The recurrence of atrial fibrillation(AF)in patients after successful radiofrequency catheter ablation(RFCA)appears to be an unresolved clinical issue and needs to be clearly elucidated.There are many factors associat...The recurrence of atrial fibrillation(AF)in patients after successful radiofrequency catheter ablation(RFCA)appears to be an unresolved clinical issue and needs to be clearly elucidated.There are many factors associated with AF recurrence,such as duration of AF,male sex,concomitant heart failure,hemodynamic parameters,chronic obstructive pulmonary disease,hypertension,obstructive sleep apnea,hyperthyroidism,smoking and obesity.However,the inflammatory changes are strongly associated with electrical and structural cardiac remodeling,cardiac damage,myocardial fibrotic changes,microvascular dysfunction and altered reparative response.In this context,biomarkers reflecting the different stages of AF pathogenesis deserve thorough investigation.The authors of the retrospective study revealed that one-year recurrence rate of non-valvular AF in the high systemic immune inflammation(SII)index group was significantly increased compared to that of the low SII index group and provided additional predictive value to the APPLE.Furthermore,the authors suggest that this biomarker may help physicians to optimize the selection of AF patients and to develop a personalized treatment approach.In conclusion,the SII index may serve as a valuable indicator of recurrent AF in patients after RFCA and may be a biomarker with plausible predictive value for poor clinical outcomes.展开更多
The present study examines the impact of short-term public opinion sentiment on the secondary market,with a focus on the potential for such sentiment to cause dramatic stock price fluctuations and increase investment ...The present study examines the impact of short-term public opinion sentiment on the secondary market,with a focus on the potential for such sentiment to cause dramatic stock price fluctuations and increase investment risk.The quantification of investment sentiment indicators and the persistent analysis of their impact has been a complex and significant area of research.In this paper,a structured multi-head attention stock index prediction method based adaptive public opinion sentiment vector is proposed.The proposedmethod utilizes an innovative approach to transform numerous investor comments on social platforms over time into public opinion sentiment vectors expressing complex sentiments.It then analyzes the continuous impact of these vectors on the market through the use of aggregating techniques and public opinion data via a structured multi-head attention mechanism.The experimental results demonstrate that the public opinion sentiment vector can provide more comprehensive feedback on market sentiment than traditional sentiment polarity analysis.Furthermore,the multi-head attention mechanism is shown to improve prediction accuracy through attention convergence on each type of input information separately.Themean absolute percentage error(MAPE)of the proposedmethod is 0.463%,a reduction of 0.294% compared to the benchmark attention algorithm.Additionally,the market backtesting results indicate that the return was 24.560%,an improvement of 8.202% compared to the benchmark algorithm.These results suggest that themarket trading strategy based on thismethod has the potential to improve trading profits.展开更多
BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestationa...BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant women.However,traditional methods for the diagnosis of LGA have limitations.Therefore,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of LGA.METHODS The multivariable prediction model was developed by carrying out the following steps.First,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<0.10.Subsequently,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the criterion.The final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<0.05.Finally,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve analyses.RESULTS After using a multistep screening method,we establish a predictive model.Several risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks.The nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 for the training cohort,validation cohort,and test cohort,respectively).The calibration curves of the three cohorts displayed good agreement.The decision curve showed that the use of the 10%-60%threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit.CONCLUSION Our nomogram incorporated easily accessible risk factors,facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.展开更多
