Objective:To explore the target management model for clinical pharmacists in primary hospitals facing current shortages of clinical pharmacists,in order to improve the work efficiency and service quality of clinical p...Objective:To explore the target management model for clinical pharmacists in primary hospitals facing current shortages of clinical pharmacists,in order to improve the work efficiency and service quality of clinical pharmacy,and promote the high-quality development of clinical pharmacy in primary hospitals.Methods:Developing a target management model,adopting a wide coverage work model of“1+1+N”(that is,1 clinical pharmacist,1 resident clinical department,and N contracted clinical departments).According to the SMART principle,various work assessment indicators were quantified.This involved setting clear work goals,diversifying work methods,personalizing work methods,standardizing workflows,and using numerical assessment indicators.Regular supervision,inspection,feedback,and improvement mechanisms were implemented.Results:The implementation of the target management model has made the work effectiveness of clinical pharmacists visualized.There were more than 200 annual consultations and multidisciplinary team(MDT)cases,with an opinion adoption rate of 90.2%and a patient improvement rate of 80.6%.More than 1500 rational drug use interventions were conducted,with a suggestion adoption rate of 83.5%.In terms of pharmaceutical indicators control.The intensity of antibacterial drug use in 2024(without CMI adjustment)was 30.07 DDDs,significantly lower than the 2023 value of 33.54 DDDs,and also significantly lower than the provincial average(32.87 DDDs)and the average for hospitals of the same level(32.49 DDDs).The daily usage of intravenous infusion per bed for hospitalized patients was 2.09,a decrease from 2.15 in 2023,significantly lower than the provincial average of 2.71 and the average of 2.56 in hospitals of the same level.The amount of the second batch of national key monitoring drugs accounts for the value was 6.48%,significantly lower than the provincial average of 8.27%and the same level hospital average of 8.82%.In terms of chronic disease pharmaceutical management,taking the pharmaceutical management of patients with chronic heart failure as an example,the usage rates of renin-aldosterone-angiotensin-system inhibitors(RAAS inhibitors)and beta-blockers for heart failure in the management group were 87.88%and 80.81%,respectively,significantly higher-1 than those in the control group(62.22%and 65.56%).Heart rate in the management group(69.54±10.68 times·min-1)was significantly lower than in the control group(80.04±17.68 times·min)(P<0.001).The low-density lipoprotein cholesterol(1.69±0.57 mmol·L-1)was significantly lower than the control group(1.95±0.77 mmol·L-1)(P<0.001),and the 1-year readmission rate was 47.47%,significantly lower than the control group 56.67%.The Minnesota Living with Heart Failure Questionnaire(MLHFQ)Score was(44.20±10.78),significantly lower than the control group(55.89±11.48)(P<0.001),indicating a significant improvement in the patient’s quality of life.Conclusions:The targeted management model for clinical pharmacists can effectively enhance communication and collaboration between clinical pharmacists and clinicians,improve the work efficiency and service quality of clinical pharmacists in primary hospitals,promote the work of clinical pharmacy towards standardization and scientificization,boost the high-quality development of pharmacy in primary hospitals,and also provide new ideas and methods for the management of clinical pharmacists in other primary hospitals.展开更多
针对锅炉过热汽温系统存在的大时延、强非线性和变量耦合等建模难题,建立了一种基于贝叶斯优化时间序列预测神经基扩展分析(neural basis expansion analysis for interpretable time series forecasting,N-BEATS)网络的过热汽温预测模...针对锅炉过热汽温系统存在的大时延、强非线性和变量耦合等建模难题,建立了一种基于贝叶斯优化时间序列预测神经基扩展分析(neural basis expansion analysis for interpretable time series forecasting,N-BEATS)网络的过热汽温预测模型。针对某600 MW超临界火电机组,结合机理分析确定模型的输入和输出变量,通过性能对比实验优化模型的输入/输出时延阶次、Block类型和激活函数,进一步利用贝叶斯优化算法对模型的超参数进行寻优,并与网格搜索、遗传算法的优化效果进行对比。采用该机组仿真运行数据进行建模实验,结果表明所提模型在预测精度方面优于传统优化方法及主流模型。展开更多
BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles....BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles.Efficient induction protocols and continuous monitoring are therefore essential.Routine exploratory surgeries are ethically untenable,making non-invasive imaging modalities attractive alternatives.High-resolution magnetic resonance imaging and microcomputed tomography deliver detailed insights but incur substantial equipment costs,radiation risks,time demands,and require specialized expertise—challenges that limit their routine use.In contrast,ultrasound(US)imaging emerges as a cost-effective,radiation-free,and rapid approach,facilitating practical and ethical longitudinal assessment of tumor progression in preclinical studies.AIM To optimize the orthotopic hepatocellular carcinoma model and evaluate the potential of US imaging for accurate and cost-effective tumor monitoring.METHODS Hepatocellular carcinoma was induced in 28 Sprague Dawley rats by implanting 5×10^(6) N1S1 cells into the left lateral hepatic lobe.Tumor progression was monitored weekly via US.Upon reaching 100-150 mm^(3),an experimental group(n=14)received Sorafenib(40 mg/kg)orally on alternate days for 28 days;efficacy was compared to untreated controls.US accuracy was validated against micro-computed tomography,gross caliper measurements and histopathological analysis.Reliability and operator proficiency in US assessment were also evaluated.RESULTS US images procured 7-day post-surgery revealed a well-defined hypoechoic nodule at the left liver lobe tip,confirming successful tumor induction(mean volume 130±39 mm^(3)).Only three animals exhibited spontaneous regression by week 2,underscoring the model’s stability.Sorafenib treatment elicited a marked tumor reduction(678±103 mm^(3))vs untreated control(6005±1760 mm^(3)).US assessment demonstrated robust intra and interobserver reproducibility with high sensitivity and specificity for tumor detection.Moreover,US derived volumes correlated strongly with gross caliper measurements,histopathological analysis,and microcomputed tomography imaging,validating its reliability as a non-invasive monitoring tool in preclinical hepatocellular carcinoma studies.CONCLUSION The results demonstrate that US imaging is a reliable,cost-effective,and animal sparing approach with an easy tomaster protocol,enabling monitoring of tumor progression and therapeutic response in orthotopic liver tumor models.展开更多
Crop performance is determined by the combined effects of the genotype of the crop and the environmental conditions of the production system. This study was undertaken to develop a dynamic model for simulating environ...Crop performance is determined by the combined effects of the genotype of the crop and the environmental conditions of the production system. This study was undertaken to develop a dynamic model for simulating environmental （temperature and solar radiation） and N supply effects on fiber fineness, maturity and micronaire. Three different experiments involving genotypes, sowing dates, and N fertilization rates were conducted to support model development and model evaluation. The growth and development duration of fiber fineness, maturity, and micronaire were scaled by using physiological development time of secondary wall synthesis （PDT SWSP ）, which was determined based on the constant ratio of SWSP/ BMP. PTP （product of relative thermal effectiveness （RTE） and photosynthetically active radiation （PAR）, MJ m-2） and subtending leaf N content per unit area （N A , g m-2） and critical subtending leaf N content per unit area （CN A , g m-2） of cotton boll were calculated or simulated to evaluate effects of temperature and radiation, and N supply. Besides, the interactions among temperature, radiation and N supply were also explained by piecewise function. The overall performance of the model was calibrated and validated with independent data sets from three field experiments with two sowing dates, three or five flowering dates and three or four N fertilization rates for three subsequent years （2005, 2007, and 2009） at three ecological locations. The average RMSE and RE for fiber fineness, maturity, and micronaire predictions were 372 m g-1 and 5.0%, 0.11 m g-1 and 11.4%, 0.3 m g-1 and 12.3%, respectively, indicating a good fit between the simulated and observed data. It appears that the model can give a reliable prediction for fiber fineness, maturity and micronaire formation under various growing conditions.展开更多
