BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI ...BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI in a Chinese population.METHODS A total of 1138 patients undergoing CABG were collected from September 2018 to May 2020 and divided into a derivation and validation cohort.AKI was defined according to the Kidney Disease Improving Global Outcomes(KDIGO)criteria.Multivariable logistic regression analysis was used to determine the independent predictors of AKI,and the predictive ability of the model was determined using a receiver operating characteristic(ROC)curve.RESULTS The incidence of cardiac surgery–associated acute kidney injury(CSA-AKI)was 24.17%,and 0.53%of AKI patients required dialysis(AKI-D).Among the derivation cohort,multivariable logistic regression showed that age≥70 years,body mass index(BMI)≥25 kg/m2,estimated glomerular filtration rate(eGFR)≤60 mL/min per 1.73 m2,ejection fraction(EF)≤45%,use of statins,red blood cell transfusion,use of adrenaline,intra-aortic balloon pump(IABP)implantation,postoperative low cardiac output syndrome(LCOS)and reoperation for bleeding were independent predictors.The predictive model was scored from 0 to32 points with three risk categories.The AKI frequencies were as follows:0-8 points(15.9%),9-17 points(36.5%)and≥18 points(90.4%).The area under of the ROC curve was 0.730(95%CI:0.691-0.768)in the derivation cohort.The predictive index had good discrimination in the validation cohort,with an area under the curve of 0.735(95%CI:0.655-0.815).The model was well calibrated according to the Hosmer-Lemeshow test(P=0.372).CONCLUSION The performance of the prediction model was valid and accurate in predicting KDIGO-AKI after CABG surgery in Chinese patients,and could improve the early prognosis and clinical interventions.展开更多
The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichm...The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichment law. This study builds porosity and fracture development and evolution models in different deposition environments, through core observation, casting thin section, SEM, porosity and permeability analysis, burial history analysis, and ＂four-property-relationships＂ analysis.展开更多
BACKGROUND The World Health Organization recommends testing all human immunodeficiency virus(HIV)patients for hepatitis C virus(HCV).In resource-constrained contexts with low-to-intermediate HCV prevalence among HIV p...BACKGROUND The World Health Organization recommends testing all human immunodeficiency virus(HIV)patients for hepatitis C virus(HCV).In resource-constrained contexts with low-to-intermediate HCV prevalence among HIV patients,as in Cambodia,targeted testing is,in the short-term,potentially more feasible and cost-effective.AIM To develop a clinical prediction score(CPS)to risk-stratify HIV patients for HCV coinfection(HCV RNA detected),and derive a decision rule to guide prioritization of HCV testing in settings where‘testing all’is not feasible or unaffordable in the short term.METHODS We used data of a cross-sectional HCV diagnostic study in the HIV cohort of Sihanouk Hospital Center of Hope in Phnom Penh.Key populations were very rare in this cohort.Score development relied on the Spiegelhalter and Knill-Jones method.Predictors with an adjusted likelihood ratio≥1.5 or≤0.67 were retained,transformed to natural logarithms,and rounded to integers as score items.CPS performance was evaluated by the area-under-the-ROC curve(AUROC)with 95% confidence intervals(CI),and diagnostic accuracy at the different cut-offs.For the decision rule,HCV coinfection probability≥1% was agreed as test-threshold.RESULTS Among the 3045 enrolled HIV patients,106 had an HCV coinfection.Of the 11 candidate predictors(from history-taking,laboratory testing),seven had an adjusted likelihood ratio≥1.5 or≤0.67:≥50 years(+1 point),diabetes mellitus(+1),partner/household member with liver disease(+1),generalized pruritus(+1),platelets<200×10^(9)/L(+1),aspartate transaminase(AST)<30 IU/L(-1),AST-to-platelet ratio index(APRI)≥0.45(+1),and APRI<0.45(-1).The AUROC was 0.84(95%CI:0.80-0.89),indicating good discrimination of HCV/HIV coinfection and HIV mono-infection.The CPS result≥0 best fits the test-threshold(negative predictive value:99.2%,95%CI:98.8-99.6).Applying this threshold,30%(n=926)would be tested.Sixteen coinfections(15%)would have been missed,none with advanced fibrosis.CONCLUSION The CPS performed well in the derivation cohort,and bears potential for other contexts of low-to-intermediate prevalence and little onward risk of transmission(i.e.cohorts without major risk factors as injecting drug use,men having sex with men),and where available resources do not allow to test all HIV patients as recommended by WHO.However,the score requires external validation in other patient cohorts before any wider use can be considered.展开更多