BACKGROUND Biliary tract cancer(BTC)is a rare,aggressive malignancy with increasing inci-dence and poor prognosis.Identifying preoperative prognostic factors is crucial for effective risk-benefit assessments and patie...BACKGROUND Biliary tract cancer(BTC)is a rare,aggressive malignancy with increasing inci-dence and poor prognosis.Identifying preoperative prognostic factors is crucial for effective risk-benefit assessments and patient stratification.The prognostic nutritional index(PNI),which reflects immune-inflammatory and nutritional status,has shown prognostic value in various cancers,but its significance in BTC remains unclear.AIM To assess the prognostic value of the preoperative PNI in BTC patients,with a focus on overall survival(OS)and disease-free survival(DFS).METHODS Comprehensive searches were conducted in the PubMed,EMBASE,and Web of Science databases from inception to April 2024.The primary outcomes of interest focused on the associations between the preoperative PNI and the prognosis of BTC patients,specifically OS and disease-free survival(DFS).Statistical analyses were conducted via STATA 17.0 software.RESULTS Seventeen studies encompassing 4645 patients met the inclusion criteria.Meta-analysis revealed that a low PNI was significantly associated with poorer OS[hazard ratio(HR)1.91,95%CI:1.59-2.29;P<0.001]and DFS(HR 1.93,95%CI:1.39-2.67;P<0.001).Subgroup analyses revealed consistent results across BTC subtypes(cholangiocarcinoma and gallbladder cancer)and stages(resectable and advanced).Sensitivity analyses confirmed the robustness of these findings,and no significant publication bias was detected.CONCLUSION This study demonstrated that a low preoperative PNI predicts poor OS and DFS in BTC patients,highlighting its potential as a valuable prognostic tool.Further prospective studies are needed to validate these findings and enhance BTC patient management.展开更多
This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatl...This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.展开更多
The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has a...The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.展开更多
The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for...The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for the PPI system and the quantitive relationship among the delay margin,the time constant of the closed-loop system, and the dead-time of the model are given. A graphicalgorithm to compute the delay margin is also developed. The phenomenon that there exist morethan one stability delay zones is discussed. The algorithm is shown to be precise by some simulations.展开更多
BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking Univers...BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.展开更多
Conical picks are by far the most widely used drag type cutting tools employed on partial face rock excavation machines.The cutting force and specific energy are two important design parameters for the conical pick pe...Conical picks are by far the most widely used drag type cutting tools employed on partial face rock excavation machines.The cutting force and specific energy are two important design parameters for the conical pick performance,and the rock cutting testing is considered as the promising tool for determining these parameters.In the absence of an instrumented cutting rig,researchers generally rely on empirical predictive plots.For this,this paper suggests predictive plots for estimating the cutting force and specific energy,in consideration of the cutting depth to define the cuttability with conical picks.In this context,rock cutting tests were carried out on six volcanic rock samples with varying cutting depths using the unrelieved and relieved cutting modes.The cutting force and specific energy were correlated with the uniaxial compressive strength,Brazilian tensile strength,elasticity modulus,and plasticity index.Predictive plots were proposed for different cutting depths in the unrelieved and relieved cutting modes and exponential relationships were obtained among the cuttability parameters,and mechanical and elastoplastic properties of rocks.展开更多
AIM: To investigate extravascular lung water indexed to predicted body weight(EVLWIp) and actual body weight(EVLWIa) on outcome of patients with severe sepsis.METHODS: Transpulmonary thermodilution was prospectively u...AIM: To investigate extravascular lung water indexed to predicted body weight(EVLWIp) and actual body weight(EVLWIa) on outcome of patients with severe sepsis.METHODS: Transpulmonary thermodilution was prospectively used to measure cardiovascular hemodynamics, EVLWIp and EVLWIa via an arterial catheter placed in each patient within 48 h of meeting the criteria for severe sepsis from a medical intensive care unit(ICU) at a university affiliated hospital. Survival was the single dependent variable. In order to examine and compare the predictive power of EVLWIp, EVLWIa and other clinically significant factors in predicting the inhospital survival status of severe sepsis patients in the medical ICU, a receiver operating characteristic(ROC) curve method to analyze the significant variables and the area under the ROC curve(AUC) of the variables, P value and 95%CI were calculated.RESULTS: In total, 33 patients were studied. In the ROC curve method analyses, EVLWIp(the AUC: 0.849; P = 0.001, 95%CI: 0.72-0.98) was as predictive for inhospital survival rate as variables with EVLWIa(AUC, 0.829; P = 0.001, 95%CI: 0.68-0.98). The proportion of patients surviving with a low EVLW(EVLWI < 10 m L/kg) was better than that of patients with a higher EVLW, whether indexed by actual(HR = 0.2; P = 0.0002, 95%CI: 0.06-0.42) or predicted body weight(HR = 0.13; P < 0.0001, 95%CI: 0.05-0.35) during their hospital stay with the Kaplan-Meier method(76% vs 12.5%, respectively).CONCLUSION: This investigation proposed that EVLWIp is as good a predictor as EVLWIa to predict inhospital survival rate among severe sepsis patients in the medical ICU.展开更多
