MRC Laboratory of Molecular Biology
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Sustainable Measures for Protection of Structures Against Earthquake Induced Liquefaction
No full textSoil liquefaction can cause excessive damage to structures as witnessed in many recent earthquakes. The damage to small/medium-sized buildings can lead to excessive death toll and economic losses due to the sheer number of such buildings. Economic and sustainable methods to mitigate liquefaction damage to such buildings are therefore required. In this paper, the use of rubble brick as a material to construct earthquake drains is proposed. The efficacy of these drains to mitigate liquefaction effects was investigated, for the first time to include the effects of the foundations of a structure by using dynamic centrifuge testing. It will be shown that performance of the foundation in terms of its settlement was improved by the rubble brick drains by directly comparing them to the foundation on unimproved, liquefiable ground. The dynamic response in terms of horizontal accelerations and rotations will be compared. The dynamic centrifuge tests also yielded valuable information with regard to the excess pore pressure variation below the foundations both spatially and temporally. Differences of excess pore pressures between the improved and unimproved ground will be compared. Finally, a simplified 3D finite element analysis will be introduced that will be shown to satisfactorily capture the settlement characteristics of the foundation located on liquefiable soil with earthquake drains
Approximate Message Passing with Spectral Initialization for Generalized Linear Models.
No full textWe consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a family of iterative algorithms with many appealing features: the performance of AMP in the high-dimensional limit can be succinctly characterized under suitable model assumptions; AMP can also be tailored to the empirical distribution of the signal entries, and for a wide class of estimation problems, AMP is conjectured to be optimal among all polynomial-time algorithms. However, a major issue of AMP is that in many models (such as phase retrieval), it requires an initialization correlated with the ground-truth signal and independent from the measurement matrix. Assuming that such an initialization is available is typically not realistic. In this paper, we solve this problem by proposing an AMP algorithm initialized with a spectral estimator. With such an initialization, the standard AMP analysis fails since the spectral estimator depends in a complicated way on the design matrix. Our main contribution is a rigorous characterization of the performance of AMP with spectral initialization in the high-dimensional limit. The key technical idea is to define and analyze a two-phase artificial AMP algorithm that first produces the spectral estimator, and then closely approximates the iterates of the true AMP. We also provide numerical results that demonstrate the validity of the proposed approach
Improved dynamic responses of room-temperature operable field-effect-transistor gas sensors enabled by programmable multi-spectral ultraviolet illumination
No full textRecently, with the increased importance of low-power human-based wearable technology incorporating multiple sensory systems, room-temperature operating sensory devices are of significant interest. In this work, we demonstrate a versatile approach to realize room-temperature operable and fast recovery amorphous oxide semiconductor (AOS)-based gas sensors using multi-wavelength ultraviolet (UV) illumination. Particularly, illumination of UV light with different wavelengths enabled an amorphous indium-gallium-zinc oxide (a-IGZO) thin film transistor (FET)-based gas sensor to monitor the sensing behaviours of nitrogen dioxide (NO2) at various concentrations down to sub-ppm level. Our systematic investigation exhibited that time period taken for reacting and detaching the NO2 gas from the surface of AOS could be significantly controlled down to 32 s and several minutes, respectively, without any thermal energy. The key point of the variable properties of NO2 sensing performances in the a-IGZO FET is the generation of diverse electron-hole-pairs owing to the difference of the photonic energy applied to the sensor. Our work introduced in this research may provide a simple and efficient way for enhancing gas-sensing properties of AOS FET gas sensors by enabling programmable multi-spectral UV illumination approaches
Single-lane > 100 Gb/s CAP-based data transmission over VCSEL-MMF links using low-complexity equalization
No full textIn this paper, we review recent work on the development of a novel low-complexity equalizer that can enable single-lane <100 Gb/s short-reach optical links based on carrierless amplitude and phase modulation. This equalizer, named the CAP equalizer, can mitigate the transmission impairments in the link due to a non-ideal channel frequency response, providing significant performance advantage over conventional FFE and DFE equalizers and enabling higher data rates and longer reach. Its use is demonstrated in a VCSEL-based MMF link achieving data transmission of 112 and 124 Gb/s over 100 m OM4 MMF
Contributions to Dynamic Behaviour of Materials Professor John Edwin Field, FRS 1936–2020
No full textProfessor John Edwin Field passed away on October 21st, 2020 at the age of 84. Professor Field was widely regarded as a leader in high-strain rate physics and explosives. During his career in the Physics and Chemistry of Solids (PCS) Group of the Cavendish Laboratory at Cambridge University, John made major contributions into our understanding of friction and erosion, brittle fracture, explosives, impact and high strain-rate effects in solids, impact in liquids, and shock physics. The contributions made by the PCS group are recognized globally and the impact of John’s work is a lasting addition to our knowledge of the dynamic effects in materials. John graduated 84 Ph.D. students and collaborated broadly in the field. Many who knew him attribute their success to the excellent grounding in research and teaching they received from John Field