In order to predict electromechanical equipments＇ nonlinear and non-stationary condition effectively, max Lyapunov exponent is introduced to the fault trend prediction of large rotating mechanical equipments based on...In order to predict electromechanical equipments＇ nonlinear and non-stationary condition effectively, max Lyapunov exponent is introduced to the fault trend prediction of large rotating mechanical equipments based on chaos theory. The predict method of chaos time series and two methods of proposing f and F are dis- cussed. The arithmetic of max prediction time of chaos time series is provided. Aiming at the key part of large rotating mechanical equipments-bearing, used this prediction method the simulation experiment is carried out. The result shows that this method has excellent performance for condition trend prediction.展开更多
Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of...Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of GIS equipment in order to improve its active safety protection level.This paper carried out research on the accurate prediction method and experimental validation of the mechanical vibration state and its defect severity development trend for the GIS equipment.Firstly,the deep and shallow vibration feature parameters for different mechanical defect signals were jointly extracted by time-domain features and deep belief network methods.Secondly,a new prediction model,incorporating the attention mechanism and the bidirectional gated recurrent unit(BiGRU),was constructed with the deep and shallow vibration feature parameters as inputs.Finally,the prediction trend effectiveness was verified based on the real-type GIS mechanical simulation platform and the field operation GIS equipment.Results show that the deep and shallow vibration feature extraction method proposed in this paper can characterise the mechanical defect information more comprehensively.The new prediction method of the vibration state trend based on the attention-BiGRU model shows ideal accuracy,and the predicted vibration state development trend is highly consistent with the actual,with an average absolute error of 0.063.The root mean square error(ERMSE)value of the prediction method is<5%,which reduces the relative error value at least 37% compared with the traditional prediction models.This paper provides a valuable reference for the proactive defence of GIS mechanical failure.展开更多
With the support by the National Natural Science Foundation of China,the research team jointly led by Porf.Liu Zaiyi(刘再毅)at Guangdong General Hospital and Prof.Tian Jie(田捷)at the Key Laboratory of Molecular Imagi...With the support by the National Natural Science Foundation of China,the research team jointly led by Porf.Liu Zaiyi(刘再毅)at Guangdong General Hospital and Prof.Tian Jie(田捷)at the Key Laboratory of Molecular Imaging,Chinese Academy of Sciences,developed a CT-based radiomics prediction model to preoperatively predict the lymph node metastasis in colorectal cancer(CRC),which was published展开更多
This project is supported by the 2007 R ＆ D Special Fund for Public Welfare by Ministry of Science and Technology and Ministry of Finance.Research tasks in this project are proposed based on the implementation plan o...This project is supported by the 2007 R ＆ D Special Fund for Public Welfare by Ministry of Science and Technology and Ministry of Finance.Research tasks in this project are proposed based on the implementation plan of the＂THORPEX（The Observing System Research and Predictability Experiment） Interactive Grand Global Ensemble（TIGGE）＂,a sub-project of the THORPEX international program.展开更多
Based on the evaluation of state-of-the-art coupled ocean-atmosphere general circulation models （CGCMs） from the ENSEMBLES （Ensemble-based Predictions of Climate Changes and Their Impacts） and DEME- TER （Developm...Based on the evaluation of state-of-the-art coupled ocean-atmosphere general circulation models （CGCMs） from the ENSEMBLES （Ensemble-based Predictions of Climate Changes and Their Impacts） and DEME- TER （Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction） projects, it is found that the prediction of the South China Sea summer monsoon （SCSSM） has improved since the late 1970s. These CGCMs show better skills in prediction of the atmospheric circulation and precipitation within the SCSSM domain during 1979-2005 than that during 1960-1978. Possible reasons for this improvement are investigated. First, the relationship between the SSTs over the tropical Pacific, North Pacific and tropical Indian Ocean, and SCSSM has intensified since the late 1970s. Meanwhile, the SCSSM-related SSTs, with their larger amplitude of interannual variability, have been better predicted. Moreover, the larger amplitude of the interannual variability of the SCSSM and improved initializations for CGCMs after the late 1970s contribute to the better prediction of the SCSSM. In addition, considering that the CGCMs have certain limitations in SCSSM rainfall prediction, we applied the year-to-year increment approach to these CGCMs from the DEMETER and ENSEMBLES projects to improve the prediction of SCSSM rainfall before and after the late 1970s.展开更多
