The batch extractive distillation (BED) process has the advantages of both batch and extractive distillation. It is one of the most promising means for the separation of azeotropic and close-boiling point systems. How...The batch extractive distillation (BED) process has the advantages of both batch and extractive distillation. It is one of the most promising means for the separation of azeotropic and close-boiling point systems. However, so far this process has not been applied in industry due to its over-complexity. A new shortcut model was proposed to simulate the operation of the batch extractive distillation operations. This algorithm is based on the assumption that the batch extractive distillation column can be considered as a continuous extractive distillation column with changing feed at any time. Namely, the whole batch process is simulated as a succession of a finite number of steady states of short duration, in which holdup is considered as constant mole. For each period of time the batch extractive distillation process is solved through the algorithm for continuous extractive distillation. Finally, the practical implementation of the shortcut model is discussed and data from the laboratory and literature are presented. It is found that this model has better adaptability, more satisfactory accuracy and less calculative load than previous rigorous model. Hence the algorithm for simulating BED is verified.展开更多
Background Frailty is a new prognostic factor in cardiovascular medicine due to the aging and increasingly complex nature of elderly patients. It is useful and meaningful to prospectively analyze the manner in which f...Background Frailty is a new prognostic factor in cardiovascular medicine due to the aging and increasingly complex nature of elderly patients. It is useful and meaningful to prospectively analyze the manner in which frailty predicts short-term outcomes for elderly patients with acute coronary syndrome （ACS）. Methods Patients aged 〉 65 years, with diagnosis of ACS from cardiology department and geriatrics department were included from single-center. Clinical data including geriatrics syndromes were collected using Comprehensive Geriatrics Assessment. Frailty was defined according to the Clinical Frailty Scale and the impact of the co-morbidities on risk was quantified by the coronary artery disease （CAD）--specific index. Patients were followed up by clinical visit or telephone consultation and the median follow-up time is 120 days. Following-up items included all-cause mortality, unscheduled return visit, in-hospital and recurrent major adverse cardiovascular events. Multivariable regression survival analysis was performed using Cox regression. Results Of the 352 patients, 152 （43.18%） were considered frail according to the study instrument （5-7 on the scale）, and 93 （26.42%） were considered moderately or se- verely frail （6-7 on the scale）. Geriatrics syndromes including incontinence, fall history, visual impairment, hearing impairment, constipation, chronic pain, sleeping disorder, dental problems, anxiety or depression, and delirium were more frequently in frail patients than in non-frail patients （P = 0.000, 0.031, 0.009, 0.014, 0.000, 0.003, 0.022, 0.000, 0.074, and 0.432, respectively）. Adjusted for sex, age, severity of coro- nary artery diseases （left main coronary artery lesion or not） and co-morbidities （CAD specific index） by Cox survival analysis, frailty was found to be strongly and independently associated with risk for the primary composite outcomes： all-canse mortality [Hazard Ratio （HR） = 5.393; 95% CI： 1.477-19.692, P = 0.011] and unscheduled return visit （HR - 2.832; 95% CI： 1.140-7.037, P = 0.025）. Conclusions Comprehensive Geriatrics Assessment and Clinical Frail Scale were useful in evaluation of elderly patients with ACS. Frailty was strongly and independently associated with short-term outcomes for elderly patients with ACS.展开更多
As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet...As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet theory, this paper combined the wavelet theory with neural network and established a MRA wavelet network with the scaling function and wavelet function as its neurons. From the analysis in the frequency domain, the results indicated that MRA wavelet network was better than other wavelet networks in the ability of approaching to the signals. An essential research was can:led out on modeling and prediction with MRA wavelet network in the non-linear system. Using the lengthwise sway data received from the experiment of ship model, a model of offline prediction was established and was applied to the short-time prediction of ship motion. The simulation results indicated that the forecasting model improved the prediction precision effectively, lengthened the forecasting time and had a better prediction results than that of AR linear model. The research indicates that it is feasible to use the MRA wavelet network in the short-time prediction of ship motion.展开更多
The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from...The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.展开更多
AIM： To evaluate the efficacy of short-term overlap lamivudine therapy with adefovir in patients with lamivudine-resistant and naive chronic hepatitis B, we compared patients receiving overlap therapy with those rece...AIM： To evaluate the efficacy of short-term overlap lamivudine therapy with adefovir in patients with lamivudine-resistant and naive chronic hepatitis B, we compared patients receiving overlap therapy with those receiving adefovir alone. METHODS： Eighty patients who had received lamivudine treatment for various periods and had a lamivudineo resistant liver function abnormality were enrolled. Forty of these patients received adefovir treatment combined with lamivudine treatment for ≥ 2 mo, while the other 40 received adefovir alone. We assessed the levels of hepatitis B virus （HBV） DNA at 0, 12 and 48 wk and serum alanine aminotransferase （ALT） levels after 0, 12, 24 and 48 wk of adefovir treatment in each group. RESULTS： We found serum ALT became normalized in 72 （87.5%） of the 80 patients, and HBV DNA decreased by ≥ 2 Ioglo copies/mL in 60 （75%） of the 80 patients at the end of a 48-wk treatment. HBV DNA levels were not significantly different between the groups. The improvements in serum ALT were also not significantly different between the two groups. CONCLUSION： These findings suggest short-term overlap lamivudine treatment results in no better virological and biological outcomes than non-overlap adefovir monotherapy.展开更多
