The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
A combined numerical model of wind, wave, tide, and storm surges was built on the basis of the “wind field model in limited sea surface areas”. When used to forecast the sea surface wind, wave height and water level...A combined numerical model of wind, wave, tide, and storm surges was built on the basis of the “wind field model in limited sea surface areas”. When used to forecast the sea surface wind, wave height and water level, it can describe them very well.展开更多
This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure o...This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.展开更多
-In order to avoid prescribing open boundary condition on the upstream side of the Hangzhou Bay, in numerical simulation of the tides and residual currents of the Bay, a 1-D model for the Qiantang River is connected t...-In order to avoid prescribing open boundary condition on the upstream side of the Hangzhou Bay, in numerical simulation of the tides and residual currents of the Bay, a 1-D model for the Qiantang River is connected to the 2-D model for the Hangzhou Bay. The harmonic constants of diurnal constituent [ (K1+O1)/2],semidiurnal constituent (M2) and shallow water constituent (M4) are obtained. The results produced by the combined model are in better agreement with the observed ones than those produced solely by the original 2-D model. The combined model gives much more reliable results for tide-induced residual water level and current.展开更多
Objective:To explore the feasibility of establishing the disease-syndrome combined animal model for immune thrombocytopenic purpura(ITP)without additional conditions.Methods:Three batches of data related to the ITP mo...Objective:To explore the feasibility of establishing the disease-syndrome combined animal model for immune thrombocytopenic purpura(ITP)without additional conditions.Methods:Three batches of data related to the ITP model mice obtained by replication at different time were analyzed,and whether the APS-injected model mice replicated through the passive immune modeling method could simulate the pathogenesis and clinical characteristics of human ITP was evaluated according to the differentiation criteria for diseasesyndrome combined model.Results:The APS-injected replicated ITP model mice possessed the following traits:(1)Compared with the normal group,the platelet count was significantly decreased,and coagulation time was significantly increased in the model group(P<.01).(2)Compared with the normal group,the medullary thrombocytogenous megakaryocytes were significantly decreased(P<.05,.01,.001).(3)The APS-injected sites and other parts of the model mice had spontaneous hemorrhage.(4)Behavioral changing signs were observed 1 week after the modeling(i.e.low activity,delayed activity,poor appetite,skin petechia/hemorrhage and spontaneous hemorrhage at the injected sites or other parts),and were getting more and more severe.Conclusion:According to the syndrome differentiation criteria for disease-syndrome combined model of ITP,the APS-injected animal model of ITP replicated through the passive immune modeling method without additional conditions possesses the characteristics of disease-syndrome combined model.It provides an ideal tool for the development of traditional Chinese medicine pharmacology experiment.展开更多
Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality cata...Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality catastrophes. Then a combined forewarning system for the quality of products is established, which contains three models, judgment rules and forewarning state illustration. Finally with an example of the practical production, this modeling system is proved fairly effective.展开更多
The combined bottleneck effect is investigated by modeling traffic systems with an on-ramp and a nearby bus stop in a two-lane cellular automaton model. Two cases, i.e. the bus stop locates in the downstream section o...The combined bottleneck effect is investigated by modeling traffic systems with an on-ramp and a nearby bus stop in a two-lane cellular automaton model. Two cases, i.e. the bus stop locates in the downstream section of the on-ramp and the bus stop locates in the upstream section of the on-ramp, are considered separately. The upstream flux and downstream flux of the main road, as well as the on-ramp flux are analysed in detail, with respect to the entering probabilities and the distance between the on-ramp and the bus stop. It is found that the combination of the two bottlenecks causes the capacity to drop off, because the vehicles entering the main road from the on-ramp would interweave with the stopping (pulling-out) buses in the downstream (upstream) case. The traffic conflict in the former case is much heavier than that in the latter, causing the downstream main road to be utilized inefficiently. This suggests that the bus stop should be set in the upstream section of the on-ramp to enhance the capacity. The fluxes both on the main road and on the on-ramp vary with the distance between the two bottlenecks in both cases. However, the effects of distance disappear gradually at large distances. These findings might give some guidance to traffic optimization and management.展开更多
