亚麻纤维热解动力学的“model free”法和Coats-Redfern模型拟合法研究

亚麻纤维是一种潜在的气化原料,本文对亚麻纤维的热解行为进行了热重分析研究。10mg粒径为0.60~0.85mm的亚麻纤维颗粒在高纯氮气的保护下分别以10、20、30、50K.min-1的升温速率线性升温到550℃。使用＂model free＂方法和Coats-Redfern模型拟合方法分析亚麻纤维的热解过程,并估算出热解反应的表观活化能。本文中＂model free＂方法包括Friedman、Flynn-wall-Ozawa、Vyazovkin and Wight三种等转化率方法及Kissinger法。三种等转化率方法均得到活化能随着转化率的升高而升高的规律。四种＂model free＂方法显示亚麻纤维的活化能主要在155~175kJ·mol-1之间,使用模型拟合方法所获得亚麻纤维热解反应的活化能值在175kJ·mol-1左右,使用模型拟合方法和＂model free＂方法所得的活化能值接近。这些活化能值可以为亚麻纤维高效的热化学利用提供基础数据。

Model Free Adaptive Predictive Control of Desulfurization Slurry pH Based on CPS Framework

In order to improve the slurry pH control accuracy of the absorption tower in the wet flue gas desulfurization process,a model free adaptive predictive control algorithm for the desulfurization slurry pH which is based on a cyber physical systems framework is proposed.First,aiming to address system characteristics of non-linearity and pure hysteresis in slurry pH change process,a model free adaptive predictive control algorithm based on compact form dynamic linearization is proposed by combining model free adaptive control algorithm with model predictive control algorithm.Then,by integrating information resources with the physical resources in the absorption tower slurry pH control process,an absorption tower slurry pH optimization control system based on cyber physical systems is constructed.It is turned out that the model free adaptive predictive control algorithm under the framework of the cyber physical systems can effectively realize the high-precision tracking control of the slurry pH of the absorption tower,and it has strong robustness.

Fuzzy Model Free Adaptive Control for Rotor Blade Full-Scale Static Testing

To eliminate the node traction coupling during wind turbine blade full-scale static testing,a model free adaptive control algorithm is presented based on fuzzy control performance function compensation. Based on the universal model theory,the fuzzy model free adaptive control( FMFAC) algorithm is designed by configuring the spot static testing experiences as compensation function F( ·). Then the algorithm implementation process is provided and its quick convergence is proved. Using software to establish static load coupling model of multi-nodes,simulate and verify the validity of FMFAC algorithm,which is applied to wind turbines blade full-scale static testing. The results show that the adaptive decoupling ability of FMFAC is better. The traction of four load points can stay steady and change coordinately. Process error is not over ± 6 k N. The error rate is lower than 1% in special phase.This algorithm effectively eliminates the traction coupling of the static testing process,and makes wind turbine blade testing steadily.

基于一种距离相关的超高维生存数据Model-Free特征筛选

随着大数据时代的来临,数据维度爆炸式增长,超高维数据的降维问题逐渐成为众多研究领域的热点话题。由于响应变量通常存在右删失,处理超高维完全数据的降维方法在右删失数据中将不再适用。本研究提出一种新的基于距离相关能有效处理超高维右删失数据的特征筛选方法。首先利用距离相关系数计算每个协变量对响应变量的边际效应,建立与该系数有关的筛选指标,然后再根据事先确立的筛选准则进行特征筛选。提出的特征筛选方法不依赖任何模型结构假定,因此可以有效避免模型指定错误带来的不良后果。此外,该方法采用的距离协方差估计量是总体距离协方差的一个无偏估计,统计准确性和计算精度高。模拟和实证研究表明,提出的方法能在保留所有重要变量的前提下快速剔除与响应变量相关程度较弱的协变量,从而达到降低参数维数的目的。

A model‑free approach to do long‑term volatility forecasting and its variants

Volatility forecasting is important in financial econometrics and is mainly based on the application of various GARCH-type models.However,it is difficult to choose a specific GARCH model that works uniformly well across datasets,and the traditional methods are unstable when dealing with highly volatile or short-sized datasets.The newly pro-posed normalizing and variance stabilizing(NoVaS)method is a more robust and accu-rate prediction technique that can help with such datasets.This model-free method was originally developed by taking advantage of an inverse transformation based on the frame of the ARCH model.In this study,we conduct extensive empirical and simu-lation analyses to investigate whether it provides higher-quality long-term volatility forecasting than standard GARCH models.Specifically,we found this advantage to be more prominent with short and volatile data.Next,we propose a variant of the NoVaS method that possesses a more complete form and generally outperforms the current state-of-the-art NoVaS method.The uniformly superior performance of NoVaS-type methods encourages their wide application in volatility forecasting.Our analyses also highlight the flexibility of the NoVaS idea that allows the exploration of other model structures to improve existing models or solve specific prediction problems.

