Forecasting China’s natural gas consumption based on a combination model

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.

A new spatial coherence model and analytical coeffi cients for multi-support response spectrum combination

In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are developed for multi-support seismic excitations. The coefficients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coefficients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coefficients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational efficiency of the analytical solutions of the modal combination coefficients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coefficients is less than 1/20 of that using numerical integral methods.

Settlement Prediction of Dredger Fill with the Optimal Combination Model

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.

AModel for the Optimization of the Shale Gas HorizontalWell Section Based on the Combination of Different Weighting Methods in the Frame of the Game Theory

Existing“evaluation indicators”are selected and combined to build a model to support the optimization of shale gas horizontal wells.Towards this end,different“weighting methods”,including AHP and the so-called entropy method,are combined in the frame of the game theory.Using a relevant test case for the implementation of the model,it is shown that the horizontal section of the considered well is in the middle sweet spot area with good physical properties and fracturing ability.In comparison with the FSI(flow scanner Image)gas production profile,the new model seems to display better abilities for the optimization of horizontal wells.

N-acetylcysteine and glycyrrhizin combination:Benefit outcome in a murine model of acetaminophen-induced liver failure

BACKGROUND Acetaminophen overdose is the most frequent cause of drug-induced liver failure in developed countries.Substantial progress has been made in understanding the mechanism of hepatocellular injury,but N-acetylcysteine remains the only effective treatment despite its short therapeutic window.Thus,other hepatoprotective drugs are needed for the delayed treatment of acetaminopheninduced hepatotoxicity.Our interest focused on glycyrrhizin for its role as an inhibitor of high mobility group box 1(HMGB1)protein,a member of the family of damage-associated molecular pattern,known to play an important pathological role in various diseases.AIM To investigate the efficacy of the N-acetylcysteine/glycyrrhizin combination compared to N-acetylcysteine alone in the prevention of liver toxicity.METHODS Eight-week-old C57BL/6J wild-type female mice were used for all our experiments.Mice fasted for 15 h were treated with acetaminophen(500 mg/kg)or vehicle(phosphate-buffered saline)by intraperitoneal injection and separated into the following groups:Glycyrrhizin(200 mg/kg);N-acetylcysteine(150 mg/kg);and N-acetylcysteine/glycyrrhizin.In all groups,mice were sacrificed 12 h following acetaminophen administration.The assessment of hepatotoxicity was performed by measuring plasma levels of alanine aminotransferase,aspartate aminotransferase and lactate dehydrogenase.Hepatotoxicity was also evaluated by histological examination of hematoxylin and eosin-stained tissues sections.Survival rates were compared between various groups using Kaplan-Meier curves.RESULTS Consistent with data published in the literature,we confirmed that intraperitoneal administration of acetaminophen(500 mg/kg)in mice induced severe liver injury as evidenced by increases in alanine aminotransferase,aspartate aminotransferase and lactate dehydrogenase but also by liver necrosis score.Glycyrrhizin administration was shown to reduce the release of HMGB1 and significantly decreased the severity of liver injury.Thus,the co-administration of glycyrrhizin and N-acetylcysteine was investigated.Administered concomitantly with acetaminophen,the combination significantly reduced the severity of liver injury.Delayed administration of the combination of drugs,2 h or 6 h after acetaminophen,also induced a significant decrease in hepatocyte necrosis compared to mice treated with N-acetylcysteine alone.In addition,administration of N-acetylcysteine/glycyrrhizin combination was associated with an improved survival rate compared to mice treated with only N-acetylcysteine.CONCLUSION We demonstrate that,compared to N-acetylcysteine alone,co-administration of glycyrrhizin decreases the liver necrosis score and improves survival in a murine model of acetaminophen-induced liver injury.Our study opens a potential new therapeutic pathway in the prevention of acetaminophen hepatotoxicity.

Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

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.

Pressure stimulated current in progressive failure process of combined coal-rock under uniaxial compression:Response and mechanism

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents(PSCs)has great potential for the understanding of dynamic disasters in underground engineering.To reveal the effect of this way,the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength combinations.The mechanism explanation of PSCs are investigated by resistivity test,atomic force microscopy(AFM)and computed tomography(CT)methods,and a PSC flow model based on progressive failure process is proposed.The influence of strength combinations on PSCs in the progressive failure process are emphasized.The results show the PSC responses between rock part,coal part and the two components are different,which are affected by multi-scale fracture characteristics and electrical properties.As the rock strength decreases,the progressive failure process changes obviously with the influence range of interface constraint effect decreasing,resulting in the different responses of PSC strength and direction in different parts to fracture behaviors.The PSC flow model is initially validated by the relationship between the accumulated charges of different parts.The results are expected to provide a new reference and method for mining design and roadway quality assessment.

A Novel Approach for QoS Prediction Based on Bayesian Combinational Model

As an important factor in evaluating service,QoS(Quality of Service) has drawn more and more concerns with the rapid increasing of Web services. However,due to the great volatility of services in Mobile Internet environments,such as internet of vehicles,Web services often do not work as announced and thus cause unacceptable problems. QoS prediction can avoid failure before it takes place,which is considered a more effective way to assure quality. However,Current QoS prediction approaches neither consider the highly dynamic of Web services,nor maintain good prediction performance all the time. Consequently we propose a novel Bayesian combinational model to predict QoS by continuously adjusting credit values of the basic models so as to keep good prediction accuracy. QoS attributes such as response time,throughput and reliability are used to validate the proposed model. Experimental results show that the model can provide stable prediction results in Mobile Internet environments.

Quantitative analysis of glutamate compounds in the swine brain following central analgesics nasal spray using proton magnetic resonance spectroscopy and linear combination model

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.

