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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.

This study sought to identify the spatial, temporal, and spatiotemporal clusters of COVID-19 cases in 366 cities in mainland China with the highest risks and to explore the possible influencing factors of imported risks and environmental factors on the spatiotemporal aggregation, which would be useful to the design and implementation of critical preventative measures. The retrospective analysis of temporal, spatial, and spatiotemporal clustering of COVID-19 during the period (January 15 to February 25, 2020) was based on Kulldorff’s time-space scanning statistics using the discrete Poisson probability model, and then the logistic regression model was used to evaluate the impact of imported risk and environmental factors on spatiotemporal aggregation. We found that the spatial distribution of COVID-19 cases was nonrandom; the Moran’s I value ranged from 0.017 to 0.453 (P < 0.001). One most likely cluster and three secondary likely clusters were discovered in spatial cluster analysis. The period from February 2 to February 9, 2020, was identified as the most likely cluster in the temporal cluster analysis. One most likely cluster and seven secondary likely clusters were discovered in spatiotemporal cluster analysis. Imported risk, humidity, and inhalable particulate matter PM2.5 had a significant impact on temporal and spatial accumulation, and temperature and PM10 had a low correlation with the spatiotemporal aggregation of COVID-19. The information is useful for health departments to develop a better prevention strategy and potentially increase the effectiveness of public health interventions.

Introduction Due to COVID-19 outbreak, since January 24, 2020, national medical teams from across the country and the armed forces have been dispatched to aid Hubei. The present review was designed to timely summarize the existing frontline information about nursing scheduling mode with special focus on the length of shifts with the aim to contribute to improve the nurses' job satisfaction and the quality of nursing services. Methods Articles from Jan 2020 to October 2020 were retrieved from China National Knowledge Infrastructure, Wanfang Data and Weipu Information, with the terms "COVID-19", "designated hospital", "Hubei-assisted", "makeshift hospital", "nursing", "nursing shift", "whole-system takeover" and variations of these, in the title and abstract fields and the Boolean combinations of these words as the retrieval strategy. Results Seventeen journal articles have been included in the target field, from the nurses in aiding Hubei Province, four kinds of shift length, 2-hour (h), 3-h, 4-h and 6-h shift have been considered, the main nursing scheduling mode adopted in designated hospitals for COVID-19 patients was dynamic scheduling based on workload, flexible scheduling based on working hours, workload and the number of critically ill patients admitted, humanized scheduling based on the daily reported health status of the nurses, and professional-integrated scheduling according to the professional distribution of nurses on the basis of four-hour shift length, and in makeshift hospitals for mild patients, the scheduling mode was 6-h based correspondingly. Conclusion The descriptive results of the present systematic review shed light on the challenges and practical solutions of nursing scheduling mode in the context of cross-regional medical assistance. Additionally, the present systematic review could provide the academic community of nurses, nurse managers and administrators with baseline information and scientific productions from the content's points of view in the target field.

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.

Introduction This systematic scoping review aims to assess the frequency and severity of clinical manifestations of pregnant women with brucellosis. Methods Three literature databases, PubMed, Web of Science and China National Knowledge Infrastructure (CNKI), and two search engines (Google and Yahoo) were adopted to identify the relevant articles that published until 31 December 2019. Two investigators independently screened the publications and extracted the data; the case reports and case series which described at least two symptoms or clinical manifestations of pregnant women with brucellosis were included. Results A total of 27 articles describing the information of 521 pregnant women with brucellosis were included. Serum agglutination test was the most common laboratory test in the diagnosis of brucellosis. A total of 36 clinical manifestations were extracted from the included articles, and the most common clinical manifestations were fever (400, 76.8%), joint pain/swelling/arthralgia (389, 74.7%), sweats (382, 73.3%), fatigue/asthenia/weakness (262, 50.3%) and back pain (189, 36.3%). Among the 32 included individual cases that with available obstetric outcome information, 10 (31.3%) suffered preterm delivery, 12 (37.5%) had an abortion and 3 (9.8%) had intrauterine fetal death. Conclusion Brucellosis is popular and threatening for pregnant women. Regarding the localized body system complications, osteoarticular system was mostly involved, the obstetrics outcomes were severe among pregnant women with brucellosis. The detailed clinical and epidemiological characteristics in this scoping review may add a better and more complete understanding of the disease for both physicians and policy-makers, and provide evidence for timely diagnosis, adequate therapy and better prevention.

