MRC Laboratory of Molecular Biology
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Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period
No full textThe emergence of COVID-19 pandemic is causing tremendous impact on our daily lives, including the way people interact with buildings. Leveraging the advances in machine learning and other supporting digital technologies, recent attempts have been sought to establish exciting smart building applications that facilitates better facility management and higher energy efficiency. However, relying on the historical data collected prior to the pandemic, the resulting smart building applications are not necessarily effective under the current ever-changing situation due to the drifts of data distribution. This paper investigates the bidirectional interaction between human and buildings that leads to dramatic change of building performance data distributions post-pandemic, and evaluates the applicability of typical facility management and energy management applications against these changes. According to the evaluation, this paper recommends three mitigation measures to rescue the applications and embedded machine learning algorithms from the data inconsistency issue in the post-pandemic era. Among these measures, incorporating occupancy and behavioural parameters as independent variables in machine learning algorithms is highlighted. Taking a Bayesian perspective, the value of data is exploited, historical or recent, pre- and post-pandemic, under a people-focused view
Recent advances of electrochemical sensors for detecting and monitoring ROS/RNS
No full textReactive oxygen species (ROS) and reactive nitrogen species (RNS) are prominent metabolic products which show well-established significance. At relatively low concentrations, they play multifaceted roles in regulating a number of physiological processes. Overproduction of ROS/RNS contributes to the pathogenesis of a plethora of physiological disorders, including but not limited to cardiovascular diseases, neurodegenerative diseases, cancer. Electrochemistry have been extensively used for detecting and monitoring ROS/RNS, benefiting from their inherent advantages including fast response, low costs, real-time detection, high sensitivity and selectivity. This review focuses on three types of ROS/RNS (H2O2, O2−, NO) with emphasis on their electrochemical detection/monitoring respectively. We demonstrate the application of electrochemical strategies for ROS/RNS detection in body fluids, in vitro, and in vivo, outlining the hardware architecture and comparing analytical performance of these sensors. This review aims for a holistic view of limitations in existing ROS/RNS detection by comprehensively explaining the shortcomings of the current works in the hope of drawing attentions to the challenges of ROS/RNS electrochemical technologies. We pay particular attention to in vitro and in vivo sensors and extend our evaluation to suggest possible solutions. Specifically, this review focuses on the development of currently nanotechnologies, biomimetic engineering, 3D-culture methods and implanted sensors to provide a guideline for future works
Automatic borescope damage assessments for gas turbine blades via deep learning
No full textTo maximise fuel economy, bladed components in aero-engines operate close to material limits. The severe operating environment leads to in-service damage on compressor and turbine blades, having a profound and immediate impact on the performance of the engine. Current methods of blade visual inspection are mainly based on borescope imaging. During these inspections, the sentencing of components under inspection requires significant manual effort, with a lack of systematic approaches to avoid human biases. To perform fast and accurate sentencing, we propose an automatic workflow based on deep learning for detecting damages present on rotor blades using borescope videos. Building upon state-of-the-art methods from computer vision, we show that damage statistics can be presented for each blade in a blade row separately, and demonstrate the workflow on two borescope videos
Electronic structure and optical properties of SnO<inf>2</inf>/HC(NH<inf>2</inf>)<inf>2</inf>PbI<inf>3</inf> interfaces from first-principles calculations
No full textInterface engineering of the device layers of halide perovskite solar cells has shown the potential to improve efficiency and stability. In this paper, the interface mechanism between the halide perovskite layer FAPbI3 and SnO2 was clarified by first-principles calculations. Results showed that the formation energies of the FAI interface and the PbI2 interface were -0.107eV and -0.087eV respectively. Compared with the PbI2 interface, the FAI interface has lower binding energy, which means that the FAI interface is more conducive to the formation. The analysis of structural deformation shows that the structure of the FAI interface is more stable. The density of states analysis shows that I-p, Pb-p, O-p, Sn-s, Sn-d are strongly hybridized. The analysis of the dielectric function shows that the FAI interface has better charge storage capacity and higher conductivity
Numerical Study on Dynamic Resistance of an HTS Switch Made of Series-Connected YBCO Stacks
No full textWhen a superconductor is exposed to an AC magnetic field whilst carrying a constant DC transport current, a DC electrical resistance can be observed, commonly referred to as 'dynamic resistance'. This dissipative effect can play a critical role in many potential higherature superconducting (HTS) applications, especially for the AC-field-actuated HTS switch, which is the key component in the HTS transformer-rectifier flux pump (TRFP). The characteristics of the HTS switch determine the performance and reliability of TRFP. In this paper, we report a numerical study of a new HTS switch design made of series-connected YBCO stacks. This study aims to obtain insights into the characteristics of dynamic resistance and power loss, including their relationships with the amplitude and the frequency of the AC magnetic field. The energy conversion efficiency of the HTS switch is also investigated. This work will help design a high-performance AC-field-actuated HTS switch
