, and electrochemistry. This project was financially supported by the Swedish Foundation for Strategic Research, the Swedish Research Council (2019-04424), the Knut and Alice Wallenberg Foundation (Wallenberg Academy Fellow), and the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linköping University (Faculty Grant SFO Mat LiU No 2009 00971). The authors further acknowledge the Swedish Research Council and Swedish Foundation for Strategic Research for access to ARTEMI, the Swedish National Infrastructure in Advanced Electron Microscopy (2021-00171 and RIF21-0026). M JD would like to acknowledge funding from the European Research Council (834677 “e-NeuroPharma” ERC-2018-ADG). A R acknowledges the funding support from the Marie Skłodowska-Curie Actions Seal of Excellence Fellowship program from the Swedish Governmental Agency for Innovation Systems, VINNOVA (grant 2021-01668). </p
When AI meets machinery – the role of the notified body
No full textOur ambition is to give an overview of the mandatory involvement of notified bodies according to the AI Act and the Machinery Regulation. Specifically, we are interested in the cases when both acts are applicable for the same product. That said, our analysis is not to be taken as legal advice but as policy research and we recommend the reader to cross-examine our conclusions by assessing the acts in relation to the products at hand. It is also worth remembering that the focus of the analysis is when a notified body is mandatory for CE-marking a product – we do not describe what is needed to meet requirements on technology and organisation, and it is always possible to opt to include a notified body in the conformity assessment even if it is not mandatory. Another limitation is that we do not explore the full interaction between the AI Act and the Machinery Regulation, or how they interact with other policies relevant for CE-marking products intended for EU’s internal market. Our main conclusions of the analysis are that: • We should not focus on how the definition of Artificial Intelligence in the AI Act relates to the concept of ”fully or partially self-evolving behaviour using machine learning approaches” as introduced by the Machinery Regulation; but instead • We should focus on when the Machinery Regulation mandates the involvement of a notified body and how that relates to the AI Act. We also foresee an up-coming bottleneck in the availability of notified bodies capable of performing the duties in relation to both the AI Act and the Machinery Regulation, something that can have an effect on access to the internal market
Collaborative Training of Data-Driven Remaining Useful Life Prediction Models Using Federated Learning
No full textRemaining useful life prediction models are a central aspect of developing modern and capable prognostics and health management systems. Recently, such models are increasingly data-driven and based on various machine learning techniques, in particular deep neural networks. Such models are notoriously “data hungry”, i.e., to get adequate performance of such models, a substantial amount of diverse training data is needed. However, in several domains in which one would like to deploy data-driven remaining useful life models, there is a lack of data or data are distributed among several actors. Often these actors, for various reasons, cannot share data among themselves. In this paper a method for collaborative training of remaining useful life models based on federated learning is presented. In this setting, actors do not need to share locally held secret data, only model updates. Model updates are aggregated by a central server, and subsequently sent back to each of the clients, until convergence. There are numerous strategies for aggregating clients’ model updates and in this paper two strategies will be explored: 1) federated averaging and 2) federated learning with personalization layers. Federated averaging is the common baseline federated learning strategy where the clients’ models are averaged by the central server to update the global model. Federated averaging has been shown to have a limited ability to deal with non-identically and independently distributed data. To mitigate this problem, federated learning with personalization layers, a strategy similar to federated averaging but where each client is allowed to append custom layers to their local model, is explored. The two federated learning strategies will be evaluated on two datasets: 1) run-to-failure trajectories from power cycling of silicon-carbide metal-oxide semiconductor field-effect transistors, and 2) C-MAPSS, a well-known simulated dataset of turbofan jet engines. Two neural network model architectures commonly used in remaining useful life prediction, long short-term memory with multi-layer perceptron feature extractors, and convolutional gated recurrent unit, will be used for the evaluation. It is shown that similar or better performance is achieved when using federated learning compared to when the model is only trained on local data
Cathodic protection shielding of coated buried pipeline
No full textDuring the 2000s, the concept of cathodic protection (CP) shielding was first raised in open literature and remains debated between coatings professionals. The mechanism of CP shielding, and its understanding continue to be studied for different coatings with different approaches and using various techniques. From the CP shielding factors to the assessment methods, the published literature merits a deep analysis to capture the established knowledge and identify the research gaps to further tackle the issue for reliable coated buried structures. A holistic approach to this topic seems necessary where coatings ageing, cathodic protection, electrochemistry, and transport processes should be considered. In the first part of the present review, the recent works related to the understanding of CP shielding, coatings properties were considered before discussing the mechanisms involved underneath coatings. Transport phenomena and their relationship with cathodic protection performance in the presence of chemical and microbiological processes are discussed in the second part. Finally, CP shielding assessment methods and modeling works are presented and discussed from different perspectives.