Purpose To describe the incidence trend, demographic and clinical characteristics, treatment and prognosis, epidemiological history and risk factors of human brucellosis in Huludao, China. Patients and Methods A total of 1887 brucellosis patients were reported in Huludao, China from January, 2014 to December, 2018 and the case questionnaires from 1149 patients were collected from Huludao Municipal Center for Disease Control and Prevention. Demographic characteristics of the patients and the information relating to the patients' clinical manifestations, diagnosis, treatment and prognosis were collected and analyzed. Results The number of annually reported brucellosis patients has dropped from 711 to 187 during the study period, with the incidence decreased from 27.31/100,000 in 2014 to 7.15/100,000 in 2018. A total of 1149 individual data were collected, with a mean age of 49.59±13.14 years and 75.7% were male. Patients aged more than 60 years were more likely to have arthralgia/myalgia than the other age groups, and patients who had an enlarged spleen in male were more than female (P

In this study, techniques have been developed to determine multiphase boundaries of C3H8/CO2/water/heavy oil systems in both the pressure-temperature (P-T) and enthalpy- temperature (H-T) phase diagrams, respectively. Experimentally, the upper three-phase boundary pressures (i.e., saturation pressures) between aqueous/liquid/vapour (ALV) and AL phases are measured for three C3H8/CO2/water/heavy oil mixtures. Moreover, the fluid samples in both L and V phases are collected to conduct compositional analysis by using the gas chromatography (GC) method. Theoretically, the previously developed water-associated model, which considers only the presence of solvent with high solubility in water, together with the new alpha functions tailored for water and non-water components are employed to predict the multiphase boundaries of the aforementioned systems. A newly developed enthalpy determination algorithm is applied to calculate enthalpy of the Lloydminster heavy oil. The recently proposed water-associated model i...

Background Increasing attention has been paid to differences in the prevalence of perinatal depression by HIV status, although inconsistent results have been reported. The aim of this systematic review and meta-analysis was to assess the relationship between perinatal depression and HIV infection. A comprehensive meta-analysis of comparative studies comparing the prevalence of antenatal or postnatal depression between HIV-infected women and HIV-negative controls was conducted. Methods Studies were identified through PubMed/Medline, Scopus, Web of Science, Cochrane Library, Embase and PsycINFO, and the reading of complementary references in August 2019. Subgroup analyses were performed for anticipated explanation of heterogeneity using methodological quality and pre-defined study characteristics, including study design, geographical location and depression screening tools for depression. The overall odds ratio (OR) and mean prevalence of each group were calculated. Results Twenty-three studies (from 21 publications), thirteen regarding antenatal depression and ten regarding postnatal depression were included, comprising 3165 subjects with HIV infection and 6518 controls. The mean prevalence of antenatal depressive symptoms in thirteen included studies was 36% (95% CI: 27, 45%) in the HIV-positive group and 26% (95% CI: 20, 32%) in the control group. The mean prevalence of postnatal depressive symptoms in ten included studies was 21% (95% CI: 14, 27%) in the HIV-positive group and 16% (95% CI: 10, 22%) in the control group. Women living with HIV have higher odds of antenatal (OR: 1.42; 95% CI: 1.12, 1.80) and postnatal depressive symptoms (OR: 1.58; 95% CI: 1.08, 2.32) compared with controls. Publication bias and moderate heterogeneity existed in the overall meta-analysis, and heterogeneity was partly explained by the subgroup analyses. Conclusions Women with HIV infection exhibit a significantly higher OR of antenatal and postnatal depressive symptoms compared with controls. For the health of both mother and child, clinicians should be aware of the significance of depression screening before and after delivery in this particular population and take effective measures to address depression among these women.

Background Matrix Gla (γ-carboxyglutamate) protein (MGP) is considered a strong inhibitor of ectopic calcification, and it has been associated with OA severity, although not conclusively. We utilized male Dunkin-Hartley (DH) guinea pigs to investigate the expression of MGP throughout aging and disease pathogenesis in a spontaneous model. Method Twenty-five male DH guinea pigs were obtained and nurtured to several timepoints, and then randomly and equally divided by age into five subgroups (1-, 3-, 6-, 9-, and 12-months, with the 1-month group as the reference group). DH guinea pigs in each group were euthanized at the designated month-age and the left or right medial tibial plateaus cartilages were randomly excised. OA severity was described by modified Mankin Score (MMS) at microscopy (Safranin O/Fast Green stain). Proteomic evaluation using isobaric tags for relative and absolute quantification (iTRAQ) was performed to validate the age-related changes in the MGP profiles, and immunohistochemistry (IHC) methods were applied for semi-quantitative determination of MGP expression in articular cartilage. Results The histopathologic findings validated the increasing severity of cartilage degeneration with age in the DH guinea pigs. The MMS showed significant, stepwise (every adjacent comparison P Conclusion Increased expression of MGP in male DH guinea pigs was present throughout aging and disease progression and may be link to increased OA severity. Further studies are needed to investigate and confirm the association between MGP levels and OA severity.