Comparisons are made between experimental data and numerical predictions based on the k-e turbulent model of low Reynolds number applicable to developing turbulent flow in rectangular ducts of arbitrary aspect ratio.T...Comparisons are made between experimental data and numerical predictions based on the k-e turbulent model of low Reynolds number applicable to developing turbulent flow in rectangular ducts of arbitrary aspect ratio.The numerical procedure utilizes the separated-layers finite-analytical method.The merits of the k-e turbulent model of low Reynolds number and the computation procedure are assessed by means of comparison with results,referred to that of the length-scale model and the full-Reynolds-stress model used in recent years.展开更多
which highlights the necessity for developing predictive biomarkers and overcoming ICB resistance.Cancer cell-intrinsic features,especially those that can be dynamically monitored via liquid biopsy,represent a broader...which highlights the necessity for developing predictive biomarkers and overcoming ICB resistance.Cancer cell-intrinsic features,especially those that can be dynamically monitored via liquid biopsy,represent a broader scope for biomarker development.In addition,a potential mode of ICB resistance is tumor-intrinsic mechanisms leading to an immunosuppressive tumor microenvironment(TME).However,the underlying interactive network remains elusive,and the generalizable biomarkers and targeting strategies are still lacking.Here,we uncovered the potential of plasma S100 calcium-binding protein A1(S100A1)for determining ICB efficacy via liquid biopsy of patients with lung cancer.Multiomics and functional studies have suggested that tumor-intrinsic S100A1 expression correlated with an immunologically"cold"TME and resistance to ICB in multiple syngeneic murine tumors and tissue samples from patients with lung cancer.Mechanistic investigations demonstrated that interfering with the tumor-intrinsic S100A1/ubiquitin-specific protease 7/p65/granulocyte-macrophage colony-stimulating factor(GM-CSF)modulatory axis could potentiate an inflamed TME by promoting M1-like macrophage polarization and T cell function.GM-CSF priming was sufficient to enhance the ICB response in tumors with high S100A1 expression in preclinical models.These findings define S100A1 as a potential blood-based biomarker and a novel synergistic target for cancer immunotherapy.展开更多
Chemical space is vast,and the space of physical properties derived from it even more so.Despite over a century of physical chemistry measurements,we still lack large,well-organised data sets of key physical propertie...Chemical space is vast,and the space of physical properties derived from it even more so.Despite over a century of physical chemistry measurements,we still lack large,well-organised data sets of key physical properties such as the interfacial tension of surfactant solutions.Access to such data sets is essential to developing the next generation of predictive models for physicochemical properties using modern approaches such as artificial intelligence and machine learning(ML).Thus,we require experimental methods which can efficiently provide large,reproducible and informative data sets.In this work,we developed a robotic,automated pendant drop module for the efficient characterisation of the interfacial properties of surfactant-containing solutions.Provided with surfactant stock solutions,the module measures a surface tension isotherm,from which multiple important physical properties can be determined,including the critical micelle concentration and the maximum surface excess concentration.The module handles critical experimental challenges and decisions such as choosing an appropriate drop volume,detecting failed measurements and selecting concentration points to measure.To obtain a maximally informative dataset,the platform leverages an active learning algorithm combining Bayesian inference and mutual information to dynamically design experiments in response to collected data.We validate the platform by characterising a range of surfactants and demonstrate the effectiveness of its capabilities by mapping the surface tension of binary surfactant mixtures.This module lays the foundation for efficiently and autonomously generating informative datasets of the interfacial properties of surfactant formulations,paving the way to the next generation of ML models for the prediction of formulation properties.展开更多
Simulations of land use/land cover(LULC)and ecosystem services(ES),which integrate national land policies,reflect the development of land and ecological functions under different scenarios and are crucial for accurate...Simulations of land use/land cover(LULC)and ecosystem services(ES),which integrate national land policies,reflect the development of land and ecological functions under different scenarios and are crucial for accurately predicting and optimizing urban ecosystem sustainable development.展开更多