Two Gaussian air quality dispersion models, the industrial source complex short-term model (ISCST3) with and without modification have been used to simulate the pollutant concentration distribution in urban areas base...Two Gaussian air quality dispersion models, the industrial source complex short-term model (ISCST3) with and without modification have been used to simulate the pollutant concentration distribution in urban areas based on the meteorological data and the emissions distribution of sulfur dioxide. The verified data show that the modified model is more accurate in the urban area of Shijiazhuang. Using the modified model predictions, the control strategies of sulfur dioxide in the urban area have been studied, and the result show that the second long-term (to 2010) strategy can mitigate air pollution significantly and maintain pollution levels within permissible limits.展开更多
In this paper, the classical economic order quantity （EOQ） inventory model assumption that all items of a certain product received from a supplier are of perfect quality is relaxed. Another basic assumption that the...In this paper, the classical economic order quantity （EOQ） inventory model assumption that all items of a certain product received from a supplier are of perfect quality is relaxed. Another basic assumption that the payment for the items is made at the beginning of the inventory cycle when they are received is also eased. We consider an inventory situation where items received from the supplier are of two types of quality, perfect and imperfect, and a short deferral in payment is allowed. The split between perfect and imperfect quality items is assumed to follow a known probability distribution. Both qualities of items have continuous demands, and items of imperfect quality are sold at a discount. A mathematical model is developed using the net present value of all cash flows involved in the inventory cycle. A numerical method for obtaining the optimal order quantity is presented, and the impact of the short-term financing is analyzed. An example is presented to validate the equations and illustrate the results.展开更多
The wavelet power system short term load forecasting(STLF) uses a mulriple periodical autoregressive integrated moving average(MPARIMA) model to model the mulriple near periodicity, nonstationarity and nonlinearity ex...The wavelet power system short term load forecasting(STLF) uses a mulriple periodical autoregressive integrated moving average(MPARIMA) model to model the mulriple near periodicity, nonstationarity and nonlinearity existed in power system short term quarter hour load time series, and can therefore accurately forecast the quarter hour loads of weekdays and weekends, and provide more accurate results than the conventional techniques, such as artificial neural networks and autoregressive moving average(ARMA) models test results. Obtained with a power system networks in a city in Northeastern part of China confirm the validity of the approach proposed.展开更多
基金Supported by National Development and Reform Commission (2005 No1899)
文摘The batch extractive distillation (BED) process has the advantages of both batch and extractive distillation. It is one of the most promising means for the separation of azeotropic and close-boiling point systems. However, so far this process has not been applied in industry due to its over-complexity. A new shortcut model was proposed to simulate the operation of the batch extractive distillation operations. This algorithm is based on the assumption that the batch extractive distillation column can be considered as a continuous extractive distillation column with changing feed at any time. Namely, the whole batch process is simulated as a succession of a finite number of steady states of short duration, in which holdup is considered as constant mole. For each period of time the batch extractive distillation process is solved through the algorithm for continuous extractive distillation. Finally, the practical implementation of the shortcut model is discussed and data from the laboratory and literature are presented. It is found that this model has better adaptability, more satisfactory accuracy and less calculative load than previous rigorous model. Hence the algorithm for simulating BED is verified.
文摘Background Frailty is a new prognostic factor in cardiovascular medicine due to the aging and increasingly complex nature of elderly patients. It is useful and meaningful to prospectively analyze the manner in which frailty predicts short-term outcomes for elderly patients with acute coronary syndrome （ACS）. Methods Patients aged 〉 65 years, with diagnosis of ACS from cardiology department and geriatrics department were included from single-center. Clinical data including geriatrics syndromes were collected using Comprehensive Geriatrics Assessment. Frailty was defined according to the Clinical Frailty Scale and the impact of the co-morbidities on risk was quantified by the coronary artery disease （CAD）--specific index. Patients were followed up by clinical visit or telephone consultation and the median follow-up time is 120 days. Following-up items included all-cause mortality, unscheduled return visit, in-hospital and recurrent major adverse cardiovascular events. Multivariable regression survival analysis was performed using Cox regression. Results Of the 352 patients, 152 （43.18%） were considered frail according to the study instrument （5-7 on the scale）, and 93 （26.42%） were considered moderately or se- verely frail （6-7 on the scale）. Geriatrics syndromes including incontinence, fall history, visual impairment, hearing impairment, constipation, chronic pain, sleeping disorder, dental problems, anxiety or depression, and delirium were more frequently in frail patients than in non-frail patients （P = 0.000, 0.031, 0.009, 0.014, 0.000, 0.003, 0.022, 0.000, 0.074, and 0.432, respectively）. Adjusted for sex, age, severity of coro- nary artery diseases （left main coronary artery lesion or not） and co-morbidities （CAD specific index） by Cox survival analysis, frailty was found to be strongly and independently associated with risk for the primary composite outcomes： all-canse mortality [Hazard Ratio （HR） = 5.393; 95% CI： 1.477-19.692, P = 0.011] and unscheduled return visit （HR - 2.832; 95% CI： 1.140-7.037, P = 0.025）. Conclusions Comprehensive Geriatrics Assessment and Clinical Frail Scale were useful in evaluation of elderly patients with ACS. Frailty was strongly and independently associated with short-term outcomes for elderly patients with ACS.