BACKGROUND: Central adrenergic nerve and 5-serotonergic nerve can influence central cholinergic nerve on learning and memory and make easy for study; however, ginsenoside of stem and leaf (GSL) can improve function...BACKGROUND: Central adrenergic nerve and 5-serotonergic nerve can influence central cholinergic nerve on learning and memory and make easy for study; however, ginsenoside of stem and leaf (GSL) can improve functions of central adrenergic nerve; moreover, 5-serotonergic nerve and the combination with choline can produce synergistic effect and enhance learning and memory ability so as to improve learning and memory disorder of patients with Alzheimer disease (AD). OBJECTIVE : To observe the effects of GSL combining with choline on learning and memory of AD model rats DESIGN : Randomized grouping design and controlled animal study SETIING : Department of Pharmacology, Taishan Medical College MATERIALS : The experiment was carried out in the Pharmacological Department of Medical College of Jilin University from October 1996 to January 1997. Forty healthy male Wistar rats of clean grade were randomly divided into 5 groups, including sham-injury group, model group, GSL group, choline group and combination group, with 8 rats in each group. Main medications: GSL with the volume more than 92.8% was provided by Department of Chemistry, Norman Bethune Medical College of Jilin University. Panaxatriol, the main component, was detected with thin layer scanning technique and regarded as the index of GSL quality [(55±1)%, CV= 2%, n = 5]. Choline was provided by the Third Shanghai Laboratory Factory. METHODS : 150 nmol quinolinic acid was used to damage bilateral Meynert basal nuclei of adult rats so as to establish AD models. Rats in GSL, choline and combination groups were intragastric administrated with 400 mg/kg GSL, 200 mg/kg choline (20 mL/kg), and both respectively last for 17 days starting from two days before operation. Rats in sham-injury group and model group were perfused with the same volume of distilled water once in each morning for the same days. (1) Passive avoidance step-down test: Five minutes later, rats jumped up safe platform when they were shocked with 36 V alternating current. If rats jumped down from the platform and the feet touched railings, the response was wrong. Numbers of wrong response were recorded within 3 minutes, and then the test was redone after 24 hours. (2) Morris water-maze spatial localization task: Swimming from jumping-off to platform directly was regarded as right response. Additionally, 4 successively right responses were regarded as the standard. Each rat was trained 10 times a day with 120 s per time for 3 successive days. The interval was 30 s. Three days later, numbers of right response were recorded. The training times were increased to 30 for unlearned rats. (3) Measurement of activity of choline acetylase in cerebral cortex: Rats were sacrificed at 17 days after operation to obtain cerebral cortex to measure activity of choline acetylase with radiochemistry technique. (4) Synergistic effect: It was expressed as Q value: Q value = factual incorporative effect/anticipant incorporative effect; Q ≥ 1 was regarded as synergistic effect. Anticipant incorporative effect = (EA+EB-EA·EB), EA and EB were single timing effect, respectively in GSL group and choline group. E(step-down test and Morris water maze test) = (x in model group - factual value in medicine groups)/x in model group; E (activity of choline acetylase) = (factual value in medicine groups -xin model group)/xin model group. MAIN OUTCOME MEASURES : (1) Passive avoidance step-down test and Morris water-maze spatial localization task in the study of learning and memory; (2) activity of choline acetylase. RESULTS : All 40 rats were involved in the final analysis. (1) Passive avoidance response: At learning phase on first day and retesting phase on the next day, numbers of wrong responses within 3 minutes were more in model group than sham operation group, and there was significant difference [(5.88±1.46), (2.25±0.87) times; (2.63±1.06), (0.50±0.53) times; P 〈 0.01]; numbers of wrong responses within 3 minutes were less in combination group than model group, and there was significant difference [learning phase: (1.12±0.83), (5.88±1.46) times; retesting phase: (0.38±0.74), (2.63±1.06)times, P 〈 0.01]; moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.07 and 1.59, respectively and it showed synergistic effect. Spatial localization task: Training times were more in model group than sham operation group, and there was significant difference [(2.9±2.5), (12.6±3.5) times; P 〈 0.01]. Training times were less in combination group than model group, and there was significant difference [(11.8±2.4), (27.9±2.5) times, P 〈 0.01]; moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.07 and it showed synergistic effect. (3) Activity of choline acetylase: Activity was lower in model group than sham operation group, and there was significant difference [(30.56±8.33), (61.11 ±8.33) nkat/g; P 〈 0.01]. Activity was higher in combination group than model group and there was significant difference [(50.00±8.33), (30.56±8.33) nkat/g, P 〈 0.01];moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.5 and it showed synergistic effect. CONCLUSZON: GSL in combination with choline can synergically improve the disorder of learning and memory of AD model rats. Its mechanism may be involved in enhancing the function of central cholinergic system.展开更多
-Combined refraction and diffraction models in the form of linear parabolic approximation are derived through smallparameter method. More strictly theoretical basis and more accuracy in the models than Lozano's (1...-Combined refraction and diffraction models in the form of linear parabolic approximation are derived through smallparameter method. More strictly theoretical basis and more accuracy in the models than Lozano's (1980) are obtained. Some theoretical defects in Liu's model (1985) with consideration of current are not only found but also eliminated. More strict and accurate models are, therefore, presented in this paper.The calculation results and analysis in applying the models to actual wave field with consideration of bottom friction will be given in the following paper.展开更多