基金supported by National Natural S cience Foundation of China(81570373)。
文摘BACKGROUND Acute kidney injury(AKI)after coronary artery bypass graft(CABG)surgery is associated with significant morbidity and mortality.This retrospective study aimed to establish a risk score for postoperative AKI in a Chinese population.METHODS A total of 1138 patients undergoing CABG were collected from September 2018 to May 2020 and divided into a derivation and validation cohort.AKI was defined according to the Kidney Disease Improving Global Outcomes(KDIGO)criteria.Multivariable logistic regression analysis was used to determine the independent predictors of AKI,and the predictive ability of the model was determined using a receiver operating characteristic(ROC)curve.RESULTS The incidence of cardiac surgery–associated acute kidney injury(CSA-AKI)was 24.17%,and 0.53%of AKI patients required dialysis(AKI-D).Among the derivation cohort,multivariable logistic regression showed that age≥70 years,body mass index(BMI)≥25 kg/m2,estimated glomerular filtration rate(eGFR)≤60 mL/min per 1.73 m2,ejection fraction(EF)≤45%,use of statins,red blood cell transfusion,use of adrenaline,intra-aortic balloon pump(IABP)implantation,postoperative low cardiac output syndrome(LCOS)and reoperation for bleeding were independent predictors.The predictive model was scored from 0 to32 points with three risk categories.The AKI frequencies were as follows:0-8 points(15.9%),9-17 points(36.5%)and≥18 points(90.4%).The area under of the ROC curve was 0.730(95%CI:0.691-0.768)in the derivation cohort.The predictive index had good discrimination in the validation cohort,with an area under the curve of 0.735(95%CI:0.655-0.815).The model was well calibrated according to the Hosmer-Lemeshow test(P=0.372).CONCLUSION The performance of the prediction model was valid and accurate in predicting KDIGO-AKI after CABG surgery in Chinese patients,and could improve the early prognosis and clinical interventions.
文摘The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichment law. This study builds porosity and fracture development and evolution models in different deposition environments, through core observation, casting thin section, SEM, porosity and permeability analysis, burial history analysis, and ＂four-property-relationships＂ analysis.
文摘BACKGROUND The World Health Organization recommends testing all human immunodeficiency virus(HIV)patients for hepatitis C virus(HCV).In resource-constrained contexts with low-to-intermediate HCV prevalence among HIV patients,as in Cambodia,targeted testing is,in the short-term,potentially more feasible and cost-effective.AIM To develop a clinical prediction score(CPS)to risk-stratify HIV patients for HCV coinfection(HCV RNA detected),and derive a decision rule to guide prioritization of HCV testing in settings where‘testing all’is not feasible or unaffordable in the short term.METHODS We used data of a cross-sectional HCV diagnostic study in the HIV cohort of Sihanouk Hospital Center of Hope in Phnom Penh.Key populations were very rare in this cohort.Score development relied on the Spiegelhalter and Knill-Jones method.Predictors with an adjusted likelihood ratio≥1.5 or≤0.67 were retained,transformed to natural logarithms,and rounded to integers as score items.CPS performance was evaluated by the area-under-the-ROC curve(AUROC)with 95% confidence intervals(CI),and diagnostic accuracy at the different cut-offs.For the decision rule,HCV coinfection probability≥1% was agreed as test-threshold.RESULTS Among the 3045 enrolled HIV patients,106 had an HCV coinfection.Of the 11 candidate predictors(from history-taking,laboratory testing),seven had an adjusted likelihood ratio≥1.5 or≤0.67:≥50 years(+1 point),diabetes mellitus(+1),partner/household member with liver disease(+1),generalized pruritus(+1),platelets<200×10^(9)/L(+1),aspartate transaminase(AST)<30 IU/L(-1),AST-to-platelet ratio index(APRI)≥0.45(+1),and APRI<0.45(-1).The AUROC was 0.84(95%CI:0.80-0.89),indicating good discrimination of HCV/HIV coinfection and HIV mono-infection.The CPS result≥0 best fits the test-threshold(negative predictive value:99.2%,95%CI:98.8-99.6).Applying this threshold,30%(n=926)would be tested.Sixteen coinfections(15%)would have been missed,none with advanced fibrosis.CONCLUSION The CPS performed well in the derivation cohort,and bears potential for other contexts of low-to-intermediate prevalence and little onward risk of transmission(i.e.cohorts without major risk factors as injecting drug use,men having sex with men),and where available resources do not allow to test all HIV patients as recommended by WHO.However,the score requires external validation in other patient cohorts before any wider use can be considered.
