Forecasting COVID-19 infection trends and new hospital admissions in England due to SARS-CoV-2 Variant of Concern Omicron

Objectives: On November 26, 2021, WHO designated the variant B.1.1.529 as a new SARS-CoV-2 variant of concern (VoC), named Omicron, originally identified in South Africa. Several mutations in Omicron indicate that it may have an impact on how it spreads, resistance to vaccination, or the severity of illness it causes. We used our previous modelling algorithms to forecast the spread of Omicron in England. Design: We followed EQUATOR TRIPOD guidance for multivariable prediction models. Setting: England. Participants: Not applicable. Interventions: Non-interventional, observational study with a predicted forecast of outcomes. Main outcome measures: Trends in daily COVID-19 cases with a 7-day moving average and of new hospital admissions. Methods: Modelling included a third-degree polynomial curve in existing epidemiological trends on the spread of Omicron and a new Gaussian curve to estimate a downward trend after a peak in England. Results: Up to February 15, 2022, we estimated a projection of 250,000 COVID-19 daily cases of Omicron spread in the worse scenario, and 170,000 in the best scenario. Omicron might represent a relative increase from the background daily rates of COVID-19 infection in England of mid December 2021 of 1.9 to 2.8-fold. With a 5-day lag-time, daily new hospital admissions would peak at around 5,063 on January 23, 2022 in the worse scenario. Conclusion: This warning of pandemic surge of COVID-19 due to Omicron is calling for further reinforcing in England and elsewhere of universal hygiene interventions (indoor ventilation, social distance, and face masks), and anticipating the need of new total or partial lockdowns in England.

In-Process Error-Matching Measurement and Compensation Method for Complex Mating

This study proposed an error-matching measurement and compensation method for curve mating and complex mating. With use of polynomial curve fitting and least squares methods for error analysis, an algorithm for error identification and error compensation were proposed. Furthermore, based on the proposed method, an online error-matching compensation system with an autorevising function module for autogenerating an error-compensated NC program for machining was built. Experimental verification results showed that the proposed method can effectively improve the accuracy of assembly matching. In a curve-type mating experiment, the matching error without compensation was 0.116 mm, and it decreased to 0.048 mm after compensation. The assembly accuracy was improved by 28%. In a complex-type mating experiment, the verification results showed that the error reductions after compensation for three mating shapes (straight line, triangle, and curve shape) were 81%, 87%, and 79%, respectively. It showed that the proposed method can improve the assembly accuracy for complex mating shapes, which would also be improved without losing production efficiency.

Contour Extraction Based on Adaptive Thresholding in Sonar Images

A common problem in underwater side-scan sonar images is the acoustic shadow generated by the beam. Apart from that, there are a number of reasons impairing image quality. In this paper, an innovative algorithm with two alternative histogram approximation methods is presented. Histogram approximation is based on automatically estimating the optimal threshold for converting the original gray scale images into binary images. The proposed algorithm clears the shadows and masks most of the impairments in side-scan sonar images. The idea is to select a proper threshold towards the rightmost local minimum of the histogram, i.e., closest to the white values. For this purpose, the histogram envelope is approximated by two alternative contour extraction methods: polynomial curve fitting and data smoothing. Experimental results indicate that the proposed algorithm produces superior results than popular thresholding methods and common edge detection filters, even after corrosion expansion. The algorithm is simple, robust and adaptive and can be used in automatic target recognition, classification and storage in large-scale multimedia databases.

Accurate Determination of Conversion Gains of SVOM VT CCDs Based on a Signal-Dependent Charge-Sharing Mechanism

The signal-variance method and the photon transfer curve method are the most valuable tools for calculating the conversion gains of charge-coupled device (CCD) detectors. This paper describes the phenomena that arise in the conversion gain measurements of space multi-band variable object monitor (SVOM) visible telescope (VT) CCDs, where the results of the signal-variance method increase with the image gray level, and the results of the photon transfer curve method appear with nonlinearity, which is caused by the signal-dependent charge sharing mechanism of back-illuminated CCDs. A numerical simulation model based on random variables was adopted to analyze the influence of the mechanism on the gain determination. The model simulates all the signals and noise in the flat field image, including the photon signal and photon-shot noise, readout noise, fixed pattern noise, and the signal-dependent charge-sharing signal, and it demonstrated agreement with the experimental data. Then, we proposed a quadratic polynomial curve-fitting formula for the photon transfer curve, and we quantitatively analyzed the relationship between the fitting coefficients and the gain, the signal-dependent charge sharing coefficient, and the full well capacity using the control variable method. Finally, the formula was used to accurately determine the conversion gains of SVOM VT CCDs.

