Lightweight adjustable partition system: evaluation of resistance to horizontal loads and functional failure from impacts

This paper presents and discusses the results of the serviciability and use condition tests carried on an innovative solution for partitions, designated AdjustMembrane developed within a research project. The proposed system is a modular non-loadbearing wall, tensioned between the pavements and ceiling slabs, which are used as anchoring elements. It allows several advantages, related with the weight reduction to achieve a good sustainable performance, such as the reduction of construction costs, energy, and materials, and it is easy to recycle and to reuse, allowing self-construction. Apart from a general presentation of the partition technology, this paper presents and discusses the results of experimental tests carried out. From the results obtained, it is possible to conclude that the solution fulfils the requirements for this typology of wall in terms of resistance to horizontal loads induced by soft and hard body impacts.

Trabalhos para casa no 1.ºCiclo: ter ou não ter, eis a questão

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

Concise server-wide causality management for eventually consistent data stores

Large scale distributed data stores rely on optimistic replication to scale and remain highly available in the face of net work partitions. Managing data without coordination results in eventually consistent data stores that allow for concurrent data updates. These systems often use anti-entropy mechanisms (like Merkle Trees) to detect and repair divergent data versions across nodes. However, in practice hash-based data structures are too expensive for large amounts of data and create too many false conflicts. Another aspect of eventual consistency is detecting write conflicts. Logical clocks are often used to track data causality, necessary to detect causally concurrent writes on the same key. However, there is a nonnegligible metadata overhead per key, which also keeps growing with time, proportional with the node churn rate. Another challenge is deleting keys while respecting causality: while the values can be deleted, perkey metadata cannot be permanently removed without coordination. Weintroduceanewcausalitymanagementframeworkforeventuallyconsistentdatastores,thatleveragesnodelogicalclocks(BitmappedVersion Vectors) and a new key logical clock (Dotted Causal Container) to provides advantages on multiple fronts: 1) a new efficient and lightweight anti-entropy mechanism; 2) greatly reduced per-key causality metadata size; 3) accurate key deletes without permanent metadata.