Particulate emissions from turbulent diffusion flames with entrained droplets: A laboratory simulation of gas flaring emissions
No full textGlobal flaring volume exceeds 140 billion m3 annually and flares are a key source of particulate air pollution. During flowback operations subsequent to fracturing of a well, droplets of flowback water—with varying levels of dissolved salts—can be entrained in the flared gas. Despite the widespread prevalence of fracturing, very little is known about the properties of particle emissions from such flares. To study these properties, we used a laboratory pipe flare producing a turbulent diffusion flame without and with entrained droplets. Entrained droplets of deionized water, sodium chloride solution, and solutions representing two typical flowback waters in Canada (Cardium and Duvernay) were used. Three different gas compositions (consisting of C1 to C7 alkanes, carbon dioxide, and nitrogen) representative of flares in the upstream oil and gas sector in Alberta, Canada were studied. The results showed that the salt in the entrained flowback droplets increased the particle concentration by about one order of magnitude by forming freshly nucleated salt particles. Moreover, soot concentration increased as a result of entrained salt. Effective density results showed that small particles (300 nm) were mostly soot—a result also confirmed by transmission electron microscopy (TEM). Electron micrographs showed that the majority of particles were either individual salt particles or internally-mixed soot-salt particles. The inorganic salt particles mainly consisted of Na and Cl, the two most abundant elements in flowback water. Raman spectroscopy indicated that the salt had much less (or no) impact on graphitic nanostructure of soot, while the fuel blend had a significant effect. The results of this study are significant as they reveal that current emission inventories based on flaring of gases only may underestimate soot emissions from flares with entrained droplets
Improving food allergen management in food manufacturing: An incentive-based approach
No full textThe improvement of food allergen management among food manufacturers has been encumbered by a lack of behavioural incentives to adopt good practices (e.g. multiple verifications and adoption of advanced technologies etc.). This study aims to tackle this challenge by proposing an incentive-based approach. We develop this approach by compiling, through a scoping literature review, a comprehensive list of operational errors in food allergen management for food manufacturers; identifying incentives with a behavioural cost‒benefit approach; and integrating machine learning and human learning into a coherent framework for sustaining behavioural incentives. Such a synthesised approach could help to develop advanced food traceability technologies, more effective regulations and better food safety culture for improving food allergen management
Spatiotemporal Attention-Based Graph Convolution Network for Segment-Level Traffic Prediction
No full textTraffic prediction, as a core component of intelligent transportation systems (ITS), has been investigated thoroughly in the literature. Nevertheless, timely accurate traffic prediction still remains an open challenge due to the nonlinearities and complex patterns of traffic flows. In addition, most of the existing traffic prediction methods focus on grid-based computing problems (e.g., crowd in-out flow prediction) and point-based computing problems (e.g., traffic detector data prediction), ignoring the segment-based traffic prediction tasks. In this study, we propose an attention-based spatiotemporal graph attention network (AST-GAT) for segment-level traffic speed prediction. In particular, a multi-head graph attention block is designed to capture the spatial dependencies among road segments. Then, a component fusion block is built for speed, volume, and weather information integration. Finally, an attention-based Long short-term memory (LSTM) block is constructed for temporal dependency learning as well as segment-based speed prediction. Experiments on a real-world dataset from Highways England demonstrate that the proposed AST-GAT model outperforms the state-of-the-art baselines, providing an efficient tool for segment-based traffic prediction and therefore filling the gap between point-based and grid-based predictions
Paradoxical relationships between active transport and global protein distributions in neurons
No full textNeural function depends on continual synthesis and targeted trafficking of intracellular components, including ion channel proteins. Many kinds of ion channels are trafficked over long distances to specific cellular compartments. This raises the question of whether cargo is directed with high specificity during transit or whether cargo is distributed widely and sequestered at specific sites. We addressed this question by experimentally measuring transport and expression densities of Kv4.2, a voltage-gated transient potassium channel that exhibits a specific dendritic expression that increases with distance from the soma and little or no functional expression in axons. In over 500 h of quantitative live imaging, we found substantially higher densities of actively transported Kv4.2 subunits in axons as opposed to dendrites. This paradoxical relationship between functional expression and traffic density supports a model—commonly known as the sushi belt model—in which trafficking specificity is relatively low and active sequestration occurs in compartments where cargo is expressed. In further support of this model, we find that kinetics of active transport differs qualitatively between axons and dendrites, with axons exhibiting strong superdiffusivity, whereas dendritic transport resembles a weakly directed random walk, promoting mixing and opportunity for sequestration. Finally, we use our data to constrain a compartmental reaction-diffusion model that can recapitulate the known Kv4.2 density profile. Together, our results show how nontrivial expression patterns can be maintained over long distances with a relatively simple trafficking mechanism and how the hallmarks of a global trafficking mechanism can be revealed in the kinetics and density of cargo
