A novel complex-high-order graph convolutional network paradigm:ChyGCN

In recent years,there has been a growing interest in graph convolutional networks(GCN).However,existing GCN and variants are predominantly based on simple graph or hypergraph structures,which restricts their ability to handle complex data correlations in practical applications.These limitations stem from the difficulty in establishing multiple hierarchies and acquiring adaptive weights for each of them.To address this issue,this paper introduces the latest concept of complex hypergraphs and constructs a versatile high-order multi-level data correlation model.This model is realized by establishing a three-tier structure of complexes-hypergraphs-vertices.Specifically,we start by establishing hyperedge clusters on a foundational network,utilizing a second-order hypergraph structure to depict potential correlations.For this second-order structure,truncation methods are used to assess and generate a three-layer composite structure.During the construction of the composite structure,an adaptive learning strategy is implemented to merge correlations across different levels.We evaluate this model on several popular datasets and compare it with recent state-of-the-art methods.The comprehensive assessment results demonstrate that the proposed model surpasses the existing methods,particularly in modeling implicit data correlations(the classification accuracy of nodes on five public datasets Cora,Citeseer,Pubmed,Github Web ML,and Facebook are 86.1±0.33,79.2±0.35,83.1±0.46,83.8±0.23,and 80.1±0.37,respectively).This indicates that our approach possesses advantages in handling datasets with implicit multi-level structures.

Motion and Special Relativity in Complex Spaces

A natural extension of the Lorentz transformation to its complex version was constructed together with a parallel extension of the Minkowski M4 model for special relativity (SR) to complex C4 space-time. As the [signed] absolute values of complex coordinates of the underlying motion’s characterization in C4 one obtains a Newtonian-like type of motion whereas as the real parts of the complex motion’s description and of the complex Lorentz transformation, all the SR theory as modeled by M4 real space-time can be recovered. This means all the SR theory is preserved in the real subspace M4 of the space-time C4 while becoming simpler and clearer in the new complex model’s framework. Since velocities in the complex model can be determined geometrically, with no primary use of time, time turns out to be definable within the equivalent theory of the reduced complex C4 model to the C3 “para-space” model. That procedure allows us to separate time from the (para)space and consider all the SR theory as a theory of C3 alone. On the other hand, the complex time defined within the C3 theory is interpreted and modeled by the single separate C1 complex plane. The possibility for application of the C3 model to quantum mechanics is suggested. As such, the model C3 seems to have unifying abilities for application to different physical theories.

The Complex Field Theory and Mass Formation—An Alternative Model to Higgs Mechanism

The electromagnetic force, strong nuclear force, weak nuclear force, and gravitational force are the four fundamental forces of nature. The Standard Model (SM) succeeded in combining the first three forces to describe the most basic building blocks of matter and govern the universe. Despite the model’s great success in resolving many issues in particle physics but still has several setbacks and limitations. The model failed to incorporate the fourth force of gravity. It infers that all fermions and bosons are massless contrary to experimental facts. In addition, the model addresses neither the 95% of the universe’s energy of Dark Matter (DM) and Dark Energy (DE) nor the universe’s expansion. The Complex Field Theory (CFT) identifies DM and DE as complex fields of complex masses and charges that encompasses the whole universe, and pervade all matter. This presumption resolves the issue of failing to detect DM and DE for the last five decades. The theory also presents a model for the universe’s expansion and presumes that every material object carries a fraction of this complex field proportional to its mass. These premises clearly explain the physical nature of the gravitational force and its complex field and pave the way for gravity into the SM. On the other hand, to solve the issue of massless bosons and fermions in the SM, Higgs mechanism introduces a pure and abstractive theoretical model of unimaginable four potentials to generate fictitious bosons as mass donors to fermions and W± and Z bosons. The CFT in this paper introduces, for the first time, a physical explanation to the mystery of the mass formation of particles rather than Higgs’ pure mathematical derivations. The analyses lead to uncovering the mystery of electron-positron production near heavy nuclei and never in a vacuum. In addition, it puts a constraint on Einstein’s mass-energy equation that energy can never be converted to mass without the presence of dense dark matter and cannot be true in a vacuum. Furthermore, CFT provides different perspectives and resolves real-world physics concepts such as the nuclear force, Casimir force, Lamb’s shift, and the anomalous magnetic moment to be published elsewhere.

Modeling the Spatio-Temporal Dynamics of Local Context for a Contextualized Diffusion of Agroecological Intensification Options in Niger

Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.

