MRC Laboratory of Molecular Biology
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Effect of Biochar Filler on the Hydration Products and Microstructure in Portland Cement-Stabilized Peat
No full textLaboratory tests demonstrated that biochar filler added to portland cement stabilized peat results in an increase of unconfined compressive strength comparable with that of a sand filler. The strength increase is significantly higher when biochar is ground to a size below 75 μm. This study investigated the changes in mineralogy, texture, and microstructure during the early hydration of cement mixed with peat and biochar filler to identify the mechanisms responsible for the strength increase. The results show that the biochar surface catalyzes nucleation of hydration products. Labile carbon in biochar promotes carbonation, with precipitation of calcite within its cells and on its surface, as well as formation of hemi and monocarboaluminate, two stable calcium aluminate hydrate (AFm) phases. For larger fragments of biochar, early hydration products do not reach the inner cells. Instead, the fine fragments tend to be fully covered, leading to a more homogeneous spatial distribution of cement and voids
Product-service systems evolution in the era of Industry 4.0
No full textRecent economic transformations have forced companies to redefine their value propositions, increasing traditional product offerings with supplementary services—the so-called Product-Service System (PSS). Among them, the adoption of Industry 4.0 technologies is very common. However, the directions that companies are undertaking to offer new value to their customers in the Industry 4.0 have not yet been investigated in detail. Based on a focus group, this paper contributes to this understanding by identifying the main trajectories that would shape a future scenario in which PSS and Industry 4.0 would merge. In addition, future research directions addressing (a) the transformation of the PSS value chain into a PSS ecosystem, (b) the transformation inside a single company towards becoming a PSS provider, and (c) the digital transformation of the traditional PSS business model are identified
Bio-assembling Macro-Scale, Lumenized Airway Tubes of Defined Shape via Multi-Organoid Patterning and Fusion.
No full textEpithelial, stem-cell derived organoids are ideal building blocks for tissue engineering, however, scalable and shape-controlled bio-assembly of epithelial organoids into larger and anatomical structures is yet to be achieved. Here, a robust organoid engineering approach, Multi-Organoid Patterning and Fusion (MOrPF), is presented to assemble individual airway organoids of different sizes into upscaled, scaffold-free airway tubes with predefined shapes. Multi-Organoid Aggregates (MOAs) undergo accelerated fusion in a matrix-depleted, free-floating environment, possess a continuous lumen, and maintain prescribed shapes without an exogenous scaffold interface. MOAs in the floating culture exhibit a well-defined three-stage process of inter-organoid surface integration, luminal material clearance, and lumina connection. The observed shape stability of patterned MOAs is confirmed by theoretical modelling based on organoid morphology and the physical forces involved in organoid fusion. Immunofluorescent characterization shows that fused MOA tubes possess an unstratified epithelium consisting mainly of tracheal basal stem cells. By generating large, shape-controllable organ tubes, MOrPF enables upscaled organoid engineering towards integrated organoid devices and structurally complex organ tubes
SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data
No full textMachine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition. However, the performance of such models in real-world settings largely depends on the availability of large datasets that captures diverse behaviors. Recently, studies in computer vision and natural language processing have shown that leveraging massive amounts of unlabeled data enables performance on par with state-of-the-art supervised models. In this work, we present SelfHAR, a semi-supervised model that effectively learns to leverage unlabeled mobile sensing datasets to complement small labeled datasets. Our approach combines teacher-student self-training, which distills the knowledge of unlabeled and labeled datasets while allowing for data augmentation, and multi-task self-supervision, which learns robust signal-level representations by predicting distorted versions of the input. We evaluated SelfHAR on various HAR datasets and showed state-of-the-art performance over supervised and previous semi-supervised approaches, with up to 12% increase in F1 score using the same number of model parameters at inference. Furthermore, SelfHAR is data-efficient, reaching similar performance using up to 10 times less labeled data compared to supervised approaches. Our work not only achieves state-of-the-art performance in a diverse set of HAR datasets, but also sheds light on how pre-training tasks may affect downstream performance
Multi-Center Hyperbonding in Phase-Change Materials
No full textA comprehensive understanding of chemical interactions underlying the network structure of chalcogenide materials is a crucial prerequisite for comprehending their microscopic structures, physicochemical properties, and capabilities for current or potential applications. However, for many chalcogenide materials, an inherent difficulty is often present in investigating their chemical properties, due to the involvement of delocalized bonding and non-bonding (“lone-pair”) electrons, which requires interaction mechanisms beyond that of conventional two-center, two-electron covalent bonding. Herein, some recent progress in the development of new interatomic interaction models for chalcogenides is reviewed, in particular focusing on the multi-center hyperbonding model, proposed in an effort to resolve this issue. The capability of this model in elucidating a diversity of interesting material properties of phase-change materials (PCMs) is highlighted, including Ge2Sb2Te5 (GST). These include the propensity of high coordination numbers of constituent atoms, linear triatomic bonding geometries with short and long bonds (often ascribed to the effect of a Peierls distortion), abnormally large Born effective charges of crystalline GST, large optical contrast between amorphous and crystalline GST, ultrafast crystallization speed of amorphous GST, and the chemical origin differentiating non-PCM from PCM chalcogenide materials. Other bonding models for these materials are also briefly discussed