Magnesium oxysulfate (MOS) cement is a typical eco-friendly cementitious material, which presents excellent performances. In this work, a novel multiscale modeling strategy is proposed to simulate the hydration and pore structure of MOS cement system. This work collected and evaluated the Gibbs free energy of formation for main hydrates and equilibrium constant of main reactions in MOS cement system based on a first principle calculation using Material Studio. Followingly, the equilibrium phase compositions of MOS cement system were simulated through PHREEQC to investigate the molar ratio dependence of equilibrium phase compositions. Results showed that large M (MgO/MgSO4) was beneficial for the formation of 5Mg(OH)2·MgSO4·7H2O (Phase 517) and large H (H2O/MgSO4) tended to decompose MOS cement paste and cause leaching. The microstructure-based method visualized the hydration status of MOS cement systems at initial and ultimate stages via MATLAB and the results showed that large M was significant to reduce porosity, and similar results for the case of small H. Fractal analysis confirms that fractal dimension of pore structure (Df) was significantly decreased after the hydration of MOS and was positively correlated to the porosity of the paste. In addition, it can be referred that large M and small H were beneficial for modifying the microstructure of MOS paste by decreasing the value of Df.

This paper will introduce the machine learning system based on text classification technology in detail. Through professional research and investigation, we can find out three advanced studies of text classification technology in the current era, such as spatial dimension reduction, classification methods and evaluation methods. Through various exploration and discovery, we can improve the learning experience and practice of relevant personnel.

In this paper, techniques have been developed to quantify phase behaviour and physical properties including phase boundaries, swelling factors, and phase volumes for reservoir fluids containing polar components from both experimental and theoretical aspects. Experimentally, a total of five pressure-volume-temperature (PVT) experiments including 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 swelling factors by using a versatile PVT setup. Theoretically, the modified Peng-Robinson equation of state (PR EOS) incorporated with the Huron-Vidal mixing rule and the Péneloux volume-translation strategy is employed as the thermodynamic model to perform phase equilibrium calculations. It is observed that the experimentally measured 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 vapour 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 presence and absence of water. In addition, a swelling effect of heavy oil can be enhanced by adding the DME and CO2 mixtures compared to only DME or CO2. The new model developed in this work is capable of accurately reproducing the experimentally measured multiphase boundaries, swelling factors, phase volumes with a root-mean-squared relative error (RMSRE) of 4.68%, 0.71%, and 9.35%, respectively, indicating that it can provide fundamental data for simulating, designing, and optimizing the hybrid solvent-thermal recovery processes for heavy oil reservoirs.

The co-occurrence analysis of Medical Subject Heading (MeSH) terms in the bibliographic database is popularly used in bibliometrics. Practically for making the result interpretable, it is necessary to apply a certain filter procedure of co-occurrence matrix for removing the low-frequency items that should not appear in the final result due to their low representativeness for co-occurrence analysis. Unfortunately, there is rare research referring to determine a critical threshold to remove noise of data for co-occurrence analysis. Here, we propose a probabilistic model for co-occurrence analysis that can calculate statistical significance (p-values) of co-occurred items. With help of this model, the dimensionality of co-occurrence network could be conveniently reduced according to selection of different levels of p-value thresholds. The conceptual model framework, simulation and practical applications are illustrated in the manuscript. Further details (including all reproducible codes) can be downloaded from the project website: https://github.com/Miao-zhou/Co-occurrence-analysis.git.

Background Monitoring and prediction of diabetic retinopathy (DR) is necessary in patients with diabetes for early discovery and timely treatment of disease. We aimed to analyze the association between DR and biochemical and metabolic parameters, and develop a predictive model for DR. Methods A total of 530 Chinese residents including 423 with type 2 diabetes (T2D) aged 18 years or older participated in this study. The association between DR and biochemical and metabolic parameters was analyzed by the univariate and multivariable logistic regression (MLR). According to the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tan-sigmoid as the transfer function of the hidden layers nodes, and pure-line of the output layer nodes, with training goal of 0.5×10-5. Results There were 51 (9.6%) diabetic participants with DR. After univariate and MLR analysis, duration of diabetes, waist to hip ratio, HbA1c and family history of diabetes were independently associated with the presence of DR (all P < 0.05). Based on these parameters, the area under the receiver operating characteristic (ROC) curve for the BP-ANN model was significantly higher than that by MLR (0.84 vs. 0.77, P < 0.001). Conclusion Our evaluation demonstrated the potential role of BP-ANN model to identify DR in screening practice. The presence of DR was well predictable using the proposed BP-ANN model based on four related parameters (duration of diabetes, waist to hip ratio, HbA1c and family history of diabetes).