Relating estimates of wood properties of birch to stem form, age and species
No full textBirch has long suffered from a lack of active forest management, leading many researchers to use material without a detailed management history. Data collected from three birch (Betula pendula Roth, B. pubescens Ehrh.) sites in southern Sweden were analyzed using regression analysis to detect any trends or differences in wood properties that could be explained by stand history, tree age and stem form. All sites were genetics trials established in the same way. Estimates of acoustic velocity (AV) from non-destructive testing (NDT) and predicted AV had a higher correlation if data was pooled across sites and other stem form factors were considered. A subsample of stems had radial profiles of X-ray wood density and ring width by year created, and wood density was related to ring number from the pith and ring width. It seemed likely that wood density was negatively related to ring width for both birch species. Linear models had slight improvements if site and species were included, but only the youngest site with trees at age 15 had both birch species. This paper indicated that NDT values need to be considered separately, and any predictive models will likely be improved if they are specific to the site and birch species measured. © 2023, The Author(s).Project funding : This work was financed by the research program FRAS—The Future Silviculture in Southern Sweden.</p
Flexible and Biocompatible Antifouling Polyurethane Surfaces Incorporating Tethered Antimicrobial Peptides through Click Reactions
No full textEfficient, simple antibacterial materials to combat implant-associated infections are much in demand. Herein, the development of polyurethanes, both cross-linked thermoset and flexible and versatile thermoplastic, suitable for “click on demand” attachment of antibacterial compounds enabled via incorporation of an alkyne-containing diol monomer in the polymer backbone, is described. By employing different polyolic polytetrahydrofurans, isocyanates, and chain extenders, a robust and flexible material comparable to commercial thermoplastic polyurethane is prepared. A series of short synthetic antimicrobial peptides are designed, synthesized, and covalently attached in a single coupling step to generate a homogenous coating. The lead material is shown to be biocompatible and does not display any toxicity against either mouse fibroblasts or reconstructed human epidermis according to ISO and OECD guidelines. The repelling performance of the peptide-coated materials is illustrated against colonization and biofilm formation by Staphylococcus aureus and Staphylococcus epidermidis on coated plastic films and finally, on coated commercial central venous catheters employing LIVE/DEAD staining, confocal laser scanning microscopy, and bacterial counts. This study presents the successful development of a versatile and scalable polyurethane with the potential for use in the medical field to reduce the impact of bacterial biofilms. This study was financed by Amicoat A/S. The authors are grateful for the analytical assistance from RISE scientists L. Brive, P. Borchardt, K. Johansson, and J. Somertune.</p
Video expert assessment of high quality video for Video Assistant Referee (VAR) : A comparative study
No full textThe International Football Association Board decided to introduce Video Assistant Referee (VAR) in 2018. This led to the need to develop methods for quality control of the VAR-systems. This article focuses on the important aspect to evaluate the video quality. Video Quality assessment has matured in the sense that there are standardized, commercial products and established open-source solutions to measure it with objective methods. Previous research has primarily focused on the end-user quality assessment. How to assess the video in the contribution phase of the chain is less studied. The novelties of this study are two-fold: 1) The user study is specifically targeting video experts i.e., to assess the perceived quality of video professionals working with video production. 