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Hand, foot, and mouth disease (HFMD) is an important public health problem and has received concern worldwide. Moreover, the coronavirus disease 2019 (COVID-19) epidemic also increases the difficulty of understanding and predicting the prevalence of HFMD. The purpose is to prove the usability and applicability of the automatic machine learning (Auto-ML) algorithm in predicting the epidemic trend of HFMD and to explore the influence of COVID-19 on the spread of HFMD. The AutoML algorithm and the autoregressive integrated moving average (ARIMA) model were applied to construct and validate models, based on the monthly incidence numbers of HFMD and meteorological factors from May 2008 to December 2019 in Henan province, China. A total of four models were established, among which the Auto-ML model with meteorological factors had minimum RMSE and MAE in both the model constructing phase and forecasting phase (training set: RMSE = 1424.40 and MAE = 812.55; test set: RMSE = 2107.83, MAE = 1494.41), so this model has the best performance. The optimal model was used to further predict the incidence numbers of HFMD in 2020 and then compared with the reported cases. And, for analysis, 2020 was divided into two periods. The predicted incidence numbers followed the same trend as the reported cases of HFMD before the COVID-19 outbreak; while after the COVID-19 outbreak, the reported cases have been greatly reduced than expected, with an average of only about 103 cases per month, and the incidence peak has also been delayed, which has led to significant changes in the seasonality of HFMD. Overall, the AutoML algorithm is an applicable and ideal method to predict the epidemic trend of the HFMD. Furthermore, it was found that the countermeasures of COVID-19 have a certain influence on suppressing the spread of HFMD during the period of COVID-19. The findings are helpful to health administrative departments.

Summary In this paper, techniques have been developed to quantify phase behavior and physical properties including phase boundaries, swelling factors (SFs), and phase volumes for reservoir fluids containing polar components from both experimental and theoretical aspects. Experimentally, a total of seven pressure-volume-temperature (PVT) experiments, including one set of dimethyl ether (DME)/heavy oil system, one set of DME/water/heavy oil system, three sets of DME/CO2/heavy oil systems, and two sets of DME/CO2/water/heavy oil systems, have been carried out to measure saturation pressures, phase volumes, and SFs by using a versatile PVT setup. Theoretically, the modified Peng-Robinson equation of state (PR EOS) incorporated with the Huron-Vidal (HV) mixing rule and the Péneloux volume-translation strategy is used as the thermodynamic model to perform phase equilibrium calculations. Once validated with the measured phase compositions of DME/water mixtures collected from the literature, the theoretical model developed in this work is used to reproduce the experimental measurements for the aforementioned reservoir fluids. It is observed that the saturation pressures of DME/CO2/water/heavy oil mixtures are higher than those of DME/CO2/heavy oil mixtures at the same temperature and same molar ratio of solvents and heavy oil, owing to the fact that more water molecules can be evaporated into the vapor phase. The binary interaction parameters (BIPs) between DME/heavy oil and CO2/DME pair, which are obtained by matching the measured saturation pressures of DME/CO2/heavy oil mixtures, work well for DME/CO2/heavy oil mixtures in the absence and presence of water. In addition, the swelling effect of heavy oil can be enhanced by adding the DME and CO2 mixtures compared with only DME or CO2. The new model developed in this work is capable of accurately reproducing the experimentally measured multiphase boundaries, SFs, and phase volumes with root-mean-squared relative errors (RMSREs) of 4.68, 0.71, and 9.35%, respectively, indicating that it can accurately provide fundamental data for simulating, designing, and optimizing the hybrid steam-solvent recovery processes for heavy oil reservoirs.