The plasticity index is an essential design parameter used as a standard input in fine-grained soil investigation programs.It is used to estimate the plasticity and physical properties of soils,and indirectly their st...The plasticity index is an essential design parameter used as a standard input in fine-grained soil investigation programs.It is used to estimate the plasticity and physical properties of soils,and indirectly their strength properties.This index is determined from the Atterberg limit tests,starting from the limits of liquidity and plasticity.However,the realization of the test considered as basic and simple,is not so much.The effects of the operator,the calibration of the apparatus and the environmental aspects during the tests affect the reliability and accuracy of the results.In this paper,the objective is to overcome these difficulties by evaluating the plasticity index of clay and loam soils by considering only the values of the liquid limit.Soil samples were collected from 0 to 5 m depth in the localities of the Khôdepression in Benin.On these samples,Atterberg limit tests were performed in the laboratory.Using MATLAB’s Curve Fitting Toolbox,linear,exponential and power prediction models were analyzed.The results showed that there is indeed a good correlation between the plasticity index and the liquid limit of the soils.For the linear model,it was observed R2 equal to 0.9891.For the exponential model,R2 is 0.98871 and for the power model 0.9802.A study of the residual plot validated the models found,as well as comparisons with well-known literature sources.Through the equations obtained,it is now possible to study the plasticity of soils in the Khôdepression only from the liquid limit,without determining the plasticity limit.展开更多
文摘The recurrence of atrial fibrillation(AF)in patients after successful radiofrequency catheter ablation(RFCA)appears to be an unresolved clinical issue and needs to be clearly elucidated.There are many factors associated with AF recurrence,such as duration of AF,male sex,concomitant heart failure,hemodynamic parameters,chronic obstructive pulmonary disease,hypertension,obstructive sleep apnea,hyperthyroidism,smoking and obesity.However,the inflammatory changes are strongly associated with electrical and structural cardiac remodeling,cardiac damage,myocardial fibrotic changes,microvascular dysfunction and altered reparative response.In this context,biomarkers reflecting the different stages of AF pathogenesis deserve thorough investigation.The authors of the retrospective study revealed that one-year recurrence rate of non-valvular AF in the high systemic immune inflammation(SII)index group was significantly increased compared to that of the low SII index group and provided additional predictive value to the APPLE.Furthermore,the authors suggest that this biomarker may help physicians to optimize the selection of AF patients and to develop a personalized treatment approach.In conclusion,the SII index may serve as a valuable indicator of recurrent AF in patients after RFCA and may be a biomarker with plausible predictive value for poor clinical outcomes.
基金funded by the Major Humanities and Social Sciences Research Projects in Zhejiang higher education institutions,grant number 2023QN082,awarded to Cheng ZhaoThe National Natural Science Foundation of China also provided funding,grant number 61902349,awarded to Cheng Zhao.
文摘The present study examines the impact of short-term public opinion sentiment on the secondary market,with a focus on the potential for such sentiment to cause dramatic stock price fluctuations and increase investment risk.The quantification of investment sentiment indicators and the persistent analysis of their impact has been a complex and significant area of research.In this paper,a structured multi-head attention stock index prediction method based adaptive public opinion sentiment vector is proposed.The proposedmethod utilizes an innovative approach to transform numerous investor comments on social platforms over time into public opinion sentiment vectors expressing complex sentiments.It then analyzes the continuous impact of these vectors on the market through the use of aggregating techniques and public opinion data via a structured multi-head attention mechanism.The experimental results demonstrate that the public opinion sentiment vector can provide more comprehensive feedback on market sentiment than traditional sentiment polarity analysis.Furthermore,the multi-head attention mechanism is shown to improve prediction accuracy through attention convergence on each type of input information separately.Themean absolute percentage error(MAPE)of the proposedmethod is 0.463%,a reduction of 0.294% compared to the benchmark attention algorithm.Additionally,the market backtesting results indicate that the return was 24.560%,an improvement of 8.202% compared to the benchmark algorithm.These results suggest that themarket trading strategy based on thismethod has the potential to improve trading profits.