Colorimetric parameters correlated with the variation in the marker constituent contents during the stir-fry processing of Schizonepetae Spica

Background: Color is an important method of authentication to evaluate the degree of Chinese medicinal material (CMM) processing. This traditional color description used for identification needs to be confirmed by modern scientific analysis. Schizonepetae Spica (SS), the dried spike of Schizonepeta tenuifolia Briq., is a traditional Chinese medicinal herb. Raw SS has the actions of dispelling the common cold and fever. Schizonepetae Spica Carbonisata (SSC; raw SS processed by stir-frying until the surface becomes blackish-brown and the interior turns dark yellow) has particularly strong efficacy in arresting bleeding from bloody stool and metrorrhagia. Methods: In this paper, a high-performance liquid chromatography-diode array detector method and colorimetry were employed to determine 6 nonvolatile marker constituents and the color parameters (L*, a* and b*) of SS during stir-fry processing, respectively. Results: According to Pearson correlation analysis, L*, a* and b* showed significant correlations with the levels of luteolin-7-O-β-D-glucoside, apigenin-7-O-β-D-glucoside, hesperidin and rosmarinic acid, while a* was significantly correlated with the amounts of luteolin and apigenin. The corresponding regression models were good fits for the color parameters as respective functions of the 6 marker constituents according to enter multiple linear regression and third-order polynomial curve fitting methods (adjusted R2 > 0.800). Conclusion: Surrogate prediction of marker compounds using color parameters provides a valuable and cost-saving tool for rapid or online monitoring of the processing degree of SS. Raw SS and SSC could be determined based on the color parameters and 6 marker constituent contents for a comprehensive quality evaluation for the first time. This paper provides scientific data to validate the relationships between color features and quality during the processing of SS.

Optimization-Driven Controller Design for a High-Performance Electro-Hydrostatic Asymmetric Actuator Operating in All Quadrants

This paper presents an optimization-driven controller design for smooth and accurate position control of a newly developed single-rod electro-hydrostatic actuator (EHA). The design approach uses logically guided iterative runs of the EHA to determine the optimal gain and poles' locations of a simple, yet effective low-bandwidth controller. The optimization algorithm used in the paper is the globalized bounded Nelder-Mead algorithm with deterministic restarts for improved globalization and lower numerical cost. The design also incorporates a pre-filter to ensure minimum jerk in the system's step input response in the beginning and while approaching steady-state. The step response of the filter is a 7th-degree polynomial curve that ensures the minimum change in acceleration. Experimental results reveal that the addition of the proposed pre-filter reduces jerk in the system by up to 90%. Results also indicate that the controller performs very well in all quadrants with external load uncertainty of up to 367 kg and thus proves the effectiveness of the design approach.

A New Parametric Function-Based Dynamic Lane Changing Trajectory Planning and Simulation Model

Lane-changing (LC) problem may cause serious accidents or create a painful traffic jam at multi-lane roads. Existing LC simulation model was created with some limitations (less fitted, without velocity and acceleration profiles, high curvature) by using well known trajectory curve such as Hyperbolic Tangent Curve (HTC), Sine-Based Curve (SC), Polynomial Curve (PC). In this study, a new parametric curve had been proposed by using curvilinear coordinate system and fitted against Next Generation Simulation (NGSIM) real dataset. Further, new profiles of velocity and acceleration were designed using the proposed LC trajectory curve. The curvature of proposed model was zero-based curvature both at LC starting and ending points. This proposed curvature was compared with two models such as HTC and SC. The average root-mean-square-error of proposed model decreased with 1.84% for left LC and 15.48% for right LC compared to HTC model and 1.74% for left LC and 15.60% for right LC compared to SC model. Similarly, the proposed model for velocity and acceleration profiles improved significantly from PC model. The proposed parametric curve solves the gap and collision points of LC vehicle with a front vehicle and rear vehicle at target lane and can be used in real LC path planning.