Ferroelectric properties of BaTiO<inf>3</inf>-BiScO<inf>3</inf> weakly coupled relaxor energy-storage ceramics from first-principles calculations
No full textWeakly coupled relaxor ferroelectrics BaTiO3-BiMeO3 (Me symbolizes trivalent or averagely trivalent cations) have received growing interest for energy-storage applications due to their extremely low remnant polarizations and slim hysteresis, which therefore provides high energy density and energy efficiency. Although large experimental progress has been made, there is still a lack of theoretical understanding from the electronic and atomic point of view. In this paper, by targeting the prototypical BaTiO3-BiScO3 (BT-BS) weakly coupled energy-storage ceramics, we investigated the ferroelectric properties at the electronic and atomic scale using first-principles calculations coupled with a phenomenological theory model. Results show that the lattice volumes expand with the increase of BS content, and an indirect band structure was found for the BT-BS ceramics. Ferroelectric polarizations become reduced and hysteresis loops get slimmer with the addition of BS. Moreover, large ionic displacement disorder of Ti/Sc atoms and strong orbital hybridization of Bi/Ti atoms with O atoms were discovered, which should serve as an origin of the reduced ferroelectric polarization and contribute to the weakly coupled relaxor behavior of the BT-BS ceramics. The employed methods and conclusions in this work should also be applicable to other BaTiO3-BiMeO3 ceramic systems, shedding light on the further enhancement of energy-storage performance from the electronic and atomic scale
A Simple Coupled Analysis of an Arch Bridge Subjected to Tunnelling-Induced Movements
No full textDue to urban tunnelling activities, bridges may be subjected to excavation-induced ground movements that can affect their serviceability. The Tideway Tunnel being constructed in London involves multiple under-crossings of bridges along the River Thames. The monitoring data collected will provide an opportunity for the application and validation of numerical methods for tunnel-bridge interaction. Although field monitoring data are not yet available for publication, the response of the Grosvenor Bridge at Battersea to tunnelling-induced displacements is examined in this work with numerical models. In particular, a simple approach for the preliminary assessment of tunnelling impact on framed structures on shallow foundations is presented; the adopted two-stage finite element model uses integral forms of Mindlin’s solutions to calculate the soil stiffness matrix, while structural members including the piers, arches, deck and spandrel columns are modelled as beam elements in the superstructure stiffness matrix. Preliminary results provide useful insights into the response of arch bridges to tunnelling-induced ground movements at different levels of model complexity
Performance assessment of urban goods vehicles
No full textControlling greenhouse gas emissions is becoming increasingly more important. With road freight contributing to a significant amount of energy usage, finding ways to improve this sector will, in turn, lead to large reductions in carbon dioxide emissions, with one method to achieve this being to use larger vehicles. Currently, prescriptive legislation dictates the dimensions a vehicle can take. An alternative to this is to use ‘Performance-Based Standards (PBS)’. This involves determining a set of manoeuvres and performance metrics that a vehicle must perform and pass in order to be road-worthy, instead of saying a vehicle can be a certain size or a certain weight. Through innovation and optimisation, using this method will then allow larger vehicles that are safe for driving on the road to be built. The research conducted here involved creating a PBS framework based on low-speed manoeuvrability for rigid delivery vehicles as well as assessing the high-speed stability of articulated vehicles to determine whether they would be safe for use on urban roads. Additionally, design changes such as incorporating rear axle steering were considered to determine whether vehicles that had failed the proposed PBS framework could be made to pass
Growth and characterisation studies of eu<inf>3</inf>o<inf>4</inf> thin films grown on si/sio<inf>2</inf> and graphene
No full textWe report the growth, structural and magnetic properties of the less studied Eu-oxide phase, Eu3O4, thin films grown on a Si/SiO2 substrate and Si/SiO2/graphene using molecular beam epitaxy. The X-ray diffraction scans show that highly textured crystalline Eu3O4 (001) films are grown on both substrates, whereas the film deposited on graphene has a better crystallinity than that grown on the Si/SiO2 substrate. The SQUID measurements show that both films have a Curie temperature of ∼ 5.5 ± 0.1 K, with a magnetic moment of ∼ 320 emu/cm3 at 2 K. The mixed valence of the Eu cations has been confirmed by the qualitative analysis of the depth-profile X-ray photoelectron spectroscopy measurements with the Eu2+: Eu3+ ratio of 28: 72. However, surprisingly, our films show no metamagnetic behaviour as reported for the bulk and powder form. Furthermore, the microscopic optical images and Raman measurements show that the graphene underlayer remains largely intact after the growth of the Eu3O4 thin films
Latency-Aware Horizontal Computation Offloading for Parallel Processing in Fog-Enabled IoT
No full textIn this article, we propose a two-step distributed horizontal architecture for computation offloading in a fog-enabled Internet of Things environment—HD-Fog—to minimize the overall energy consumption, and latency while executing hard real-time applications. HD stands for the horizontal distribution of the tasks in the fog layer. Each sensor in the user devices independently captures data of varying formats. Parallel execution on these data is possible based on its directed acyclic task graph (DATG), and the corresponding results facilitate the ease of decision-making. Toward this, in HD-Fog, the sensor nodes in user devices offload their tasks to a nearby fog node based on a greedy selection criterion. This fog node then further offloads the smaller subtasks, based on the DATG, among other fog nodes for parallel execution. Through extensive real-life metric-based emulation and comparison against traditional Fog and Cloud computing schemes, we observe that our approach 1) reduces the overall operational delays by 29% and 96%, and 2) offers promising speedup values. The proposed HD-Fog scheme also indicates a reduction in energy consumption by 30% compared to traditional fog computing schemes