Optimal Parameter and Uncertainty Estimation of a Land Surface Model: Sensitivity to Parameter Ranges and Model Complexities

Most previous land-surface model calibration studies have defined globalranges for their parameters to search for optimal parameter sets. Little work has been conducted tostudy the impacts of realistic versus global ranges as well as model complexities on the calibrationand uncertainty estimates. The primary purpose of this paper is to investigate these impacts byemploying Bayesian Stochastic Inversion (BSI) to the Chameleon Surface Model (CHASM). The CHASM wasdesigned to explore the general aspects of land-surface energy balance representation within acommon modeling framework that can be run from a simple energy balance formulation to a complexmosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem,importance sampling, and very fast simulated annealing. The model forcing data and surface flux datawere collected at seven sites representing a wide range of climate and vegetation conditions. Foreach site, four experiments were performed with simple and complex CHASM formulations as well asrealistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parametersets were used for each run. The results show that the use of global and realistic ranges givessimilar simulations for both modes for most sites, but the global ranges tend to produce someunreasonable optimal parameter values. Comparison of simple and complex modes shows that the simplemode has more parameters with unreasonable optimal values. Use of parameter ranges and modelcomplexities have significant impacts on frequency distribution of parameters, marginal posteriorprobability density functions, and estimates of uncertainty of simulated sensible and latent heatfluxes. Comparison between model complexity and parameter ranges shows that the former has moresignificant impacts on parameter and uncertainty estimations.

Inclusion complexes of cefuroxime axetil with β-cyclodextrin:Physicochemical characterization, molecular modeling and effect of Larginine on complexation

The inclusion complexes of poorly water-soluble cephalosporin, cefuroxime axetil(CFA), were prepared with β-cyclodextrin(βCD) with or without addition of L-arginine(ARG) to improve its physicochemical properties. We also investigated the effect of ARG on complexation efficiency(CE) of βCD towards CFA in an aqueous medium through phase solubility behaviour according to Higuchi and Connors. Although phase solubility studies showed AL(linear) type of solubility curve in presence and absence of ARG, the CE and association constant(Ks) of βCD towards CFA were significantly promoted in presence of ARG,justifying its use as a ternary component. The solid systems of CFA with βCD were obtained by spray drying technique with or without incorporation of ARG and characterized by differential scanning calorimetry(DSC), X-ray powder diffractometry(XRPD), scanning electron microscopy(SEM), and saturation solubility and dissolution studies. The molecular modeling studies provided a better insight into geometry and inclusion mode of CFA inside βCD cavity. The solubility and dissolution rate of CFA were significantly improved upon complexation with βCD as compared to CFA alone. However, ternary system incorporated with ARG performed better than binary system in physicochemical evaluation. In conclusion, ARG could be exploited as a ternary component to improve the physicochemical properties of CFA via βCD complexation.

Petrology and phase equilibrium modeling of sapphirine ＋ quartz assemblage from the Napier Complex, East Antarctica: Diagnostic evidence for Neoarchean ultrahigh-temperature metamorphism

A synthesis of the petrological characters of granulite facies rocks that contain equilibrium sapphirine ＋ quartz assemblage from two localities （Tonagh Island （TI） and Priestley Peak （PP）） in the Napier Complex,East Antarctica,provides unequivocal evidence for extreme crustal metamorphism possibly associated with the collisional orogeny during Neoarchean.The reaction microstructures associated with sapphirine ＋ quartz vary among the samples,probably suggesting different tectonic conditions during the metamorphic evolution.Sapphirine and quartz in TI sample were probably in equilibrium at the peak stage,but now separated by corona of Grt ＋ Sil ＋ Opx suggesting near isobaric cooling after the peak metamorphism,whereas the Spr ＋ Qtz ＋ Sil ＋ Crd ＋ Spl assemblage replaces garnet in PP sample suggesting post-peak decompression.The application of mineral equilibrium modeling in NCKFMASHTO system demonstrated that Spr ＋ Qtz stability is lowered down to 930 ℃ due to small Fe3＋ contents in the rocks （mole Fe2O3/（FeO ＋ Fe2O3） =0.02）.The TI sample yields a peak p-T range of 950-1100 ℃ and 7.5-11 kbar,followed by cooling toward a retrograde stage of 800-950 ℃ and 8-10 kbar,possibly along a counterclockwise p-T path.In contrast,the peak condition of the PP sample shows 1000-1050 ℃ and ＞12 kbar,which was followed by the formation ofSpr ＋ Qtz corona around garnet at 930-970 ℃ and 6.7-7.7 kbar,suggesting decompression possibly along a clockwise p-T trajectory.Such contrasting p-T paths are consistent with a recent model on the structural framework of the Napier Complex that correlates the two areas to different crustal blocks.The different p-T paths obtained from the two localities might reflect the difference in the tectonic framework of these rocks within a complex Neoarchean subduction/collision belt.

