A modular, efficient formalisation of real algebraic numbers

This paper presents a construction of the real algebraic numbers with executable arithmetic operations in Isabelle/HOL. Instead of verified resultants, arithmetic operations on real algebraic numbers are based on a decision procedure to decide the sign of a bivariate polynomial (with rational coefficients) at a real algebraic point. The modular design allows the safe use of fast external code. This work can be the basis for decision procedures that rely on real algebraic numbers.The CSC Cambridge International Scholarship is generously funding Wenda Li’s Ph.D. course.This is the author accepted manuscript. The final version is available from the Association for Computing Machinery via http://dx.doi.org/10.1145/2854065.285407

Investigation of metaldehyde removal by powdered activated carbon from different water samples

Metaldehyde as a widely used pesticide has been detected in surface water and drinking water in the UK with concentrations higher than the EU and UK standard (0.1 μg L−1). Previous studies have shown that powdered activated carbon (PAC) can adsorb metaldehyde even with the presence of natural organic matter, suggesting a promising solution to the problem. This paper studies the adsorption of metaldehyde onto PAC using different water samples including synthetic water, natural surface water, and water samples taken at different treatment processes from a water treatment plant. Metaldehyde (5 μg L−1) was effectively removed by PAC (50 mg L−1) from all water samples in this study, regardless of the water quality (74.3% to 99.7%). A PAC dosage of 100 mg L−1 was considered appropriate to remove metaldehyde at 5 μg L−1 after the first treatment process of pre-ozone treatment with a maximum adsorption capacity (qm) of 0.25 μg mg−1 given by the data fitted to the Langmuir isotherm model. Removal of metaldehyde by PAC was found to be most effective when PAC was applied after the static flocculation treatment process (98.4%) with a qm of 0.29 μg mg−1. The low adsorption capacity of PAC for low initial concentrations of metaldehyde solution was observed due to the lower driving force for mass transfer in the process of adsorption and competition with water molecules for adsorption sites on PAC

The application of GAC sandwich slow sand filtration to remove pharmaceutical and personal care products

Lab-scale GAC sandwich slow sand filters with different GAC layer depths were evaluated for the first time to remove selected pharmaceutical and personal care products (PPCPs) (namely DEET, paracetamol, caffeine and triclosan, 25 μg/L). Coarse sand (effective grain size of 0.6 mm) was used instead of conventional fine sand. In addition to single sand and GAC filters, GAC sandwich filters were assessed at three filtration rates (i.e. 5 cm/h, 10 cm/h and 20 cm/h) to compare removals. Sandwich filter with 20 cm GAC achieved the best average PPCP removal (98.2%) at 10 cm/h rate. No significant difference of average PPCP removal was found between 10 and 20 cm/h filtration rates for the three GAC sandwich filters (p > 0.05). Among the selected PPCPs, DEET, the recalcitrant compound, was most effectively removed by the GAC sandwich filters. Combining the GAC layers with the slow sand filters significantly enhanced the removal of the target PPCP compounds (p  0.05). Results of this lab-scale investigation show that GAC sandwich slow sand filter is potentially an effective process for removing PPCPs from tertiary wastewater

A novel high-throughput analytical method to quantify microplastics in water by flow cytometry

Microplastics (MPs) are pervasive contaminants with unclear toxicological impacts. Current research on MP pollution relies on low-throughput methodologies, which are time-consuming and cannot directly measure MP concentration in suspensions. This study presents a qualitative and quantitative flow cytometry-based method for analysing MPs in water, offering a faster and more sustainable alternative. The method involves density separation to remove interfering particles, UV irradiation to eliminate microorganisms, and filtration to remove particles above 100 µm. The sensitivity of the method for different types of MPs, such as polystyrene (PS), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), and polyamide (PA) microbeads, ranges from 2 µg/L to 1 mg/L. For these MPs, good linearity was found in matrix-matched calibration where the most concentrated standard was 5 mg/L (R2 0.9820–0.9989) although the linear range can be larger (e.g. 42 mg MP/L for PS microbeads). The repeatability and reproducibility of the method for the model PS MP were <17.0% and 8.5%, respectively. The sample treatment method consisting of density separation and UV pretreatment, when carried out independently, led to 95.0% and 93.4% recoveries. The overall trueness of the optimized method for various sizes and compositions of microbeads is about 97%, according to validation supported by microscopy analysis. This method can substitute the traditional quantitative analytical approach based on counting microbeads with microscopy

Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment

Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection. Most existing AU detection works often treat face alignment as a preprocessing and handle the two tasks independently. In this paper, we propose a novel end-to-end deep learning framework for joint AU detection and face alignment, which has not been explored before. In particular, multi-scale shared features are learned firstly, and high-level features of face alignment are fed into AU detection. Moreover, to extract precise local features, we propose an adaptive attention learning module to refine the attention map of each AU adaptively. Finally, the assembled local features are integrated with face alignment features and global features for AU detection. Experiments on BP4D and DISFA benchmarks demonstrate that our framework significantly outperforms the state-of-the-art methods for AU detection.Comment: This paper has been accepted by ECCV 201

Preliminary study on low-density polystyrene microplastics bead removal from drinking water by coagulation-flocculation and sedimentation

