MRC Laboratory of Molecular Biology
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Gemini principles-based digital twin maturity model for asset management
No full textVarious maturity models have been developed for understanding the diffusion and implementation of new technologies/approaches. However, we find that existing maturity models fail to understand the implementation of emerging digital twin technique comprehensively and quantitatively. This research aims to develop an innovative maturity model for measuring digital twin maturity for asset management. This model is established based on Gemini Principles to form a systematic view of digital twin development and implementation. Within this maturity model, three main dimensions consisting of nine sub-dimensions have been defined firstly, which were further articulated by 27 rubrics. Then, a questionnaire survey with 40 experts involved is designed and conducted to examine these rubrics. This model is finally illustrated and validated by two case studies in Shanghai and Cambridge. The results show that the digital twin maturity model is effective to qualitatively evaluate and compare the maturity of digital twin implementation at the project level. It can also initiate the roadmap for improving the performance of digital twin supported asset management
Evanescent inertial waves
No full textWe investigate evanescent inertial waves, both theoretically and experimentally, in a fluid subject to a background rotation of. We predict that there is a smooth transition from conventional inertial waves to evanescent disturbances at a frequency of, and that at this cross-over frequency the evanescent disturbances are spatially extensive, having a horizontal extent which is limited only by viscosity, or by the size of the domain. These findings are confirmed by our experiments, which, to the best of our knowledge, represent the first quantitative experimental investigation of evanescent inertial waves
HeDI: Healthcare Device Interoperability for IoT-Based e-Health Platforms
No full textIn this work, we propose and develop HeDI (Healthcare Device Interoperability) – a system to enable device interoperability in IoT-enabled in-home healthcare monitoring platforms. The system consists of multiple sensors, each connected wirelessly to an edge device, acting as a wireless communication gateway to a remote server. The system initiates information handshaking between the sensor adapters and edge device at the beginning of the operation, which is later used to detect the sensor settings to process the data received from the sensor. The system is scalable and dynamically accommodates multiple sensors without any predefined ontologies at the edge device. The implementation of our system avoids dependencies on a system’s physical ports. The low form factor and wireless connectivity of the adapter make the system portable and convenient for in-home health monitoring. Additionally, the system allows multiple homogeneous sensors to operate at the same time in the same system. We implement and evaluate our system with a 3-lead ECG, pulse, and temperature sensors against two different network configurations – Star and Mesh. We use the data set generated from our implemented system for performance analysis. The network-level analysis of our system shows an average packet delivery ratio of 0.92 for star network configuration and 0.98 for mesh network configuration, ensuring the reliability of performance and its suitability for healthcare monitoring systems
Unsteady vorticity force decomposition-evaluating gust distortion
No full textThe impulse theory used to calculate the force from a vorticity distribution in two-dimensional, incompressible flow, is re-cast with the aim of estimating the forces generated by a specific flow feature, such as a region of external vorticity passing an object. Specifically, the effect of gust shear layer distortion on the force during a flat plate sharp-edged gust encounter is studied. This is made possible because the force acting on any object is split up into several core contributions. The first component arises from the time variation of the bodies boundary layer. The second is generated by the advection of any free vorticity located in the flowfield by the objects boundary layer vorticity. The final force contribution is due to new vorticity being shed. To test the theory, it is applied to two multi-body flowfields consisting of a circular cylinder and a flat plate at incidence in close proximity. Force balance measurements and planar particle image velocimetry data are simultaneously obtained at Reynolds numbers of 10 000 and 20 000. The forces acting on the cylinder are successfully recovered from the vorticity data using the derived formulation, verifying its accuracy. Thereafter, the proposed force formulation is applied to the vorticity data of a flat plate gust encounter, to identify the force created by the gust shear layers. The gust is formed by a sharp-edged region of uniform cross flow, resembling a ‘top-hat’ vertical velocity profile. The gust ratios explored are 0.5, 1 and 1.5. It is found that with increasing gust ratio, gust distortion has an increasing influence on the magnitude of the non-circulatory gust force. At a gust ratio of 1.5, the real maximum noncirculatory force is approximately 50 % lower than the theoretical Küssner model equivalent, which assumes rigid gust shear layers. The deflection of the gust delays the growth of the gust vortex sheet contributing to the boundary layer and therefore reduces its force contribution. An additional force of opposite sign is created by the advection of the gust vorticity by the plate boundary layer. Together, these two force components lead to the observed reduction of the non-circulatory force
Performance-oriented risk evaluation and maintenance for multi-asset systems: A Bayesian perspective
No full textIn this article, we present a risk evaluation and maintenance strategy optimization approach for systems with parallel identical assets subject to continuous deterioration. System performance is defined by the number of functional assets, and the penalty cost is measured by the loss of performance. To overcome the practical challenges of information sparsity, we employ a Bayesian framework to dynamically update unknown parameters in a Wiener degradation model. Order statistics are utilized to describe the failure times of assets and the stepwise incurred performance penalty cost. Furthermore, based on the Bayesian parameter inferences, we propose a short-term value-based replacement policy to minimize the expected cost rate in the current planning horizon. The proposed strategy simultaneously considers the variability of parameter estimators and the inherent uncertainty of the stochastic degradation processes. A simulation study and a realistic example from the petrochemical industry are presented to demonstrate the proposed framework