基金Supported by National Natural Science Foundation of China,No.81870546Nanjing Medical Science and Technique Development Foundation,No.YKK23151Science and Technology Development Foundation Item of Nanjing Medical University,No.NMUB20210117.
文摘BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy outcomes.It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant women.However,traditional methods for the diagnosis of LGA have limitations.Therefore,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of LGA.METHODS The multivariable prediction model was developed by carrying out the following steps.First,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<0.10.Subsequently,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the criterion.The final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<0.05.Finally,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve analyses.RESULTS After using a multistep screening method,we establish a predictive model.Several risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks.The nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 for the training cohort,validation cohort,and test cohort,respectively).The calibration curves of the three cohorts displayed good agreement.The decision curve showed that the use of the 10%-60%threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit.CONCLUSION Our nomogram incorporated easily accessible risk factors,facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.
文摘BACKGROUND Biliary tract cancer(BTC)is a rare,aggressive malignancy with increasing inci-dence and poor prognosis.Identifying preoperative prognostic factors is crucial for effective risk-benefit assessments and patient stratification.The prognostic nutritional index(PNI),which reflects immune-inflammatory and nutritional status,has shown prognostic value in various cancers,but its significance in BTC remains unclear.AIM To assess the prognostic value of the preoperative PNI in BTC patients,with a focus on overall survival(OS)and disease-free survival(DFS).METHODS Comprehensive searches were conducted in the PubMed,EMBASE,and Web of Science databases from inception to April 2024.The primary outcomes of interest focused on the associations between the preoperative PNI and the prognosis of BTC patients,specifically OS and disease-free survival(DFS).Statistical analyses were conducted via STATA 17.0 software.RESULTS Seventeen studies encompassing 4645 patients met the inclusion criteria.Meta-analysis revealed that a low PNI was significantly associated with poorer OS[hazard ratio(HR)1.91,95%CI:1.59-2.29;P<0.001]and DFS(HR 1.93,95%CI:1.39-2.67;P<0.001).Subgroup analyses revealed consistent results across BTC subtypes(cholangiocarcinoma and gallbladder cancer)and stages(resectable and advanced).Sensitivity analyses confirmed the robustness of these findings,and no significant publication bias was detected.CONCLUSION This study demonstrated that a low preoperative PNI predicts poor OS and DFS in BTC patients,highlighting its potential as a valuable prognostic tool.Further prospective studies are needed to validate these findings and enhance BTC patient management.
文摘This paper presents a multivariable generalized predictive controller with proportion and integration structure by modifying the quadratic criterion of the usual MGPC. The control performance has been improved greatly. The effectiveness of the controller is demonstrated by the simulation result.
基金Supported by the National Natural Science Foundation of China(21676299,21476261and 21606255)
文摘The dividing wall column （DWC） is considered as a major breakthrough in distillation technology and has good prospect of industrialization. Model predictive control （MPC） is an advanced control strategy that has acquired extensive applications in various industries. In this study, MPC is applied to the process for separating ethanol, n-propanol, and n-butanol ternary mixture in a fully thermally coupled DWC. Both composition control and tem- perature inferent/al control are considered. The multiobjective genetic algor/thm function ＂gamult/obj＂ in Matlab is used for the weight tuning of MPC. Comparisons are made between the control performances of MPC and PI strategies. Simulation results show that although both MPC and PI schemes can stabilize the DWC in case of feed disturbances, MPC generally behaves better than the PI strategy for both composition control and tempera- ture inferential control, resulting in a more stable and superior performance with lower values of integral of squared error （ISE）.
文摘The variation of plant dead-time deeply a?ects the stability of the predictive PI controlsystem. It is important for designing and applying the PPI controller to calculate the delay margin.A criterion of stability for the PPI system and the quantitive relationship among the delay margin,the time constant of the closed-loop system, and the dead-time of the model are given. A graphicalgorithm to compute the delay margin is also developed. The phenomenon that there exist morethan one stability delay zones is discussed. The algorithm is shown to be precise by some simulations.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2020D01C236)
文摘BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.