Based on the assumption that only the presence of water and solvent is considered in the aqueous phase, a robust and pragmatic water-associated isenthalpic flash (WAIF) model has been developed to perform multiphase isenthalpic flash calculations for water/solvent/hydrocarbon mixtures at high pressures and elevated temperatures. More specifically, the phase boundary diagram in enthalpy-temperature (H-T) space is constructed first for a given water/solvent/hydrocarbon system at a specified pressure. Then, the phase transition enthalpies and temperatures are determined from the H-T diagram, and thus one-, two-, or three-phase isenthalpic flash calculations can be conducted directly without resorting to stability test for a given system at a specified enthalpy and pressure. In addition, a recursive method has been proposed to initialize the temperature so that the energy conservation equation and material balance equation can be solved simultaneously to overcome the convergence difficulties. The newly proposed isenthalpic flash model has been compared with the water-free isenthalpic flash (WFIF) model and conventional three-phase isenthalpic flash (CTIF) model through three case studies. The WAIF model is found to handle the narrow-boiling constraints effectively and accurately. Furthermore, as for Water/C3H8/C16H34 mixture and Water/CO2/C16H34 mixture, a good agreement is achieved between the WFIF model and the WAIF model as the solubility of solvents (i.e., C3H8 and CO2) in the aqueous phase is quite small. With respect to Water/dimethyl ether (DME)/C16H34 mixture, however, the WAIF model is found to more accurately predict the phase behaviour of water/solvent/hydrocarbon mixtures than the WFIF model since the solubility of DME in the aqueous phase cannot be neglected. The case studies demonstrate that the newly developed water-associated isenthalpic flash model for water/solvent/hydrocarbon systems is robust, efficient, and accurate.

Objective Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain infectious diseases to effectively control their prevalence and outbreak potential. Compared to the use of one base model, model stacking can often produce better forecasting results. In this study, we fitted the monthly reported cases of HFRS in mainland China with a model stacking approach and compared its forecasting performance with those of five base models. Method We fitted the monthly reported cases of HFRS ranging from January 2004 to June 2019 in mainland China with an autoregressive integrated moving average (ARIMA) model; the Holt-Winter (HW) method, seasonal decomposition of the time series by LOESS (STL); a neural network autoregressive (NNAR) model; and an exponential smoothing state space model with a Box-Cox transformation; ARMA errors; and trend and seasonal components (TBATS), and we combined the forecasting results with the inverse rank approach. The forecasting performance was estimated based on several accuracy criteria for model prediction, including the mean absolute percentage error (MAPE), root-mean-squared error (RMSE) and mean absolute error (MAE). Result There was a slight downward trend and obvious seasonal periodicity inherent in the time series data for HFRS in mainland China. The model stacking method was selected as the best approach with the best performance in terms of both fitting (RMSE 128.19, MAE 85.63, MAPE 8.18) and prediction (RMSE 151.86, MAE 118.28, MAPE 13.16). Conclusion The results showed that model stacking by using the optimal mean forecasting weight of the five abovementioned models achieved the best performance in terms of predicting HFRS one year into the future. This study has corroborated the conclusion that model stacking is an easy way to enhance prediction accuracy when modeling HFRS.

Background This study aimed to use the stretched-exponential nonlinear regression analysis model to explore the value of the energy spectral curve in the differential diagnosis of clear cell renal cell carcinoma (ccRCC), minimal fat renal angiomyolipoma (RAML), and hypovascular renal cell carcinoma. Methods Sixty-five cases with renal tumors were enrolled retrospectively who had undergone a preoperative multiphase spectral CT scan of the kidney in pre-enhance and double-phase enhanced scanning. The normalized iodine concentrations (NIC) of these lesions, normal renal cortex, and psoas major were measured and calculated. The spectral curves of these lesions and normal tissues were analyzed to calculate the stretched-exponential index (α) and b value with the stretched-exponential nonlinear regression analysis model (y=-b·Xα). The differences between α, b value, and NIC of these lesions and normal tissues in pre-enhance and two enhanced phases were compared using one-way ANOVA. The correlation between α, b value, and NIC was evaluated using the Pearson coefficient test, with significance assigned at the 5% level. Results There was no significant difference in α value between the groups in pre-enhance scanning. In the Cortical phase (CP), there were no significant differences in NIC and α value between minimal fat RAML and hypovascular renal cell carcinoma, or between ccRCC and the normal renal cortex. However, in the nephrographic phase (NP), a significant difference in α value was found between minimal fat RAML and hypovascular renal cell carcinoma, but no difference in NIC between them. In NP, there were significant differences in NIC and α values between ccRCC and the normal renal cortex. In CP and NP, there were significant differences between the psoas major and other groups in all parameters. For b value, in pre-enhance scanning, there was a significant difference between the psoas major and other groups, and between ccRCC and the normal renal cortex. There was no significant difference between other groups. After enhancement, in CP and NP, significant differences were observed between the psoas major and other groups in b value, but no significant differences were observed between all renal tumors and the normal renal cortex. A linear correlation was found between α values and NIC in CP (r=0.780, P=0.00) and NP (r=0.693, P=0.00). The b values and NIC had a low correlation in CP, with no correlation in NP. Conclusions Quantitative spectral CT with the stretched-exponential nonlinear regression analysis model may enhance the differential diagnosis ability for renal tumors. Its clinical value remains to be further explored in other types of soft tissue lesions.