Objective:To study the application effect of short video combined with BOPPPS teaching mode in clinical anesthesia practice.Method:48 students assigned to clinical anesthesia in digestive endoscopy of Shanxi Bethune H...Objective:To study the application effect of short video combined with BOPPPS teaching mode in clinical anesthesia practice.Method:48 students assigned to clinical anesthesia in digestive endoscopy of Shanxi Bethune Hospital from July 1,2022 to April 1,2023 were selected as research objects.They were randomly divided into the control group(PowerPoint presentation teaching group)and the observation group(short video combined with BOPPPS teaching group),with 24 students in each group.After the internship,the students’theoretical and technical scores were tested,the effects of the two teaching modes were compared,and the students’satisfaction was investigated.Results:The test scores of students in the observation group were significantly better than those in the control group(P<0.05).The short video combined with BOPPPS teaching mode can significantly improve students’learning interest,operation skills,and memory(P<0.05).The students’satisfaction in the observation group was higher than that in the control group(P<0.05).Conclusion:In clinical practice,the application of short video combined with BOPPPS teaching mode has achieved great effect,which is worth further promotion and research.展开更多
Combining with engineering examples,this paper introduces BIM into architectural design model and adopts Revit rapid modeling.It focuses on realizing rapid combination modeling of similar components through secondary ...Combining with engineering examples,this paper introduces BIM into architectural design model and adopts Revit rapid modeling.It focuses on realizing rapid combination modeling of similar components through secondary development,improving information conversion efficiency between engineering CAD and Revit building structure modeling,and quickly generating BIM structure construction drawings.展开更多
Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentat...Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.展开更多
Ensuring a sufficient energy supply is essential to a country. Natural gas constitutes a vital part in energy supply and therefore forecasting natural gas consumption reliably and accurately is an essential part of a ...Ensuring a sufficient energy supply is essential to a country. Natural gas constitutes a vital part in energy supply and therefore forecasting natural gas consumption reliably and accurately is an essential part of a country's energy policy. Over the years, studies have shown that a combinative model gives better projected results compared to a single model. In this study, we used Polynomial Curve and Moving Average Combination Projection (PCMACP) model to estimate the future natural gas consumption in China from 2009 to 2015. The new proposed PCMACP model shows more reliable and accurate results: its Mean Absolute Percentage Error (MAPE) is less than those of any previous models within the investigated range. According to the PCMACP model, the average annual growth rate will increase for the next 7 years and the amount of natural gas consumption will reach 171600 million cubic meters in 2015 in China.展开更多
Achieving accurate speed prediction provides the most critical support parameter for high-level energy management of plug-in hybrid electric vehicles.Nowadays,people often drive a vehicle on fixed routes in their dail...Achieving accurate speed prediction provides the most critical support parameter for high-level energy management of plug-in hybrid electric vehicles.Nowadays,people often drive a vehicle on fixed routes in their daily travels and accurate speed predictions of these routes are possible with random prediction and machine learning,but the prediction accuracy still needs to be improved.The prediction accuracy of traditional prediction algorithms is difficult to further improve after reaching a certain accuracy;problems,such as over fitting,occur in the process of improving prediction accuracy.The combined prediction model proposed in this paper can abandon the transitional dependence on a single prediction.By combining the two prediction algorithms,the fusion of prediction performance is achieved,the limit of the single prediction performance is crossed,and the goal of improving vehicle speed prediction performance is achieved.In this paper,an extraction method suitable for fixed route vehicle speed is designed.The application of Markov and back propagation(BP)neural network in predictions is introduced.Three new combined prediction methods,all named Markov and BP Neural Network(MBNN)combined prediction algorithm,are proposed,which make full use of the advantages of Markov and BP neural network algorithms.Finally,the comparison among the prediction methods has been carried out.The results show that the three MBNN models have improved by about 19%,28%,and 29%compared with the Markov prediction model,which has better performance in the single prediction models.Overall,the MBNN combined prediction models can improve the prediction accuracy by 25.3%on average,which provides important support for the possible optimization of plug-in hybrid electric vehicle energy consumption.展开更多
Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. ...Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.展开更多
