High temperature cobalt-base alloy Patent

High temperature cobalt-base alloy resistant to corrosion by liquid metals and to sublimation in vacuum environmen

Effect of variations in silicon and iron content on embrittlement of L-605 /HS-25/

Silicon and iron content effects on ductility and tensile strength of cobalt alloy after agin

Nasa developments in cobalt-base superalloys

Chemical, mechanical and physical properties of cobalt-refractory-metal superalloys for high temperature aerospace application

Development of a cobalt-tungsten ferromagnetic, high-temperature, structural alloy

Cobalt-tungsten ferromagnetic, high temperature structural alloy for rotor applications in space power generator

Semantically enhancing multimedia lifelog events

Lifelogging is the digital recording of our everyday behaviour in order to identify human activities and build applications that support daily life. Lifelogs represent a unique form of personal multimedia content in that they are temporal, synchronised, multi-modal and composed of multiple media. Analysing lifelogs with a view to supporting content-based access, presents many challenges. These include the integration of heterogeneous input streams from different sensors, structuring a lifelog into events, representing events, and interpreting and understanding lifelogs. In this paper we demonstrate the potential of semantic web technologies for analysing lifelogs by automatically augmenting descriptions of lifelog events. We report on experiments and demonstrate how our re- sults yield rich descriptions of multi-modal, multimedia lifelog content, opening up even greater possibilities for managing and using lifelogs

Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201

Performative interaction in public space

Building on the assumption that every human action in public space has a performative aspect, this workshop seeks to explore issues of interactions with technology in public settings. More and more interfaces are used in public on an everyday basis. Simultaneously, metaphors from performance and theatre studies find their way into research on these interfaces, addressing how interaction with technology can be understood in a performative sense. However, the term 'performativity' is rarely addressed in ways that accentuate its nuances and its analytic power, and this is the focus of the workshop. We will examine the design of performative technologies, the evaluation of user experience, the importance of spectator and performer roles, and the social acceptability of performative actions in public spaces

Perspective: Current advances in solid-state NMR spectroscopy

In contrast to the rapid and revolutionary impact of solution-state Nuclear Magnetic Resonance (NMR) on modern chemistry, the field of solid-state NMR has matured more slowly. This reflects the major technical challenges of much reduced spectral resolution and sensitivity in solid-state as compared to solution-state spectra, as well as the relative complexity of the solid state. In this perspective, we outline the technique developments that have pushed resolution to intrinsic limits and the approaches, including ongoing major developments in the field of Dynamic Nuclear Polarisation, that have enhanced spectral sensitivity. The information on local structure and dynamics that can be obtained using these gains in sensitivity and resolution is illustrated with a diverse range of examples from large biomolecules to energy materials and pharmaceuticals and from both ordered and highly disordered materials. We discuss how parallel developments in quantum chemical calculation, particularly density functional theory, have enabled experimental data to be translated directly into information on local structure and dynamics, giving rise to the developing field of “NMR crystallography

The potential of wildflower strips to enhance pollination services in sweet cherry orchards grown under polytunnels

Sweet cherry production benefits from insect pollination, but the extent to which wildflower strips can boost pollinator visitation under polytunnels is unknown. Wildflowers were established in alleyways between tree rows under polytunnels in 10 commercial cherry orchards. Their management involved either a single cut in September (Standard Wildflower Strips (SWS)) or being actively maintained to 20 cm with regular cutting (Actively Managed Wildflower Strips (AMWS)), compared with unsown Control Strips (CS). Flower visitors of cherry and wildflowers were recorded by visual observations for 3 years (2017–2019), while cherry production (quantity and quality) was assessed in 2019. In total, 67 visitor species were identified; managed commercial species (Apis mellifera and Bombus terrestris) made up ~74% of all records. During the cherry blossom period (anthesis), AMWS had the highest visitor density to cherry blossoms compared with CS and SWS but no significant difference in harvestable fruit was recorded. After anthesis, greater visitor density, diversity and richness were observed in both wildflower treatments compared with CS, being greatest in SWS, which was consistent with differences in floral communities between treatments. Although visitor density was not correlated with fruit set, pollinating insects were key for fruit yields and quality. Fruit set was ~17% from blossoms exposed to visitors compared with <1% when excluded. Furthermore, hand pollination resulted in ~32% fruit set, indicating greatest pollination deficits in CS (~50%) compared with AMWS (~28%) and SWS (~35%). Synthesis and applications. Sweet cherry is highly dependent on pollinators to underpin commercial yields, and pollination deficits exist under polytunnels. Growers should, therefore, reconsider their pollination strategies and look to combine effective pollinator management with polytunnel use to mitigate deficits; establishing and actively managing wildflowers in alleyways could enhance wild visitors and pollination