Background We are now in the third generation of medical education reform. To fully grasp this transformation, we need to identify the field’s knowledge structure. This study conducted a bibliometric analysis to discover the general publication statue during the last three decades (1989–2018) with an eye for identifying prolific institutions, core journals, international collaboration, and the evolution of key themes.Methods We retrieved 15,329 papers from the Web of Science Core Collection database that were published between 1989 and 2018 , and we analysed them to determine prolific institutions, core journals, institutional collaboration statue, and hot spots of research. R studio, SciMAT, and VOSviewer were jointly applied. For a better understanding of thematic evolution in the field, we split the study period into three sub-periods with equal time spans.Results We discovered that, worldwide, scholars are increasingly attracted to research on medical education. Medical Education is the most prolific journal in the field. While the US publishes an overwhelming proportion of the most relevant papers, articles published by the UK are, on average, most frequently cited. We identify five key research centres based on the most prolific academic institutions, and our analysis of relevant collaborations reveals that international collaboration is common. The hottest themes during each sub-period are revealed and how they evolve across different time spans are also detected.Conclusions This bibliometric study identifies the scientific structure of medical education research over the past three decades. Ultimately, it may help scholars identify new topics and future research challenges in this field and, moreover, highlight meaningful evidence for policymakers in the field of medical teaching innovation.

ObjectivesHuman brucellosis is a public health problem endangering health and property in China. Predicting the trend and the seasonality of human brucellosis is of great significance for its prevention. In this study, a comparison between the autoregressive integrated moving average (ARIMA) model and the eXtreme Gradient Boosting (XGBoost) model was conducted to determine which was more suitable for predicting the occurrence of brucellosis in mainland China.DesignTime-series study.SettingMainland China.MethodsData on human brucellosis in mainland China were provided by the National Health and Family Planning Commission of China. The data were divided into a training set and a test set. The training set was composed of the monthly incidence of human brucellosis in mainland China from January 2008 to June 2018, and the test set was composed of the monthly incidence from July 2018 to June 2019. The mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to evaluate the effects of model fitting and prediction.ResultsThe number of human brucellosis patients in mainland China increased from 30 002 in 2008 to 40 328 in 2018. There was an increasing trend and obvious seasonal distribution in the original time series. For the training set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)12 model were 338.867, 450.223 and 10.323, respectively, and the MAE, RSME and MAPE of the XGBoost model were 189.332, 262.458 and 4.475, respectively. For the test set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)12 model were 529.406, 586.059 and 17.676, respectively, and the MAE, RSME and MAPE of the XGBoost model were 249.307, 280.645 and 7.643, respectively.ConclusionsThe performance of the XGBoost model was better than that of the ARIMA model. The XGBoost model is more suitable for prediction cases of human brucellosis in mainland China.

In this paper, techniques have been developed to determine multiphase boundaries of solvent(s)/heavy oil mixtures at high pressures and elevated temperatures in pressure-temperature (P-T), enthalpy-temperature (H-T), and pressure-enthalpy (P-H) phase diagrams, respectively. Theoretically, the Peng-Robinson equation of state (PR EOS) incorporated with a new alpha function as well as the previously developed enthalpy calculation algorithm are used to predict the multiphase boundaries of the solvent(s)/heavy oil systems by characterizing the heavy oil as a single pseudocomponent. The PR EOS associated with the newly developed alpha function is found to be accurate in reproducing the experimentally measured VL1L2 (V represents the vapour phase, L1 denotes the high density hydrocarbon-rich liquid phase, and L2 refers to the low density CO2 liquid phase) three-phase boundary pressures with an overall absolute average relative deviation (AARD) of 2.01% and maximum average relative deviation (MARD) of 3.54%, respectively. In addition, the VL1L2 three-phase boundaries are expanded and tended to move toward the region with higher temperatures and lower pressures in the P-T phase diagram with the addition of either C3H8 or n-C4H10 to CO2/heavy oil systems compared to those of only CO2 exists in heavy oil systems. The enthalpy changes rapidly with variation of temperature in both H-T and P-H phase diagrams within the three-phase region. Either two-phase (VL1) or three-phase (VL1L2) isenthalpic flash calculations can be performed straightly to determine phase fractions and compositions together with system temperature without conducting the stability analysis for a provided solvent(s)/heavy oil mixture at a constant enthalpy and pressure with the constructed H-T phase diagram.