BACKGROUND: In localized brain proton magnetic resonance spectroscopy (^1H-MRS), metabolite levels are often expressed as ratios, rather than absolute concentrations. Frequently, the denominator is creatine, which ...BACKGROUND: In localized brain proton magnetic resonance spectroscopy (^1H-MRS), metabolite levels are often expressed as ratios, rather than absolute concentrations. Frequently, the denominator is creatine, which is assumed to be stable in normal, as well as many pathological, states. However, in vivo creatine levels do not remain constant. Therefore, absolute metabolite measurements, which provide the precise concentrations of certain chemical compounds, are superior to metabolite ratios for determining pathological and evolutional changes. OBJECTIVE: To investigate the feasibility of quantification analysis of brain metabolite changes caused by central analgesics nasal spray using the ^1H-MRS and linear combination model (LCModel) methods. DESIGN, TIME AND SETTING: This neuroimaging, observational, animal study was performed at the Laboratory of the Department of Medical Imaging, Second Affiliated Hospital, Medical College, Shantou University, China from July to December 2007. MATERIALS: Butorphanol tartrate nasal spray, as a mixed agonist-antagonist opioid analgesic, was purchased from Shanghai Hengrui Pharmacy, China. A General Electric Signa 1.5T System (General Electric Medical Systems, Milwaukee, WI, USA) and LCModel software (Stephen Provencher, Oakville, Ontario, Canada) were used in this study. METHODS: MRS images were acquired in ten healthy swine aged 2 weeks using single-voxel point-resolved spectroscopic sequence. A region of interest (2 cm × 2 cm × 2 cm) was placed in the image centers of maximum brain parenchyma. Repeated MRS scanning was performed 15-20 minutes after intranasal administration of 1 mg of butorphanol tartrate. Three settings of repetition time/echo time were selected before and after nasal spray administration 3 000 ms/30 ms,1 500 ms/30 ms, and 3 000 ms/50 ms. Metabolite concentrations were estimated by LCModel software. MAIN OUTCOME MEASURES: ^1H-MRS spectra was obtained using various repetition time/echo time settings. Concentrations of glutamate compounds (glutamate + glutamine), N-acetyl aspartate, and choline were detected in swine brain prior to and following nasal spray treatment. RESULTS: The glutamate compounds curve was consistent with original spectra, when a repetition time/echo time of 3 000 ms/30 ms was adopted. Concentrations of glutamate compounds, N-acetyl aspartate, and choline decreased following administration. The most significant reduction was observed in glutamate compound concentrations from (9.28 ± 0.54) mmol/kg to (7.28 ± 0.54) mmol/kg (P 〈 0.05). CONCLUSION: ^1H-MRS and LCModel software were effectively utilized to quantitatively analyze and measure brain metabolites. Glutamate compounds might be an important neurotransmitter in central analgesia.展开更多
Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. Ac...Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. According to the knowledge structure of course and text, the relation among knowledge points, knowledge units from three levels of media material, we can build education resource components, and build TKCM (Teaching Knowledge Combination Model) based on resource components. Builders can build and assemble knowledge system structure and make knowledge units can be self assembled, thus we can develop and consummate them continually. Users can make knowledge units can be self assembled and renewed, and build education knowledge system to satisfy users' demand under the form of education knowledge system.展开更多
Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a mo...Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a more reliable reference in terms of artificial intelligence index investment,this paper selects the NASDAQ CTA Artificial Intelligence and Robotics(AIRO)Index as the research target,and proposes innovative hybrid methods to forecast returns by considering its multiple structural characteristics.Specifically,this paper uses the ensemble empirical mode decomposition(EEMD)method and the modified iterative cumulative sum of squares(ICSS)algorithm to decompose the index returns and identify the structural breakpoints.Furthermore,it combines the least-square support vector machine approach with the particle swarm optimization method(PSO-LSSVM)and the generalized autoregressive conditional heteroskedasticity(GARCH)type models to construct innovative hybrid forecasting methods.On the one hand,the empirical results indicate that the AIRO index returns have complex structural characteristics,and present time-varying and nonlinear characteristics with high complexity and mutability;on the other hand,the newly proposed hybrid forecasting method(i.e.,the EEMD-PSO-LSSVM-ICSS-GARCH models)which considers these complex structural characteristics,can yield the optimal forecasting performance for the AIRO index returns.展开更多
Teachers are key participants in universities,and the performance appraisal of teacher is an important part of college work.By analyzing the data of behavior generated by different departments in university,analytic h...Teachers are key participants in universities,and the performance appraisal of teacher is an important part of college work.By analyzing the data of behavior generated by different departments in university,analytic hierarchy process(AHP) is used to establish the preliminary library of performance indicators for teachers,and the correlation among all the performance indicators is inspected by using data mining method at this time.On this basis,a more objective,comprehensive and scientific performance appraisal system is constructed through principal components analysis(PCA),which is more suitable for university itself.Finally,in order to solve the problems existed in current performance appraisal system,a dynamic evaluation model is put forward by regulating the weight of indicator according to the historical data,highlighting the continuity of the system.展开更多
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
基金This work supported by Stress Project(KZ952-S1-420)Chinese Academy of Sciences+1 种基金863 Project(863-818-06-05)(863-818-Q-07).
