MRC Laboratory of Molecular Biology
CUED - Cambridge University Engineering DepartmentNot a member yet
45551 research outputs found
Sort by
Repeatability precision error analysis of the distributed fiber optic strain monitoring
No full textThe precision error of the Brillouin optical time domain reflectometry (BOTDR)-based distributed fiber optic strain measurement is normally evaluated based on strain change from the initial zero strain state. In many structural health monitoring applications, however, there is initial strain caused by the installation process of a fiber optic sensor cable to a structure. Engineers are interested in the incremental strain profile from the initial strain profile to assess the performance of the structure. The initial strain profile is often not constant throughout the cable length due to the manner that the fiber optic cables are installed (e.g., gluing, clamping, or embedding). This uneven strain distribution causes precision error in the strain incremental values, which in turn leads to difficulty in data interpretation. This paper discusses why large initial strain variation (or initial strain gradient) increases the precision error of the subsequent incremental strain reading and how to evaluate the magnitude of such precision error. A relationship between strain gradient and precision error is demonstrated. A sectional shift method is proposed to minimize the precision error. Results from laboratory tests and a field case study show that the method can reduce the precision error approximately 50% when the strain gradient is large
OESense: Employing occlusion effect for in-ear human sensing
No full textSmart earbuds are recognized as a new wearable platform for personal-scale human motion sensing. However, due to the interference from head movement or background noise, commonly-used modalities (e.g. accelerometer and microphone) fail to reliably detect both intense and light motions. To obviate this, we propose OESense, an acoustic-based in-ear system for general human motion sensing. The core idea behind OESense is the joint use of the occlusion effect (i.e., the enhancement of low-frequency components of bone-conducted sounds in an occluded ear canal) and inward-facing microphone, which naturally boosts the sensing signal and suppresses external interference. We prototype OESense as an earbud and evaluate its performance on three representative applications, i.e., step counting, activity recognition, and hand-to-face gesture interaction. With data collected from 31 subjects, we show that OESense achieves 99.3% step counting recall, 98.3% recognition recall for 5 activities, and 97.0% recall for five tapping gestures on human face, respectively. We also demonstrate that OESense is compatible with earbuds' fundamental functionalities (e.g. music playback and phone calls). In terms of energy, OESense consumes 746 mW during data recording and recognition and it has a response latency of 40.85 ms for gesture recognition. Our analysis indicates such overhead is acceptable and OESense is potential to be integrated into future earbuds
Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-differentiable Priors
No full textThe use of nondifferentiable priors in Bayesian statistics has become increasingly popular, in particular in Bayesian imaging analysis. Current state-of-the-art methods are approximate in the sense that they replace the posterior with a smooth approximation via Moreau-Yosida envelopes, and apply gradient-based discretized diffusions to sample from the resulting distribution. We characterize the error of the Moreau-Yosida approximation and propose a novel implementation using underdamped Langevin dynamics. In misson-critical cases, however, replacing the posterior with an approximation may not be a viable option. Instead, we show that piecewise-deterministic Markov processes (PDMP) can be used for exact posterior inference from distributions satisfying almost everywhere differentiability. Furthermore, in contrast with diffusion-based methods, the suggested PDMP-based samplers place no assumptions on the prior shape, nor require access to a computationally cheap proximal operator, and consequently have a much broader scope of application. Through detailed numerical examples, including a nondifferentiable circular distribution and a nonconvex genomics model, we elucidate the relative strengths of these sampling methods on problems of moderate to high dimensions, underlining the benefits of PDMP-based methods when accurate sampling is decisive. Supplementary materials for this article are available online
Numerical Study on Effect of Current Injection Methods on Terminal Resistance of Superconducting Compact Cables
No full textImplement of low-resistive and compact terminal between superconducting cables and bus-bars is one of the most important challenges for industrial application of conductor on round core (CORC) cables. In this paper, a three-dimensional numerical model capable of simulating the terminal resistance and joint resistance of CORC cables is developed and validated by experimental data. On basis of this, the effect of different current injection methods on terminal resistance and the effect of trimming of HTS tapes on current distribution are discussed in this paper. Results shows a wide range of variation in terminal resistance and the homogeneity of current distribution. We expect conclusions obtained from this paper could provide guidelines for commercial and practical terminal fabrication of CORC cables
Bioethanol from autoclaved municipal solid waste: Assessment of environmental and financial viability under policy contexts