Experimental and theoretical techniques have been developed to quantify phase behaviour and physical properties in terms of phase boundaries, swelling factors, phase volumes, and phase compositions. Experimentally, five sets of PVT experiments of pentane, hexane, and heptane, respectively, mixed with bitumen have been conducted to measure phase behaviour data in the absence and presence of water by using a conventional PVT setup at elevated temperatures up to 438.2 K. Theoretically, the Athabasca bitumen is characterized as four pseudocomponents, while the binary interaction parameters (BIPs) are optimized by reproducing the measured saturation pressures. The original Peng-Robinson equation of state (PR EOS) has been advanced to perform flash calculations by incorporating a recently modified alpha function and an improved volume translation method together with the Huron-Vidal mixing rule, while the results have been compared with those obtained from CMG WinProp module incorporated with the original alpha function as well as default and optimized BIP correlations. It is from the experimental observation that the saturation pressures of n-alkane solvents/water/bitumen mixtures are decreased with carbon numbers at the same conditions. Also, the saturation pressures of n-alkane solvents/bitumen mixtures are increased with the addition of water because water molecules are evaporated into vapour phase at relatively low pressure and high temperature conditions. The BIPs of pure solvent/bitumen pairs, which are optimized through fitting the measured saturation pressures, work well for n-alkanes/bitumen mixtures in the absence and presence of water. Such an advanced PR EOS (APR EOS) model can accurately reproduce the experimentally obtained multiphase boundaries, swelling factors, phase volumes and compositions with an average absolute relative derivation (AARD) of 7.82%, 2.11%, 6.78%, and 4.38%, respectively, indicating that it can provide fundamental data for the design and optimization of the hybrid solvent-steam recovery method for bitumen resources.

The hybrid steam-solvent injection has been considered as a promising technique for enhancing heavy oil/bitumen recovery, while its main mechanisms including the heat transferred and dissolution of solvents (e.g., C3H8, C4H10, CO2, N2, and DME) into heavy oil/bitumen to reduce its viscosity and swell it are closely related to the phase behaviour of the solvents/water/heavy oil systems. To allow the seamless integration with the existing reservoir simulators, the traditional cubic equations of state (i.e., SRK EOS and PR EOS) have been modified and improved to accurately quantify the phase behaviour and physical properties of the aforementioned systems under equilibrium and nonequilibrium conditions. Firstly, a huge database has been built to develop the corresponding alpha functions by minimizing the deviation between the measured and calculated vapour pressures for water as well as nonhydrocarbon and hydrocarbon compounds available from the public domain. Such obtained alpha functions are further validated with enthalpy of vaporization for pure substances, and then the reduced temperature has been optimized and the eccentric factor has been redefined. Finally, a pressure-implicit strategy has been developed to optimize the binary interaction parameters (BIPs) by treating heavy oil as one pseudocomponent (PC) or multiple PCs. Also, the contributions of each solvent to the aforementioned systems have been compared and analyzed within a consistent and unified framework. In addition to new alpha functions for hydrocarbons and water, respectively, the reduced temperature is found to have its optimum value of 0.59 for the two equations of state (EOSs), while 0.60 is recommended for practical use. Such improved EOSs have been further employed to reproduce the experimentally measured multiphase boundaries (or pseudo-bubble-point pressures), density, viscosity, (mutual) solubility, and preferential mass transfer for the aforementioned mixtures under equilibrium and nonequilibrium conditions. The swelling effect for the heavy oil can be enhanced due to the addition of C3H8 and/or C4H10 or their mixtures into the CO2 stream. Due to the existence of water, isenthalpic flash leads to more accurate quantification of multiphase boundaries and physical properties for the hybrid solvent-thermal processes. Each component of a binary or ternary gas mixture is found to diffuse preferentially into heavy oil at high pressures and elevated temperatures in the absence and presence of porous media, while each of them is found to exsolve differently from gas-saturated heavy oil under nonequilibrium conditions.

For concrete with low water-to-binder ratio, the autogenous shrinkage often takes up most of the total shrinkage. In restrained structures, this kind of shrinkage will produce tensile stress. Once the tensile stress exceeds the tensile strength , it will lead to cracks and seriously endanger the durability of the structure. In this paper, the updated autogenous shrinkage prediction models of concrete in recent years are reviewed in detail. By comparing and analyzing these models, the latest research progress of autogenous shrinkage models is understood, and a direction for the subsequent research of autogenous shrinkage models of concrete is provided. Finally, the problems existing in current autogenous shrinkage models are summarized and prospected.