Background Immune cells in the tumor microenvironment are an important prognostic indicator in diffuse large B-cell lymphoma (DLBCL). However, information on the heterogeneity and risk stratification of these cells is limited. We sought to develop a novel immune model to evaluate the prognostic intra-tumoral immune landscape of patients with DLBCL. Methods The ESTIMATE and CIBERSORT algorithms were used to estimate the numbers of 22 infiltrating immune cells based on the gene expression profiles of 229 patients with DLBCL who were recruited from a public database. The least absolute shrinkage and selection operator (Lasso) penalized regression analyses and nomogram model were used to construct and evaluate the prognostic immunoscore (PIS) model for overall survival prediction. An immune gene prognostic score (IGPS) was generated by Gene Set Enrichment Analysis (GSEA) and Cox regression analysis was and validated in an independent NCBI GEO dataset (GSE10846). Results A higher proportion of activated natural killer cells was associated with a poor outcome. A total of five immune cells were selected in the Lasso model and DLBCL patients with high PIS showed a poor prognosis (hazard ratio (HR) 2.16; 95% CI [1.33–3.50]; P = 0.002). Differences in immunoscores and their related outcomes were attributed to eight specific immune genes involved in the cytokine–cytokine receptor interaction and chemokine signaling pathways. The IGPS based on a weighted formula of eight genes is an independent prognostic factor (HR: 2.14, 95% CI [1.40–3.28]), with high specificity and sensitivity in the validation dataset. Conclusions Our findings showed that a PIS model based on immune cells is associated with the prognosis of DLBCL. We developed a novel immune-related gene-signature model associated with the PIS model and enhanced the prognostic functionality for the prediction of overall survival in patients with DLBCL.

Climate change is a challenge for the sustainable development of an international economy and society. The impact of climate change on infectious diseases has been regarded as one of the most urgent research topics. In this paper, an analysis of the bibliometrics, co-word biclustering, and strategic diagram was performed to evaluate global scientific production, hotspots, and developing trends regarding climate change and infectious diseases, based on the data of two decades (1999&ndash, 2008 and 2009&ndash, 2018) from PubMed. According to the search strategy and inclusion criteria, a total of 1443 publications were found on the topic of climate change and infectious diseases. There has been increasing research productivity in this field, which has been supported by a wide range of subject categories. The top highly-frequent major MeSH (medical subject headings)/subheading combination terms could be divided into four clusters for the first decade and five for the second decade using a biclustering analysis. At present, some significant public health challenges (global health, and travel and tropical climate, etc.) are at the center of the whole target research network. In the last ten years, &ldquo, Statistical model&rdquo, &ldquo, Diarrhea&rdquo, Dengue&rdquo, Ecosystem and biodiversity&rdquo, and &ldquo, Zoonoses&rdquo, have been considered as emerging hotspots, but they still need more attention for further development.

Two epidemiological models were applied to simulate whether animals with latent infections were contagious and calculate the outcomes of people that contracting brucellosis by all possible transmission routes under control measures implemented by the Chinese government. The health and economic burden of brucellosis overall presented an increasing trend from 2004 to 2017. Scenarios from epidemiological models showed that a larger scale of vaccine coverage would contribute to fewer infections in livestock and humans. S2 vaccine, the disinfection of the environment and the protection of the susceptible animals and humans could effectively reverse the trend of increasing brucellosis and reduce the incidence rates of brucellosis in humans to curb the epidemic of brucellosis in China.

Diabetes mellitus (DM) is one of the growing public health threats globally and as one of the common serious microvascular complications of DM, diabetic retinopathy (DR) is the leading cause of irreversible visual impairments and blindness. There is growing concern about the role of microRNAs (miRNAs) in the pathogenesis of DR. This meta-analysis was designed to collect those published miRNA expression profiling studies that compared the miRNA expression profiles in the biological samples of DR patients with those in the control group. Eight publications were finally included in the meta-analysis, and a total of 93 differentially expressed miRNAs were reported. Although six miRNAs were reported in at least two studies and with the consistent direction, after stratification by the type of biological samples, miR-320a was consistently reported to be upregulated in two serum sample-based studies and miR-423-5p was consistently reported to be upregulated in two vitreous humor sample-based studies. miR-27b was consistently reported to be downregulated in two serum sample-based studies. In conclusion, the results of this meta-analysis of human DR miRNAs' expression profiling studies might provide some clues of the potential biomarkers of DR. Further investigation of the mechanisms of miRNAs and more external validation studies are warranted with the aim of developing new diagnostic markers for preventing or reversing DR.