Model-Free Feature Screening via Maximal Information Coefficient (MIC) for Ultrahigh-Dimensional Multiclass Classification

It is common for datasets to contain both categorical and continuous variables. However, many feature screening methods designed for high-dimensional classification assume that the variables are continuous. This limits the applicability of existing methods in handling this complex scenario. To address this issue, we propose a model-free feature screening approach for ultra-high-dimensional multi-classification that can handle both categorical and continuous variables. Our proposed feature screening method utilizes the Maximal Information Coefficient to assess the predictive power of the variables. By satisfying certain regularity conditions, we have proven that our screening procedure possesses the sure screening property and ranking consistency properties. To validate the effectiveness of our approach, we conduct simulation studies and provide real data analysis examples to demonstrate its performance in finite samples. In summary, our proposed method offers a solution for effectively screening features in ultra-high-dimensional datasets with a mixture of categorical and continuous covariates.

Model-Free Ultra-High-Dimensional Feature Screening for Multi-Classified Response Data Based on Weighted Jensen-Shannon Divergence

In ultra-high-dimensional data, it is common for the response variable to be multi-classified. Therefore, this paper proposes a model-free screening method for variables whose response variable is multi-classified from the point of view of introducing Jensen-Shannon divergence to measure the importance of covariates. The idea of the method is to calculate the Jensen-Shannon divergence between the conditional probability distribution of the covariates on a given response variable and the unconditional probability distribution of the covariates, and then use the probabilities of the response variables as weights to calculate the weighted Jensen-Shannon divergence, where a larger weighted Jensen-Shannon divergence means that the covariates are more important. Additionally, we also investigated an adapted version of the method, which is to measure the relationship between the covariates and the response variable using the weighted Jensen-Shannon divergence adjusted by the logarithmic factor of the number of categories when the number of categories in each covariate varies. Then, through both theoretical and simulation experiments, it was demonstrated that the proposed methods have sure screening and ranking consistency properties. Finally, the results from simulation and real-dataset experiments show that in feature screening, the proposed methods investigated are robust in performance and faster in computational speed compared with an existing method.

Modeling of multiphase flow in low permeability porous media:Effect of wettability and pore structure properties

Multiphase flow in low permeability porous media is involved in numerous energy and environmental applications.However,a complete description of this process is challenging due to the limited modeling scale and the effects of complex pore structures and wettability.To address this issue,based on the digital rock of low permeability sandstone,a direct numerical simulation is performed considering the interphase drag and boundary slip to clarify the microscopic water-oil displacement process.In addition,a dual-porosity pore network model(PNM)is constructed to obtain the water-oil relative permeability of the sample.The displacement efficiency as a recovery process is assessed under different wetting and pore structure properties.Results show that microscopic displacement mechanisms explain the corresponding macroscopic relative permeability.The injected water breaks through the outlet earlier with a large mass flow,while thick oil films exist in rough hydrophobic surfaces and poorly connected pores.The variation of water-oil relative permeability is significant,and residual oil saturation is high in the oil-wet system.The flooding is extensive,and the residual oil is trapped in complex pore networks for hydrophilic pore surfaces;thus,water relative permeability is lower in the water-wet system.While the displacement efficiency is the worst in mixed-wetting systems for poor water connectivity.Microporosity negatively correlates with invading oil volume fraction due to strong capillary resistance,and a large microporosity corresponds to low residual oil saturation.This work provides insights into the water-oil flow from different modeling perspectives and helps to optimize the development plan for enhanced recovery.

A Proper Time Integration with Split Stepping for the Explicit Free-Surface Modeling

Errors due to split time stepping are discussed for an explicit free–surface ocean model. In commonly used split time stepping, the way of time integration for the barotropic momentum equation is not compatible with that of the baroclinic one. The baroclinic equation has three–time–level structure because of leapfrog scheme. The barotropic one, however, has two–time–level structure when represented in terms of the baroclinic time level, on which the baroclinic one is integrated. This incompatibility results in the splitting errors as shown in this paper. The proper split time stepping is therefore proposed in such a way that the compatibility is kept between the barotropic and baroclinic equations. Its splitting errors are shown extremely small, so that it is particularly relevant to long–term integration for climate studies. It is applied to a free–surface model for the North Pacific Ocean.