Ultra-Broadband Interleaver for Extreme Wavelength Scaling in Silicon Photonic Links
No full textWe demonstrate an ultra-broadband silicon photonic interleaver capable of interleaving and de-interleaving frequency comb lines over a 125 nm bandwidth in the extended C- and L-bands. We use a ring-assisted asymmetric Mach Zehnder interferometer to achieve a flat-top passband response while maintaining a compact device footprint. The device has a 400 GHz free spectral range to divide an optical frequency comb with 200 GHz channel spacing into two output groups, each with a channel spacing of 400 GHz, yielding a potential capacity of 78 total wavelength-division multiplexed channels between 1525 nm and 1650 nm. This device represents an important step towards realizing highly parallel integrated optical links with broadband frequency comb sources within the silicon photonics platform
Wrist-driven passive grasping: Interaction-based trajectory adaption with a compliant anthropomorphic hand
No full textThe structure of the human musculo-skeletal systems shows complex passive dynamic properties, critical for adaptive grasping and motions. Through wrist and arm actuation, these passive dynamic properties can be exploited to achieve nuanced and diverse environment interactions. We have developed a passive anthropomorphic robot hand that shows complex passive dynamics. We require arm/wrist control with the ability to exploit these. Due to the soft hand structures and high degrees of freedom during passive-object interactions, bespoke generation of wrist trajectories is challenging. We propose a new approach, which takes existing wrist trajectories and adapts them to changes in the environment, through analysis and classification of the interactions. By analysing the interactions between the passive hand and object, the required wrist motions to achieve them can be mapped back to control of the hand. This allows the creation of trajectories which are parameterized by object size or task. This approach shows up to 86% improvement in grasping success rate with a passive hand for object size changes up to 50%
Risk prediction of microcystins based on water quality surrogates: A case study in a eutrophicated urban river network
No full textMicrocystins (MCs), the toxic by-products from harmful algal bloom (HAB), have caused world-wide concern due to their acute toxicity in freshwater ecosystems. Most studies on HAB have been conducted for shallow freshwater lakes, such as Taihu Lake in China. However, algal blooms in urban rivers located downstream of eutrophicated lakes are also a serious problem for local administrators. It is important for them to know the current and potential risk level of MCs. This environmental issue is rarely reported or discussed. Within this context, we monitored MC concentrations in the Binhu River Network (BRN) in the algal bloom season (Aug, Sep, and Oct) in 2019. To note if the MC concentrations were dangerous, we used 1.0 μg/L suggested by the World Health Organization as the standard value. The proportions of MC samples violating the standard value were 31.78% (Aug), 21.14% (Sep) and 30.77% (Oct). We also designed two statistical models to predict MC concentrations and the possibility to exceed the standard level based on 10 water quality surrogates: Artificial Neural Network (ANN) and Logistic Regression (LR) models. These two models were trained and validated by the monitoring dataset (n = 224). Both models had good performances during training and testing. Although the water quality varied diversely both in spatial and temporal scale, Cluster Analysis (CA) could detect similarities among the samples and separated them into 3 classes, with each class denoting different types of rivers based on the 10 water quality surrogates. Then the ANN and LR were applied as a function of chl-a in each class; by gradually increasing chl-a concentration, we detected chl-a thresholds in class 1, 2, 3 were 25.5, 224, and 109.5 μg/L, respectively, when MCs have a 50% possibility to exceed standard level. The threshold values provided important implications for MC management in the BRN
Frequency-Modulated Wireless Direct-Drive Motor Control
No full textThis article proposes and implements a frequency-modulated wireless direct-drive motor control (WDMC) for a promising application of underground in-pipe pumping. Accordingly, a novel urban drainage scheme is conceived, which offers high robustness, mobility, and flexibility. This scheme can help with the emergency response to prevent severe weather hazards, such as heavy rainfall. To power one energy-demanding unit of pumping network, a movable energy-carrying electric vehicle can park above the underground in-pipe pump and wirelessly drive the motor for accelerating the flow rate as required. Also, a pulse frequency modulation is newly used for wireless motor speed control with frequency-reduced zero-voltage switching. The system efficiencies can reach 87.6% and 83.9% with two tested power levels of 430 W at rated load and around 600 W at overload, respectively. Theoretical analysis, computer simulation, and practical experimentation are given to verify the feasibility of the proposed drainage system using the frequency-modulated WDMC
Cadmium-induced dysfunction of the blood-brain barrier depends on ROS-mediated inhibition of PTPase activity in zebrafish
No full textIncreasing evidence has demonstrated that cadmium accumulation in the blood increases the risk of neurological diseases. However, how cadmium breaks through the blood-brain barrier (BBB) and is transferred from the blood circulation into the central nervous system is still unclear. In this study, we examined the toxic effect of cadmium chloride (CdCl2) on the development and function of BBB in zebrafish. CdCl2 exposure induced cerebral hemorrhage, increased BBB permeability and promoted abnormal vascular formation by promoting VEGF production in zebrafish brain. Furthermore, in vivo and in vitro experiments showed that CdCl2 altered cell-cell junctional morphology by disrupting the proper localization of VE-cadherin and ZO-1. The potential mechanism involved in the inhibition of protein tyrosine phosphatase (PTPase) mediated by cadmium-induced ROS was confirmed with diphenylene iodonium (DPI), a ROS production inhibitor. Together, these data indicate that BBB is a critical target of cadmium toxicity and provide in vivo etiological evidence of cadmium-induced neurovascular disease in a zebrafish BBB model