No full textGlobally, 2.01 billion tonnes of municipal solid waste (MSW) were generated in 2016, about 37% of which was disposed of into landfills. This study evaluates the environmental and financial viability of producing ethanol from autoclaved MSW via fermentation. Experimental screening of four different microorganisms (i.e., S. cerevisiae, Z. mobilis, E. coli, and S. pombe) and process modelling indicate that MSW-derived ethanol can significantly reduce greenhouse gas emissions relative to gasoline (84% reduction following EU Renewable Energy Directive accounting methodology, and by 156–231% reduction following the US Energy Independence and Security Act methodology). Utilisation of wastes for biofuel production in the UK benefits from policy support and financial support for renewable fuels (Renewable Transport Fuel Certificates). Financial analysis highlights that microorganisms achieving higher ethanol yield and productivity (S. cerevisiae and Z. mobilis) can achieve financial viability with higher cumulative net present value than E. coli, S. pombe. However, the positive net present value can be achieved primarily due to the benefit of gate fees received by diverting wastes to autoclave and ethanol production (64% of total revenues), rather than from revenues from ethanol sales (7% of total revenues). Key process improvements must be achieved to improve the financial viability of ethanol production from MSW and deliver a clear advantage over waste incineration, specifically improving hydrolysis yield, reducing enzyme loading rate and, to a lesser extent, increasing solid loading rate. The results provide significant insights into the role of policy and technology development to achieve viable waste-to-biofuel systems
XiA: Send-it-Anyway Q-Routing for 6G-Enabled UAV-LEO Communications
No full textIn this paper, we propose a delay-aware Q-learning-based routing algorithm - XiA - for sending data from users to nearest Access Points (APs) through Unmanned Aerial Vehicle (UAV) swarms communicating using 6G technology. These UAVs assist the ground networks in overcoming communication voids while maneuvering through different demographics. However, the communication links in the THz band have limited transmission range, causing the UAVs to frequently disconnect from the swarm. We overcome such issues by waiting until the UAV comes in contact with others in case of non-time-sensitive data. In the case of time-sensitive data, the UAVs send the data to the APs through Low Earth Orbit (LEO) satellites. To empower XiA to adapt to the changing environments and expensive delays in LEO, we model the rewards by accounting for spreading and absorption in the 6G channels, and Doppler effect and pointing error in the satellite channel. We show our bias for the parameters through extensive simulations and prove that the Q-model in XiA achieves convergence under all conditions. Additionally, in comparison with state-of-the-art solutions, we observe that XiA offers an improved delay of 82%
3D field confinement in the near-field interaction between graphene and Si/SiGe axially heterostructured NWs
No full textInterest in the integration of graphene and semiconductor nanowires (NWs) increased dramatically during the last two decades along with the overwhelming development of graphene technology. The possibility of combining the countless properties of graphene with the singular optical behavior of semiconductor NWs leads the way to the design of unique photonic nanodevices. In this work, the optical response of Si/SiGe axially heterostructured NWs deposited over a graphene monolayer is investigated. The results demonstrate the enhancement of the graphene Raman signal under the influence of the NW. Moreover, the presence of an axial heterojunction in the NW is shown to locally hinder this enhancement through the full confinement of the incident electromagnetic field inside the NW body around the heterojunction. This complex interaction could be the basis for near-field probes for molecules or 2D materials, and optoelectronic devices including graphene/NW interfaces
Investigating the thermal behaviour of geothermal pavements using Thermal Response Test (TRT)
No full textGeothermal pavements represents a novel approach to shallow geothermal energy applications, in which horizontal ground heat exchangers are implemented within the pavement structure instead of traditional purpose-built trenches, thus decreasing capital costs. This study aims to better understand the feasibility and potential of these systems, by investigating the thermal response of the ground in a full scale geothermal pavements system, the first of its kind in Australasia. For this purpose, a fully instrumented geothermal pavements segment, measuring 20 m × 10 m, was constructed in the city of Adelaide, Australia. The geothermal pavement was subjected to Thermal Response Testing (TRT) and numerical modelling is adopted herein and validated using TRT data to further understand the ground response. In addition to providing insights on the capacity of energy provision for geothermal pavements, this work also introduces and discusses various methods of TRT data analysis for the geothermal pavement, specifically for obtaining the effective ground thermal conductivity, a key parameter in shallow geothermal design. The results indicate that from the considered methods, the conventional semi-log method can lead to overestimation of thermal conductivity, the guarded hot plate model tends to underestimate its value and detailed numerical modelling is most accurate, but computationally more expensive. The results also show that the radius of influence of the geothermal pavement in the examined case is close to 0.5 m and even though the geothermal pavement is considerably affected by the ambient temperature, it can be a viable solution for heating and cooling purposes, showing a heat exchange of 50.2 W/m2 and a rate per length of the pipe of 25 W/m in the case analysed here
A Co-Design Approach for a Smart Cooking Appliance. The Application of a Domain Specific Language
No full textOur environment, whether at work, in public spaces, or at home, is becoming more connected, adaptive and increasingly responsive. This is due in part to the significant number of sensors that detect information and data around us. Connected technologies are also emerging as a support to address daily challenges for people with disabilities and for ageing people, bringing care from hospitals into the community and increased provision of health services into homes. Meal preparation, even when it involves simply heating ready-made food, can be perceived as a complex process for people with disabilities. This research aimed to prototype, using a co-Design approach, a Community Supported Appliance (CSA) by developing a Domain Specific Language (DSL), precisely created for a semi/automated cooking process. The DSL was shaped and expressed in the users’ idiom and allowed the CSA to support independence for users while performing daily cooking activities