文摘A combined numerical model of wind, wave, tide, and storm surges was built on the basis of the “wind field model in limited sea surface areas”. When used to forecast the sea surface wind, wave height and water level, it can describe them very well.
基金supported by the State Grid Science and Technology Project (No.52999821N004)。
文摘This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.
基金This work was sponsored by the National Natural Science Foundation of China
文摘-In order to avoid prescribing open boundary condition on the upstream side of the Hangzhou Bay, in numerical simulation of the tides and residual currents of the Bay, a 1-D model for the Qiantang River is connected to the 2-D model for the Hangzhou Bay. The harmonic constants of diurnal constituent [ (K1+O1)/2],semidiurnal constituent (M2) and shallow water constituent (M4) are obtained. The results produced by the combined model are in better agreement with the observed ones than those produced solely by the original 2-D model. The combined model gives much more reliable results for tide-induced residual water level and current.
基金Project of National Key Basic Research Program(973 Program)(No.2013CB531705).
文摘Objective:To explore the feasibility of establishing the disease-syndrome combined animal model for immune thrombocytopenic purpura(ITP)without additional conditions.Methods:Three batches of data related to the ITP model mice obtained by replication at different time were analyzed,and whether the APS-injected model mice replicated through the passive immune modeling method could simulate the pathogenesis and clinical characteristics of human ITP was evaluated according to the differentiation criteria for diseasesyndrome combined model.Results:The APS-injected replicated ITP model mice possessed the following traits:(1)Compared with the normal group,the platelet count was significantly decreased,and coagulation time was significantly increased in the model group(P<.01).(2)Compared with the normal group,the medullary thrombocytogenous megakaryocytes were significantly decreased(P<.05,.01,.001).(3)The APS-injected sites and other parts of the model mice had spontaneous hemorrhage.(4)Behavioral changing signs were observed 1 week after the modeling(i.e.low activity,delayed activity,poor appetite,skin petechia/hemorrhage and spontaneous hemorrhage at the injected sites or other parts),and were getting more and more severe.Conclusion:According to the syndrome differentiation criteria for disease-syndrome combined model of ITP,the APS-injected animal model of ITP replicated through the passive immune modeling method without additional conditions possesses the characteristics of disease-syndrome combined model.It provides an ideal tool for the development of traditional Chinese medicine pharmacology experiment.
文摘Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality catastrophes. Then a combined forewarning system for the quality of products is established, which contains three models, judgment rules and forewarning state illustration. Finally with an example of the practical production, this modeling system is proved fairly effective.
基金Project supported by the National Basic Research Program of China (Grant No 2006CB705500)the National Natural Science Foundation of China (Grant Nos 70631001,70701004 and 70501004)
文摘The combined bottleneck effect is investigated by modeling traffic systems with an on-ramp and a nearby bus stop in a two-lane cellular automaton model. Two cases, i.e. the bus stop locates in the downstream section of the on-ramp and the bus stop locates in the upstream section of the on-ramp, are considered separately. The upstream flux and downstream flux of the main road, as well as the on-ramp flux are analysed in detail, with respect to the entering probabilities and the distance between the on-ramp and the bus stop. It is found that the combination of the two bottlenecks causes the capacity to drop off, because the vehicles entering the main road from the on-ramp would interweave with the stopping (pulling-out) buses in the downstream (upstream) case. The traffic conflict in the former case is much heavier than that in the latter, causing the downstream main road to be utilized inefficiently. This suggests that the bus stop should be set in the upstream section of the on-ramp to enhance the capacity. The fluxes both on the main road and on the on-ramp vary with the distance between the two bottlenecks in both cases. However, the effects of distance disappear gradually at large distances. These findings might give some guidance to traffic optimization and management.