Experimental porcine model of complex fistula-in-ano

AIM To establish and evaluate an experimental porcine model of fistula-in-ano.METHODS Twelve healthy pigs were randomly divided into two groups. Under general anesthesia, the experimental group underwent rubber band ligation surgery, and the control group underwent an artificial damage technique. Clinical magnetic resonance imaging(MRI) and histopathological evaluation were performed on the 38 th d and 48 th d after surgery in both groups, respectively. RESULTS There were no significant differences between the experimental group and the control group in general characteristics such as body weight, gender, and the number of fistula(P > 0.05). In the experimental group, 15 fistulas were confirmed clinically, 13 complex fistulas were confirmed by MRI, and 11 complex fistulas were confirmed by histopathology. The success rate in the porcine complex fistula model establishment was 83.33%. Among the 18 fistulas in the control group, 5 fistulas were confirmed clinically, 4 complex fistulas were confirmed by MRI, and 3 fistulas were confirmed by histopathology. The success rate in the porcine fistula model establishment was 27.78%. Thus, the success rate of the rubber band ligation group was significantly higher than the control group(P < 0.05). CONCLUSION Rubber band ligation is a stable and reliable method to establish complex fistula-in-ano models. Large animal models of complex anal fistulas can be used for the diagnosis and treatment of anal fistulas.

VALIDATION OF NEAR-SURFACE WINDS OBTAINED BY A HYBRID WRF/CALMET MODELING SYSTEM OVER A COASTAL ISLAND WITH COMPLEX TERRAIN

The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.

The Fuzzy Modeling Algorithm for Complex Systems Based on Stochastic Neural Network

A fuzzy modeling method for complex systems is studied. The notation of general stochastic neural network (GSNN) is presented and a new modeling method is given based on the combination of the modified Takagi and Sugeno's (MTS) fuzzy model and one-order GSNN. Using expectation-maximization(EM) algorithm, parameter estimation and model selection procedures are given. It avoids the shortcomings brought by other methods such as BP algorithm, when the number of parameters is large, BP algorithm is still difficult to apply directly without fine tuning and subjective tinkering. Finally, the simulated example demonstrates the effectiveness.

Landscape Design of Commercial Housing Based on the Comprehensive Development Model of City Complex——A Case Study on Landscape Design of Chenglong-International

With the acceleration of urbanization, city complex as an intensive urban organization form has gradually grown up in China. By consulting relevant documents of city complex, emergence background and related concepts of city complex were introduced, landscape design of Chenglong-International was analyzed to propose landscape design principles and concepts of city complex under the compound development model, landscape processing techniques of outdoor functional subareas and transitional areas were introduced to provide useful reference for the landscape design of city complex.

GPR Wave Propagation Model in a Complex Geoelectric Structure Using Conformal First-Order Symplectic Euler Algorithm

Possessing advantages such as high computing efficiency and ease of programming,the Symplectic Euler algorithm can be applied to construct a groundpenetrating radar(GPR)wave propagation numerical model for complex geoelectric structures.However,the Symplectic Euler algorithm is still a difference algorithm,and for a complicated boundary,ladder grids are needed to perform an approximation process,which results in a certain amount of error.Further,grids that are too dense will seriously decrease computing efficiency.This paper proposes a conformal Symplectic Euler algorithm based on the conformal grid technique,amends the electric/magnetic fieldupdating equations of the Symplectic Euler algorithm by introducing the effective dielectric constant and effective permeability coefficient,and reduces the computing error caused by the ladder approximation of rectangular grids.Moreover,three surface boundary models(the underground circular void model,the undulating stratum model,and actual measurement model)are introduced.By comparing reflection waveforms simulated by the traditional Symplectic Euler algorithm,the conformal Symplectic Euler algorithm and the conformal finite difference time domain(CFDTD),the conformal Symplectic Euler algorithm achieves almost the same level of accuracy as the CFDTD method,but the conformal Symplectic Euler algorithm improves the computational efficiency compared with the CFDTD method dramatically.When the dielectric constants of the two materials vary greatly,the conformal Symplectic Euler algorithm can reduce the pseudo-waves almost by 80% compared with the traditional Symplectic Euler algorithm on average.

