MRC Laboratory of Molecular Biology
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Sequential dual site-selective protein labelling enabled by lysine modification
No full textMethods that allow for chemical site-selective dual protein modification are scarce. Here, we provide proof-of-concept for the orthogonality and compatibility of a method for regioselective lysine modification with strategies for protein modification at cysteine and genetically encoded ketone-tagged amino acids. This sequential, orthogonal approach was applied to albumin and a therapeutic antibody to create functional dual site-selectively labelled proteins
Ability of fabric face mask materials to filter ultrafine particles at coughing velocity.
No full textOBJECTIVE: We examined the ability of fabrics which might be used to create home-made face masks to filter out ultrafine (0.02-0.1 µm) particles at the velocity of adult human coughing. METHODS: Twenty commonly available fabrics and materials were evaluated for their ability to reduce air concentrations of ultrafine particles at coughing face velocities. Further assessment was made on the filtration ability of selected fabrics while damp and of fabric combinations which might be used to construct home-made masks. RESULTS: Single fabric layers blocked a range of ultrafine particles. When fabrics were layered, a higher percentage of ultrafine particles were filtered. The average filtration efficiency of single layer fabrics and of layered combination was found to be 35% and 45%, respectively. Non-woven fusible interfacing, when combined with other fabrics, could add up to 11% additional filtration efficiency. However, fabric and fabric combinations were more difficult to breathe through than N95 masks. CONCLUSIONS: The current coronavirus pandemic has left many communities without access to N95 face masks. Our findings suggest that face masks made from layered common fabric can help filter ultrafine particles and provide some protection for the wearer when commercial face masks are unavailable
Support Recovery in the Phase Retrieval Model: Information-Theoretic Fundamental Limit
No full textThe support recovery problem consists of determining a sparse subset of variables that is relevant in generating a set of observations. In this paper, we study the support recovery problem in the phase retrieval model consisting of noisy phaseless measurements, which arises in a diverse range of settings such as optical detection, X-ray crystallography, electron microscopy, and coherent diffractive imaging. Our focus is on information-theoretic fundamental limits under an approximate recovery criterion, considering both discrete and Gaussian models for the sparse non-zero entries, along with Gaussian measurement matrices. In both cases, our bounds provide sharp thresholds with near-matching constant factors in several scaling regimes on the sparsity and signal-to-noise ratio. As a key step towards obtaining these results, we develop new concentration bounds for the conditional information content of log-concave random variables, which may be of independent interest
Machine learning interatomic potential developed for molecular simulations on thermal properties of β-Ga2O3.
No full textThe thermal properties of β-Ga2O3 can significantly affect the performance and reliability of high-power electronic devices. To date, due to the absence of a reliable interatomic potential, first-principles calculations based on density functional theory (DFT) have been routinely used to probe the thermal properties of β-Ga2O3. DFT calculations can only tackle small-scale systems due to the huge computational cost, while the thermal transport processes are usually associated with large time and length scales. In this work, we develop a machine learning based Gaussian approximation potential (GAP) for accurately describing the lattice dynamics of perfect crystalline β-Ga2O3 and accelerating atomic-scale simulations. The GAP model shows excellent convergence, which can faithfully reproduce the DFT potential energy surface at a training data size of 32 000 local atomic environments. The GAP model is then used to predict ground-state lattice parameters, coefficients of thermal expansion, heat capacity, phonon dispersions at 0 K, and anisotropic thermal conductivity of β-Ga2O3, which are all in excellent agreement with either the DFT results or experiments. The accurate predictions of phonon dispersions and thermal conductivities demonstrate that the GAP model can well describe the harmonic and anharmonic interactions of phonons. Additionally, the successful application of our GAP model to the phonon density of states of a 2500-atom β-Ga2O3 structure at elevated temperature indicates the strength of machine learning potentials to tackle large-scale atomic systems in long molecular simulations, which would be almost impossible to generate with DFT-based molecular simulations at present
Assessment of corrosion-induced bond deterioration in reinforced concrete: Towards a splitting crack-based approach