A Model-Free Method for Structual Change Detection Multivariate Nonlinear Time Series

In this paper, we apply the recursive genetic programming (RGP) approach to the cognition of a system, and then proceed to the detecting procedure for structural changes in the system whose components are of long memory. This approach is adaptive and model-free, which can simulate the individual activities of the system's participants, therefore, it has strong ability to recognize the operating mechanism of the system. Based on the previous cognition about the system, a testing statistic is developed for the detection of structural changes in the system. Furthermore, an example is presented to illustrate the validity and practical value of the proposed.

DYNAMIC FREE ENERGY HYSTERESIS MODEL IN MAGNETOSTRICTIVE ACTUATORS

A dynamic free energy hysteresis model in magnetostrictive actuators is presented. It is the free energy hysteresis model coupled to an ordinary different equation in an unusual way. According to its special structure, numerical implementation method of the dynamic model is provided. The resistor parameter in the dynamic model changes according to different frequency ranges. This makes numerical implementation results reasonable in the discussed operating frequency range. The validity of the dynamic free energy model is illustrated by comparison with experimental data.

Prevalence of Congenital Heart Disease at Extremely High Altitudes in Tibet and the Establishment of a New Free Treatment Model

Background: This study aimed to illustrate the prevalence of CHD by screening children in extremely high-altitudeareas (over 4000 m to even 5000 m above sea level) and explore an aid model for early diagnosis and treatmentfor the Tibetan population. Methods: A total of 2242 students from different schools in Ngamring County,Xigaze City, Tibet from September 2019 to September 2020 were selected for screening. The students were examinedthrough the inquiry of their current medical history and family history, cardiac auscultation and a physicalexamination, in order to screen out the suspected cases of CHD, and then the suspected cases were confirmed bycardiac color ultrasound examinations. After that, positive patients were be transferred to Shandong Province forfree treatment. Results: The prevalence of CHD among children in Ngamring County was 3.70% (83 cases),which is the highest incidence rate ever reported. The most common type of CHD was patent ductus arteriosus(PDA), accounting for 55.42% of the total number of cases screened, followed by atrial septal defect (ASD) andventricular septal defect (VSD), accounting for 28.92% and 12.05%, respectively. The prevalence of CHD in childrenat high altitude was significantly higher than that in children at low altitude. The children with CHD weretransferred to Shandong Province for surgery, the operations were successful and their recoveries went well.Conclusions: The results show that high altitude is closely related to the prevalence of CHD, and the incidencein Ngamring County is much higher than that in previous reports.

Free radical reaction model for n-pentane pyrolysis

A mathematical mechanism of the n-pentane pyrolysis process based on free radical reaction model was presented.The kinetic parameters of n-pentane pyrolysis are obtained by quantum chemistry and the reaction network is established. The solution of the stiff ordinary differential equations in the n-pentane pyrolysis model is completed by semi implicit Eular algorithm. Then the pyrolysis mechanism based on free radical reaction model is built,and the computational efficiency increases 10 times by algorithm optimization. The validity of this model and its solution method is confirmed by the experimental results of n-pentane pyrolysis.

Introduction of parameterized sea ice drag coefficients into ice free-drift modeling

Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient （Ca） and oceanic drag coefficient （Cw）. Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factor a and the deflection angle θ between sea ice drift and wind velocity as well as the ratio of Ca to Cw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean, Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level （0.2-0.25） for large floes in the central ice zone. The wind factor a increases rapidly at first and approaches a steady level of 0.018 when A is greater than 20%. And the deflection angle ~ drops rapidly from an initial value of approximate 80° and decreases slowly as A is greater than 20% without a steady level like a. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient （Cs＇/Cs） and the ratio of ridge form drag coefficient （Cr＇/Cr） to the value of Ca/Cw, a, and 8, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.