Microplastics (MPs), sized ~150 μm, have been found in tap water at levels of ~5 particles/L, suggesting that water treatment plants are not effectively removing MPs. Therefore, there is an urgent need to evaluate their fate in drinking water treatment processes. Coagulation-flocculation and sedimentation are applied in water treatment to primarily decrease turbidity, and MPs contribute to water turbidity. This study focuses on the removal of polystyrene (PS) beads of 100 μm with density 1.04–1.06 g/cm3. The low-density PS beads pose a removal challenge because they have similar density to the media. The effects of initial water pH and stirring speed on MPs removal by coagulation-flocculation and sedimentation were studied. The most effective conditions found for removing the PS beads from water, that led to removal rates up to 98.9 ± 0.94%, were 3.4 mg Al/L of coagulant, pH 5, flocculation time of 7 min and sedimentation time of 30 min. For the first time, floc breakage and regrowth following the addition of Al, has shown to favour the removal of the PS beads. Based on this research, coagulation-flocculation can play a very important role in removing MPs during drinking water treatment

The role of SARS-CoV-2 aerosol transmission during the COVID-19 pandemic

The COVID-19 pandemic, caused by the virus SARS-CoV-2, has touched most parts of the world and devastated the lives of many. The high transmissibility coupled with the initial poor outcome for the elderly led to crushingly high fatalities. The scientific response to the pandemic has been formidable, aided by advancements in virology, computing, data analysis, instrumentation, diagnostics, engineering and infection control. This has led to improvements in understanding and has helped to challenge some established orthodoxies. Sufficient time has elapsed since the start of the COVID-19 pandemic that a clearer view has emerged about transmission and infection risks, public health responses and related societal and economic impacts. This timely volume has provided an opportunity for the science community to report on these new developments

Thermal States as Universal Resources for Quantum Computation with Always-On Interactions

Measurement-based quantum computation utilizes an initial entangled resource state and proceeds with subsequent single-qubit measurements. It is implicitly assumed that the interactions between qubits can be switched off so that the dynamics of the measured qubits do not affect the computation. By proposing a model spin Hamiltonian, we demonstrate that measurement-based quantum computation can be achieved on a thermal state with always-on interactions. Moreover, computational errors induced by thermal fluctuations can be corrected and thus the computation can be executed fault tolerantly if the temperature is below a threshold value

Increased E. coli bio-adsorption resistance of microfiltration membranes, using a bio-inspired approach

Cells have inherent anti-fouling properties. The mechanisms underpinning these natural properties inform the design of an anti-biosorption coating for a polyethersulfone microfiltration membrane, which includes polydopamine and chitosan layers. This tri-layered membrane is created using quick and easy synthesis method. Its ability to resist bio-adsorption and membrane extracellular polymeric substances (EPS) formation is investigated using the bacterium E. coli (ATCC 11775, 1.5 × 10^{7} CFU/mL). In addition, the proliferative bio-adsorption process is explored on the microfiltration membrane surface, using natural water under static and shaken conditions, while monitoring the bio-adsorption kinetics and EPS dynamic changes. The characterization results show that the modification by polydopamine and chitosan change the membrane surface morphology and increase its hydrophilicity. After 10 min dipping in 5 g/L chitosan solution, the pure water flux of the modified membrane is 5469 ± 30 L/(m^{2} ·h) (0.2 bar) and the contact angle decreases to 36.7 ± 1.0°, compared with 9889 ± 23 L/(m^{2} ·h) (0.2 bar) and 60.3 ± 1.5° for the unmodified polyethersulfone membrane, respectively. In proliferative bio-adsorption tests, the modified membrane is shown to decrease bio-adsorption by 0.4–2.3 orders of magnitude. However, no antimicrobial function is observed, probably due to the alkaline environment and insufficient functional amino groups. A series of linear and non-linear kinetic models is applied to fit the proliferative bio-adsorption process. The pseudo-second-order model is found to describe the proliferative bio-adsorption process best. Neither total organic carbon (TOC) nor protein is detected on the modified membrane surface. In contrast, on the unmodified PES membrane the ratios of protein/TOC (%), TOC/abundance ((μg/cm^{2}/CFU (log)) and protein/abundance ((μg/cm^{2}/CFU(log)) are 10%–16%, 0.17–0.28 and 0.02–0.04, respectively. No significant difference (p > 0.05) is found between static and shaken conditions. All these results point to improved anti-biosorption properties for water treatment applications, encouraging further studies on this membrane

Degradation of metaldehyde in water by nanoparticle catalysts and powdered activated carbon

Metaldehyde, an organic pesticide widely used in the UK, has been detected in drinking water in the UK with a low concentration (<1 μg L−1) which is still above the European and UK standard requirements. This paper investigates the efficiency of four materials: powdered activated carbon (PAC) and carbon-doped titanium dioxide nanocatalyst with different concentrations of carbon (C-1.5, C-40, and C-80) for metaldehyde removal from aqueous solutions by adsorption and oxidation via photocatalysis. PAC was found to be the most effective material which showed almost over 90% removal. Adsorption data were well fitted to the Langmuir isotherm model, giving a qm (maximum/saturation adsorption capacity) value of 32.258 mg g−1 and a KL (Langmuir constant) value of 2.013 L mg−1. In terms of kinetic study, adsorption of metaldehyde by PAC fitted well with a pseudo-second-order equation, giving the adsorption rate constant k2 value of 0.023 g mg−1 min−1, implying rapid adsorption. The nanocatalysts were much less effective in oxidising metaldehyde than PAC with the same metaldehyde concentration and 0.2 g L−1 loading concentration of materials under UV light; the maximum removal achieved by carbon-doped titanium dioxide (C-1.5) nanocatalyst was around 15% for a 7.5 ppm metaldehyde solution