文摘BACKGROUND: Central adrenergic nerve and 5-serotonergic nerve can influence central cholinergic nerve on learning and memory and make easy for study; however, ginsenoside of stem and leaf (GSL) can improve functions of central adrenergic nerve; moreover, 5-serotonergic nerve and the combination with choline can produce synergistic effect and enhance learning and memory ability so as to improve learning and memory disorder of patients with Alzheimer disease (AD). OBJECTIVE : To observe the effects of GSL combining with choline on learning and memory of AD model rats DESIGN : Randomized grouping design and controlled animal study SETIING : Department of Pharmacology, Taishan Medical College MATERIALS : The experiment was carried out in the Pharmacological Department of Medical College of Jilin University from October 1996 to January 1997. Forty healthy male Wistar rats of clean grade were randomly divided into 5 groups, including sham-injury group, model group, GSL group, choline group and combination group, with 8 rats in each group. Main medications: GSL with the volume more than 92.8% was provided by Department of Chemistry, Norman Bethune Medical College of Jilin University. Panaxatriol, the main component, was detected with thin layer scanning technique and regarded as the index of GSL quality [(55±1)%, CV= 2%, n = 5]. Choline was provided by the Third Shanghai Laboratory Factory. METHODS : 150 nmol quinolinic acid was used to damage bilateral Meynert basal nuclei of adult rats so as to establish AD models. Rats in GSL, choline and combination groups were intragastric administrated with 400 mg/kg GSL, 200 mg/kg choline (20 mL/kg), and both respectively last for 17 days starting from two days before operation. Rats in sham-injury group and model group were perfused with the same volume of distilled water once in each morning for the same days. (1) Passive avoidance step-down test: Five minutes later, rats jumped up safe platform when they were shocked with 36 V alternating current. If rats jumped down from the platform and the feet touched railings, the response was wrong. Numbers of wrong response were recorded within 3 minutes, and then the test was redone after 24 hours. (2) Morris water-maze spatial localization task: Swimming from jumping-off to platform directly was regarded as right response. Additionally, 4 successively right responses were regarded as the standard. Each rat was trained 10 times a day with 120 s per time for 3 successive days. The interval was 30 s. Three days later, numbers of right response were recorded. The training times were increased to 30 for unlearned rats. (3) Measurement of activity of choline acetylase in cerebral cortex: Rats were sacrificed at 17 days after operation to obtain cerebral cortex to measure activity of choline acetylase with radiochemistry technique. (4) Synergistic effect: It was expressed as Q value: Q value = factual incorporative effect/anticipant incorporative effect; Q ≥ 1 was regarded as synergistic effect. Anticipant incorporative effect = (EA+EB-EA·EB), EA and EB were single timing effect, respectively in GSL group and choline group. E(step-down test and Morris water maze test) = (x in model group - factual value in medicine groups)/x in model group; E (activity of choline acetylase) = (factual value in medicine groups -xin model group)/xin model group. MAIN OUTCOME MEASURES : (1) Passive avoidance step-down test and Morris water-maze spatial localization task in the study of learning and memory; (2) activity of choline acetylase. RESULTS : All 40 rats were involved in the final analysis. (1) Passive avoidance response: At learning phase on first day and retesting phase on the next day, numbers of wrong responses within 3 minutes were more in model group than sham operation group, and there was significant difference [(5.88±1.46), (2.25±0.87) times; (2.63±1.06), (0.50±0.53) times; P 〈 0.01]; numbers of wrong responses within 3 minutes were less in combination group than model group, and there was significant difference [learning phase: (1.12±0.83), (5.88±1.46) times; retesting phase: (0.38±0.74), (2.63±1.06)times, P 〈 0.01]; moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.07 and 1.59, respectively and it showed synergistic effect. Spatial localization task: Training times were more in model group than sham operation group, and there was significant difference [(2.9±2.5), (12.6±3.5) times; P 〈 0.01]. Training times were less in combination group than model group, and there was significant difference [(11.8±2.4), (27.9±2.5) times, P 〈 0.01]; moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.07 and it showed synergistic effect. (3) Activity of choline acetylase: Activity was lower in model group than sham operation group, and there was significant difference [(30.56±8.33), (61.11 ±8.33) nkat/g; P 〈 0.01]. Activity was higher in combination group than model group and there was significant difference [(50.00±8.33), (30.56±8.33) nkat/g, P 〈 0.01];moreover, effect was stronger than that in GSL group and choline group. The Q value was 1.5 and it showed synergistic effect. CONCLUSZON: GSL in combination with choline can synergically improve the disorder of learning and memory of AD model rats. Its mechanism may be involved in enhancing the function of central cholinergic system.
基金Project supported by the State Natural Science Fund
文摘-Combined refraction and diffraction models in the form of linear parabolic approximation are derived through smallparameter method. More strictly theoretical basis and more accuracy in the models than Lozano's (1980) are obtained. Some theoretical defects in Liu's model (1985) with consideration of current are not only found but also eliminated. More strict and accurate models are, therefore, presented in this paper.The calculation results and analysis in applying the models to actual wave field with consideration of bottom friction will be given in the following paper.