Effects of Chuanxiongqin hydrochloride on increasing the fluidity of brain cell membrane and scavenging free radicals in model rats with ischemia/reperfusion injury

BACKGROUND: The fluidity of cell membrane can be affected by various factors. Many experiments have confirmed that the ischemia/reperfusion of organic tissue can increase the contents of free radicals, which lead to high rigidity and low fluidity of cell membrane, and the conditions can be changed by Chuanxiongqin. OBJECTIVE: To observe the effect and mechanism of Chuanxiongqin hydrochloride on the fluidity of brain cell membrane in rat models of ischemia/reperfusion. DESIGN: A completely randomized controlled animal trial. SETTINGS: Institute of Brain Sciences; Department of Physiology, Medical College, Datong University. MATERIALS: Twenty male grade Ⅰ Wistar rats of 170-220 g were randomly divided into model group (n =10) and control group (n =10). Chuanxiongqin hydrochloride (molecular mass was 172.2) was purchased from the National Institute for the Control of Pharmaceutical and Biological Products (batch number: 0817-9803); Spin labelers: 5-doxyl-stearlic acid methylester (5DS), 16-doxyl-stearlic acid methylester (16DS), xanthine, xanthine oxidase (XOD) and 5,5-dimeth-1-pyrroline- N-oxide (DMPO) from Sigma Company; Bruker ESP 300 electron paramagnetic resonance (EPR) spectrometer by Bruker Company (Germany). METHODS: The experiments were carried out in the State Key Laboratory of Natural and Biomimetic Drugs, Peking University from June 2001 to July 2002. In the model group, rats were made into models of cerebral ischemia by 30-minute ligation and 2-hour reperfusion of common carotid arteries; The rats in the control group were not made into models. The order parameter (S) and rotational correlation time (τc) were detected with the ESR spectrometer by means of spin labeling. The greater the S and τc, the smaller the fluidity. Meanwhile, the clearance rate of free radicals was detected with ESR spin trapping. The measurement data were compared using the t test. MAIN OUTCOME MEASURES: The S, τc and clearance rates of O2 · and OH· free radicals were compared between the model group and control group. RESULTS: The S and τc in the model group [0.738 4±0.003 5; (8.472±0.027)×10-10 s/circle] were obviously different from those in the control group [0.683 9±0.008 3; (7.945±0.082)×10-10 s/circle, t =5.731, 5.918, P < 0.05], which suggested that ischemia/reperfusion injury decreased the fluidity of brain cell membrane. After adding Chuanxiongqin hydrochloride, there were no obvious differences between the model group [0.688 5±0.030 5; (7.886±0.341)×10-10 s/circle] and control group (P > 0.05), indicating that Chuanxiongqin hydrochloride could recover the fluidity of brain cell membrane after ischemia/reperfusion injury close to the level in the normal control group. Chuanxiongqin hydrochloride could directly scavenge the O2 · and OH· free radicals, and the maximal clearance rates were 83.92% and 44.99% respectively. CONCLUSION: Chuanxiongqin hydrochloride increases the fluidity of membrane of ischemia-injured brain cell by scavenging both O2 ·and OH· free radicals.

Malicious Code Modeling and Analysis in Weighted Scale-Free Networks

We study the detailed malicious code propagating process in scale-free networks with link weights that denotes traffic between two nodes. It is found that the propagating velocity reaches a peak rapidly then decays in a power-law form, which is different from the well-known result in unweighted network case. Simulation results show that the nodes with larger strength are preferential to be infected, but the hierarchical dynamics are not clearly found. The simulation results also show that larger dispersion of weight of networks leads to slower propagating, which indicates that malicious code propagates more quickly in unweighted scale-free networks than in weighted scale-free networks under the same condition. These results show that not only the topology of networks but also the link weights affect the malicious propagating process.

A Novel Neighbor-Preferential Growth Scale-Free Network Model and its Properties

In this paper, we propose a novel neighbor-preferential growth (NPG) network model. Theoretical analysis and numerical simulations indicate the new model can reproduce not only a scale-free degree distribution and its power exponent is related to the edge-adding number m, but also a small-world effect which has large clustering coefficient and small average path length. Interestingly, the clustering coefficient of the model is close to that of globally coupled network, and the average path length is close to that of star coupled network. Meanwhile, the synchronizability of the NPG model is much stronger than that of BA scale-free network, even stronger than that of synchronization-optimal growth network.

Model-free Adaptive Control for Spacecraft Attitude

A model-free adaptive control method is proposed for the spacecrafts whose dynamical parameters change over time and cannot be acquired accurately. The algorithm is based on full form dynamic linearization.A dimension reduction matrix is introduced to construct an augmented system with the same dimension input and output. The design of the controller depends on the system input and output data rather than the knowledge of the controlled plant. The numerical simulation results show that the improved controller can deal with different models with the same set of controller parameters,and the controller performance is better than that of PD controller for the time-varying system with disturbance.