Performance-based fractal fracture model for complex fracture network simulation

The paper presents a novel hydraulic fracturing model for the characterization and simulation of the complex fracture network in shale gas reservoirs. We go beyond the existing method that uses planar or orthogonal conjugate fractures for representing the ＇＇complexity＇＇ of the network. Bifurcation of fractures is performed utilizing the Lindenmayer system based on fractal geometry to describe the fracture propagation pattern, density and network connectivity. Four controlling parameters are proposed to describe the details of complex fractures and stimulated reservoir volume（SRV）. The results show that due to the multilevel feature of fractal fractures, the model could provide a simple method for contributing reservoir volume calibration. The primary-and second-stage fracture networks across the overall SRV are the main contributions to the production, while the induced fracture network just contributes another 20% in the late producing period. We also conduct simulation with respect to different refracturing cases and find that increasing the complexity of the fracture network provides better performance than only enhancing the fracture conductivity.

Evaluaton model for the geometry complexity of casting based on fuzzy theory

The parameters that describe the complex degree of a certain casting are of some uncertainty. Therefore, a new method based on the fuzzy theory to classify the complex degree of castings has been presented in this paper. The feasibility of fuzzy theory in describing the complex degree of castings has been discussed and the procedure of this method has been specified by analyzing the complex degrees of some typical castings. The element factors that influence the casting complexity, have been summarized, which include the wall-thickness and the number of transition surface, etc. The results show that it is reasonable and practicable to classify the complex degree of castings with the fuzzy theory.

MM CALCULATIONS OF THE METAL-PROTEIN MODEL COMPLEXES Ⅰ.MOLECULAR FORCE FIELD FOR COBALT COMPEXES

Cobalt-protein complexes play an important role in biochemical processes.The structure of the model molecule,Co(H_2O)_3SO_4(phen) has been studied by molecular mechanics.The molecular force field (MM2) parameters have been developed for the particular class of the complexes.

STUDIES ON POLYMERIZATION MECHANISM OF CONJUGATED DIENE WITH η~3-ALLYL RARE EARTH MODEL COMPLEX

(η^-C_H_5)_2CeCl_5Mg_2(tmed)_2 was used as a catalyst to polymerize isoprene,Terminal ends of polyisoprene were identified as -CH_2-CH=CH_,which indicates that the insertion reaction of the monomer occurred between η^-allyl and cerium ion and gives a direct evidence for the η^-allyl mechanism of conjugated diene polymerzation with rare earth coordination catalysts.

An Incremental Model Transfer Method for Complex Process Fault Diagnosis

Fault diagnosis is an important measure to ensure the safety of production, and all kinds of fault diagnosis methods are of importance in actual production process. However, the complexity and uncertainty of production process often lead to the changes of data distribution and the emergence of new fault classes, and the number of the new fault classes is unpredictable. The reconstruction of the fault diagnosis model and the identification of new fault classes have become core issues under the circumstances. This paper presents a fault diagnosis method based on model transfer learning and the main contributions of the paper are as follows: 1) An incremental model transfer fault diagnosis method is proposed to reconstruct the new process diagnosis model. 2) Breaking the limit of existing method that the new process can only have one more class of faults than the old process, this method can identify M faults more in the new process with the thought of incremental learning. 3) The method offers a solution to a series of problems caused by the increase of fault classes. Experiments based on Tennessee-Eastman process and ore grinding classification process demonstrate the effectiveness and the feasibility of the method.

A dynamic epidemic control model on uncorrelated complex networks

In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered （SIR） model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.

Study on water saturation computation models in complex pore volcanic reservoir

Determination of water saturation is important for reservoir evaluation.When complex pore structures such as fracture and cavity are present in reservoir,Archie equation is no longer suitable.According to different models of pore structure division,the authors studied water saturation computation models.The results show that dual porosity system is divided into four models.The first model is based on dual laterolog,the second is Dual Porosity Ⅰ,the third is Dual Porosity Ⅱ,and the last one is based on the conductive pore.Besides,the triple porosity system is triple porosity model.Compute water saturation was using all the above five models in volcanic reservoir in Songnan gas field.The triple porosity system is the most suitable model for water saturation computation in complex pore structure volcanic reservoir.