Education Knowledge System Combination Model Based on the Components

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.

Forecasting Alzheimer’s Disease Using Combination Model Based on Machine Learning

As the acceleration of aged population tendency, building models to forecast Alzheimer’s Disease (AD) is essential. In this article, we surveyed 1157 interviewees. By analyzing the results using three machine learning methods—BP neural network, SVM and random forest, we can derive the accuracy of them in forecasting AD, so that we can compare the methods in solving AD prediction. Among them, random forest is the most accurate method. Moreover, to combine the advantages of the methods, we build a new combination forecasting model based on the three machine learning models, which is proved more accurate than the models singly. At last, we give the conclusion of the connection between life style and AD, and provide several suggestions for elderly people to help them prevent AD.

A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

To solve the medium and long term power load forecasting problem,the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward.This model is divided into two stages which are forecasting model selection and weighted combination forecasting.Based on Markov chain conversion and cloud model,the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting.For the weighted combination forecasting,a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model.The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439%and 0.3198%,respectively,while the maximum values of these two indexes of single forecasting models are 5.2278%and 1.9497%.It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.

Combined model based on optimized multi-variable grey model and multiple linear regression

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.

A Numerical Study on Effects of Land-Surface Heterogeneity from' Combined Approach' on Atmospheric ProcessPart II: Coupling-Model Simulations

Two land surface schemes, one the standard Biosphere / Atmosphere Transfer Scheme Version ie (BOZ) and the other B1Z based on B0Z and heterogeneously-treated by' combined approach' , were co 'pled to the meso-scale model MM4, respectively. Through the calculations of equations from the companion paper, parameters representing land surface heterogeneity and suitable for the coupling models were found out. Three cases were simulated for heavy rainfalls during 36 hours, and the sensitivity of short-term weather modeling to the land surface heterogeneity was tested. Through the analysis of the simulations of the three heavy rainfalls, it was demonstrated that BIZ, compared with BOZ, could more realistically reflect the features of the land surface heterogeneity, therefore could more realistically reproduce the circulation and precipitation amount in the heavy rainfall processes of the three cases. This shows that even short-term weather is sensitive to the land surface heterogeneity, which is more obvious with time passing, and whose influence is more pronounced in the lower layer and gradually extends to the middle and upper layer. Through the analysis of these simulations with BlZ, it is suggested that the bulk effect of smaller-scale fluxes (i.e., the momentum, water vapor and sensible heat fluxes) near the s ig nificantly-heterogeneous land surface is to change the larger-scale (i.e., meso-scale) circulation, and then to influence the development of the low-level jets and precipitation. And also, the complexity of the land-atmosphere interaction was shown in these simulations.

Study of the mechanisms of streamline-adjustment-assisted heterogeneous combination flooding for enhanced oil recovery for post-polymer-flooded reservoirs

Streamline-adjustment-assisted heterogeneous combination flooding is a new technology for enhanced oil recovery for post-polymer-flooded reservoirs.In this work,we first carried out a series of 2D visualization experiments for different chemical flooding scenarios after polymer flooding.Then,we explored the synergistic mechanisms of streamline-adjustment-assisted heterogeneous combination flooding for enhanced oil recovery and the contribution of each component.Test results show that for single heterogeneous combination flooding,the residual oil in the main streamline area after polymer flooding is ready to be driven,but it is difficult to be recovered in the non-main streamline area.Due to the effect of drainage and synergism,the streamline-adjustment-assisted heterogeneous combination flooding diverts the injected chemical agent from the main streamline area to the non-main streamline area,which consequently expands the active area of chemical flooding.Based on the results from the single-factor contribution of the quantitative analysis,the contribution of temporary plugging and profile control of branched preformed particle gels ranks in the first place and followed by the polymer profile control and the effect of streamline adjustment.On the contrary,the surfactant contributes the least to enhance the efficiency of oil displacement.

A combined numerical tidal model for the Hangzhou Bay and Qiantang River

-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.

Subdivision surface modeling system based on arbitrary topological curves network and combined subdivision

Arbitrary topological curve network has no restriction in topology structure,so it has more powerful representing ability in defining complex surfaces.A complex surface modeling system is presented based on arbitrary topological curve network and the improved combined subdivision method,its functions including creating and editing curve network,and generating and modifying curve network＇s interpolated surface.This modeling system can be used to the process of products＇concept design,and its applications is also significant to the development of subdivision method.

Mathematical rules for synergistic,additive,and antagonistic effects of multi-drug combinations and their application in research and development of combinatorial drugs and special medical food combinations

Multi-drug(or multi-element)combinations are often prescribed in the practice of clinical medicine and as foods for special medical purposes.The main motivations for these combinations are that most diseases contain multiple related targets and an appropriate combination can maximize benefits while minimizing adverse reactions.As such,it is especially important to derive mathematical models for their quantitative calculation.In this paper,we introduce mathematical rules for the synergistic,additive,and antagonistic effects of multi-drug combinations developed in our laboratory.We have established a“onebelt,one-line”model and provide examples of the quantitative calculation of the synergistic,additive,and antagonistic effects of a combination of multiple components.We also explain how to scientifically and precisely determine the intensity of these synergies,additions and antagonisms,as well as their corresponding dose ranges,thereby laying a solid theoretical foundation for market listing combinatorial drugs and foods for special medical purposes.

Image Denoising Combining the P-M Model and the LLT Model

In this paper, we present a noise removal technique by combining the P-M model with the LLT model. The combined technique takes full use of the advantage of both filters which is able to preserve edges and simultaneously overcomes the staircase effect. We use a weighting function in our model, and compare this model with the P-M model as well as other fourth-order functional both in theory and numerical experiment.