Foreign Body Reaction to Implanted Biomaterials and Its Impact in Nerve Neuroprosthetics
No full textThe implantation of any foreign material into the body leads to the development of an inflammatory and fibrotic process—the foreign body reaction (FBR). Upon implantation into a tissue, cells of the immune system become attracted to the foreign material and attempt to degrade it. If this degradation fails, fibroblasts envelop the material and form a physical barrier to isolate it from the rest of the body. Long-term implantation of medical devices faces a great challenge presented by FBR, as the cellular response disrupts the interface between implant and its target tissue. This is particularly true for nerve neuroprosthetic implants—devices implanted into nerves to address conditions such as sensory loss, muscle paralysis, chronic pain, and epilepsy. Nerve neuroprosthetics rely on tight interfacing between nerve tissue and electrodes to detect the tiny electrical signals carried by axons, and/or electrically stimulate small subsets of axons within a nerve. Moreover, as advances in microfabrication drive the field to increasingly miniaturized nerve implants, the need for a stable, intimate implant-tissue interface is likely to quickly become a limiting factor for the development of new neuroprosthetic implant technologies. Here, we provide an overview of the material-cell interactions leading to the development of FBR. We review current nerve neuroprosthetic technologies (cuff, penetrating, and regenerative interfaces) and how long-term function of these is limited by FBR. Finally, we discuss how material properties (such as stiffness and size), pharmacological therapies, or use of biodegradable materials may be exploited to minimize FBR to nerve neuroprosthetic implants and improve their long-term stability
Inelastic displacement ratios for non-structural components in steel framed structures under forward-directivity near-fault strong-ground motion
No full textThis paper describes a detailed numerical investigation into the inelastic displacement ratios of non-structural components mounted within multi-storey steel framed buildings and subjected to ground motions with forward-directivity features which are typical of near-fault events. The study is carried out using detailed multi-degree-of-freedom models of 54 primary steel buildings with different structural characteristics. In conjunction with this, 80 secondary non-structural elements are modelled as single-degree-of-freedom systems and placed at every floor within the primary framed structures, then subsequently analysed through extensive dynamic analysis. The influence of ground motions with forward-directivity effects on the mean response of the inelastic displacement ratios of non-structural components are compared to the results obtained from a reference set of strong-ground motion records representing far-field events. It is shown that the mean demand under near-fault records can be over twice as large as that due to far-fault counterparts, particularly for non-structural components with periods of vibration lower than the fundamental period of the primary building. Based on the results, a prediction model for estimating the inelastic displacement ratios of non-structural components is calibrated for far-field records and near-fault records with directivity features. The model is valid for a wide range of secondary non-structural periods and primary building fundamental periods, as well as for various levels of inelasticity induced within the secondary non-structural elements
The Effect of Isentropic Exponent on Supersonic Turbine Wakes
No full textThe isentropic exponent is known to have a large impact on turbine aerodynamics yet there is little research into how this impacts the development of turbine wakes. This study aims to explore how the aerodynamics of a supersonic turbine cascade are affected by the isentropic exponent. This is achieved through both experimental and computational methods with working fluids of air, CO 2 and R134a which gives a range of isentropic exponents from 1.07 to 1.4. The experiments are performed using a newly modified transient wind tunnel with the capability to obtain total pressure measurements in the wake of the cascade. This paper describes the development of the experimental apparatus as well as reporting the first-of-their-kind wake measurements from a turbine cascade operating with R134a. The resultant experimental wake measurements serve as a validation data set for various computational fluid dynamic approaches
Infrared absorbing nanoparticle impregnated self-heating fabrics for significantly improved moisture management under ambient conditions
No full textPropensity of a textile material to evaporate moisture from its surface, commonly referred to as the 'moisture management' ability, is an important characteristic that dictates the applicability of a given textile material in the activewear garment industry. Here, an infrared absorbing nanoparticle impregnated self-heating (IRANISH) fabric is developed by impregnating tin-doped indium oxide (ITO) nanoparticles into a polyester fabric through a facile high-pressure dyeing approach. It is observed that under simulated solar radiation, the impregnated ITO nanoparticles can absorb IR radiation, which is effectively transferred as thermal energy to any moisture present on the fabric. This transfer of thermal energy facilitates the enhanced evaporation of moisture from the IRANISH fabric surface and as per experimental findings, a 54 ± 9% increase in the intrinsic drying rate is observed for IRANISH fabrics compared with control polyester fabrics that are treated under identical conditions, but in the absence of nanoparticles. Approach developed here for improved moisture management via the incorporation of IR absorbing nanomaterials into a textile material is novel, facile, efficient and applicable at any stage of garment manufacture. Hence, it allows us to effectively overcome the limitations faced by existing yarn-level and structural strategies for improved moisture management