2) Six video quality models have been independently benchmarked against the user data and evaluated to show which of the models could provide the best predictions of perceived quality. The independent evaluation is important to get unbiased results as shown by the Video Quality Experts Group. An experiment was performed involving 25 video experts in which they rated the perceived quality. The video formats tested were High-Definition TV both progressive and interlaced as well as a quarters size format that was scaled down half the size in both width and height. The videos were encoded with both H.264 and Motion JPEG for the full size but only H.264 for the quarter size. Bitrates ranged from 80 Mbit/s down to 10 Mbit/s. We could see that for H.264 that the quality was overall very good but dropped somewhat for 10 Mbit/s. For Motion JPEG the quality dropped over the whole range. For the interlaced format the degradation that was based on a simple deinterlacing method did receive overall low ratings. For the quarter size three different scaling algorithms were evaluated. Lanczos performed the best and Bilinear the worst. The performance of six different video quality models were evaluated for 1080p and 1080i. The Video Quality Metric for Variable Frame Delay had the best performance for both formats, followed by Video Multimethod Assessment Fusion method and the Video Quality Metric General model. This work was funded by Fédération Internationale de Football Association (FIFA) and Sweden´s Innovation Agency (VINNOVA, dnr. 2021-02107) through the Celtic-Next project IMMINENCE (C2020/2-2), which is hereby gratefully acknowledged.</p
Batteriförordningens* referenser till standarder och standardisering : En delrapport inom Re:Source projektet CIRC-BAT (2022-09-01 –2024-09-30)
No full text*EUROPAPARLAMENTETS OCH RÅDETS FÖRORDNING (EU) 2023/1542 av den 12 juli 2023 om batterier och förbrukade batterier, om ändring av direktiv 2008/98/EG och förordning (EU) 2019/1020 och om upphävande av direktiv 2006/66/EG</p
Measuring sustainable transformation of small and medium-sized enterprises using management systems standards
No full textSmall- and medium-sized enterprises (SMEs) represent a significant number of industries in need of moving towards more sustainable development. A sustainability perspective on business activities is today crucial for SMEs to achieve a new level of competitiveness. Identifying which is a suitable set of sustainability indicators for an individual SME is a big challenge. The availability of so many methods and systems can leave SMEs reluctant to implement them in their small business. Therefore, this research aims to create a sustainability maturity model for SMEs to visualize goals and assess progress on their transformation journey. Progress is assessed by indicators, exemplified by indicators of the Global Reporting Initiative and the maturity is verified as stepwise growth along international management system standards. Using the developed model, it is possible to determine the SMEs’ sustainability performance. The research has resulted in a stepwise classification of the organization’s maturity is compiled into training and auditing material in different regions and sectors. © 2024 The Author(s). Business Strategy and the Environment published by ERP Environment and John Wiley & Sons Ltd
The influence of recycling on the localized corrosion susceptibility of extruded AA6063 alloys
No full textAn approach involving the quantification of microstructure characterized by different techniques such as SEM, EDS, and SKPFM is statistically treated to provide a deeper insight into the influence of recycling AA6063 on localized corrosion susceptibility. Particularly, the intermetallic particles and the two forms of localized corrosion – pitting and intergranular corrosion are systematically documented, measured, and analyzed. Even trace amounts of Cu and Zn introduced into the alloy from recycling had a remarkable effect on the localized corrosion susceptibility. The study found that the initiation and early evolution of the two localized corrosions are in competition, and the predominance of one over the other is closely linked to the composition of the alloy, and microstructure. Recycled variants with higher trace Cu made the alloy more susceptible to pitting attack whereas higher trace Zn is linked with greater IGC susceptibility. The trace amount of higher Zn addition has a particularly beneficial effect on pitting susceptibility as it reduces the likelihood of pitting even in alloys with a higher trace Cu content. The SKPFM results obtained in this study provided a basis for the circumferential pitting susceptibility around intermetallic particles, as a higher volta potential difference (∆V) implied a higher driving force for corrosion. ∆V differences between the different variants were further explained based on trace recycled element distribution in the microstructure. The authors sincerely acknowledge the funding received from Vinnova, Sweden’s Innovation Agency (Project ID: 2022-02952).</p