A generalized, lumped-parameter ecological model PnET-CN was calibrated and validated for a subtropical coniferous plantation in southern China. PnET-CN model describes the biogeochemical cycles of carbon （C） and ni...A generalized, lumped-parameter ecological model PnET-CN was calibrated and validated for a subtropical coniferous plantation in southern China. PnET-CN model describes the biogeochemical cycles of carbon （C） and nitrogen （N） and can assist in estimating carbon sequestration potential. For validation of PnET-CN, data from coniferous forest plantations in southern China was used. Simulated daily gross primary productivity （GPP） from 2005 to 2007 agreed well with observations （R2=0.56, S.D.=0.009）. Simulations of monthly soil respiration （Rs） from 2005-2007 agreed well with Rs observations （R2=0.67, S.D. =0.03）. Simu- lated annual net primary productivity （NPP） from 1998-2006 was 803＋33 gCm 2a-1, about 4% higher than NPP observation （752＋51 gCm-2a-1）. Simulations of annual NEP from 2005-2007 only overestimate 9 gCm-2a-1 （4%）, 4 gCm 2a-1 （1%） and 34 gCm 2a-1 （8%） compared to NEP observations, respectively. Simulated annual foliar N concentration （FolNCon） （1.09%） is 10% lower than observed monthly FolNCon （0.87%-1.58%）. Simulated annual N leaching （0.26 gNm-2） is about 10% lower than leaching observation （0.29 gNm-2）. PnET-CN model validation indicates that PnET-CN is capable to simulate daily GPP, annual NPP, annual NEP, monthly Rs, annual FolNCon and annual nitrate N leaching for subtropical coniferous planta- tions in southern China. The results obtained from the validation test revealed that PnET-CN model can be used to simulate carbon sequestration of planted coniferous forests in southern China to a high level of precision. Sensitivity analysis suggests that great care should be taken in developing generalizations as to how forests will respond to a changing climate. PnET-CN performed satisfactorily in comparison to other models that have already been calibrated and validated in coniferous planted subtropical forests in China. Based on PnET-CN validation and its comparison to other models, future improvement of PnET-CN should focus on seasonal foliar N dynamics and the effects of water stress on autotrophic respirations in subtropical coniferous plantations in southern China.展开更多
This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient ou...This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.展开更多
We investigate the area distribution of clusters （loops） in the honeycomb O（n） loop model by means of the worm algorithm with n = 0.5, 1, 1.5, and 2. At the critical point, the number of clusters, whose enclosed a...We investigate the area distribution of clusters （loops） in the honeycomb O（n） loop model by means of the worm algorithm with n = 0.5, 1, 1.5, and 2. At the critical point, the number of clusters, whose enclosed area is greater than A, is proportional to A-1 with a proportionality constant C. We confirm numerically that C is universal, and its value agrees well with the predictions based on the Coulomb gas method.展开更多
The dissemination of cattle brucellosis in Zhejiang province of China can be attributed to the transport of cattle between cities within the province. In this paper,an n-patch dynamical model is proposed to study the ...The dissemination of cattle brucellosis in Zhejiang province of China can be attributed to the transport of cattle between cities within the province. In this paper,an n-patch dynamical model is proposed to study the effect of cattle dispersal on brucellosis spread. Theoretically,we analyze the dynamical behavior of the muti-patch model. For the 2-patch submodel,sensitivity analyses of the basic reproduction number R0 and the number of the infectious cattle in term of model parameters are carried out. By numerical analysis,it is obtained that the dispersal of susceptible cattle between patches and the centralization of infected cattle to the large scale patch can alleviate the epidemic and are in favor of the control of disease in the whole region.展开更多
An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods ...An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.展开更多
In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and ...In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and transformation of several forms of nitrogen in the agro-eeosystem, which is affected by climate, soil, crop growth and management practices. The simulation of daily N2O fluxes, along with key daily environmental variables, was validated with three-year observations conducted in East China. The validation demonstrated that the model simulated well daily solar radiation, soil temperature and moisture, and also captured the dynamics and magnitude of accumulated rice aboveground biomass and mineral nitrogen in the soil. The simulated daily N2O emissions over all three years investigated were generally in good agreement with field observations. Particularly well simulated were the peak N2O emissions induced by fertilizations, rainfall events or mid-season drainages. The model simulation also represented closely the inter-annuM variation in N2O emission. These validations imply that the model has the capability to capture the general characteristics of N2O emission from a typical rice-wheat rotation agro-ecosystem. Sensitivity analyses revealed that the simulated N2O emission is most sensitive to the fertilizer application rate and the soil organic matter content, but it is much less sensitive to variations in soil pH and texture, temperature, precipitation and crop residue incorporation rate under local conditions.展开更多