No full textReinforced concrete structures are subjected to several sources of deterioration that can reduce their load-resisting capacity over time. This has significant consequences for the management of infrastructure, leading to high costs of maintenance, repair, strengthening and premature decommissioning. Assessing the residual capacity of structures is challenging but paramount to manage the infrastructure network effectively. Corrosion of the internal steel reinforcement is among the main causes of deterioration in reinforced concrete bridges. The subsequent reduction in steel-to-concrete bond strength is difficult to evaluate with accuracy. There is no unified theory of general validity. Most existing models adopt measures of the level of corrosion as the key parameter to evaluate the bond reduction. In this paper, a different approach is investigated. Corrosion-induced splitting crack widths are used as the fundamental indicator of bond strength reduction, irrespective of the associated degree of steel corrosion. Available experimental results on deformed steel bars embedded in concrete subjected to either natural or accelerated corrosion, with or without transverse reinforcement, are analysed and compared with a different perspective. The analysis indicates that this new splitting crack-based approach can lead to more accurate predictions. This contributes to a better understanding of the fundamental principles underlying bond of corroded reinforcing bars. Enhanced assessment strategies can lead to a reduction of the safety risks, maintenance costs and environmental footprint of the infrastructure network
Capturing the psychological well-being of Chinese factory workers
No full textPurpose: Businesses are under pressure to ensure social responsibility in their globalised supply chains. However, conventional factory audits are not providing adequate data about production workers’ well-being. Industry attempts to measure working conditions have shown bias and inconsistency, and there is no consensus on what to measure, or how. Well-being can be intangible and difficult to capture without appropriate theoretical and methodological frameworks. This paper investigates factors influencing the well-being of a Chinese factory’s workers, tests an innovative research method, and proposes interventions to improve well-being in factories. Design/methodology/approach: This is a longitudinal study using the diaries of production workers at a large assembly manufacturing site in China. Workers left daily digital voice diaries about their day, which were analysed to identify factors related to their well-being at work. Findings: The picture is more complex than the concerned Western narrative suggests. Workers’ personal and professional concerns extend beyond the criteria currently measured in audits, tending to be more relational and less about their physical state. Practical implications: The current approach of auditing management practices neglects workers’ well-being. This study offers a more comprehensive view of well-being and tests a new method of investigation. Originality/value: This is the first study to use diary methods in a Chinese factory. It addresses an issue supported by little empirical evidence. It is the first longitudinal study to hear from factory workers themselves about how they are and what impacts their well-being daily
The 100 mm × 100 mm Extreme Ultraviolet Graphite Pellicle: Nano-Pellicle Production Using the Lowest Free Energy at the Graphite–Water Interface
No full textExtreme ultraviolet (EUV) lithography is developed and implemented to fabricate nanodevices under 7 nm. Among the various challenges of EUV lithography, it is certainly a priority for a pellicle, as a physical shield, to protect a reflective EUV mask. Here, a practical, facile, industrial-friendly pellicle fabrication method is suggested to suspend a nanometer-thick graphite film (NGF) onto a pellicle frame (inner hole: 100 mm × 100 mm) by the vertical transfer (VT) method, benefitting from the lowest total free energy at the interfaces between NGF, water, and air. Based on the plate model of Neumann and Good, the free energy at the interfaces at various scooping angles is obtained; it is minimized at 90° (VT). Finally, for the very first time an NGF pellicle (100 mm × 100 mm) and 80.6% transmission at 13.5 nm (EUV) using the VT method are demonstrated
Phase field predictions of microscopic fracture and R-curve behaviour of fibre-reinforced composites
No full textWe present a computational framework to explore the effect of microstructure and constituent properties upon the fracture toughness of fibre-reinforced polymer composites. To capture microscopic matrix cracking and fibre-matrix debonding, the framework couples the phase field fracture method and a cohesive zone model in the context of the finite element method. Virtual single-notched three point bending tests are conducted. The actual microstructure of the composite is simulated by an embedded cell in the fracture process zone, while the remaining area is homogenised to be an anisotropic elastic solid. A detailed comparison of the predicted results with experimental observations reveals that it is possible to accurately capture the crack path, interface debonding and load versus displacement response. The sensitivity of the crack growth resistance curve (R-curve) to the matrix fracture toughness and the fibre-matrix interface properties is determined. The influence of porosity upon the R-curve of fibre-reinforced composites is also explored, revealing a stabler response with increasing void volume fraction. These results shed light into microscopic fracture mechanisms and set the basis for efficient design of high fracture toughness composites