基金Shanxi Bethune Hospital Teaching Reform Project(2022JX06)Shanxi Provincial College Teaching Reform and Innovation Project(J20230467)。
文摘Objective:To study the application effect of short video combined with BOPPPS teaching mode in clinical anesthesia practice.Method:48 students assigned to clinical anesthesia in digestive endoscopy of Shanxi Bethune Hospital from July 1,2022 to April 1,2023 were selected as research objects.They were randomly divided into the control group(PowerPoint presentation teaching group)and the observation group(short video combined with BOPPPS teaching group),with 24 students in each group.After the internship,the students’theoretical and technical scores were tested,the effects of the two teaching modes were compared,and the students’satisfaction was investigated.Results:The test scores of students in the observation group were significantly better than those in the control group(P<0.05).The short video combined with BOPPPS teaching mode can significantly improve students’learning interest,operation skills,and memory(P<0.05).The students’satisfaction in the observation group was higher than that in the control group(P<0.05).Conclusion:In clinical practice,the application of short video combined with BOPPPS teaching mode has achieved great effect,which is worth further promotion and research.
文摘Combining with engineering examples,this paper introduces BIM into architectural design model and adopts Revit rapid modeling.It focuses on realizing rapid combination modeling of similar components through secondary development,improving information conversion efficiency between engineering CAD and Revit building structure modeling,and quickly generating BIM structure construction drawings.
文摘Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.
基金supported by the Youth Fund of Chinese Academy of Sciences Knowledge Innovation Program area frontier projects (No. S200603)the Innovation Team Project of Education Department of Liaoning Province (No. 2007T050)
文摘Ensuring a sufficient energy supply is essential to a country. Natural gas constitutes a vital part in energy supply and therefore forecasting natural gas consumption reliably and accurately is an essential part of a country's energy policy. Over the years, studies have shown that a combinative model gives better projected results compared to a single model. In this study, we used Polynomial Curve and Moving Average Combination Projection (PCMACP) model to estimate the future natural gas consumption in China from 2009 to 2015. The new proposed PCMACP model shows more reliable and accurate results: its Mean Absolute Percentage Error (MAPE) is less than those of any previous models within the investigated range. According to the PCMACP model, the average annual growth rate will increase for the next 7 years and the amount of natural gas consumption will reach 171600 million cubic meters in 2015 in China.
基金National Natural Science Foundation of China(Grant No.51775478)Hebei Provincial Natural Science Foundation of China(Grant Nos.E2016203173,E2020203078).
文摘Achieving accurate speed prediction provides the most critical support parameter for high-level energy management of plug-in hybrid electric vehicles.Nowadays,people often drive a vehicle on fixed routes in their daily travels and accurate speed predictions of these routes are possible with random prediction and machine learning,but the prediction accuracy still needs to be improved.The prediction accuracy of traditional prediction algorithms is difficult to further improve after reaching a certain accuracy;problems,such as over fitting,occur in the process of improving prediction accuracy.The combined prediction model proposed in this paper can abandon the transitional dependence on a single prediction.By combining the two prediction algorithms,the fusion of prediction performance is achieved,the limit of the single prediction performance is crossed,and the goal of improving vehicle speed prediction performance is achieved.In this paper,an extraction method suitable for fixed route vehicle speed is designed.The application of Markov and back propagation(BP)neural network in predictions is introduced.Three new combined prediction methods,all named Markov and BP Neural Network(MBNN)combined prediction algorithm,are proposed,which make full use of the advantages of Markov and BP neural network algorithms.Finally,the comparison among the prediction methods has been carried out.The results show that the three MBNN models have improved by about 19%,28%,and 29%compared with the Markov prediction model,which has better performance in the single prediction models.Overall,the MBNN combined prediction models can improve the prediction accuracy by 25.3%on average,which provides important support for the possible optimization of plug-in hybrid electric vehicle energy consumption.
基金National Natural Science Foundations of China(Nos.41172236,41402243,and 40911120044)Basic Research Project of Jilin University,China(No.450060491448)
文摘Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.