文摘Objective:To explore the target management model for clinical pharmacists in primary hospitals facing current shortages of clinical pharmacists,in order to improve the work efficiency and service quality of clinical pharmacy,and promote the high-quality development of clinical pharmacy in primary hospitals.Methods:Developing a target management model,adopting a wide coverage work model of“1+1+N”(that is,1 clinical pharmacist,1 resident clinical department,and N contracted clinical departments).According to the SMART principle,various work assessment indicators were quantified.This involved setting clear work goals,diversifying work methods,personalizing work methods,standardizing workflows,and using numerical assessment indicators.Regular supervision,inspection,feedback,and improvement mechanisms were implemented.Results:The implementation of the target management model has made the work effectiveness of clinical pharmacists visualized.There were more than 200 annual consultations and multidisciplinary team(MDT)cases,with an opinion adoption rate of 90.2%and a patient improvement rate of 80.6%.More than 1500 rational drug use interventions were conducted,with a suggestion adoption rate of 83.5%.In terms of pharmaceutical indicators control.The intensity of antibacterial drug use in 2024(without CMI adjustment)was 30.07 DDDs,significantly lower than the 2023 value of 33.54 DDDs,and also significantly lower than the provincial average(32.87 DDDs)and the average for hospitals of the same level(32.49 DDDs).The daily usage of intravenous infusion per bed for hospitalized patients was 2.09,a decrease from 2.15 in 2023,significantly lower than the provincial average of 2.71 and the average of 2.56 in hospitals of the same level.The amount of the second batch of national key monitoring drugs accounts for the value was 6.48%,significantly lower than the provincial average of 8.27%and the same level hospital average of 8.82%.In terms of chronic disease pharmaceutical management,taking the pharmaceutical management of patients with chronic heart failure as an example,the usage rates of renin-aldosterone-angiotensin-system inhibitors(RAAS inhibitors)and beta-blockers for heart failure in the management group were 87.88%and 80.81%,respectively,significantly higher-1 than those in the control group(62.22%and 65.56%).Heart rate in the management group(69.54±10.68 times·min-1)was significantly lower than in the control group(80.04±17.68 times·min)(P<0.001).The low-density lipoprotein cholesterol(1.69±0.57 mmol·L-1)was significantly lower than the control group(1.95±0.77 mmol·L-1)(P<0.001),and the 1-year readmission rate was 47.47%,significantly lower than the control group 56.67%.The Minnesota Living with Heart Failure Questionnaire(MLHFQ)Score was(44.20±10.78),significantly lower than the control group(55.89±11.48)(P<0.001),indicating a significant improvement in the patient’s quality of life.Conclusions:The targeted management model for clinical pharmacists can effectively enhance communication and collaboration between clinical pharmacists and clinicians,improve the work efficiency and service quality of clinical pharmacists in primary hospitals,promote the work of clinical pharmacy towards standardization and scientificization,boost the high-quality development of pharmacy in primary hospitals,and also provide new ideas and methods for the management of clinical pharmacists in other primary hospitals.
文摘针对锅炉过热汽温系统存在的大时延、强非线性和变量耦合等建模难题,建立了一种基于贝叶斯优化时间序列预测神经基扩展分析(neural basis expansion analysis for interpretable time series forecasting,N-BEATS)网络的过热汽温预测模型。针对某600 MW超临界火电机组,结合机理分析确定模型的输入和输出变量,通过性能对比实验优化模型的输入/输出时延阶次、Block类型和激活函数,进一步利用贝叶斯优化算法对模型的超参数进行寻优,并与网格搜索、遗传算法的优化效果进行对比。采用该机组仿真运行数据进行建模实验,结果表明所提模型在预测精度方面优于传统优化方法及主流模型。
基金Supported by Amrita Vishwa Vidyapeetham Seed Grant,No.K-PHAR-24-722DST INSPIRE Fellowship,No.IF190226.