Introduction This systematic scoping review aims to assess the frequency and severity of clinical manifestations of pregnant women with brucellosis. Methods Three literature databases, PubMed, Web of Science and China National Knowledge Infrastructure (CNKI), and two search engines (Google and Yahoo) were adopted to identify the relevant articles that published until 31 December 2019. Two investigators independently screened the publications and extracted the data; the case reports and case series which described at least two symptoms or clinical manifestations of pregnant women with brucellosis were included. Results A total of 27 articles describing the information of 521 pregnant women with brucellosis were included. Serum agglutination test was the most common laboratory test in the diagnosis of brucellosis. A total of 36 clinical manifestations were extracted from the included articles, and the most common clinical manifestations were fever (400, 76.8%), joint pain/swelling/arthralgia (389, 74.7%), sweats (382, 73.3%), fatigue/asthenia/weakness (262, 50.3%) and back pain (189, 36.3%). Among the 32 included individual cases that with available obstetric outcome information, 10 (31.3%) suffered preterm delivery, 12 (37.5%) had an abortion and 3 (9.8%) had intrauterine fetal death. Conclusion Brucellosis is popular and threatening for pregnant women. Regarding the localized body system complications, osteoarticular system was mostly involved, the obstetrics outcomes were severe among pregnant women with brucellosis. The detailed clinical and epidemiological characteristics in this scoping review may add a better and more complete understanding of the disease for both physicians and policy-makers, and provide evidence for timely diagnosis, adequate therapy and better prevention.

Apnea should be monitored continuously in the post anesthesia care unit (PACU) to avoid serious complications. It has been confirmed that tracheal sounds can be used to detect apnea during sedation in healthy subjects, but the performance of this acoustic method has not been evaluated in patients with frequent apnea events in the PACU. Tracheal sounds were acquired from the patients in the PACU using a microphone encased in a plastic bell. Concurrently, a processed nasal pressure signal was used as a reference standard to identify real respiratory events. The logarithm of the tracheal sound variance (log-var) was used to detect apnea, and the results were compared to the reference method. Sensitivity, specificity, positive likelihood ratios (PLR), and negative likelihood ratios (NLR) were calculated. One hundred and twenty-one patients aged 55.5 ± 13.2 years (mean ± SD) with a body mass index of 24.6 ± 3.7 kg/m2 were included in data analysis. The total monitoring time was 52.6 h. Thirty-four patients experienced 236 events of apnea lasting for a total of 122.2 min. The log-var apnea detection algorithm detected apnea with 92% sensitivity, 98% specificity, 46 PLR and 0.08 NLR. The performance of apnea detection in the PACU using the log-var tracheal sounds method proved to be reliable and accurate. Tracheal sounds could be used to minimize the potential risks from apnea in PACU patients.

Background World Health Organization (WHO), the World Bank, UN System Influenza Coordination (UNSIC) and other international organizations released a series of documents to fight against the influenza pandemic. Those documents have great significance on guiding influenza pandemic preparedness and responses and providing a multilevel, multi-directional influenza pandemic prevention and control network for their member countries. This study focuses on the above-mentioned influenza pandemic preparedness guidelines with the aim of exploring the roles of the society, defining the relationship of different interventions and evaluating the planning on influenza pandemic preparedness. Methods Documents about pandemic influenza preparedness were retrieved from the official websites of the following three international organizations, World Health Organization (WHO), the World Bank, UN System Influenza Coordination (UNSIC) with the key words ‘pandemic’, ‘influenza’ and the Boolean combinations of these words as the retrieval strategy. Guidelines, research study and meeting reports were included in the study. The categories of the ministries/departments involved and their roles/responsibilities in pandemic influenza preparedness were summarized. Word frequency of selected vocabularies about pandemic influenza preventive measures were collected from the documents and the correlations between the word frequency of these measures were analyzed. Ochiai coefficient was employed to show the correlation between the word vocabularies. Results A total of 38 records on the topic of pandemic influenza preparedness were included. The responsibilities of the whole-of-society mentioned in the international organizations’ documents varied across the 2009 influenza pandemic period. Meanwhile, it had been emphasized that a comprehensive influenza prevention and control plan in every sector should be developed and evaluated. Because various measures were emphasized in the guidelines after 2009 pandemic influenza, the correlations between the word frequencies of the various influenza preventive measures became stronger after the pandemic influenza. Conclusions Responsibilities of ministries of education, ministries of energy, ministries of agriculture and animal health, ministries of communication and the business sector in the pandemic influenza preparedness were described more comprehensively in the international organizations’ documents in 2017. Better understanding the variations of the guidelines delivered by international organizations would be useful for the member countries to strengthen their influenza control network. Electronic supplementary material The online version of this article (10.1186/s12879-018-3286-3) contains supplementary material, which is available to authorized users.