基金the National Natural Science Foundation of China,No. 3047051530570480
文摘BACKGROUND: In localized brain proton magnetic resonance spectroscopy (^1H-MRS), metabolite levels are often expressed as ratios, rather than absolute concentrations. Frequently, the denominator is creatine, which is assumed to be stable in normal, as well as many pathological, states. However, in vivo creatine levels do not remain constant. Therefore, absolute metabolite measurements, which provide the precise concentrations of certain chemical compounds, are superior to metabolite ratios for determining pathological and evolutional changes. OBJECTIVE: To investigate the feasibility of quantification analysis of brain metabolite changes caused by central analgesics nasal spray using the ^1H-MRS and linear combination model (LCModel) methods. DESIGN, TIME AND SETTING: This neuroimaging, observational, animal study was performed at the Laboratory of the Department of Medical Imaging, Second Affiliated Hospital, Medical College, Shantou University, China from July to December 2007. MATERIALS: Butorphanol tartrate nasal spray, as a mixed agonist-antagonist opioid analgesic, was purchased from Shanghai Hengrui Pharmacy, China. A General Electric Signa 1.5T System (General Electric Medical Systems, Milwaukee, WI, USA) and LCModel software (Stephen Provencher, Oakville, Ontario, Canada) were used in this study. METHODS: MRS images were acquired in ten healthy swine aged 2 weeks using single-voxel point-resolved spectroscopic sequence. A region of interest (2 cm × 2 cm × 2 cm) was placed in the image centers of maximum brain parenchyma. Repeated MRS scanning was performed 15-20 minutes after intranasal administration of 1 mg of butorphanol tartrate. Three settings of repetition time/echo time were selected before and after nasal spray administration 3 000 ms/30 ms,1 500 ms/30 ms, and 3 000 ms/50 ms. Metabolite concentrations were estimated by LCModel software. MAIN OUTCOME MEASURES: ^1H-MRS spectra was obtained using various repetition time/echo time settings. Concentrations of glutamate compounds (glutamate + glutamine), N-acetyl aspartate, and choline were detected in swine brain prior to and following nasal spray treatment. RESULTS: The glutamate compounds curve was consistent with original spectra, when a repetition time/echo time of 3 000 ms/30 ms was adopted. Concentrations of glutamate compounds, N-acetyl aspartate, and choline decreased following administration. The most significant reduction was observed in glutamate compound concentrations from (9.28 ± 0.54) mmol/kg to (7.28 ± 0.54) mmol/kg (P 〈 0.05). CONCLUSION: ^1H-MRS and LCModel software were effectively utilized to quantitatively analyze and measure brain metabolites. Glutamate compounds might be an important neurotransmitter in central analgesia.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2002AA111010 2003AA001032)
文摘Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. According to the knowledge structure of course and text, the relation among knowledge points, knowledge units from three levels of media material, we can build education resource components, and build TKCM (Teaching Knowledge Combination Model) based on resource components. Builders can build and assemble knowledge system structure and make knowledge units can be self assembled, thus we can develop and consummate them continually. Users can make knowledge units can be self assembled and renewed, and build education knowledge system to satisfy users' demand under the form of education knowledge system.
基金support from National Natural Science Foundation of China(Nos.71774051,72243003)National Social Science Fund of China(No.22AZD128)the seminar participants in Center for Resource and Environmental Management,Hunan University,China.
文摘Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability,and the development of the artificial intelligence industry.To provide investors with a more reliable reference in terms of artificial intelligence index investment,this paper selects the NASDAQ CTA Artificial Intelligence and Robotics(AIRO)Index as the research target,and proposes innovative hybrid methods to forecast returns by considering its multiple structural characteristics.Specifically,this paper uses the ensemble empirical mode decomposition(EEMD)method and the modified iterative cumulative sum of squares(ICSS)algorithm to decompose the index returns and identify the structural breakpoints.Furthermore,it combines the least-square support vector machine approach with the particle swarm optimization method(PSO-LSSVM)and the generalized autoregressive conditional heteroskedasticity(GARCH)type models to construct innovative hybrid forecasting methods.On the one hand,the empirical results indicate that the AIRO index returns have complex structural characteristics,and present time-varying and nonlinear characteristics with high complexity and mutability;on the other hand,the newly proposed hybrid forecasting method(i.e.,the EEMD-PSO-LSSVM-ICSS-GARCH models)which considers these complex structural characteristics,can yield the optimal forecasting performance for the AIRO index returns.
基金985 Construction Projects of Tongji,China(No.4218142801)
文摘Teachers are key participants in universities,and the performance appraisal of teacher is an important part of college work.By analyzing the data of behavior generated by different departments in university,analytic hierarchy process(AHP) is used to establish the preliminary library of performance indicators for teachers,and the correlation among all the performance indicators is inspected by using data mining method at this time.On this basis,a more objective,comprehensive and scientific performance appraisal system is constructed through principal components analysis(PCA),which is more suitable for university itself.Finally,in order to solve the problems existed in current performance appraisal system,a dynamic evaluation model is put forward by regulating the weight of indicator according to the historical data,highlighting the continuity of the system.