基金Supported by the National Defence Science and Industry Committee(41314020201)
文摘As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet theory, this paper combined the wavelet theory with neural network and established a MRA wavelet network with the scaling function and wavelet function as its neurons. From the analysis in the frequency domain, the results indicated that MRA wavelet network was better than other wavelet networks in the ability of approaching to the signals. An essential research was can:led out on modeling and prediction with MRA wavelet network in the non-linear system. Using the lengthwise sway data received from the experiment of ship model, a model of offline prediction was established and was applied to the short-time prediction of ship motion. The simulation results indicated that the forecasting model improved the prediction precision effectively, lengthened the forecasting time and had a better prediction results than that of AR linear model. The research indicates that it is feasible to use the MRA wavelet network in the short-time prediction of ship motion.
基金the National Natural Science Foundation of China under Grant No.61261016，Wuhan Science and technology project for the Solar energy intelligent management system development and application demonstration
文摘The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.
基金Grants from Catholic Medical Center,The MedicalCollege of the Catholic University of Korea
文摘AIM： To evaluate the efficacy of short-term overlap lamivudine therapy with adefovir in patients with lamivudine-resistant and naive chronic hepatitis B, we compared patients receiving overlap therapy with those receiving adefovir alone. METHODS： Eighty patients who had received lamivudine treatment for various periods and had a lamivudineo resistant liver function abnormality were enrolled. Forty of these patients received adefovir treatment combined with lamivudine treatment for ≥ 2 mo, while the other 40 received adefovir alone. We assessed the levels of hepatitis B virus （HBV） DNA at 0, 12 and 48 wk and serum alanine aminotransferase （ALT） levels after 0, 12, 24 and 48 wk of adefovir treatment in each group. RESULTS： We found serum ALT became normalized in 72 （87.5%） of the 80 patients, and HBV DNA decreased by ≥ 2 Ioglo copies/mL in 60 （75%） of the 80 patients at the end of a 48-wk treatment. HBV DNA levels were not significantly different between the groups. The improvements in serum ALT were also not significantly different between the two groups. CONCLUSION： These findings suggest short-term overlap lamivudine treatment results in no better virological and biological outcomes than non-overlap adefovir monotherapy.
文摘Two Gaussian air quality dispersion models, the industrial source complex short-term model (ISCST3) with and without modification have been used to simulate the pollutant concentration distribution in urban areas based on the meteorological data and the emissions distribution of sulfur dioxide. The verified data show that the modified model is more accurate in the urban area of Shijiazhuang. Using the modified model predictions, the control strategies of sulfur dioxide in the urban area have been studied, and the result show that the second long-term (to 2010) strategy can mitigate air pollution significantly and maintain pollution levels within permissible limits.
文摘In this paper, the classical economic order quantity （EOQ） inventory model assumption that all items of a certain product received from a supplier are of perfect quality is relaxed. Another basic assumption that the payment for the items is made at the beginning of the inventory cycle when they are received is also eased. We consider an inventory situation where items received from the supplier are of two types of quality, perfect and imperfect, and a short deferral in payment is allowed. The split between perfect and imperfect quality items is assumed to follow a known probability distribution. Both qualities of items have continuous demands, and items of imperfect quality are sold at a discount. A mathematical model is developed using the net present value of all cash flows involved in the inventory cycle. A numerical method for obtaining the optimal order quantity is presented, and the impact of the short-term financing is analyzed. An example is presented to validate the equations and illustrate the results.
文摘The wavelet power system short term load forecasting(STLF) uses a mulriple periodical autoregressive integrated moving average(MPARIMA) model to model the mulriple near periodicity, nonstationarity and nonlinearity existed in power system short term quarter hour load time series, and can therefore accurately forecast the quarter hour loads of weekdays and weekends, and provide more accurate results than the conventional techniques, such as artificial neural networks and autoregressive moving average(ARMA) models test results. Obtained with a power system networks in a city in Northeastern part of China confirm the validity of the approach proposed.