Purpose To describe the incidence trend, demographic and clinical characteristics, treatment and prognosis, epidemiological history and risk factors of human brucellosis in Huludao, China. Patients and Methods A total of 1887 brucellosis patients were reported in Huludao, China from January, 2014 to December, 2018 and the case questionnaires from 1149 patients were collected from Huludao Municipal Center for Disease Control and Prevention. Demographic characteristics of the patients and the information relating to the patients’ clinical manifestations, diagnosis, treatment and prognosis were collected and analyzed. Results The number of annually reported brucellosis patients has dropped from 711 to 187 during the study period, with the incidence decreased from 27.31/100,000 in 2014 to 7.15/100,000 in 2018. A total of 1149 individual data were collected, with a mean age of 49.59±13.14 years and 75.7% were male. Patients aged more than 60 years were more likely to have arthralgia/myalgia than the other age groups, and patients who had an enlarged spleen in male were more than female (P

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.

This study reports the results from a discrete choice experiment conducted in Beijing China. It aims to elicit monetary values for the value of a statistical life (VSL) and the value of a statistical illness (VSI) that can be considered for policy purposes in China, and to examine how different payment regimes influence willingness to pay (WTP) and whether WTP is age-dependent. We find that our estimates are robust between different econometric model specifications and that they are reliable when compared to previous Chinese findings. We find no evidence of any VSL–age relationship but we find that the payment scheme had an effect on the levels of the estimates of the VSL and VSI, and that taking into account the payment regimes when estimating the models improved their performance. However, levels were relatively close and not statistically significantly different for VSL which may suggest that respondents considered both schemes as similar.

In this paper, the newly developed techniques have been applied to determine multiphase boundaries and physical properties of solvent(s)/heavy oil mixtures at various pressures and temperatures in pressure–temperature (P-T), enthalpy-temperature (H-T), and pressure-enthalpy (P-H) phase diagrams, respectively. Theoretically, the Peng-Robinson equation of state (PR EOS) incorporated with a modified alpha function as well as the previously developed enthalpy calculation algorithm are used to predict the multiphase boundaries of the solvent(s)/heavy oil systems consisting of non-hydrocarbon solvents of CO2 and dimethyl ether (DME) as well as hydrocarbon solvents of C3H8 and n-C4H10. The PR EOS associated with the recently modified alpha function is found to be accurate in reproducing the experimentally measured VL1L2 (V represents the vapour phase, L1 denotes the high density hydrocarbon-rich liquid phase, and L2 refers to the low density CO2 liquid phase) three-phase boundary pressures with an overall absolute average relative deviation (AARD) of 2.01% and a maximum average relative deviation (MARD) of 4.34%, respectively. In addition, the VL1L2 three-phase boundaries are expanded and tended to move toward the region with higher temperatures and lower pressures in the P-T phase diagram with the addition of either C3H8 or n-C4H10 to CO2/heavy oil systems compared to those of only CO2 exists in heavy oil systems. Also, the new theoretical model developed in this study is able to reproduce the experimentally measured VL1 two-phase boundaries of alkane solvents/CO2/heavy oil mixtures as well as DME/heavy oil mixtures with an AARD of 4.52% and 2.88%, respectively. The enthalpy changes rapidly with variation of temperature in both H-T and P-H phase diagrams within the three-phase region.

Expanding-Solvent Steam-Assisted Gravity Drainage (ES-SAGD) is proposed to develop the oil sands more efficiently than conventional SAGD. Even in the rising phase when the steam hasn't reached the overburden, the heat-mass transfer in the wellbore can be one of the reasons for the non-uniform chamber growth of ES-SAGD along the horizontal well. Furthermore, the time and oil production during the rising phase greatly determine the final benefits of the ES-SAGD. In this study, a mathematical method is established to evaluate the performance of ES-SAGD in the rising phase. The calculated results show that: pentane can help increase the oil rate in the rising phase significantly, while the effect of heptane is not quite obvious. Although propane is also a widely used solvent, the oil rate with it is even lower than that of conventional SAGD. The differentials between the cases, which consider the wellbore or not, is different for different solvent-steam co-injections. Specifically, the oil rate differential between the situations considering the wellbore effect or not for propane-SAGD is the highest and is almost twice that of conventional SAGD which has the least differential. Pentane-SAGD has the second-largest differential which is followed by heptane-SAGD. Therefore, for the sake of a more accurate evaluation of ES-SAGD performance in the chamber rising phase, the effects of solvent diffusion into the bitumen and the heat-mass transfer in the wellbore should be comprehensively considered.