文摘Conical picks are by far the most widely used drag type cutting tools employed on partial face rock excavation machines.The cutting force and specific energy are two important design parameters for the conical pick performance,and the rock cutting testing is considered as the promising tool for determining these parameters.In the absence of an instrumented cutting rig,researchers generally rely on empirical predictive plots.For this,this paper suggests predictive plots for estimating the cutting force and specific energy,in consideration of the cutting depth to define the cuttability with conical picks.In this context,rock cutting tests were carried out on six volcanic rock samples with varying cutting depths using the unrelieved and relieved cutting modes.The cutting force and specific energy were correlated with the uniaxial compressive strength,Brazilian tensile strength,elasticity modulus,and plasticity index.Predictive plots were proposed for different cutting depths in the unrelieved and relieved cutting modes and exponential relationships were obtained among the cuttability parameters,and mechanical and elastoplastic properties of rocks.
基金Supported by Grants from Taiwan National Science Council,No.NSC-100-2314-B-182A-054Chang Gung Memorial Hospital,Nos.CMRPG3B0831,CMRPG3B0832 and CMRPG3A0562
文摘AIM: To investigate extravascular lung water indexed to predicted body weight(EVLWIp) and actual body weight(EVLWIa) on outcome of patients with severe sepsis.METHODS: Transpulmonary thermodilution was prospectively used to measure cardiovascular hemodynamics, EVLWIp and EVLWIa via an arterial catheter placed in each patient within 48 h of meeting the criteria for severe sepsis from a medical intensive care unit(ICU) at a university affiliated hospital. Survival was the single dependent variable. In order to examine and compare the predictive power of EVLWIp, EVLWIa and other clinically significant factors in predicting the inhospital survival status of severe sepsis patients in the medical ICU, a receiver operating characteristic(ROC) curve method to analyze the significant variables and the area under the ROC curve(AUC) of the variables, P value and 95%CI were calculated.RESULTS: In total, 33 patients were studied. In the ROC curve method analyses, EVLWIp(the AUC: 0.849; P = 0.001, 95%CI: 0.72-0.98) was as predictive for inhospital survival rate as variables with EVLWIa(AUC, 0.829; P = 0.001, 95%CI: 0.68-0.98). The proportion of patients surviving with a low EVLW(EVLWI < 10 m L/kg) was better than that of patients with a higher EVLW, whether indexed by actual(HR = 0.2; P = 0.0002, 95%CI: 0.06-0.42) or predicted body weight(HR = 0.13; P < 0.0001, 95%CI: 0.05-0.35) during their hospital stay with the Kaplan-Meier method(76% vs 12.5%, respectively).CONCLUSION: This investigation proposed that EVLWIp is as good a predictor as EVLWIa to predict inhospital survival rate among severe sepsis patients in the medical ICU.
文摘The plasticity index is an essential design parameter used as a standard input in fine-grained soil investigation programs.It is used to estimate the plasticity and physical properties of soils,and indirectly their strength properties.This index is determined from the Atterberg limit tests,starting from the limits of liquidity and plasticity.However,the realization of the test considered as basic and simple,is not so much.The effects of the operator,the calibration of the apparatus and the environmental aspects during the tests affect the reliability and accuracy of the results.In this paper,the objective is to overcome these difficulties by evaluating the plasticity index of clay and loam soils by considering only the values of the liquid limit.Soil samples were collected from 0 to 5 m depth in the localities of the Khôdepression in Benin.On these samples,Atterberg limit tests were performed in the laboratory.Using MATLAB’s Curve Fitting Toolbox,linear,exponential and power prediction models were analyzed.The results showed that there is indeed a good correlation between the plasticity index and the liquid limit of the soils.For the linear model,it was observed R2 equal to 0.9891.For the exponential model,R2 is 0.98871 and for the power model 0.9802.A study of the residual plot validated the models found,as well as comparisons with well-known literature sources.Through the equations obtained,it is now possible to study the plasticity of soils in the Khôdepression only from the liquid limit,without determining the plasticity limit.