文摘BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles.Efficient induction protocols and continuous monitoring are therefore essential.Routine exploratory surgeries are ethically untenable,making non-invasive imaging modalities attractive alternatives.High-resolution magnetic resonance imaging and microcomputed tomography deliver detailed insights but incur substantial equipment costs,radiation risks,time demands,and require specialized expertise—challenges that limit their routine use.In contrast,ultrasound(US)imaging emerges as a cost-effective,radiation-free,and rapid approach,facilitating practical and ethical longitudinal assessment of tumor progression in preclinical studies.AIM To optimize the orthotopic hepatocellular carcinoma model and evaluate the potential of US imaging for accurate and cost-effective tumor monitoring.METHODS Hepatocellular carcinoma was induced in 28 Sprague Dawley rats by implanting 5×10^(6) N1S1 cells into the left lateral hepatic lobe.Tumor progression was monitored weekly via US.Upon reaching 100-150 mm^(3),an experimental group(n=14)received Sorafenib(40 mg/kg)orally on alternate days for 28 days;efficacy was compared to untreated controls.US accuracy was validated against micro-computed tomography,gross caliper measurements and histopathological analysis.Reliability and operator proficiency in US assessment were also evaluated.RESULTS US images procured 7-day post-surgery revealed a well-defined hypoechoic nodule at the left liver lobe tip,confirming successful tumor induction(mean volume 130±39 mm^(3)).Only three animals exhibited spontaneous regression by week 2,underscoring the model’s stability.Sorafenib treatment elicited a marked tumor reduction(678±103 mm^(3))vs untreated control(6005±1760 mm^(3)).US assessment demonstrated robust intra and interobserver reproducibility with high sensitivity and specificity for tumor detection.Moreover,US derived volumes correlated strongly with gross caliper measurements,histopathological analysis,and microcomputed tomography imaging,validating its reliability as a non-invasive monitoring tool in preclinical hepatocellular carcinoma studies.CONCLUSION The results demonstrate that US imaging is a reliable,cost-effective,and animal sparing approach with an easy tomaster protocol,enabling monitoring of tumor progression and therapeutic response in orthotopic liver tumor models.
基金funded by the National Natural Science Foundation of China (30771277 and 30771279)
文摘Crop performance is determined by the combined effects of the genotype of the crop and the environmental conditions of the production system. This study was undertaken to develop a dynamic model for simulating environmental （temperature and solar radiation） and N supply effects on fiber fineness, maturity and micronaire. Three different experiments involving genotypes, sowing dates, and N fertilization rates were conducted to support model development and model evaluation. The growth and development duration of fiber fineness, maturity, and micronaire were scaled by using physiological development time of secondary wall synthesis （PDT SWSP ）, which was determined based on the constant ratio of SWSP/ BMP. PTP （product of relative thermal effectiveness （RTE） and photosynthetically active radiation （PAR）, MJ m-2） and subtending leaf N content per unit area （N A , g m-2） and critical subtending leaf N content per unit area （CN A , g m-2） of cotton boll were calculated or simulated to evaluate effects of temperature and radiation, and N supply. Besides, the interactions among temperature, radiation and N supply were also explained by piecewise function. The overall performance of the model was calibrated and validated with independent data sets from three field experiments with two sowing dates, three or five flowering dates and three or four N fertilization rates for three subsequent years （2005, 2007, and 2009） at three ecological locations. The average RMSE and RE for fiber fineness, maturity, and micronaire predictions were 372 m g-1 and 5.0%, 0.11 m g-1 and 11.4%, 0.3 m g-1 and 12.3%, respectively, indicating a good fit between the simulated and observed data. It appears that the model can give a reliable prediction for fiber fineness, maturity and micronaire formation under various growing conditions.