基金Sponsored by Key Funding Project for Science and Technology under the Beijing Municipal Education Commission(KZ200910772001)
文摘In order to predict electromechanical equipments＇ nonlinear and non-stationary condition effectively, max Lyapunov exponent is introduced to the fault trend prediction of large rotating mechanical equipments based on chaos theory. The predict method of chaos time series and two methods of proposing f and F are dis- cussed. The arithmetic of max prediction time of chaos time series is provided. Aiming at the key part of large rotating mechanical equipments-bearing, used this prediction method the simulation experiment is carried out. The result shows that this method has excellent performance for condition trend prediction.
基金National Key R&D Program of China,Grant/Award Numbers:2022YFB2403700,2022YFB2403705Natural Science Foundation of Chongqing,Grant/Award Number:CSTB2022NSCQ-MSX1247。
文摘Mechanical vibration defect is the key factor leading to sudden failure of gas-insulated switchgear(GIS)equipment.It is important to realise effective prediction of the me-chanical vibration state development trend of GIS equipment in order to improve its active safety protection level.This paper carried out research on the accurate prediction method and experimental validation of the mechanical vibration state and its defect severity development trend for the GIS equipment.Firstly,the deep and shallow vibration feature parameters for different mechanical defect signals were jointly extracted by time-domain features and deep belief network methods.Secondly,a new prediction model,incorporating the attention mechanism and the bidirectional gated recurrent unit(BiGRU),was constructed with the deep and shallow vibration feature parameters as inputs.Finally,the prediction trend effectiveness was verified based on the real-type GIS mechanical simulation platform and the field operation GIS equipment.Results show that the deep and shallow vibration feature extraction method proposed in this paper can characterise the mechanical defect information more comprehensively.The new prediction method of the vibration state trend based on the attention-BiGRU model shows ideal accuracy,and the predicted vibration state development trend is highly consistent with the actual,with an average absolute error of 0.063.The root mean square error(ERMSE)value of the prediction method is<5%,which reduces the relative error value at least 37% compared with the traditional prediction models.This paper provides a valuable reference for the proactive defence of GIS mechanical failure.
文摘With the support by the National Natural Science Foundation of China,the research team jointly led by Porf.Liu Zaiyi(刘再毅)at Guangdong General Hospital and Prof.Tian Jie(田捷)at the Key Laboratory of Molecular Imaging,Chinese Academy of Sciences,developed a CT-based radiomics prediction model to preoperatively predict the lymph node metastasis in colorectal cancer(CRC),which was published
文摘This project is supported by the 2007 R ＆ D Special Fund for Public Welfare by Ministry of Science and Technology and Ministry of Finance.Research tasks in this project are proposed based on the implementation plan of the＂THORPEX（The Observing System Research and Predictability Experiment） Interactive Grand Global Ensemble（TIGGE）＂,a sub-project of the THORPEX international program.
基金Supported by the National Natural Science Foundation of China(41421004,41325018,and 41575079)State Administration for Foreign Expert Affairs of the Chinses Academy of Sciences(CAS/SAFEA)
文摘Based on the evaluation of state-of-the-art coupled ocean-atmosphere general circulation models （CGCMs） from the ENSEMBLES （Ensemble-based Predictions of Climate Changes and Their Impacts） and DEME- TER （Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction） projects, it is found that the prediction of the South China Sea summer monsoon （SCSSM） has improved since the late 1970s. These CGCMs show better skills in prediction of the atmospheric circulation and precipitation within the SCSSM domain during 1979-2005 than that during 1960-1978. Possible reasons for this improvement are investigated. First, the relationship between the SSTs over the tropical Pacific, North Pacific and tropical Indian Ocean, and SCSSM has intensified since the late 1970s. Meanwhile, the SCSSM-related SSTs, with their larger amplitude of interannual variability, have been better predicted. Moreover, the larger amplitude of the interannual variability of the SCSSM and improved initializations for CGCMs after the late 1970s contribute to the better prediction of the SCSSM. In addition, considering that the CGCMs have certain limitations in SCSSM rainfall prediction, we applied the year-to-year increment approach to these CGCMs from the DEMETER and ENSEMBLES projects to improve the prediction of SCSSM rainfall before and after the late 1970s.
文摘Comparisons are made between experimental data and numerical predictions based on the k-e turbulent model of low Reynolds number applicable to developing turbulent flow in rectangular ducts of arbitrary aspect ratio.The numerical procedure utilizes the separated-layers finite-analytical method.The merits of the k-e turbulent model of low Reynolds number and the computation procedure are assessed by means of comparison with results,referred to that of the length-scale model and the full-Reynolds-stress model used in recent years.
基金the following funding sources:National Key R&D Program of China(2022YFC2505000)NSFC general program(82272796)+3 种基金NSFC general program(8197112364)NSFC special program(82241229)CAMS Innovation Fund for Medical Sciences(CIFMS 2022-12M-1-009)Heilongjiang Province"Unveiling the Leader"Science and Technology Research Project(2022ZXJ03CO).
文摘which highlights the necessity for developing predictive biomarkers and overcoming ICB resistance.Cancer cell-intrinsic features,especially those that can be dynamically monitored via liquid biopsy,represent a broader scope for biomarker development.In addition,a potential mode of ICB resistance is tumor-intrinsic mechanisms leading to an immunosuppressive tumor microenvironment(TME).However,the underlying interactive network remains elusive,and the generalizable biomarkers and targeting strategies are still lacking.Here,we uncovered the potential of plasma S100 calcium-binding protein A1(S100A1)for determining ICB efficacy via liquid biopsy of patients with lung cancer.Multiomics and functional studies have suggested that tumor-intrinsic S100A1 expression correlated with an immunologically"cold"TME and resistance to ICB in multiple syngeneic murine tumors and tissue samples from patients with lung cancer.Mechanistic investigations demonstrated that interfering with the tumor-intrinsic S100A1/ubiquitin-specific protease 7/p65/granulocyte-macrophage colony-stimulating factor(GM-CSF)modulatory axis could potentiate an inflamed TME by promoting M1-like macrophage polarization and T cell function.GM-CSF priming was sufficient to enhance the ICB response in tumors with high S100A1 expression in preclinical models.These findings define S100A1 as a potential blood-based biomarker and a novel synergistic target for cancer immunotherapy.
基金funding from the National Growth Fund project“Big Chemistry”(1420578)funded by the Ministry of Education,Culture and ScienceThis project was also supported by the European Union and the Swiss State Secretariat for Education,Research and Innovation(SERI)under contract numbers 22.00017 and 22.00034(Horizon Europe Research and Innovation Project CORENET).
文摘Chemical space is vast,and the space of physical properties derived from it even more so.Despite over a century of physical chemistry measurements,we still lack large,well-organised data sets of key physical properties such as the interfacial tension of surfactant solutions.Access to such data sets is essential to developing the next generation of predictive models for physicochemical properties using modern approaches such as artificial intelligence and machine learning(ML).Thus,we require experimental methods which can efficiently provide large,reproducible and informative data sets.In this work,we developed a robotic,automated pendant drop module for the efficient characterisation of the interfacial properties of surfactant-containing solutions.Provided with surfactant stock solutions,the module measures a surface tension isotherm,from which multiple important physical properties can be determined,including the critical micelle concentration and the maximum surface excess concentration.The module handles critical experimental challenges and decisions such as choosing an appropriate drop volume,detecting failed measurements and selecting concentration points to measure.To obtain a maximally informative dataset,the platform leverages an active learning algorithm combining Bayesian inference and mutual information to dynamically design experiments in response to collected data.We validate the platform by characterising a range of surfactants and demonstrate the effectiveness of its capabilities by mapping the surface tension of binary surfactant mixtures.This module lays the foundation for efficiently and autonomously generating informative datasets of the interfacial properties of surfactant formulations,paving the way to the next generation of ML models for the prediction of formulation properties.
基金The Special Fund for the Basic Research and Development Program at the Central Non-profit Research Institutes of China(no.CAFYBB2020ZB008)provided financial support for this study
文摘Simulations of land use/land cover(LULC)and ecosystem services(ES),which integrate national land policies,reflect the development of land and ecological functions under different scenarios and are crucial for accurately predicting and optimizing urban ecosystem sustainable development.