基金National Natural Science Foundation of China, No.31070438 The Key Project of CAS Knowledge Innovation Program, No.KZCX2-YW-305-3+1 种基金 No.KZCX2-YW-QN301 State Key Basic Research Development Proiect, No.2010CB833503
文摘A generalized, lumped-parameter ecological model PnET-CN was calibrated and validated for a subtropical coniferous plantation in southern China. PnET-CN model describes the biogeochemical cycles of carbon （C） and nitrogen （N） and can assist in estimating carbon sequestration potential. For validation of PnET-CN, data from coniferous forest plantations in southern China was used. Simulated daily gross primary productivity （GPP） from 2005 to 2007 agreed well with observations （R2=0.56, S.D.=0.009）. Simulations of monthly soil respiration （Rs） from 2005-2007 agreed well with Rs observations （R2=0.67, S.D. =0.03）. Simu- lated annual net primary productivity （NPP） from 1998-2006 was 803＋33 gCm 2a-1, about 4% higher than NPP observation （752＋51 gCm-2a-1）. Simulations of annual NEP from 2005-2007 only overestimate 9 gCm-2a-1 （4%）, 4 gCm 2a-1 （1%） and 34 gCm 2a-1 （8%） compared to NEP observations, respectively. Simulated annual foliar N concentration （FolNCon） （1.09%） is 10% lower than observed monthly FolNCon （0.87%-1.58%）. Simulated annual N leaching （0.26 gNm-2） is about 10% lower than leaching observation （0.29 gNm-2）. PnET-CN model validation indicates that PnET-CN is capable to simulate daily GPP, annual NPP, annual NEP, monthly Rs, annual FolNCon and annual nitrate N leaching for subtropical coniferous planta- tions in southern China. The results obtained from the validation test revealed that PnET-CN model can be used to simulate carbon sequestration of planted coniferous forests in southern China to a high level of precision. Sensitivity analysis suggests that great care should be taken in developing generalizations as to how forests will respond to a changing climate. PnET-CN performed satisfactorily in comparison to other models that have already been calibrated and validated in coniferous planted subtropical forests in China. Based on PnET-CN validation and its comparison to other models, future improvement of PnET-CN should focus on seasonal foliar N dynamics and the effects of water stress on autotrophic respirations in subtropical coniferous plantations in southern China.
基金supported by the Research Start Funds for Introducing High-level Talents of North China University of Water Resources and Electric Power
文摘This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10975127)the Specialized Research Fund for the Doctoral Program of Higher Education, China (Grant No. 20113402110040)
文摘We investigate the area distribution of clusters （loops） in the honeycomb O（n） loop model by means of the worm algorithm with n = 0.5, 1, 1.5, and 2. At the critical point, the number of clusters, whose enclosed area is greater than A, is proportional to A-1 with a proportionality constant C. We confirm numerically that C is universal, and its value agrees well with the predictions based on the Coulomb gas method.
基金supported by the National Natural Science Foundation of China under Grant（11331009,11171314,11147015,11301490） the National Youth Natural Science Foundation（11201434）+1 种基金 the Specialized Research Fund for the Doctoral Program of Higher Education（20121420130001） the Research Project Supported by Shanxi Scholarship Council of China（2013-3）
文摘The dissemination of cattle brucellosis in Zhejiang province of China can be attributed to the transport of cattle between cities within the province. In this paper,an n-patch dynamical model is proposed to study the effect of cattle dispersal on brucellosis spread. Theoretically,we analyze the dynamical behavior of the muti-patch model. For the 2-patch submodel,sensitivity analyses of the basic reproduction number R0 and the number of the infectious cattle in term of model parameters are carried out. By numerical analysis,it is obtained that the dispersal of susceptible cattle between patches and the centralization of infected cattle to the large scale patch can alleviate the epidemic and are in favor of the control of disease in the whole region.
文摘An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.
基金supported by the Chinese Academy of Sciences (KZCX2-YW-204, KSCX3-SW-440, KZCX1-SW-01)the National Natural Science Foundation of China (40425010, 40331014)+1 种基金the European Union (NitroEurope IP 017841)the Helmholtz Society via the Sino-German Joint Laboratory project ENTRANCE
文摘In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and transformation of several forms of nitrogen in the agro-eeosystem, which is affected by climate, soil, crop growth and management practices. The simulation of daily N2O fluxes, along with key daily environmental variables, was validated with three-year observations conducted in East China. The validation demonstrated that the model simulated well daily solar radiation, soil temperature and moisture, and also captured the dynamics and magnitude of accumulated rice aboveground biomass and mineral nitrogen in the soil. The simulated daily N2O emissions over all three years investigated were generally in good agreement with field observations. Particularly well simulated were the peak N2O emissions induced by fertilizations, rainfall events or mid-season drainages. The model simulation also represented closely the inter-annuM variation in N2O emission. These validations imply that the model has the capability to capture the general characteristics of N2O emission from a typical rice-wheat rotation agro-ecosystem. Sensitivity analyses revealed that the simulated N2O emission is most sensitive to the fertilizer application rate and the soil organic matter content, but it is much less sensitive to variations in soil pH and texture, temperature, precipitation and crop residue incorporation rate under local conditions.
